Subjects -> ENGINEERING (Total: 2922 journals)
    - CHEMICAL ENGINEERING (261 journals)
    - CIVIL ENGINEERING (252 journals)
    - ELECTRICAL ENGINEERING (181 journals)
    - ENGINEERING (1477 journals)
    - HYDRAULIC ENGINEERING (60 journals)
    - INDUSTRIAL ENGINEERING (101 journals)
    - MECHANICAL ENGINEERING (119 journals)

ELECTRICAL ENGINEERING (181 journals)                     

Showing 1 - 181 of 181 Journals sorted alphabetically
3C TIC     Open Access   (Followers: 4)
Acta Electronica Malaysia     Open Access  
Acta Universitatis Sapientiae Electrical and Mechanical Engineering     Open Access  
Actuators     Open Access   (Followers: 4)
Advanced Electromagnetics     Open Access   (Followers: 20)
Advances in Electrical and Electronic Engineering     Open Access   (Followers: 10)
Advances in Electrical Engineering     Open Access   (Followers: 52)
Advances in Microelectronic Engineering     Open Access   (Followers: 13)
Advances in Signal Processing     Open Access   (Followers: 16)
American Journal of Electrical and Electronic Engineering     Open Access   (Followers: 28)
American Journal of Sensor Technology     Open Access   (Followers: 4)
APSIPA Transactions on Signal and Information Processing     Open Access   (Followers: 8)
Archives of Control Sciences     Open Access   (Followers: 3)
Archives of Electrical Engineering     Open Access   (Followers: 16)
Atom Indonesia     Open Access   (Followers: 2)
Australian Journal of Electrical and Electronics Engineering     Hybrid Journal  
Balkan Journal of Electrical and Computer Engineering     Open Access  
Bulletin of Electrical Engineering and Informatics     Open Access   (Followers: 10)
Carpathian Journal of Electronic and Computer Engineering     Open Access  
Case Studies in Mechanical Systems and Signal Processing     Open Access  
CES Transactions on Electrical Machines and Systems     Open Access   (Followers: 1)
Chinese Journal of Electrical Engineering     Open Access   (Followers: 2)
Circuits, Systems, and Signal Processing     Hybrid Journal   (Followers: 15)
Computers & Electrical Engineering     Hybrid Journal   (Followers: 9)
CPSS Transactions on Power Electronics and Applications     Open Access   (Followers: 2)
CSEE Journal of Power and Energy Systems     Open Access   (Followers: 4)
Current Trends in Signal Processing     Full-text available via subscription   (Followers: 6)
ECTI Transactions on Computer and Information Technology (ECTI-CIT)     Open Access  
ECTI Transactions on Electrical Engineering, Electronics, and Communications     Open Access   (Followers: 2)
Edu Elektrika Journal     Open Access   (Followers: 1)
Electric Power Components and Systems     Hybrid Journal   (Followers: 10)
Electric Power Systems Research     Partially Free   (Followers: 24)
Electrica     Open Access  
Electrical and Electronic Engineering     Open Access   (Followers: 61)
Electrical Engineering     Hybrid Journal   (Followers: 23)
Electrical Engineering and Automation     Open Access   (Followers: 9)
Electrical Engineering and Power Engineering     Open Access   (Followers: 2)
Electrical Engineering in Japan     Hybrid Journal   (Followers: 8)
Electrical, Control and Communication Engineering     Open Access   (Followers: 15)
Electrochemical Energy Reviews     Hybrid Journal   (Followers: 1)
Elektron     Open Access  
Elektronika ir Elektortechnika     Open Access   (Followers: 5)
Elkha : Jurnal Teknik Elektro     Open Access  
Emerging and Selected Topics in Circuits and Systems     Hybrid Journal   (Followers: 7)
Emitor : Jurnal Teknik Elektro     Open Access   (Followers: 8)
ETRI Journal     Open Access  
EURASIP Journal on Advances in Signal Processing     Open Access   (Followers: 8)
Ferroelectrics     Hybrid Journal   (Followers: 1)
Ferroelectrics Letters Section     Hybrid Journal   (Followers: 1)
Frequenz     Hybrid Journal   (Followers: 1)
Frontiers of Electrical and Electronic Engineering     Hybrid Journal   (Followers: 8)
Frontiers of Information Technology & Electronic Engineering     Hybrid Journal  
IEEE Access     Open Access   (Followers: 121)
IEEE Electrical Insulation Magazine     Full-text available via subscription   (Followers: 77)
IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology     Hybrid Journal   (Followers: 3)
IEEE Journal of Photovoltaics     Hybrid Journal   (Followers: 18)
IEEE Journal of Radio Frequency Identification     Hybrid Journal   (Followers: 4)
IEEE Journal of Selected Topics in Signal Processing     Hybrid Journal   (Followers: 42)
IEEE Journal on Miniaturization for Air and Space Systems     Hybrid Journal   (Followers: 2)
IEEE Letters on Electromagnetic Compatibility Practice and Applications     Hybrid Journal   (Followers: 4)
IEEE Networking Letters     Hybrid Journal   (Followers: 3)
IEEE Open Access Journal of Power and Energy     Open Access   (Followers: 3)
IEEE Open Journal of Antennas and Propagation     Open Access   (Followers: 7)
IEEE Open Journal of Circuits and Systems     Open Access   (Followers: 3)
IEEE Open Journal of Intelligent Transportation Systems     Open Access   (Followers: 8)
IEEE Open Journal of Power Electronics     Open Access   (Followers: 5)
IEEE Open Journal of Signal Processing     Open Access   (Followers: 4)
IEEE Sensors Journal     Hybrid Journal   (Followers: 103)
IEEE Sensors Letters     Hybrid Journal   (Followers: 3)
IEEE Signal Processing Magazine     Full-text available via subscription   (Followers: 90)
IEEE Solid-State Circuits Letters     Hybrid Journal   (Followers: 3)
IEEE Transactions on Control of Network Systems     Hybrid Journal   (Followers: 27)
IEEE Transactions on Dielectrics and Electrical Insulation     Hybrid Journal   (Followers: 29)
IEEE Transactions on Green Communications and Networking     Hybrid Journal   (Followers: 3)
IEEE Transactions on Network Science and Engineering     Hybrid Journal   (Followers: 3)
IEEE Transactions on Quantum Engineering     Open Access   (Followers: 3)
IEEE Transactions on Radiation and Plasma Medical Sciences     Hybrid Journal   (Followers: 4)
IEEE Transactions on Signal and Information Processing over Networks     Hybrid Journal   (Followers: 14)
IEEE Transactions on Sustainable Energy     Hybrid Journal   (Followers: 18)
IEEJ Transactions on Electrical and Electronic Engineering     Hybrid Journal   (Followers: 19)
IET Control Theory & Applications     Open Access   (Followers: 27)
IET Electric Power Applications     Open Access   (Followers: 47)
IET Electrical Systems in Transportation     Open Access   (Followers: 11)
IET Energy Systems Integration     Open Access   (Followers: 1)
IET Nanodielectrics     Open Access  
IET Smart Grid     Open Access   (Followers: 1)
IETE Journal of Education     Open Access   (Followers: 3)
IJEIS (Indonesian Journal of Electronics and Instrumentation Systems)     Open Access   (Followers: 3)
InComTech : Jurnal Telekomunikasi dan Komputer     Open Access   (Followers: 1)
Indonesian Journal of Electrical Engineering and Computer Science     Open Access   (Followers: 18)
Industrial Technology Research Journal Phranakhon Rajabhat University     Open Access  
InfoMat     Open Access  
Infotekmesin : Media Komunikasi Ilmiah Politeknik Cilacap     Open Access  
Ingeniería Electrónica, Automática y Comunicaciones     Open Access  
Integrated Ferroelectrics: An International Journal     Hybrid Journal  
International Journal of Advances in Telecommunications, Electrotechnics, Signals and Systems     Open Access   (Followers: 12)
International Journal of Electrical and Computer Engineering     Open Access   (Followers: 12)
International Journal of Electrical Engineering Education     Hybrid Journal   (Followers: 7)
International Journal of Electrical Power & Energy Systems     Open Access   (Followers: 34)
International Journal of Emerging Electric Power Systems     Hybrid Journal   (Followers: 7)
International Journal of Microwave Engineering and Technology     Full-text available via subscription   (Followers: 5)
International Journal of Monitoring and Surveillance Technologies Research     Full-text available via subscription   (Followers: 3)
International Journal of Nano Devices, Sensors and Systems     Open Access   (Followers: 14)
International Journal of Nuclear Security     Open Access   (Followers: 1)
International Journal of Turbomachinery, Propulsion and Power     Open Access   (Followers: 11)
International Transaction of Electrical and Computer Engineers System     Open Access   (Followers: 2)
International Transactions on Electrical Energy Systems     Hybrid Journal   (Followers: 9)
Iranian Journal of Science and Technology, Transactions of Electrical Engineering     Hybrid Journal  
Izvestiya Vysshikh Uchebnykh Zavedenii. Materialy Elektronnoi Tekhniki : Materials of Electronics Engineering     Full-text available via subscription  
J3eA     Open Access   (Followers: 2)
JAREE (Journal on Advanced Research in Electrical Engineering)     Open Access  
Journal of Control, Automation and Electrical Systems     Hybrid Journal   (Followers: 10)
Journal of Electrical and Computer Engineering     Open Access   (Followers: 9)
Journal of Electrical and Computer Engineering Innovations     Open Access   (Followers: 7)
Journal of Electrical and Electronics Engineering Research     Open Access   (Followers: 39)
Journal of Electrical Bioimpedance     Open Access   (Followers: 2)
Journal of Electrical Engineering     Open Access   (Followers: 44)
Journal of Electrical Engineering & Electronic Technology     Hybrid Journal   (Followers: 7)
Journal of Electrical Engineering & Technology     Hybrid Journal  
Journal of Electrical Systems and Information Technology     Open Access   (Followers: 7)
Journal of Electrical, Electronics and Informatics     Open Access  
Journal of Field Robotics     Hybrid Journal   (Followers: 5)
Journal of International Council on Electrical Engineering     Open Access  
Journal of Micro-Bio Robotics     Hybrid Journal   (Followers: 1)
Journal of Microwaves, Optoelectronics and Electromagnetic Applications     Open Access   (Followers: 10)
Journal of Power Technologies     Open Access   (Followers: 7)
Journal of Science and Application Technology     Open Access  
Journal of the Society for Information Display     Hybrid Journal  
Journal of World's Electrical Engineering and Technology     Open Access   (Followers: 2)
Journal on Today's Ideas - Tomorrow's Technologies     Open Access   (Followers: 1)
JPhys Energy     Open Access  
JPhys Materials     Open Access  
Jurnal ELTIKOM : Jurnal Teknik Elektro, Teknologi Informasi dan Komputer     Open Access  
Jurnal Ilmiah Mahasiswa SPEKTRUM     Open Access  
Jurnal Nasional Teknik Elektro     Open Access   (Followers: 4)
Jurnal Rekayasa Elektrika     Open Access  
Jurnal Teknik Elektro     Open Access  
Jurnal Teknik Elektro     Open Access   (Followers: 1)
Jurnal Teknik Elektro dan Komputer     Open Access  
Jurnal Teknologi Elektro     Open Access  
Kinetik : Game Technology, Information System, Computer Network, Computing, Electronics, and Control     Open Access   (Followers: 1)
La Rivista del Nuovo Cimento     Hybrid Journal   (Followers: 2)
Majalah Ilmiah Teknologi Elektro : Journal of Electrical Technology     Open Access   (Followers: 2)
Majlesi Journal of Electrical Engineering     Open Access   (Followers: 1)
Material Design & Processing Communications     Hybrid Journal  
Metrology and Instruments / Метрологія та прилади     Open Access  
Micro and Nano Systems Letters     Open Access   (Followers: 6)
Nanotechnology Development     Open Access   (Followers: 19)
npj Materials Degradation     Open Access  
Open Electrical & Electronic Engineering Journal     Open Access  
Open Signal Processing Journal     Open Access   (Followers: 2)
Periodica Polytechnica Electrical Engineering and Computer Science     Open Access  
Presence : Teleoperators and Virtual Environments     Hybrid Journal   (Followers: 3)
Progress in Additive Manufacturing     Hybrid Journal   (Followers: 5)
Quantum Beam Science     Open Access   (Followers: 1)
Radio Science     Full-text available via subscription   (Followers: 43)
Recent Advances in Communications and Networking Technology     Hybrid Journal   (Followers: 3)
Recent Advances in Electrical & Electronic Engineering     Hybrid Journal   (Followers: 11)
Research & Reviews : Journal of Embedded System & Applications     Full-text available via subscription   (Followers: 6)
Russian Electrical Engineering     Hybrid Journal   (Followers: 5)
SAIEE Africa Research Journal     Open Access   (Followers: 1)
Sampling Theory, Signal Processing, and Data Analysis     Hybrid Journal  
SID Symposium Digest of Technical Papers     Hybrid Journal  
Signal Processing     Hybrid Journal   (Followers: 9)
Signals     Open Access   (Followers: 1)
Simetris : Jurnal Teknik Mesin, Elektro dan Ilmu Komputer     Open Access  
Sustainable Energy, Grids and Networks     Hybrid Journal   (Followers: 6)
Synthesis Lectures on Electrical Engineering     Full-text available via subscription   (Followers: 2)
System analysis and applied information science     Open Access  
Telematique     Open Access  
The Scientific Bulletin of Electrical Engineering Faculty     Open Access  
Transactions of the International Society for Music Information Retrieval     Open Access   (Followers: 1)
Transactions on Electrical and Electronic Materials     Hybrid Journal   (Followers: 1)
Transactions on Environment and Electrical Engineering     Open Access  
Trends in Electrical Engineering     Full-text available via subscription   (Followers: 4)
Tri Dasa Mega : Jurnal Teknologi Reaktor Nuklir     Open Access  
Turkish Journal of Electrical Engineering and Computer Science     Open Access   (Followers: 2)
Universal Journal of Electrical and Electronic Engineering     Open Access   (Followers: 7)
Ural Radio Engineering Journal     Open Access   (Followers: 1)
Wireless Engineering and Technology     Open Access   (Followers: 5)
Електротехніка і Електромеханіка     Open Access   (Followers: 1)


