A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

  Subjects -> SCIENCES: COMPREHENSIVE WORKS (Total: 374 journals)
The end of the list has been reached or no journals were found for your choice.
Similar Journals
Journal Cover
ARO. The Scientific Journal of Koya University
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2410-9355 - ISSN (Online) 2307-549X
Published by Koya University Homepage  [1 journal]
  • Driver Drowsiness Detection Using Gray Wolf Optimizer Based on Voice

    • Authors: Sarah S. Jasim; Alia K. Abdul Hassan , Scott Turner
      Abstract: Globally, drowsiness detection prevents accidents. Blood biochemicals, brain impulses, etc., can measure tiredness. However, due to user discomfort, these approaches are challenging to implement. This article describes a voice-based drowsiness detection system and shows how to detect driver fatigue before it hampers driving. A neural network and Gray Wolf Optimizer are used to classify sleepiness automatically. The recommended approach is evaluated in alert and sleep-deprived states on the driver tiredness detection voice real dataset. The approach used in speech recognition is mel-frequency cepstral coefficients (MFCCs) and linear prediction coefficients (LPCs). The SVM algorithm has the lowest accuracy (71.8%) compared to the typical neural network. GWOANN employs 13-9-7-5 and 30-20-13-7 neurons in hidden layers, where the GWOANN technique had 86.96% and 90.05% accuracy, respectively, whereas the ANN model achieved 82.50% and 85.27% accuracy, respectively.
      PubDate: Mon, 05 Dec 2022 13:00:17 +000
  • Employing Neural Style Transfer for Generating Deep Dream Images

    • Authors: Lafta R. Al-Khazraji; Ayad R. Abbas, Abeer S. Jamil
      Abstract: In recent years, deep dream and neural style transfer emerged as hot topics in deep learning. Hence, mixing those two techniques support the art and enhance the images that simulate hallucinations among psychiatric patients and drug addicts. In this study, our model combines deep dream and neural style transfer (NST) to produce a new image that combines the two technologies. VGG-19 and Inception v3 pre-trained networks are used for NST and deep dream, respectively. Gram matrix is a vital process for style transfer. The loss is minimized in style transfer while maximized in a deep dream using gradient descent for the first case and gradient ascent for the second. We found that different image produces different loss values depending on the degree of clarity of that images. Distorted images have higher loss values in NST and lower loss values with deep dreams. The opposite happened for the clear images that did not contain mixed lines, circles, colors, or other shapes.
      PubDate: Thu, 01 Dec 2022 00:00:00 +000
  • Effect of Substrate Temperature on the Electrical Properties of Al-doped
           Zinc Oxide Films Deposited on Polyethylene Terephthalate

    • Authors: Mohammad G. Faraj
      Abstract: To prepare homogeneous thin films of zinc oxide (ZnO) doped with aluminum (Al) on a polyethylene terephthalate (PET) substrate at different temperatures (200-250 °C), the process is carried out by utilizing the chemical spraying pyrolysis approach. A study of the effects of substrate temperature on the Al-doped Zinc Oxide (AZO) films' electrical characteristics and roughness is performed. The measurements of atomic force microscopy (AFM) shows that the root mean square (RMS) roughness of the AZO films is increased with the increase of PET substrate temperature. Hall measurements show that the electrical resistivity decreases as the substrate temperature increases. Upon the increment of substrate temperature, there is an increase in the carrier concentration value from 9.98 × 1019 to 5.4 × 1020 cm−3 and an increase in the carrier mobility value from 5.5 to 9.76 cm2.(V. S)−1.
      PubDate: Wed, 23 Nov 2022 00:00:00 +000
  • Some Enzymatic and Non-enzymatic Antioxidants Response under Nickel and
           Lead Stress for Some Fabaceae Trees

    • Authors: Sargul A. Khudhur; lkbal M. Albarzinji
      Abstract: This study investigates the effects of soil contamination by nickel and lead on some enzymatic and non-enzymatic antioxidants in addition to the nitrate reductase (NR) enzyme activity for Gleditsia triacanthos, Leucaena leucocephala, and Robinia pseudoacacia plant species. The results of this study show a significant increase in peroxidase enzyme activity and a significant decrease in catalase enzyme activity, proline, total carotenoids, and total carbohydrate content of leaves of the three species with increasing the concentration of Ni and Pb except for the total carbohydrate, which increased only for L. leucocephala species. Each NR enzyme activity and ascorbic acid content are increased significantly with increasing the concentration of Ni and Pb for G. triacanthos, L. leucocephala, and on the contrary, they decreased significantly for R. pseudoacacia species. From the result, we can conclude a general increase or decrease in leaves content of some antioxidants content for all the species, whereas there is some peculiarity according to the plant species regarding other contents, which in turn reflects different mechanisms of these species to tolerant heavy metal stress  
      PubDate: Sun, 20 Nov 2022 00:00:00 +000
  • Evaluation and Assessment of Existing Design Codes and Standards for
           Building Construction

