Subjects -> COMPUTER SCIENCE (Total: 2313 journals)
    - ANIMATION AND SIMULATION (33 journals)
    - ARTIFICIAL INTELLIGENCE (133 journals)
    - AUTOMATION AND ROBOTICS (116 journals)
    - CLOUD COMPUTING AND NETWORKS (75 journals)
    - COMPUTER ARCHITECTURE (11 journals)
    - COMPUTER ENGINEERING (12 journals)
    - COMPUTER GAMES (23 journals)
    - COMPUTER PROGRAMMING (25 journals)
    - COMPUTER SCIENCE (1305 journals)
    - COMPUTER SECURITY (59 journals)
    - DATA BASE MANAGEMENT (21 journals)
    - DATA MINING (50 journals)
    - E-BUSINESS (21 journals)
    - E-LEARNING (30 journals)
    - ELECTRONIC DATA PROCESSING (23 journals)
    - IMAGE AND VIDEO PROCESSING (42 journals)
    - INFORMATION SYSTEMS (109 journals)
    - INTERNET (111 journals)
    - SOCIAL WEB (61 journals)
    - SOFTWARE (43 journals)
    - THEORY OF COMPUTING (10 journals)

COMPUTER SCIENCE (1305 journals)                  1 2 3 4 5 6 7 | Last

Showing 1 - 200 of 872 Journals sorted alphabetically
3D Printing and Additive Manufacturing     Full-text available via subscription   (Followers: 27)
Abakós     Open Access   (Followers: 3)
ACM Computing Surveys     Hybrid Journal   (Followers: 29)
ACM Inroads     Full-text available via subscription   (Followers: 1)
ACM Journal of Computer Documentation     Free   (Followers: 4)
ACM Journal on Computing and Cultural Heritage     Hybrid Journal   (Followers: 5)
ACM Journal on Emerging Technologies in Computing Systems     Hybrid Journal   (Followers: 11)
ACM SIGACCESS Accessibility and Computing     Free   (Followers: 2)
ACM SIGAPP Applied Computing Review     Full-text available via subscription  
ACM SIGBioinformatics Record     Full-text available via subscription  
ACM SIGEVOlution     Full-text available via subscription  
ACM SIGHIT Record     Full-text available via subscription  
ACM SIGHPC Connect     Full-text available via subscription  
ACM SIGITE Newsletter     Open Access   (Followers: 1)
ACM SIGMIS Database: the DATABASE for Advances in Information Systems     Hybrid Journal  
ACM SIGUCCS plugged in     Full-text available via subscription  
ACM SIGWEB Newsletter     Full-text available via subscription   (Followers: 3)
ACM Transactions on Accessible Computing (TACCESS)     Hybrid Journal   (Followers: 3)
ACM Transactions on Algorithms (TALG)     Hybrid Journal   (Followers: 13)
ACM Transactions on Applied Perception (TAP)     Hybrid Journal   (Followers: 3)
ACM Transactions on Architecture and Code Optimization (TACO)     Hybrid Journal   (Followers: 9)
ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP)     Hybrid Journal  
ACM Transactions on Autonomous and Adaptive Systems (TAAS)     Hybrid Journal   (Followers: 10)
ACM Transactions on Computation Theory (TOCT)     Hybrid Journal   (Followers: 11)
ACM Transactions on Computational Logic (TOCL)     Hybrid Journal   (Followers: 5)
ACM Transactions on Computer Systems (TOCS)     Hybrid Journal   (Followers: 19)
ACM Transactions on Computer-Human Interaction     Hybrid Journal   (Followers: 15)
ACM Transactions on Computing Education (TOCE)     Hybrid Journal   (Followers: 9)
ACM Transactions on Computing for Healthcare     Hybrid Journal  
ACM Transactions on Cyber-Physical Systems (TCPS)     Hybrid Journal   (Followers: 1)
ACM Transactions on Design Automation of Electronic Systems (TODAES)     Hybrid Journal   (Followers: 5)
ACM Transactions on Economics and Computation     Hybrid Journal  
ACM Transactions on Embedded Computing Systems (TECS)     Hybrid Journal   (Followers: 4)
ACM Transactions on Information Systems (TOIS)     Hybrid Journal   (Followers: 18)
ACM Transactions on Intelligent Systems and Technology (TIST)     Hybrid Journal   (Followers: 11)
ACM Transactions on Interactive Intelligent Systems (TiiS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Internet of Things     Hybrid Journal   (Followers: 2)
ACM Transactions on Modeling and Performance Evaluation of Computing Systems (ToMPECS)     Hybrid Journal  
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)     Hybrid Journal   (Followers: 10)
ACM Transactions on Parallel Computing     Full-text available via subscription  
ACM Transactions on Reconfigurable Technology and Systems (TRETS)     Hybrid Journal   (Followers: 6)
ACM Transactions on Sensor Networks (TOSN)     Hybrid Journal   (Followers: 9)
ACM Transactions on Social Computing     Hybrid Journal  
ACM Transactions on Spatial Algorithms and Systems (TSAS)     Hybrid Journal   (Followers: 1)
ACM Transactions on Speech and Language Processing (TSLP)     Hybrid Journal   (Followers: 11)
ACM Transactions on Storage     Hybrid Journal  
ACS Applied Materials & Interfaces     Hybrid Journal   (Followers: 39)
Acta Informatica Malaysia     Open Access  