Similar Journals
Journal Cover
Bulletin of Electrical Engineering and Informatics
Number of Followers: 10  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2089-3191 - ISSN (Online) 2302-9285
Published by Universitas Ahmad Dahlan Homepage  [17 journals]
  • A smart partial discharge classification SOM with optimized statistical
           transformation feature

    • Authors: Z. H. Bohari; M. Isa, A. Z. Abdullah, P. J. Soh, M. F. Sulaima
      Abstract: Condition-based monitoring (CBM) has been a vital engineering method to assess high voltage (HV) equipment and power cables conditions or health levels. One of the effective CBM methods is partial discharge (PD) measurement or detection. PD event is the phenomenon that always associated with insulation healthiness. PD has been measured and evaluated in this paper to discriminate PD signals from a good signal. A mixed-signal being fed at an AI technique with statistical modified input data to do fast classification (less than five seconds) with nearly zero error. In this paper, an unsupervised neural network is applied for PD classification. The methods combine the self-organizing maps (SOMs) and feature statistical transformation. By the combination of these methods, the ‘range’ normalization method produced the best classification outcomes. This development decided that PD information was effectively correlated and grouped by means of MATLAB’s SOM Toolbox and transformation device to discriminate the normal signal from the PD signal.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Threshold benchmarking for feature ranking techniques

    • Authors: Ruchika Malhotra; Anjali Sharma
      Abstract: In prediction modeling, the choice of features chosen from the original feature set is crucial for accuracy and model interpretability. Feature ranking techniques rank the features by its importance but there is no consensus on the number of features to be cut-off. Thus, it becomes important to identify a threshold value or range, so as to remove the redundant features. In this work, an empirical study is conducted for identification of the threshold benchmark for feature ranking algorithms. Experiments are conducted on Apache Click dataset with six popularly used ranker techniques and six machine learning techniques, to deduce a relationship between the total number of input features (N) to the threshold range. The area under the curve analysis shows that ≃ 33-50% of the features are necessary and sufficient to yield a reasonable performance measure, with a variance of 2%, in defect prediction models. Further, we also find that the log2(N) as the ranker threshold value represents the lower limit of the range.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A genetic algorithm for prediction of RNA-seq malaria vector gene
           expression data classification using SVM kernels

    • Authors: Marion O. Adebiyi; Micheal O. Arowolo, Oludayo Olugbara
      Abstract: Malaria larvae embrace unpredictable variable life periods as they spread across many stratospheres of the mosquito vectors. There are transcriptomes of a thousand distinct species. Ribonucleic acid sequencing (RNA-seq) is a ubiquitous gene expression strategy that contributes to the improvement of genetic survey recognition. RNA-seq measures gene expression transcripts data, including methodological enhancements to machine learning procedures. Scientists have suggested many addressed learning for the study of biological evidence. An enhanced optimized Genetic Algorithm feature selection technique is used in this analysis to obtain relevant information from a high-dimensional Anopheles gambiae dataset and test its classification using SVM-Kernel algorithms. The efficacy of this assay is tested, and the outcome of the experiment obtained an accuracy metric of 93% and 96% respectively.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Real-time mask detection and face recognition using eigenfaces and local
           binary pattern histogram for attendance system

    • Authors: Mohd Suhairi Md Suhaimin; Mohd Hanafi Ahmad Hijazi, Chung Seng Kheau, Chin Kim On
      Abstract: Face recognition is gaining popularity as one of the biometrics methods for an attendance system in an organization. Due to the pandemic, the common face recognition system needs to be modified to meet the current needs, whereby facemask detection is necessary. The main objective of this paper is to investigate and develop a real-time face recognition system for the attendance system based on the current scenarios. The proposed framework consists of face detection, mask detection, face recognition, and attendance report generation modules. The face and facemask detection is performed using the haar cascade classifier. Two techniques for face recognition were investigated, the eigenfaces and local binary pattern histogram. The initial experimental results and implementation at Kuching Community College show the effectiveness of the system. For future work, an approach that is able to perform masked face recognition will be investigated.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Robust large image steganography using LSB algorithm and 5D hyper-chaotic

    • Authors: Jinan N. Shehab; Hussein A. Abdulkadhim, Taqwa F.H. Al-Tameemi
      Abstract: This paper contains a robust hiding system proposed to hide and reconstruct efficiently a large size secret image based on merging encrypting and hiding. This approach deals with a video utilized as a cover of frames to hide the blocks of large image inside it. Frames are selected according to 5D hyperchaotic algorithms and consequently change value of the pixel in the original image depends on it. Secret image will divide into many blocks and hide each block in one frame selected by 5D chaotic. This method will support and enhance the techniques of information security with less time and morecapacity of transmission. The results obtained are analyzed under criteria including: Peak signal to noise ratio, Mean square error, key space and sensitivity, correlation coefficient and capacity of hiding. The results demonstrate both of the secret color image and cover video, where retaining its explicitness and properties after reconstruction in the receiver. However, the results prove stability and reliability of the proposed system under several conditions and can avoid attacks.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Optimization of triple-junction hydrogenated silicon solar cell
           nc-Si:H/a-Si:H/a-SiGe:H using step graded Si1‑xGex layer