    • Authors: Diman N. Abdulqader; Dawood S. Atrushi
      Abstract: Building design codes (BDC) are used to control the construction industry in general and building design in particular. The BDC offers the construction sector with a standard language and set of requirements. There are several BDCs developed and utilized for construction purposes throughout the world. Certain design codes are employed in structural design to assure the structure’s health and safety, as well as its cost-effectiveness. It also assures that the structure is sufficiently sturdy to endure all potential climatic conditions, bear its intended load, and is integrated to ensure effective use of building materials and resources. This research aims to compare various building construction design codes to identify and explore the most appropriate standard in terms of safe design, economics, and availability of details. In Kurdistan and different parts of Iraq, many international companies have designed building structures with various codes during the past 20 years. This is a bad condition since the government has no control over the construction of the buildings, which includes both the code and the building materials. There is currently no overview of the design codes in use in Kurdistan, nor is it clear whether they are congruent with what students’ study in institutions.
      PubDate: Sat, 19 Nov 2022 09:51:04 +000
  • Landfill Site Selection for Solid Waste Using GIS-based Multi-Criteria
           Spatial Modeling

    • Authors: Rostam S. Aziz
      Abstract: This study gains insight into landfill sites with the observance of all the political, economic and environmental difficulties for the implementing appropriate site measures by adopting a collection of geospatial technique and weighted linear combination (WLC) in TqaTaq sub-district. In the current study, there are several areas determined as appropriate sites for landfill location. In this study, the criteria of distance from the roads, the city center, rivers, surface water, and land use map were used. According to this analysis, only 25.21% of the TaqTaq sub district is suitable for a landfill. Thus, basing on the findings, 20.93% of the concerned sub-district is regarded as least adequate site for this mission, whereas only 3.25% of the area is regarded as moderate suitable. Thus, this study has found out that 1.03% area is the most suitable. The majority of suitable area was located in the North of the Town, where waste production is more than other locations. It should be noted that based on the outcome of this study, the amount of waste produced in the TaqTaq Town for the next 10 years, from 2022 to 2032, is predicted to be about 4080 tons. According to the density calculated for the waste of this area and considering the height of 4 m for the landfill center, in the next 10 years, about 3000 m2 of land is required for the landfill location. Since the suitable area found in this research is about 15 hectares.
      PubDate: Thu, 17 Nov 2022 00:00:00 +000
  • Medicinal Plants Traditionally Used in the Management of COVID-19 in
           Kurdistan Region of Iraq

    • Authors: Mahmoud D. Abdulrahman; Fattma Z. Mohammed, Saber W. Hamad, Harmand A. Hama, Abubakar A. Lema
      Abstract: Coronaviruses are infectious respiratory tract illnesses, but they can also affect the digestive tract and infect both humans and animals. The new coronavirus results in complicated health problems all over the world. The most urgent concern of all researchers around the world has been the treatment of the virus. The following study aimed to use quantitative ethnobotany to help scientist in addressing the deadly virus. Expert sampling method was adopted with the aid of an in-depth interview guide. Thirty-nine respondents were interviewed. Eighty-one medicinal plant species from 35 families were documented. Males 25 (64.1%) constitute the greater percentage of the total respondents. Majority of the respondents had formal education. Eighty-one medicinal plant species from 35 families were documented. Leaves are the most utilized 25.8 followed by seed 17.7 and fruits 12.1%, respectively. Relative frequency of citation ranged from 0.5 to 0.9, whereas the FL value ranged from 0.4 to 0.85, revealing how effective the documented plant species are in the management of COVID-19 in the region. A greater amount of research into documented medicinal plants is warranted because of the high likelihood that they contain many active ingredients.
      PubDate: Tue, 15 Nov 2022 00:00:00 +000
  • Investigation of Bacterial Persistence and Filaments Formation in Clinical
           Klebsiella pneumoniae