Acta Universitatis Cibiniensis. Technical Series     Open Access   (Followers: 1)
Ad Hoc Networks     Hybrid Journal   (Followers: 12)
Adaptive Behavior     Hybrid Journal   (Followers: 8)
Additive Manufacturing Letters     Open Access   (Followers: 3)
Advanced Engineering Materials     Hybrid Journal   (Followers: 32)
Advanced Science Letters     Full-text available via subscription   (Followers: 9)
Advances in Adaptive Data Analysis     Hybrid Journal   (Followers: 9)
Advances in Artificial Intelligence     Open Access   (Followers: 31)
Advances in Catalysis     Full-text available via subscription   (Followers: 7)
Advances in Computational Mathematics     Hybrid Journal   (Followers: 20)
Advances in Computer Engineering     Open Access   (Followers: 13)
Advances in Computer Science : an International Journal     Open Access   (Followers: 18)
Advances in Computing     Open Access   (Followers: 3)
Advances in Data Analysis and Classification     Hybrid Journal   (Followers: 52)
Advances in Engineering Software     Hybrid Journal   (Followers: 26)
Advances in Geosciences (ADGEO)     Open Access   (Followers: 19)
Advances in Human-Computer Interaction     Open Access   (Followers: 19)
Advances in Image and Video Processing     Open Access   (Followers: 20)
Advances in Materials Science     Open Access   (Followers: 19)
Advances in Multimedia     Open Access   (Followers: 1)
Advances in Operations Research     Open Access   (Followers: 13)
Advances in Remote Sensing     Open Access   (Followers: 59)
Advances in Science and Research (ASR)     Open Access   (Followers: 8)
Advances in Technology Innovation     Open Access   (Followers: 5)
AEU - International Journal of Electronics and Communications     Hybrid Journal   (Followers: 8)
African Journal of Information and Communication     Open Access   (Followers: 6)
African Journal of Mathematics and Computer Science Research     Open Access   (Followers: 5)
AI EDAM     Hybrid Journal   (Followers: 2)
Air, Soil & Water Research     Open Access   (Followers: 6)
AIS Transactions on Human-Computer Interaction     Open Access   (Followers: 5)
Al-Qadisiyah Journal for Computer Science and Mathematics     Open Access   (Followers: 2)
AL-Rafidain Journal of Computer Sciences and Mathematics     Open Access   (Followers: 3)
Algebras and Representation Theory     Hybrid Journal  
Algorithms     Open Access   (Followers: 13)
American Journal of Computational and Applied Mathematics     Open Access   (Followers: 8)
American Journal of Computational Mathematics     Open Access   (Followers: 6)
American Journal of Information Systems     Open Access   (Followers: 4)
American Journal of Sensor Technology     Open Access   (Followers: 2)
Analog Integrated Circuits and Signal Processing     Hybrid Journal   (Followers: 15)
Animation Practice, Process & Production     Hybrid Journal   (Followers: 4)
Annals of Combinatorics     Hybrid Journal   (Followers: 3)
Annals of Data Science     Hybrid Journal   (Followers: 14)
Annals of Mathematics and Artificial Intelligence     Hybrid Journal   (Followers: 16)
Annals of Pure and Applied Logic     Open Access   (Followers: 4)
Annals of Software Engineering     Hybrid Journal   (Followers: 12)
Annual Reviews in Control     Hybrid Journal   (Followers: 7)
Anuario Americanista Europeo     Open Access  
Applicable Algebra in Engineering, Communication and Computing     Hybrid Journal   (Followers: 3)
Applied and Computational Harmonic Analysis     Full-text available via subscription  
Applied Artificial Intelligence: An International Journal     Hybrid Journal   (Followers: 17)
Applied Categorical Structures     Hybrid Journal   (Followers: 4)
Applied Clinical Informatics     Hybrid Journal   (Followers: 4)
Applied Computational Intelligence and Soft Computing     Open Access   (Followers: 16)
Applied Computer Systems     Open Access   (Followers: 6)
Applied Computing and Geosciences     Open Access   (Followers: 3)
Applied Mathematics and Computation     Hybrid Journal   (Followers: 31)
Applied Medical Informatics     Open Access   (Followers: 11)
Applied Numerical Mathematics     Hybrid Journal   (Followers: 4)
Applied Soft Computing     Hybrid Journal   (Followers: 13)
Applied Spatial Analysis and Policy     Hybrid Journal   (Followers: 5)
Applied System Innovation     Open Access   (Followers: 1)
Archive of Applied Mechanics     Hybrid Journal   (Followers: 4)
Archive of Numerical Software     Open Access  
Archives and Museum Informatics     Hybrid Journal   (Followers: 97)
Archives of Computational Methods in Engineering     Hybrid Journal   (Followers: 5)
arq: Architectural Research Quarterly     Hybrid Journal   (Followers: 7)
Array     Open Access   (Followers: 1)
Artifact : Journal of Design Practice     Open Access   (Followers: 8)
Artificial Life     Hybrid Journal   (Followers: 7)