    • Authors: Nji Raden Poespawati; Rizqy Pratama Rahman, Junivan Sulistianto, Retno Wigajatri Purnamaningsih, Tomy Abuzairi
      Abstract: This paper shows the attempt to increase the performance of triple-junction hydrogenated silicon solar cells with structure nc-Si:H/a-Si:H/a-SiGe:H. The wxAMPS software was used to simulate and optimize the design. In an attempt to increase the performance, an a-SiC:H layer on the p-layer was replaced with an a-Si:H layer and an a-SiGe layer was replaced with a step graded Si1-xGex layer. Then, to achieve the best performing device, we optimized the concentration of germanium and thickness of the step graded Si1-xGex layer. The result shows that the optimum concentration of germanium in the p-i upper layer and i-n lower layer are 0.86 and 0.90, respectively and the optimum thicknesses are 10 nm and 230 nm, respectively. The optimized device performed with an efficiency of 19.08%, adding 3 more percent of efficiency from the original design. Moreover, there is a significant possibility of increasing the efficiency of a triple-junction solar cell by modifying it into a step graded Si1-xGex layer.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Proposition of local automatic algorithm for landmark detection in 3D

    • Authors: Mohammed Ed-dhahraouy; Hicham Riri, Manal Ezzahmouly, Abdelmajid El moutaouakkil, Hakima Aghoutan, Farid Bourzgui
      Abstract: This study proposes a new contribution to solve the problem of automatic landmarks detection in three-dimensional cephalometry. 3D images obtained from CBCT (cone beam computed tomography) equipment were used for automatic identification of twelve landmarks. The proposed method is based on a local geometry and intensity criteria of skull structures. After the step of preprocessing and binarization, the algorithm segments the skull into three structures using the geometry information of nasal cavity and intensity information of the teeth. Each targeted landmark was detected using local geometrical information of the volume of interest containing this landmark. The ICC and confidence interval (95% CI) for each direction were 0, 91 (0.75 to 0.96) for x- direction; 0.92 (0.83 to 0.97) for y-direction; 0.92 (0.79 to 0.97) for z-direction. The mean error of detection was calculated using the Euclidian distance between the 3D coordinates of manually and automatically detected landmarks. The overall mean error of the algorithm was 2.76 mm with a standard deviation of 1.43 mm. Our proposed approach for automatic landmark identification in 3D cephalometric was capable of detecting 12 landmarks on 3D CBCT images which can be facilitate the use of 3D cephalometry to orthodontists.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Experimental analysis of non-Gaussian noise resistance on global method
           optical flow using bilateral in reverse confidential

    • Authors: Darun Kesrarat; Vorapoj Patanavijit
      Abstract: This paper presents the analytical of non-Gaussian noise resistance with the aid of the use of bilateral in reverse confidential with the optical flow. In particular, optical flow is the sample of the image’s motion from the consecutive images caused by the object’s movement. It is a 2-D vector where every vector is a displacement vector displaying the motion from the first image to the second. When the noise interferes with the image flow, the approximated performance on the vector in optical flow is poor. We ensure greater appropriate noise resistance by applying bilateral in reverse confidential in optical flow in the experiment by concerning the error vector magnitude (EVM). Many noise resistance models of the global method optical flow are using for comparison in our experiment. And many sequenced image data sets where they are interfered with by several types of non-Gaussian noise are used for experimental analysis.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Microscopy images segmentation algorithm based on shearlet neural network

    • Authors: Nemir Ahmed Al-Azzawi
      Abstract: Microscopic images are becoming important and need to be studied to know the details and how-to quantitatively evaluate decellularization. Most of the existing research focuses on deep learning-based techniques that lack simplification for decellularization. A new computational method for the segmentation microscopy images based on the shearlet neural network (SNN) has been introduced. The proposal is to link the concept of shearlets transform and neural networks into a single unit. The method contains a feed-forward neural network and uses a single hidden layer. The activation functions are depending on the standard shearlet transform. The proposed SNN is a powerful technology for segmenting an electron microscopic image that is trained without relying on the pre-information of the data. The shearlet neural networks capture the features of full accuracy and contextual information, respectively. The expected value for specific inputs is estimated by learning the functional configuration of a network for the sequence of observed value. Experimental results on the segmentation of two-dimensional microscopy images are promising and confirm the benefits of the proposed approach. Lastly, we investigate on a challenging datasets ISBI 2012 that our method (SNN) achieves superior outcomes when compared to classical and deep learning-based methods.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • ASSAS: An automatic smart students attendance system based on normalized

    • Authors: Ruaa H. Ali Al-Mallah; Dheyaa Alhelal, Razan Abdulhammed
      Abstract: A smart student attendance system (SSAS) is presented in this paper. The system is divided into two phases: hardware and software. The Hardware phase is implemented based on Arduino's camera while the software phase is achieved by using image processing with face recognition depended on the cross-correlation technique. In comparison with traditional attendance systems, roll call, and sign-in sheet, the proposed system is faster and more reliable (because there is no action needed by a human being who by its nature makes mistakes). At the same time, it is cheaper when compared with other automatic attendance systems. The proposed system provides a faster, cheaper and reachable system for an automatic smart student attendance that monitors and generates attendance report automatically.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • An in-depth exploration of Bangla blog post classification

    • Authors: Tanvirul Islam; Ashik Iqbal Prince, Md. Mehedee Zaman Khan, Md. Ismail Jabiullah, Md. Tarek Habib
      Abstract: Bangla blog is increasing rapidly in the era of information, and consequently, the blog has a diverse layout and categorization. In such an aptitude, automated blog post classification is a comparatively more efficient solution in order to organize Bangla blog posts in a standard way so that users can easily find their required articles of interest. In this research, nine supervised learning models which are Support Vector Machine (SVM), multinomial naïve Bayes (MNB), multi-layer perceptron (MLP), k-nearest neighbours (k-NN), stochastic gradient descent (SGD), decision tree, perceptron, ridge classifier and random forest are utilized and compared for classification of Bangla blog post. Moreover, the performance on predicting blog posts against eight categories, three feature extraction techniques are applied, namely unigram TF-IDF (term frequency-inverse document frequency), bigram TF-IDF, and trigram TF-IDF. The majority of the classifiers show above 80% accuracy. Other performance evaluation metrics also show good results while comparing the selected classifiers.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Pre-convoluted neural networks for fashion classification

    • Authors: Mustafa Amer Obaid; Wesam M. Jasim
      Abstract: In this work, concept of the fashion-MNIST images classification constructed on convolutional neural networks is discussed. Whereas, 28×28 grayscale images of 70,000 fashion products from 10 classes, with 7,000 images per category, are in the fashion-MNIST dataset. There are 60,000 images in the training set and 10,000 images in the evaluation set. The data has been initially pre-processed for resizing and reducing the noise. Then, this data is normalized for ensuring that all the data are on the same scale and this usually improves the performance. After normalizing the data, it is augmented where one image will be in three forms of output. The first output image is obtained by rotating the actual one; the second output image is obtained as acute angle image; and the third is obtained as tilt image. The new data set is of 180,000 images for training phase and 30,000 images for the testing phase. Finally, data is sent to training process as input for training model of the pre-convolution network. The pre-convolution neural network with the five layered convoluted deep neural network and do the training with the augmented data, The performance of the proposed system shows 94% accuracy where it was 93% in VGG16 and 92% in AlexNetnetworks.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A new model for early diagnosis of alzheimer's disease based on
           BAT-SVM classifier

    • Authors: Shereen A. Taie; Wafaa Ghonaim
      Abstract: Magnetic Resonance Images (MRI) of the Brain is a significant tool to diagnosis Alzheimer's disease due to its ability to measure regional changes in the brain that reflect disease progression to detect early stages of the disease. In this paper, we propose a new model that adopts Bat for parameter optimization problem of Support vector machine (SVM) to diagnose Alzheimer’s disease via MRI biomedical image. The proposed model uses MRI for biomedical image classification to diagnose three classes; normal controls (NC), mild cognitive impairment (MCI) and Alzheimer’s disease (AD). The proposed model based on segmentation for the most involved areas in the disease hippocampus, the features of MRI brain images are extracted to build feature vector of the brain, then extracting the most significant features in neuroimaging to reduce the high dimensional space of MRI images to lower dimensional subspace, and submitted to machine learning classification technique. Moreover, the model is applied on different datasets to validate the efficiency which show that the new Bat-SVM model can yield promising acceptable level of accuracy reached to 95.36 % using maximum number of bats equal to 50 and number of generation equal to 10.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Advanced modulation coding schemes for an optical transceiver
           systems–based OWC communication channel model

    • Authors: Hazem M. El-Hageen; Aadel M. Alatwi, Ahmed Nabih Zaki Rashed
      Abstract: This paper examines advanced modulation coding schemes for an optical transceiver systems–based optical wireless communication (OWC) channel model. These modulation techniquesinclude On-Off keying and return to zero (RZ)/non–return to zero (NRZ) coding. The signal power level against time and frequency spectral variations are measured. The max. Q factor and min. bit error rate (BER) are estimated and clarified for each modulation code scheme by using an optisystem simulation model. Transmission bit rates of up to 40 Gb/s can be achieved for possible distances up to 500 km with acceptable Q factor. The received power and max. Q factor are measured and clarified with OWC distance variations. The On-Off keying modulation code scheme resulted in better performance than the other modulation code schemes did.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Design and optimization of multi user OFDM orthogonal chaotic vector shift
           keying communication system