    • Authors: Sarah N. Aziz; Mohammed F. Al Marjani
      Abstract: Bacterial persistence is recognized as a major cause of antibiotic therapy failure, causing biofilms, and chronic intractable infections. The emergence of persisters in Klebsiella pneumoniae isolates has become a worldwide public health concern. The goal of the present study is to investigate the formation of persister cells beside filaments in Iraqi K. pneumoniae isolates. A total of fifty clinical K. pneumoniae isolates were collected from different clinical specimens and identified using the genotypic identification by using specific primer (rpoB gene) from housekeeping genes. Persister cells investigation is performed by exposure of stationary phase K. pneumoniae isolates to a high concentration of ciprofloxacin (×10 MIC) and counting the number of viable persister cells by CFU counts. Bacterial filament formation is detected and measured by light microscope scanning electron microscope. The results show the  bility of these pathogenic bacteria to form persister cells to survive the bactericidal antibiotics and to cause chronic infection.Furthermore, persistent isolates have the ability to change in shape and size extensively, about 4 times increase in cell length than their normal length. These phenomena are possibly the initial stages of bacterial resistance prevalence.
      PubDate: Fri, 28 Oct 2022 00:00:00 +000
  • Classification of Different Shoulder Girdle Motions for Prosthesis Control
           Using a Time-Domain Feature Extraction Technique

    • Authors: Huda M. Radha; Alia K. Abdul Hassan, Ali H. Al-Timemy
      Abstract: Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, which are root mean square, four-order autoregressive, wavelength, slope sign change, zero crossing (ZC), mean absolute value, and cardinality. In this article, the time-domain features were first extracted from the EMG and acceleration signals. Then, the spectral regression (SR) and principal component analysis dimensionality reduction methods are employed to identify the most salient features, which are then passed to the linear discriminant analysis (LDA) classifier. EMG and axial acceleration signal datasets from six intact-limbed and four amputee participants exhibited an average classification error of 15.68 % based on SR dimensionality reduction using the LDA classifier.
      PubDate: Sat, 22 Oct 2022 20:00:15 +000
  • Determination of the Potassium Content in Fruit Samples by Gamma
           Spectrometry to Emphasize its Health Implications

    • Authors: Dedawan S. Saleh; Saddon T. Ahmad, Sarmad R. Kareem
      Abstract: In this study, the activity concentration of 40K and its’ concentrations in 24 different types of fruits were determined using high purity germanium (HPGe) and sodium iodide scintillation (NaI) detectors. The results of the two measurements are consistent. The Maximum and minimum activities of 40K in dry samples were 750.61 ± 11.88 and 15.64 ± 0.86 Bq kg−1 in apricot and olive, respectively, while in fresh samples they were 152.27 ± 2.12 and 1.99 ± 0.11 Bq kg−1 in dates and olive, respectively. The highest and lowest potassium contents were 489.81 and 6.42 mg/100gm in fresh dates and olives, respectively.  Drupe and Tropical fruits, as a fruit family, typically had the highest level of 40K activity and potassium concentration, whereas pome fruits showed the lowest levels. Many of these commonly consumed fresh fruits with rich potassium and water contents are lowering hypertension and improving the hydration status (HS) in people's nutrition. The rate of potassium-40 and total potassium concentration intake for a single unit or portion of the fruits was calculated.  
      PubDate: Thu, 20 Oct 2022 15:04:18 +000
  • Toxic Metals in Some Decorative Cosmetics and Nail Products

    • Authors: Bashdar I. Meena; Tara F. Tahir, Shalaw Z. Sdeeq, Khalid N. Sediq
      Abstract: Cosmetic marketing is one of the most profitable and fast increasing markets in Kurdistan Region of Iraq. In recent years, the use of cosmetics has witnessed a rapid increase, especially with the emergence of social media and its impact on this trade. The market is full of different cosmetic brands and nail products. Moderate and low-quality brands of cosmetic samples that available in the local markets were selected to investigate their heavy metals and chemical composition. Samples from face foundation, eye shadow, and nail polish products were taken and examined to evaluate the concentration of metals, that is, Hg, Pb, Cd, As, Mn, Cr, Ni, Co, Fe, Zn, Cu, and Al ions, using X-ray diffraction and X-ray fluorescence techniques. The examination results show high concentrations of Fe and Al metals in the lipstick samples whereas the Hg, Cd, Cr, and Ni were out of detection limit. Moreover, the results show contamination of Hg heavy metal in one of the examined nail polishes brands, whereas the rest of foundation and eye shadow samples show a higher concentration of Al and Fe. Curcumin, as a natural bio-friendly chelate, has been used to deplete metal ions using ultraviolet-visible Spectrophotometer.
      PubDate: Fri, 14 Oct 2022 00:00:00 +000
  • Data Analytics and Techniques