    • Authors: Ansam M. Abed; Fadhil S. Hasan
      Abstract: This paper study and present, power allocation strategy on sub-carriers of multiuser OFDM employed for orthogonal chaotic vector shift keying (MU OFDM-OCVSK) over multipath frequency selective fading channels. firstly, the MU OFDM-OCVSK system is modeled with power allocated on reference and information bearing subcarriers. Then, the computed bit error rate equation of the power allocation MU OFDM-OCVSK system is derived. The optimal power allocation strategy on subcarriers is obtained using convex optimization. Finally, compared with the traditional MU OFDM-DCSK and MU OFDM-OCVSK without power allocation system the proposed system can achieve an excellent BER performance under multipath Rayleigh fading channels. Numerical and Simulation results emphasize the remarkable features of the proposed optimal power allocation strategy.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Benefiting wireless power transfer scheme in power domain based multiple
           access: ergodic rate performance evaluation

    • Authors: Anh-Tu Le; Minh-Sang Van Nguyen, Dinh-Thuan Do
      Abstract: Power domain based multiple access scheme is introduced in this paper, namely Non-orthogonal multiple-access (NOMA). We deploy a wireless network using NOMA together with a wireless power transfer (WPT) scheme for dedicated user over Nakagami-$m$ fading channel. When combined, these promising techniques (NOMA and WPT) improve the system performance in term of ergodic performance at reasonable coefficient of harvested power. However, fixed power allocation factors for each NOMA user can be adjusted at the base station and it further provide performance improvement. We design a new signal frame to deploy a NOMA scheme in WPT which adopts a linear energy harvesting model. The ergodic capacity in such a NOMA network and power allocation factors can be updated frequently in order to achieve a fair distribution among NOMA users. The exact expressions of ergodic capacity for each user is derived. The simulation results show that an agreement between analytic performance and Monte-Carlo simulation can be achieved. 
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Implement of multiple access technique by wireless power transfer and
           relaying network

    • Authors: Anh-Tu Le; Dinh-Thuan Do
      Abstract: In this paper, we investigate non-orthogonal multiple access (NOMA) network relying on wireless power transfer to prolong lifetime. The base station (BS) sends common signals to the relay with two functions (energy harvesting (EH) and signal processing) to further serve two NOMA users in downlink. Performance gap exists since different power allocation factor assigned from power splitting protocol adopted at the relay and such relay employs both amplify-and-forward (AF) and decode-and-forward schemes. To provide performance metrics, we prove formulas of the outage probability which is a function of transmit signal to noise ratio. Simulation results indicate specific parameters to adjust system performance of two user in the considered EH-NOMA system. This finding is important recommendation to design EH-NOMA which shows particular outage performance at required target rates.

      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Interference mitigation using antenna selection for the heterogeneous

    • Authors: Adel Khaled; Sally Hassaneen, Salah ElAgooz, Heba Soliman
      Abstract: A rapid increase in the wireless internet-based applications led to an enormous increase in wireless data rates. Intensification of future wireless networks faces a great challenge to meet such growing demand for payload data. A suggested solution that can be used to resolve this issue is to overlay small cell networks with macro cell networks to provide higher network capacity and better coverage. Small cell networks experience large interference from macro cell base stations (BSs) making data rates received by the small cell users not reliably. In this paper, an antenna selection scheme based on small cell user’s (SCU) channel gain is proposed. Whereas, the two tiers use the same network bandwidth resources; the macro BS selects a subset of antennas which has a minimum interfering effect to the SCU based on a pilot sent from SCU to macro cell. The proposed selection scheme has been compared with convex optimization antenna selection scheme. Simulation results show that the SCU data rates are significantly improved using proposed scheme. Execution time required for antenna selection is reduced significantly using the proposed scheme.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Joint impacts of relaying scheme and wireless power transfer in multiple
           access of cellular networks

    • Authors: Anh-Tu Le; Dinh-Thuan Do
      Abstract: This paper considers ergodic capacity of energy harvesting (EH) based cellular networks. Such a network employs non-orthogonal multiple access (NOMA) together with relaying scheme to serve two far users. In this system model, relay is facilitated power splitting (PS) protocol to implement energy harvesting (EH). To examine capacity, expressions of signal to noise ratio (SNR) need be computed to achieve capacity. Power allocation factors are different for two users in such system and hence performance gap happens to distinguish requirements for separated users. It can be confirmed that the proposed paradigm exhibits maximal achievable capacity in some scenarios of setting parameters. To confirm exactness of the analytical expressions and show advantages of the proposed EH-NOMA, simulation results are performed in terms of ergodic capacity.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Mutual antenna coupling influence on the channel correlation matrix for
           linear antenna arrays

    • Authors: Tatiana K. Artemova; Aleksey S. Gvozdarev, Konstantin S. Artemov
      Abstract: The paper presents the results of the research of electromagnetic mutual coupling impact on the structure of the correlation matrices in multiantenna communication systems. Classical correlation structures employed in most of the up-to-date communication systems descriptions and designs usually assume unit autocorrelation and exponentially decreasing cross-correlation of antenna elements in the receiving/transmitting array. At the same time numerous studies had shown that these assumptions may not hold under certain conditions. The performed research relates the correlation effects with the imbalances of the array impedance matrix terms and studies the impact of antenna elements mutual electromagnetic interaction upon the diagonal (autocorrelation) and off-diagonal (cross-correlation) terms of correlation matrix, depending of the geometry of the array: number of elements and their spatial separation. To exemplify quantitative results the analysis was carried out for the 5G NR #78 band, being one of the most wideband subchannels in Under-6 GHz regime for 5G systems. The obtained results also justified the applicability of the banded correlation matrix model for wireless communications.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Secure outage probability of cognitive radio network relying
           non-orthogonal multiple access scheme

    • Authors: Chi-Bao Le; Dinh-Thuan Do
      Abstract: This paper studies the secondary network relying relay selection to transmit signal from the secondary source (base station) to two destinations. Especially, two destinations are required non-orthogonal multiple access (NOMA) scheme and it benefits to implementation of the Internet of Things (IoT) systems. However, eavesdropper over-hears signal related link from selected relay to destination. This paper measure secure performance via metric, namely secure outage probability (SOP). In particular, signal to noise ratio (SNR) criterion is used to evalute SOP to provide reliable transmission to the terminal node. Main results indicates that the considered scheme provides performance gap among two signals at destination. The exactness of derived expressions is confirmed via numerical simulation.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Live migration using checkpoint and restore in userspace (CRIU): Usage
           analysis of network, memory and CPU

    • Authors: Adityas Widjajarto; Deden Witarsyah Jacob, Muharman Lubis
      Abstract: Currently, cloud service providers have used a variety of operational mechanisms to support the company's business processes. Therefore, the services are stored on the company's server, which presents in the form of infrastructure, platform, software, and function. There are several vulnerabilities that have been faced in the implementation such as system failure, natural disasters, human errors, or attacks from unauthorized parties. In addition, the time of unavailability of services can be minimized by doing an LM, in which many servers have been used the containers to behave like a service provider. Actually, its existence replaces the virtual machine that requires more resources although the process only can be done through docker with checkpoint and restore in userspace (CRIU). In this research, LM processes are done to the docker container using CRIU by analyzing the quality of service (QoS), memory, and CPU usage. Thus, the simulation is carried out by establishing the LM using 2 (two) different platforms through scenarios with one and three containers respectively. The performance analysis results aim to examine several indicators in comparison with the achievable result to reduce problems that occurred in the cloud service.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Studying strictly positive secure capacity in cognitive radio-based
           non-orthogonal multiple access

    • Authors: Chi-Bao Le; Dinh-Thuan Do
      Abstract: This paper studies a downlink security-aware secure outage performance in the secondary network of cognitive radio-assisted non-orthogonal multiple access network (CR-NOMA). The multiple relay is employed to assist transmission from the secondary source to destinations. The security-aware performance is subject to constraints in fixed power allocation factor assigned to each secondary user. The security-aware secure performance is based on channel state information (CSI) at the physical layer in which an eavesdropper intends to steal information. According to the considered system, exact expressions of Strictly positive secure capacity (SPSC) are proved to analyze system in terms of secure performance. Finally, the secondary user secure problem is evaluated via Monte-Carlo simulation method. The main results indicate that the secure performance of proposed system can be improved significantly.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Rabid Euclidean direction search algorithm for various adaptive array

    • Authors: Aseel Abdul-Karim Qasim; Adheed Hassan Sallomi, ِAli Khalid Jassim
      Abstract: One of the exciting technologies used to meet the increasing demand for wireless communication services is a smart antenna. A smart antenna is basically confirmed by an array of antennas and a digital beamformer unit through which cellular base station can direct the beam toward the desired user and set nulls toward interfering users. In this paper, different array configurations (linear, circular, and planer) with the REDS algorithm are implemented in the digital beam-forming unit. The wireless system performance is investigated to check the smart antenna potentials assuming Rayleigh fading channel environment beside the AWGN channel. Results show how the REDS algorithm offers a significant improvement through antenna radiation pattern optimization, sidelobe level, and interference reduction, and also the RDES algorithm proves fast convergence with minimum MSE and better sidelobe level reduction comparing with other algorithms. 
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Predicting machine failure using recurrent neural network-gated recurrent
           unit (RNN-GRU) through time series data