    • Authors: Safa S. Abdul-Jabbar; Alaa k. Farhan
      Abstract: Big data of different types, such as texts and images, are rapidly generated from the internet and other applications. Dealing with this data using traditional methods is not practical since it is available in various sizes, types, and processing speed requirements. Therefore, data analytics has become an important tool because only meaningful information is analyzed and extracted, which makes it essential for big data applications to analyze and extract useful information. This paper presents several innovative methods that use data analytics techniques to improve the analysis process and data management. Furthermore, this paper discusses how the revolution of data analytics based on artificial intelligence algorithms might provide improvements for many applications. In addition, critical challenges and research issues were provided based on published paper limitations to help researchers distinguish between various analytics techniques to develop highly consistent, logical, and information-rich analyses based on valuable features. Furthermore, the findings of this paper may be used to identify the best methods in each sector used in these publications, assist future researchers in their studies for more systematic and comprehensive analysis and identify areas for developing a unique or hybrid technique for data analysis.
      PubDate: Sat, 08 Oct 2022 05:48:49 +000
  • A Computational Model for Temperature Monitoring During Human Liver
           Treatment by Nd:YaG Laser Interstitial Thermal Therapy (LITT)

    • Authors: Bazhdar N. Mohammed; Dilshad S. Ismael
      Abstract: Describing heat transfer in biological organs is absolutely challenging because it is involved with many complex phenomena. Therefore, understanding the optical and thermal properties of living system during external irradiation sources such as laser interstitial thermal therapy (LITT) are too important for therapeutic purposes, especially for hyperthermia treatments. The purpose of this study was to determine a proper laser power and irradiation time for LITT applicator to irradiate liver tissue during hyperthermia treatment. For this aim, bioheat equation in one-dimensional spherical coordinate is solved by Green function method to simulate temperature distribution and rate of damage around irradiated target and how thermal and optical properties such as laser power, laser exposure time, and blood perfusion rate affect the rate of temperature distribution. Guiding equations according to the suggested boundary conditions are written and solved by MATLAB software. The outcomes show that increasing laser exposure time and power increase the temperature, especially at the nearest distance from the center of diffusion. Accordingly, a decrease in blood perfusion rate leads to decrease temperature distribution. The findings show that the model is useful to help the physicians to monitor the amount of heat diffusion by laser power during the treatment to protect healthy cells.
      PubDate: Mon, 26 Sep 2022 00:00:00 +000
  • An Investigation on Disparity Responds of Machine Learning Algorithms to
           Data Normalization Method

    • Authors: Haval A. Ahmed; Peshawa J. Muhammad Ali, Abdulbasit K. Faeq, Saman M. Abdullah
      Abstract: Data normalization can be useful in eliminating the effect of inconsistent ranges in some machine learning (ML) techniques and in speeding up the optimization process in others. Many studies apply different methods of data normalization with an aim to reduce or eliminate the impact of data variance on the accuracy rate of ML-based models. However, the significance of this impact aligning with the mathematical concept of the ML algorithms still needs more investigation and tests. To identify that, this work proposes an investigation methodology involving three different ML algorithms, which are support vector machine (SVM), artificial neural network (ANN), and Euclidean-based K-nearest neighbor (E-KNN). Throughout this work, five different datasets have been utilized, and each has been taken from different application fields with different statistical properties. Although there are many data normalization methods available, this work focuses on the min-max method, because it actively eliminates the effect of inconsistent ranges of the datasets. Moreover, other factors that are challenging the process of min-max normalization, such as including or excluding outliers or the least significant feature, have also been considered in this work. The finding of this work shows that each ML technique responds differently to the min-max normalization. The performance of SVM models has been improved, while no significant improvement happened to the performance of ANN models. It is been concluded that the performance of E-KNN models may improve or degrade with the min-max normalization, and it depends on the statistical properties of the dataset.
      PubDate: Mon, 19 Sep 2022 11:57:40 +000
  • Train Support Vector Machine Using Fuzzy C-means Without a Prior Knowledge
           for Hyperspectral Image Content Classification