    • Authors: Zainuddin Z; P. Akhir E. A, Hasan M. H.
      Abstract: Time series data often involves big size environment that lead to high dimensionality problem. Many industries are generating time series data that continuously update each second. The arising of machine learning may help in managing the data. It can forecast future instance while handling large data issues. Forecasting is related to predicting task of an upcoming event to avoid any circumstances happen in current environment. It helps those sectors such as production to foresee the state of machine in line with saving the cost from sudden breakdown as unplanned machine failure can disrupt the operation and loss up to millions. Thus, this paper offers a deep learning algorithm named recurrent neural network-gated recurrent unit (RNN-GRU) to forecast the state of machines producing the time series data in an oil and gas sector. RNN-GRU is an affiliation of recurrent neural network (RNN) that can control consecutive data due to the existence of update and reset gates. The gates decided on the necessary information to be kept in the memory. RNN-GRU is a simpler structure of long short-term memory (RNN-LSTM) with 87% of accuracy on prediction.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A comparative study of different network simulation tools and
           experimentation platforms for underwater communication

    • Authors: Tejaswini R. Murgod; S. Meenakshi Sundaram
      Abstract: Study of computer networks and their performance parameters like delay, bandwidth utilization, throughput, latency, jittering, and packet loss. have gained significant importance in the recent times. Simulation studies have been preferred for these parameters in computer networks, which in a real time is a difficult task. A network consists of many networking devices as gateways, routers, bridges, wireless access points and hub connected to it. To implement any new protocol or algorithm in a network is costlier and time consuming. Recently lot of research is going on underwater wireless sensor networks (UWSNs). Conducting real time experiments for underwater applications are overpriced, so as an alternative solution for this, we can conduct simulation studies to reduce the cost and quicken the research activities.In this paper we explore the different experimentation platforms and simulation tools available that help the network architects to develop new protocols or do changes to the existing protocol in a productive manner. We classify the tools based on various parameters and provide guidelines for researchers to choose a suitable platform based on their requirements.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Detection of water quality in crayfish ponds with IoT

    • Authors: Abdurrasyid Abdurrasyid; Indrianto Indrianto, Meilia Nur Indah Susanti, Yudhi S. Purwanto
      Abstract: Data from the Central Bureau of Statistics shows that during the first quarter of 2014 to 2019, the tendency of Indonesian crayfish export increases by an average of 3.54% in 2019 and reach 7.09 million USD. This number still fails to meet the global market demand caused by poor water quality due to cultivators’ lack of experience and education. Two parameters measured in water quality are temperature and pH. Thus, a device was made using IoT to maintain those conditions in order to increase the viability of the crayfish in the pond. The perceptron method is used to classify water quality based on those parameters. To send the data, ESP8266 is used as an intermediary for Arduino and cloud server. The result is that the information about the ponds’ condition can be seen via a smartphone. The method gives a value of 98.06% accurate in determining water quality.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • The first FOSD-tacotron-2-based text-to-speech application for Vietnamese

    • Authors: Duc Chung Tran
      Abstract: Recently, with the development and deployment of voicebots which help to minimize personnels at call centers, text-to-speech (TTS) systems supporting English and Chinese have attracted attentions of researchers and corporates worldwide. However, there is very limited published works in TTS developed for Vietnamese. Thus, this paper presents in detail the first Tacotron-2-based TTS application development for Vietnamese that utilizes the publicly available FPT open speech dataset (FOSD) containing approximately 30 hours of labeled audio files together with their transcripts. The dataset was made available by FPT Corporation with an open access license. A new cleaner was developed for supporting Vietnamese language rather than English which was provided by default in Mozilla TTS source code. After 225,000 training steps, the generated speeches have mean opinion score (MOS) well above the average value of 2.50 and center around 3.00 for both clearness and naturalness in a crowd-source survey.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • BCH codes in UFMC: A new contender candidate for 5G communication systems

    • Authors: Ghasan Ali Hussain; Lukman Audah
      Abstract: Nowadays, fifth generation (5G) wireless network is considered one of the most important research topics in wireless industry and it will be substituting with fourth generation (4G) in several aspects. Although the robustness of orthogonal frequency division multiplexing (OFDM) system against channel delays which is the reason behind using it in LTE/LTE Advanced however, it is suffering from high peak to average power ration (PAPR) and out of band side lobes. So, universal filtered multi-carrier (UFMC) technique is considered a new modulation scheme for 5G wireless communication system to overcome on the common OFDM demits. In contrast, to achieve reliable data transmission in digital communication systems, using error correcting codes are considered an essential over noisy channels. In this paper, BCH code has been used for UFMC system over AWGN. The results showed that using BCH codes in UFMC contributed in enhancing BER performance while could decreasing both of PAPR and OOBE values better than conventional OFDM system.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Evaluation of weighted fusion for scalar images in multi-sensor network

    • Authors: C. Jittawiriyanukoon; V. Srisarkun
      Abstract: The regular image fusion method based on scalar has the problem how to prioritize and proportionally enrich image details in multi-sensor network. Based on multiple sensors to fuse and manipulate patterns of computer vision is practical. A fusion (integration) rule, bit-depth conversion, and truncation (due to conflict of size) on the image information are studied. Through multi-sensor images, the fusion rule based on weighted priority is employed to restructure prescriptive details of a fused image. Investigational results confirm that the associated details between multiple images are possibly fused, the prescription is executed and finally, features are improved. Visualization for both spatial and frequency domains to support the image analysis is also presented.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Architecture exploration of recent GPUs to analyze the efficiency of
           hardware resources

    • Authors: Viet Tan Vo; Cheol Hong Kim
      Abstract: This study analyzes the efficiency of parallel computational applications with the adoption of recent graphics processing units (GPUs). We investigate the impacts of the additional resources of recent architecture on the popular benchmarks compared with previous architecture. Our simulation results demonstrate that Pascal GPU architecture improves the performance by 273% on average compared to old-fashioned Fermi architecture. To evaluate the performance improvement depending on specific hardware resources, we divide the hardware resources into two types: computing and memory resources. Computing resources have bigger impact on performance improvement than memory resources in most of benchmarks. For Hotspot and B+ tree, the architecture adopting only enhanced computing resources can achieve similar performance gains of the architecture adopting both computing and memory resources. We also evaluate the influence of the number of warp schedulers in the SM (Streaming Multiprocessor) to the GPU performance in relationship with barrier waiting time. Based on these analyses, we propose the development direction for the future generation of GPUs.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A wearable device for machine learning based elderly's activity
           tracking and indoor location system

    • Authors: Nour Eddin Tabbakha; Chee Pun Ooi, Wooi Haw Tan, Yi-Fei Tan
      Abstract: The number of older people is increasing in many countries. By 2030, it is estimated that 15% of the overall population will be comprised of people aged 65 and above. Hence, the monitoring and tracking of elder activities to ensure they live an active life has become a major research topic in recent years. In this work, an elderly sub-activity tracking system is developed to detect the sub-activity of the elderly based on their physical activities and indoor location. The physical activities tracking system and indoor location system is combined in this project to enhance the context of the elderly activities (i.e. sub-activities as defined in this project). An indoor location system is developed by using Bluetooth Low Energy (BLE) beacon and BLE scanners to measure the Received Signal Strength Indicator (RSSI) signal to detect the location of the elderly. The activity tracking is carried out via a waist wearable device worn by the elderly. Random forest and Support Vector Machine (SVM) are used as machine learning classifiers to predict the activity and indoor location with an accuracy of 95.03% and 86.58%, respectively. The data from activity tracking and indoor location sub-systems will then be combined to derive the sub-activity and push to an online Internet of Things (IoT) platform for remote monitoring and notification.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Design and development of intelligent waste bin system with advertisement

    • Authors: Tarig Faisal; Moath Awawdeh, Anees Bashir
      Abstract: In cities where a large geographical area of the city is densely populated, the process of waste collection is cumbersome, tiresome and expensive. Often, the burden of manually tracking and collecting of waste causes waste management companies enormous wasted effort and get them involved in tasks that are not necessary. No doubt, a digital interaction between waste management companies and targeted waste collection areas could ensure the process becomes fast, efficient and traceable as they become aware of the states of the wastes, aptly. It will considerably reduce any discrepancies that may occur due to the lack of information available during a particular time. Accordingly, this paper proposes a novel approach towards waste management combined with the internet of things to reduce the problems that would occur due to the accumulation of wastes and hence improvise waste collection/management process. Additionally, an innovative feature which generates revenue and creates business opportunities for waste management companies is introduced via advertisement solution based on network-attached storage technology.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Automated diagnosis of attacks in internet of things using machine
           learning and frequency distribution techniques

    • Authors: Toufik Ghrib; Mohamed Benmohammed, Purnendu.Shekhar Pandey
      Abstract: The Internet of Things (IoT) is the interconnection of things around us to make our daily process more efficient by providing more comfort and productivity. However, these connections also reveal a lot of sensitive data. Therefore, thinking about the methods of information security and coding are important as the security approaches that rely heavily on coding are not a strong match for these restricted devices. Consequently, this research aims to contribute to filling this gap, which adopts machine learning techniques to enhance network-level security in the low-power devices that use the lightweight MQTT protocol for their work. This study used a set of tools tools and, through various techniques, trained the proposed system ranging from Ensemble methods to deep learning models. The system has come to know what type of attack has occurred, which helps protect IoT devices. The log loss of the Ensemble methods is 0.44, and the accuracy of multi-class classification is 98.72% after converting the table data into an image set. The work also uses a Convolution Neural Network, which has a log loss of 0.019 and an accuracy of 99.3%. It also aims to implement these functions in IDS.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Vietnamese character recognition based on CNN model with reduced character

    • Authors: Thi Ha Phan; Duc Chung Tran, Mohd Fadzil Hassan
      Abstract: This article will detail the steps to build and train the convolutional neural network (CNN) model for Vietnamese character recognition in educational books. Based on this model, a mobile application for extracting text content from images in Vietnamese textbooks was built using OpenCV and Canny edge detection algorithm. There are 178 characters classes in Vietnamese with accents. However, within the scope of Vietnamese character recognition in textbooks, some classes of characters only differ in terms of actual sizes, such as “c” and “C”, “o” and “O”. Therefore, the authors built the classification model for 138 Vietnamese character classes after filtering out similar character classes to increase the model's effectiveness.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Measuring prevailing practices of healthcare professional on electronic
           health record through the lens of Iraq

    • Authors: Murtaja Ali Saare; Alia Ahmed Mahdi, Saima Anwar Lashari, Sari Ali Sari, Norhamreeza Abdul Hamid
      Abstract: Paper based approach to clinical documentation such as handwritten notes among health care providers are cause of errors in medical field. Therefore, health record system needs to be replaced with electronic health record (EHR). Many health professionals in developing countries specifically in Iraq refuse to use the systems implemented for their benefits due to many reasons. Thus, the use of electronic services is important for successful electronic health implementations. Therefore, this study is intended to identify the main factors affecting the intention of use of the electronic health record in Iraq. Health professional staff who work in the main hospital in Dhi-Qar is chosen because this province is the first local province that implemented many electronic projects. The present study examined use of user acceptance of technology, based on the technology acceptance model (TAM). Moreover, the quantitative method approach for data collection using survey from staff who work in the main hospital in Dhi-Qar. Data was analyzed using Structural Equation Modeling using AMOS. The results indicated significant relationship between Ease of Use, Usefulness, Usefulness, Attitude, and Intention of use of EHR. These finding have implementation for decision makers in Iraq government to improve future implementation of e-health services.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Comparison of the trend moment and double moving average methods for
           forecasting the number of dengue hemorrhagic fever patients

    • Authors: Dyna Marisa Khairina; Rizka Khairunnisa, Heliza Rahmania Hatta, Septya Maharani
      Abstract: Spread of Dengue Hemorrhagic Fever (DHF) is influenced by an increase in air temperature due to changes in weather and population density so that there is a lot of exchange of dengue virus through the bite of the Aedes aegypti mosquito. Forecasting models are needed to predict the number of DHF patients in the future so that monitoring of the number of DHF patients can be carried out as anticipation and consideration of decision making. Forecasting the number of patients is based on actual data within 2 (two) previous years by comparing the two methods, namely trend moment and double moving average. To measure the accuracy of the forecasting results from the two forecasting methods, tracking signal and moving range are used. Based on the test results, it shows that the forecasting results are said to be good because no one has passed the upper control limit and lower control limit values so that the difference between the actual data and the forecasting results is not too significant and the trend moment more recommended because the difference in actual data and forecasting results are approached and shown in the pattern graph by looking at the data difference in each period.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • The COVID-19 fake news detection in Thai social texts

    • Authors: Pakpoom Mookdarsanit; Lawankorn Mookdarsanit
      Abstract: One important obstruction against Thai COVID-19 recovery is fake news shared on social media that is one of the “Artificial Intelligence Open Issues against COVID-19” reported by Montreal.AI. Misinformation spread is one of the main cyber-security threats that should be filtered out as the IDS for maintaining COVID-19 information quality. To detect fake news in Thai texts, Thai-NLP techniques are necessary. This paper proposes a state-of-the-art Thai COVID-19 fake news detection among word relations using transfer learning models. For pre-training from the global open COVID-19 datasets, the source dataset is constructed by English to Thai translating. The novel feature shifting is formulated to enlarge Thai text examples in target dataset. Machine translation can be used for constructing Thai source dataset to cope with the lack of local dataset for future Thai-NLP applications. To lead the knowledge in Thai text understanding forward, feature shifting is a promising accuracy improvement in fine-tuning stage.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Real-time monitoring of clinic risks using an integrated RFID-FA scheme

    • Authors: Nisreen A. Hussein; Mohammed M. Fayyadh
      Abstract: Patient safety is a global public health concern because of increases in the number of mistreatments due to the improper identification of patients or the improper administration of drugs. Risk in clinic management refers to the systematic process used to specify, control, and analyze organizational risks. The present article developed a new method to detect different objects automatically in real-time by monitoring and controlling the hospital workflow using radio frequency identification (RFID). The system methodology starts with identifying the functional area by detecting the room optical characters. Then clustering and matching the symmetrical functional area using histogram matching technique. For the monitoring process, the radio frequency network planning RNP has been used. Density-based scan algorithm (DBSCAN) was used for clustering and extracting the area, then all gathered data transferred to the firefly algorithm to track drug distribution and specify doctor and nurse locations. The simulation results observe real-time tracking and identification of people and drugs based on hospital zone designs. The results present 87% tag real-time coverage for managing and monitoring human inside the hospital. The effectiveness of this system shows that it was useful in monitoring clinic operations and effective for a hospital network solution.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • The search for science and technology verses in Qur’an and hadith

    • Authors: Ichsan Taufik; Mohamad Jaenudin, Fatimah Ulwiyatul Badriyah, Beki Subaeki, Opik Taupik Kurahman
      Abstract: Currently, the Vector Space Model algorithm has been widely implemented for the document search feature because of its reliability in retrieving information. One of them in the search for verses of the Qur'an based on the translation. However, if the phrase or word used is different (even though it has one meaning) with the word in the document in the database, the system will not display the verse. As we know that the Qur'an has a very deep meaning, so an interpretation of the verse is needed. Therefore, this research focuses on implementing the Vector Space Model (VSM) algorithm for searching verses and hadiths in science and technology by using the discussion parameters of these verses or hadiths. The test results obtained with 20 keyword samples using metric recall were 81% with an average time of 2.24 seconds.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Recent research in finding the optimal path by ant colony optimization

    • Authors: Sari Ali Sari; Kamaruddin Malik Mohamad
      Abstract: The computation of the optimal path is one of the critical problems in graph theory. It has been utilized in various practical ranges of real world applications including image processing, file carving and classification problem. Numerous techniques have been proposed in finding optimal path solutions including using ant colony optimization (ACO). This is a nature-inspired metaheuristic algorithm, which is inspired by the foraging behavior of ants in nature. Thus, this paper study the improvement made by many researchers on ACO in finding optimal path solution. Finally, this paper also identifies the recent trends and explores potential future research directions in file carving.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Overview about GIS multi-criteria spatial analysis for micro hydropower
           plant site suitability in South Ogan Komering Ulu District, South
           Sumatera, Indonesia

    • Authors: Wawan Hendriawan Nur; Yuliana Yuliana, Yuliana Susilowati, Yugo Kumoro, Yunarto Yunarto
      Abstract: Morphology in South OKU District is the potential of a micro hydropower plant (MHPP) as an alternative power source. This potential has not been fully utilized, although many un-electrified villages are in several remote areas. Identification planning for MHPP is one of the most critical planning tasks and requires excellent multi-criteria spatial analysis. GIS and multi-criteria analysis have played an essential role in analyzing suitable locations for MHPP development. GIS and multi-criteria spatial analysis consist of detailed investigations of ongoing sites and suitability for specific planning. This research aims to overview GIS multi-criteria spatial analysis for MHPP site suitability based on electricity South OKU demands. The most critical data and criteria to decide the best site suitability are un-electrified villages, rivers, land use, slope, landslide vulnerability, and elevation. All of the data were generated into the raster data format. Quantitative modeling used AHP as a multi-criteria analysis method, and a weighted score is determined by considering the comparison of each criterion. Finally, the criterion layer was calculated by open-source QGIS to create a site suitability map. The field study verified the resulting map, and there is a match between the preferred locations and the field survey. The research results preferred Sungai Are, Sindang Danau, and Kisam Tinggi Sub-district as the best suitability for MHPP development.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Rasefiberry: Secure and efficient Raspberry-Pi based gateway for smarthome
           IoT architecture

    • Authors: Vincent Simadiputra; Nico Surantha
      Abstract: Internet-of-Things or IoT technology becomes essential in everyday lives. The risk of security and privacy towards IoT devices, especially smarthomes IoT gateway device, becoming apparent as IoT technology progressed. The need for affordable, secure smarthome gateway device or router that smarthome user prefer. The problem of low-performance smarthome gateways was running security programs on top of smarthome gateway programs. This problem motivates the researcher designing a secure and efficient smarthome gateway using Raspberry Pi hardware as an affordable smarthome gateway device and able to run both smarthome gateways and security programs. In this research, researchers implemented snort as intrusion detection system (IDS), openHab as IoT gateway applications, and well-known encryption algorithms for file encryption in Raspberry PI 3B+ model. The researcher evaluated Snort capability on network attacks and compared each of the well-known encryption algorithm efficiency. From the result, we found Rasefiberry customized snort configuration for Raspberry pi 60 percent of the simulated network attacks. Twofish encryption algorithms were found to have best encryption time, throughput, and power consumption compared to other encryption algorithms in the research. Rasefiberry architecture successfully processes both lightweight security programs and Openhab smarthome gateway programs with a lowperformance computing device such as Raspberry Pi.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Scaled conjugate gradient ANN for industrial sensors calibration

    • Authors: Karam Mazin Zeki Othman; Abdulkreem M Salih
      Abstract: In this paper, artificial neural network is used to calibrate sensors that are commonly used in industry. Usually, such sensors have nonlinear input output characteristic that makes their calibration process rather inaccurate and unsatisfied. Artificial neural network is utilized in an inverse model learning mode to precisely calibrate such sensors. The scaled conjugate gradient (SCG) algorithm is used in the learning process. Three types of industrial sensors which are gas concentration sensor, force sensors and humidity sensors are considered in this work. It is found that the proposed calibration technique gives fast, robust and satisfactory results.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Application of Content Based Image Retrieval in Digital Image Search