    • Authors: Akar H. Taher
      Abstract: In this paper, a new cooperative classification method called auto-train support vector machine (SVM) is proposed. This new method converts indirectly SVM to an unsupervised classification method. The main disadvantage of conventional SVM is that it needs a priori knowledge about the data to train it. To avoid using this knowledge that is strictly required to train SVM, in this cooperative method, the data, that is, hyperspectral images (HSIs), are first clustered using Fuzzy C-means (FCM); then, the created labels are used to train SVM. At this stage, the image content is classified using the auto-trained SVM. Using FCM, clustering reveals how strongly a pixel is assigned to a class thanks to the fuzzification process. This information leads to gaining two advantages, the first one is that no prior knowledge about the data (known labels) is needed and the second one is that the training data selection is not done randomly (the training data are selected according to their degree of membership to a class). The proposed method gives very promising results. The method is tested on two HSIs, which are Indian Pines and Pavia University. The results obtained have a very high accuracy of the classification and exceed the existing manually trained methods in the literature.
      PubDate: Sat, 10 Sep 2022 07:56:23 +000
  • Machine Learning Algorithms for Detecting and Analyzing Social Bots Using
           a Novel Dataset

    • Authors: Niyaz Jalal; Kayhan Z. Ghafoor
      Abstract: Social media is internet-based technology and an electronic form of communication that facilitates sharing of ideas, documents, and personal information. Twitter is a microblogging platform and is the most effective social service for posting microblogs and likings, commenting, sharing, and communicating with others. The problem we are shedding light on in this paper is the misuse of bots on Twitter. The purpose of bots is to automate specific repetitive tasks instead of human interaction. However, bots are misused to influence people’s minds by spreading rumors and conspiracy related to controversial topics. In this paper, we initiate a new benchmark created on a 1.5M Twitter profile. We train different supervised machine learning on our benchmark to detect bots on Twitter. In addition to increasing benchmark scalability, various autofeature selections are utilized to identify the most influential features and remove the less influential ones. Furthermore, over-under-sampling is applied to reduce the imbalance effect on the benchmark. Finally, our benchmark compared with other stateof-the-art benchmarks and achieved a 6% higher area under the curve than other datasets in the case of generalization, improving the model performance by at least 2% by applying over-/undersampling.
      PubDate: Sat, 10 Sep 2022 07:55:28 +000
  • A New Design Approach for a Compact Microstrip Diplexer with Good Passband

    • Authors: Abbas Rezaei; Salah I. Yahya
      Abstract: This paper presents an efficient theoretical design approach of a very compact microstrip diplexer for modern wireless communication system applications. The proposed basic resonator is made of coupled lines, simple transmission line and a shunt stub. The coupled lines and transmission line make a U-shape resonator while the shunt stub is loaded inside the U-shape cell to save the size significantly, where the overall size of the presented diplexer is only 0.008 λg2 . The configuration of this resonator is analyzed to increase intuitive understanding of the structure and easier optimization. The first and second resonance frequencies are f o1 = 895 MHz and f o2 = 2.2 GHz. Both channels have good properties so that the best simulated insertion loss at the first channel (0.075 dB) and the best simulated common port return losses at both channels (40.3 dB and 31.77 dB) are achieved. The presented diplexer can suppress the harmonics acceptably up to 3 GHz (3.3 fo1 ). Another feature is having 31% fractional bandwidth at the first channel.
      PubDate: Thu, 25 Aug 2022 00:00:00 +000
  • In Silico Domain Structural Model Analysis of Coronavirus ORF1ab

    • Authors: Mohammed I. Jameel; Rabar J. Noori, Soma F. Rasul
      Abstract: The world today is battling with a coronavirus infection that is considered a global pandemic. Coronavirus infection is mainly attribute to the varying technique of the replication and release of different genomic components of the virus. The present study aims to establish the physical and chemical features, as well as the basic structural and functional properties of Coronavirus ORF1ab domain. A molecular approach was adopt in this study using the Swiss Model and Phyre2 server whereas the prediction of the active ligand binding sites was done using Phyre2. The analysis of the structure of the protein showed that it has good structural and heat stability, as well as better hydrophilic features and acidic in nature. Based on the Homology modeling, only two binding active sites were noted with catalytic function being mediated by Zn2+ as the metallic heterogeneous ligand for binding sites prediction. The proteins mostly exhibited helical secondary configurations. This study can help in predicting and understanding the role of this domain protein in active coronavirus infection.
      PubDate: Thu, 25 Aug 2022 00:00:00 +000
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762

Your IP address:
Home (Search)
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-