    • Authors: Syamsul Yakin; Tasrif Hasanuddin, Nia Kurniati
      Abstract: Multimedia data is growing rapidly in the current digital era, one of which isdigital image data. The increasing need for a large number of digital imagedatasets makes the constraints faced eventually drain a lot of time and causethe process of image description to be inconsistent. Therefore, a method isneeded in processing the data, especially in searching digital image data inlarge image dataset to find image data that are relevant to the query image.One of the proposed methods for searching information based on imagecontent is Content Based Image Retrieval (CBIR). The main advantage ofthe CBIR method is automatic retrieval process, compared to traditionalkeyword. This research was conducted on a combination of the HSV colorhistogram methods and the discrete wavelet transform to extract colorfeatures and textures features, while the chi-square distance technique wasused to compare the test images with images into a database. The resultshave showed that the digital image search system with color and texturefeatures have a precision value of 37.5% - 100%, with an average precisionvalue of 80.71%, while the percentage accuracy is 93.7% - 100% with anaverage accuracy is 98.03%.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Performance evaluation for vehicular ad-hoc networks based routing

    • Authors: Hussain Falih Mahdi; Mohammed Salah Abood, Mustafa Maad Hamdi
      Abstract: VANET is a branch of MANETS, where each vehicle is a node, and a wireless router will run. The vehicles are similar to each other will interact with a wide range of nodes or vehicles and establish a network. VANETs provide us with the infrastructure to build new solutions for improving safety and comfort for drivers and passengers. There are several routing protocols proposed and evaluated for improving VANET 's performance. The simulator is preferred over external experience because it is easy, simple, and inexpensive. In this paper, we choose AODV protocol, DSDV protocol, and DSR protocol with five different nodes density. For each protocol, as regards specific parameters like (throughput, packet delivery ratio, and end- to- end delay). On simulators that allow users to build real-time navigation models of simulations using VANET. Tools (SUMO, MOVE, and NS 2) were used for this paper, then graphs were plotted for evaluation using Trace-graph. The results showed the DSR is much higher than AODV and DSDV, In terms of throughput. While DSDV is the best choice because of the low average end to end delay. From the above, we conclude that each strategy has its own negative and positive aspects that make it ideally suited to a particular scenario than other scenarios.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Towards a formal analysis of the multi-robot task allocation problem using
           set theory

    • Authors: Farouq Zitouni; Ramdane Maamri, Saad Harous
      Abstract: Nowadays, the multi-robot task allocation problem is one of the most challenging problems in multi-robot systems. It concerns the optimal assignment of a set of tasks to several robots while optimizing a given criterion subject to some constraints. This problem is very complex, particularly when handling large groups of robots and tasks. We propose a formal analysis of the task allocation problem in a multi-robot system, based on set theory concepts. We believe that this analysis will help researchers understand the nature of the problem, its time complexity, and consequently develop efficient solutions. Also, we used that formal analysis to formulate two well-known taxonomies of multi-robot task allocation problems. Finally, a generic solving scheme of multi-robot task allocation problems is proposed and illustrated on assigning papers to reviewers within a journal.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Realistic Influence Maximization based on Followers Score and Engagement
           Grade on Instagram

    • Authors: Kristo Radion Purba; Yulia Yulia
      Abstract: In recent years, the emergence of social media influencers attracts the study of a realistic influence maximization (IM) technique. The theoretical performance of IM has become matured. However, it is not enough since IM has to be implemented in a social media environment. Realistic IM algorithms and diffusion models have been proposed, such as the addition of user factors or a learning agent. However, most studies still relied on the influence spread benchmark, which makes the usefulness questionable. This research is among the first IM study using Instagram data. In this study, two diffusion models are proposed, which are based on the original IC and LT models, with the addition of the engagement grade (EG) factor. An algorithm called IMFS (IM with Followers Score) is proposed to accommodate the new models as well as IC and LT. In addition, realistic benchmark methods are proposed, namely the average engagement of the activated users, and the overlapping between post likers and activated users. The result shows that the proposed models are 2-3x more realistic if compared to IC and LT.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A GMM supervector approach for spoken Indian language identification for
           mismatch utterance length

    • Authors: Aarti Bakshi; Sunil Kumar Kopparapu
      Abstract: Gaussian Mixture Model-Universal Background Model (GMM‑UBM) supervectors are used to identify spoken Indian languages. The supervectors are calculated from short-time MFCC, its first and second derivatives. The UBM builds a generalized Indian language model, and mean adaptation transforms it to a duration normalized language-specific GMM. Multi-class support vector machine and artificial neural network classifiers are used to identify language labels from the supervectors. Experimental evaluations are performed using 30 sec speech utterances from nine Indian languages comprised five Indo-Aryan and four Dravidian languages, extracted from All India Radio broadcast news data-set. Eight smaller duration data-sets were manually derived to study the effect of training and test duration mismatch. In mismatch conditions, identification accuracy decreases with a decrease in test and train utterance duration. Investigations showed that the 32-mixture model with ANN classifier has optimal performance.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Locating and Sizing of Capacitor Banks and Multiple DGs in Distribution

    • Authors: Mehrdad Ahmadi Kamarposhti; Seyed Mohsen Mousavi Khormandichali
      Abstract: DG sources have been introduced as one of the most widely used and effective methods among various methods providing losses reduction in power systems. In this paper, the artificial bee colony algorithm has been employed with the aim of determining location and capacity of distributed generations (DGs) and capacitor banks (CBs) in distribution systems. The proposed objective function includes power losses and ENS reliability index, which is used by deploying weight coefficients as objective function in the algorithms. Accordingly, the standard 37-bus network have been used for studies. The Simulation results demonstrate that the artificial bee colony algorithm is more effective in all sections and has higher capability in reducing losses and improving reliability as well.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • An intelligent digital low voltage power factor optimizer

    • Authors: Mustafa Ahmed Nayyef; Yasir Abdulhafedh Ahmed, Omar Kamil Dahham Alazzawi
      Abstract: In this paper, an intelligent digital low voltage power factor optimizer has been built. This power factor optimizer operates according to the measurement the value of phase shift angle between both of current and voltage, thus the power factor has been measured. It is simply that it will improve the power factor through connecting a set of shunt capacitors in order to reach to an optimal value of the power factor (close to unity). The proposed intelligent digital power factor optimizer for low voltage is built and simulated using the software which is called electronic work bench package (EWB) Multisim. Finally, this optimizer presents a good result when applied to different loads and variable currents. This optimizer is feasible, affordable and ready to be implemented especially in countries that suffer from higher prices of electrical power.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A new T-circuit model of wind turbine generator for power system steady
           state studies

    • Authors: Rudy Gianto; Kho Hie Khwee
      Abstract: Modeling of wind power plant (WPP) is a crucial issue in power system steady state (i.e. load flow) studies. In this paper, a new model of WPP is proposed. Similar to the previous T-circuit based models, it is also developed based on equivalent T-circuit of the WPP induction generator.  However, unlike in the previous models, the mathematical formulation of the new model is shorter and less complicated. Moreover, the derivation of the model in the present work is also much simpler. Only minimal mathematical operations are required in the process. Furthermore, the rotor voltage value of the WPP induction generator is readily available as an output of the proposed new model. This rotor voltage value can be used as a basis to calculate the induction generator slip. Validity of the new method is tested on a representative 9-bus electrical power system installed with WPP. Comparative studies between the proposed method (new model) and other method (previous model) are also presented.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Hardware-in-the-loop based comparative analysis of speed controllers using
           nonlinear control for two-mass system using induction motor drive fed by
           voltage source inverter with ideal control performance of stator current

    • Authors: VO THANH HA; Tung Lam Nguyen, Vo Thu Ha
      Abstract: A comparative study of speed control performance of an induction motor drive system connecting to a load via a non-rigid shaft. The nonrigidity of the coupling is represented by stiffness and damping coefficients deteriorating speed regulating operations of the system and can be regarded as a two-mass system. In the paper, the ability of flatness based and Backstepping controls in control the two-mass system is verified through comprehensive hardware-in-the-loop experiments and with the assumption of ideal stator current loop performance. Step-by-step control design procedures are given, in addition, system responses with classical PID control are also provided for parallel comparisons.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • An investigation on the application and challenges for wide area
           monitoring and control in smart grid

    • Authors: Marwan Ahmed Abdullah Sufyan; Mohd Zuhaib, Mohd Rihan
      Abstract: The complexity and dynamics of the modern power system are continuously changing due to the penetration of a large number of renewable energy sources and changing load patterns. These growing complexities have caused numerous outages around the world, primarily due to the lack of situational awareness about the grid operating states. Rectification of this problem requires advanced sensing technology to accurately capture the dynamics of the system for better monitoring and control. Measurement of synchrophasors is a potential solution to improve situational awareness in the grid. The synchrophasors technology is now widely accepted throughout the world and has the potential to replace the existing SCADA system in monitoring and control of the power system. Their installation enables efficient resolution to substantially improve transmission system planning, maintenance, operation, and energy trading. This paper reviews the state of the art potential applications that the PMU based WAMC offers to the power system. It also includes technical perspectives, challenges, and future possibilities.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A comparative study of performance of AC and DC electric drive control
           systems with variable moment of inertia

    • Authors: Addasi E. Said; Abdullah M. Eial Awwad
      Abstract: In electric drive control systems, the main goal is to maintain the driving motor speed to meet the mechanism’s requirements. In some practical industrial applications the mechanically-coupled load to the motor shaft has a varying mass during the system operation. Therefore, the change of mass changes the value of the moment of inertia of the system. The moment of inertia impacts the system operation, particularly the transient performance. Therefore, the variation of moment of inertia on the motor shaft during its operation creates additional challenges to accomplish a high-quality speed control. The main purpose of the current work is to study the impact of the variation of moment of inertia on the performance of both ac and dc electric drive control systems and to make a comparison between them. A mathematical analysis and simulations of the control system models had been presented; one time with three-phase induction motor and another time with dc motor, both with variable moment of inertia. A simulation of both systems had been accomplished using the Simulink software in Matlab. The simulation results of operation of these systems have been analysed in order to get useful conclusions and recommendations for the electric drive control system designer.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A streamlined 17-level cascaded H-bridge multilevel converter with solar
           PV integration

    • Authors: Muhammad Hamza Shahbaz; Kashif Amjad, Naqash Ahmad, Arslan Ahmad Amin, Sajid Iqbal, Muhammad Gufran Khan, Muhammad Adnan
      Abstract: The quest for a green electrical power system has increased the use of renewable energy resources and power electronic converters in the existing power system. These power electronic converters, however, are a major cause of harmonics and result in the degradation of power quality. In the last two decades, researchers have proposed various designs of multilevel converters to minimize these harmonic distortions, however, a comprehensive solution for stand-alone solar photovoltaic (PV) systems with low THD is still missing in the present body of knowledge. This paper proposes a single-phase 17-level Cascaded H-Bridge Multilevel Converter (CHMC) model for a stand-alone system using solar PV arrays. The proposed model employs eight different flexible PV arrays that can be replaced with DC voltage sources when required to meet the load demand. The proposed model does not include any capacitor and filter thus saving a lot of cost in the overall system. The model has been implemented in the Simulink environment using a model-based design approach. The simulation results show that the proposed model has reduced the total harmonic distortion (THD) to almost 7% as compared to the existing models. The cost comparison of the proposed converter also proved its economic benefit over other types. 
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Controller design for underwater robotic vehicle based on improved whale
           optimization algorithm

    • Authors: Mustafa Wassef Hasan; Nizar Hadi Abbas
      Abstract: This paper presents the impact of introducing a two-controller on the linearized autonomous underwater vehicle (AUV) for vertical motion control. These controllers are presented to overcome the sensor noise of the AUV control model that effect on the tolerance and stability of the depth motion control. linear quadratic Gaussian (LQG) controller is cascaded with AUV model to adapt the tolerance and the stability of the system and compared with FOPID established by the improved whale optimization algorithm (IWOA) to identify which controlling method can make the system more harmonize and tolerable. The developed algorithm is based on improving the original WOA by reshaping a specific detail on WOA to earn a warranty that the new IWOA will have values for the update position lower than the identified lower-bound (LB), and upper-bound (UB). Furthermore, the algorithm is examined by a set of test functions that include (unimodal, multimodal and fixed dimension multimodal functions). The privileges of applying IWOA are reducing the executing time and obtaining the semi-optimal objective function as compared with the original WOA algorithm and other popular swarm-intelligence optimization algorithms.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Design and development of sensorless based 5-DOF bilaterally controlled
           surgical manipulator: A prototype

    • Authors: Sakol Nakdhamabhorn; M. Branesh Pillai, Jackrit Suthakorn
      Abstract: Minimally invasive surgery (MIS) is one of the most challenging tasks in surgical procedures due to the lack of visibility of the surgical area, instrument orientation, and depth perception. A tele-operated robot assisted minimally invasive surgery is developed to enhance a surgeon's hand dexterity and accuracy. To perform MIS, the surgeon controls a slave manipulator via a master manipulator, so the force feedback and motion feedback are required to imitate an amount of action and reaction force between master and slave manipulator. The complicated MIS requires more complex surgical manipulator with multi DOFs and multiple force feedback. The limitation of multiple DOFs force feedback is a bandwidth of torque sensors. Therefore, this study proposes a sensorless based 5-DOF Bilaterally controlled surgical manipulation. In this research disturbance observer (DOB) is used to identify the internal disturbance of the system, which is used to estimate the reaction torque. This research mainly focuses on a 5-DOF bilaterally controlled surgical manipulator to maintain a position and additional force. The result of torque error in contact motion is less than 2%, the non-contact motion error is not over 5%, and it is evident that the error is always less than 0.3% for the position response.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Sigmoid PID based adaptive safe experimentation dynamics algorithm of
           portable duodopa pump for Parkinson’s disease patients

    • Authors: Najwa Hidayah Abdul Razak Ramesh; Mohd Riduwan Ghazali, Mohd Ashraf Ahmad
      Abstract: This paper emphasizes on the development of an appropriate closed-loop control strategy for traditional portable duodopa pump (PDP); thereby ensuring an automated drug infusion without wearing off. In particular, a sigmoid proportional integral derivative (SPID) controller is adopted to control the blood plasma level of dopamine. The parameters of SPID controller are tuned using the adaptive safe experimentation dynamics (ASED) algorithm. The efficiency of the suggested SPID-ASED is evaluated by concerning the convergence plot of the cost function, the amount of dopamine in the blood plasma (BP) of the patient, the statistical analysis of cost function, norm of error and norm of input, and time responses specifications. The simulation results show that the proposed SPID-ASED outperforms the standard PID controller in terms of better control accuracy with minimum overshoot and settling time.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Optimum speed controller structure utilizing the MCA approach

    • Authors: Khulood Moosa Omran; Basil Hani Jasim, Kadhim H. Hassan
      Abstract: In this paper, an optimal speed controller for dc motor is considered using a PID controller and tuned its parameters of gain to offer an optimal solution by using a modified camel algorithm MCA approach. The proposed MCA scheme was applied to solve the difficulty of getting the optimum gains of PID parameters. The MCA has good evolutionary speed with the simple construction of optimization depend on camel searching performance. The characteristics of the MCA algorithm was confirmed by optimizing the gains parameters of proportional, integral, derivative PID controller. The performance of PID-MCA is comparing with a classic PID controller enhanced with GA genetic algorithm optimization method to tune the gain parameters of the speed controller system. It was shown that the utilize of optimization processes indicated better performance for the MCA procedure in term of speed of execution and the size of memory compared with the GA method by applying computer simulations analysis. The proposed scheme has an efficient feature that includes the ease of implementation, good efficiency of computational performances with stable convergence characteristics. The results indicated that the proposed MCA scheme is a useful tool for searchability, produced efficient outcomes compared with the GA optimized method when applied in the proposed system.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • A cost-effective GPS-aided autonomous guided vehicle for global path

    • Authors: Gorgees Akhshirsh; Nawzad Al-Salihi, Oussama H. Hamid
      Abstract: This paper presents a robotic platform of a cost-effective GPS-aided autonomous guided vehicle (AGV) for global path planning. The platform is made of a mechanical radio controlled (RC) rover and an Arduino Uno microcontroller. An installed magnetic digital compass helps determine the right direction of the RC rover by continuously synchronising the heading and bearing of the vehicle. To ensure effective monitoring of the vehicle's position as well as track the corresponding path, an LCD keypad shield was, further, used. The contribution of the work is that the designed GPS-aided AGV can successfully navigate its way towards a destination point in an obstacle-free outdoor environment by solely relying on its calculations of the shortest path and utilising the corresponding GPS data. This result is achieved with a minimum error possible that lies within a circle of one meter radius around the given destination. As a result, the devised GPS-aided AGV could be used in a variety of applications such as landmine detection and removal.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • State feedback linearization using block companion similarity

    • Authors: Kessal Farida; Hariche Kamel, Bentarzi Hamid, Boushaki Razika
      Abstract: In this research work, a new method is proposed for linearizing a class of nonlinear multivariable system; where the number of inputs divides exactly the number of states. The idea of proposed method consists in representing the original nonlinear system into a state-dependent coefficient form and applying block similarity transformations that allow getting the linearized system in block companion form. Because the linearized system’s eigenstructure can determine system performance and robustness far more directly and explicitly than other indicators, the given class multivariable system is chosen. Examples are used to illustrate the application and show the effectiveness of the given approach.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
  • Investigation of wireless magnetometer in sensing magnetic field changes
           at different car direction and speed

    • Authors: Chin Fhong Soon; Siti Hajar Aminah Ali, See Khee Ye, Munzilah Md Rohani, Kian Sek Tee, Marlia Morsin, Nafarizal Nayan, Chiok Chuan Lim
      Abstract: The embedment of induction loop underground for traffic volume monitoring caused damaging effects to the road and reduced road surface aesthetics. A wireless magnetometer implanted underground in a small uniform area was developed to detect three-axis magnetic flux changes due to the perturbation of vehicle passing over the sensor. In this project, a wireless magnetometer sensor system operating at a radio frequency of 2.4 GHz for detecting and transmitting Z-field data has been developed to investigate the patterns of magnetic field associated with the car directions and speed. This is the first report in revealing the responses of the sensor to different car speed and sensing directions. Field tests were conducted by car passes over in a direction in-line or countering the X and Y axes of the magnetometer. The results showed that the strong magnetic field density as low as -100 to -230 μT could be generated when a car passed over the sensor in a direction countering X and Y axes. The speed detection limit of the sensor is < 60 kmph. The X, Y and Z flux patterns obtained is important in designing an algorithm for accurate detection and counting of vehicles.
      PubDate: Thu, 01 Apr 2021 00:00:00 +000
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Heriot-Watt University
Edinburgh, EH14 4AS, UK
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