Asian Journal of Computer Science and Information Technology     Open Access   (Followers: 3)
Asian Journal of Control     Hybrid Journal  
Asian Journal of Research in Computer Science     Open Access   (Followers: 4)
Assembly Automation     Hybrid Journal   (Followers: 2)
Automatic Control and Computer Sciences     Hybrid Journal   (Followers: 6)
Automatic Documentation and Mathematical Linguistics     Hybrid Journal   (Followers: 5)
Automatica     Hybrid Journal   (Followers: 13)
Automatika : Journal for Control, Measurement, Electronics, Computing and Communications     Open Access  
Automation in Construction     Hybrid Journal   (Followers: 8)
Balkan Journal of Electrical and Computer Engineering     Open Access  
Basin Research     Hybrid Journal   (Followers: 7)
Behaviour & Information Technology     Hybrid Journal   (Followers: 32)
BenchCouncil Transactions on Benchmarks, Standards, and Evaluations     Open Access   (Followers: 4)
Big Data and Cognitive Computing     Open Access   (Followers: 5)
Big Data Mining and Analytics     Open Access   (Followers: 10)
Biodiversity Information Science and Standards     Open Access   (Followers: 1)
Bioinformatics     Hybrid Journal   (Followers: 216)
Bioinformatics Advances : Journal of the International Society for Computational Biology     Open Access   (Followers: 1)
Biomedical Engineering     Hybrid Journal   (Followers: 11)
Biomedical Engineering and Computational Biology     Open Access   (Followers: 11)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 43)
British Journal of Educational Technology     Hybrid Journal   (Followers: 93)
Bulletin of Taras Shevchenko National University of Kyiv. Series: Physics and Mathematics     Open Access  
c't Magazin fuer Computertechnik     Full-text available via subscription   (Followers: 1)
Cadernos do IME : Série Informática     Open Access  
CALCOLO     Hybrid Journal  
CALICO Journal     Full-text available via subscription   (Followers: 1)
Calphad     Hybrid Journal  
Canadian Journal of Electrical and Computer Engineering     Full-text available via subscription   (Followers: 14)
Catalysis in Industry     Hybrid Journal  
CCF Transactions on High Performance Computing     Hybrid Journal  
CCF Transactions on Pervasive Computing and Interaction     Hybrid Journal  
CEAS Space Journal     Hybrid Journal   (Followers: 6)
Cell Communication and Signaling     Open Access   (Followers: 3)
Central European Journal of Computer Science     Hybrid Journal   (Followers: 4)
CERN IdeaSquare Journal of Experimental Innovation     Open Access  
Chaos, Solitons & Fractals     Hybrid Journal   (Followers: 1)
Chaos, Solitons & Fractals : X     Open Access   (Followers: 1)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 13)
ChemSusChem     Hybrid Journal   (Followers: 7)
China Communications     Full-text available via subscription   (Followers: 8)
Chinese Journal of Catalysis     Full-text available via subscription   (Followers: 2)
Chip     Full-text available via subscription   (Followers: 3)
Ciencia     Open Access  
CIN : Computers Informatics Nursing     Hybrid Journal   (Followers: 11)
Circuits and Systems     Open Access   (Followers: 16)
CLEI Electronic Journal     Open Access  
Clin-Alert     Hybrid Journal   (Followers: 1)
Clinical eHealth     Open Access  
Cluster Computing     Hybrid Journal   (Followers: 1)
Cognitive Computation     Hybrid Journal   (Followers: 2)
Cognitive Computation and Systems     Open Access  
COMBINATORICA     Hybrid Journal  
Combinatorics, Probability and Computing     Hybrid Journal   (Followers: 4)
Combustion Theory and Modelling     Hybrid Journal   (Followers: 18)
Communication Methods and Measures     Hybrid Journal   (Followers: 12)
Communication Theory     Hybrid Journal   (Followers: 29)
Communications in Algebra     Hybrid Journal   (Followers: 1)
Communications in Partial Differential Equations     Hybrid Journal   (Followers: 2)
Communications of the ACM     Full-text available via subscription   (Followers: 59)
Communications of the Association for Information Systems     Open Access   (Followers: 15)
Communications on Applied Mathematics and Computation     Hybrid Journal   (Followers: 1)
COMPEL: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering     Hybrid Journal   (Followers: 4)
Complex & Intelligent Systems     Open Access   (Followers: 1)
Complex Adaptive Systems Modeling     Open Access  
Complex Analysis and Operator Theory     Hybrid Journal   (Followers: 2)
Complexity     Hybrid Journal   (Followers: 8)
Computación y Sistemas     Open Access  
Computation     Open Access   (Followers: 1)
Computational and Applied Mathematics     Hybrid Journal   (Followers: 3)
Computational and Mathematical Methods     Hybrid Journal  
Computational and Mathematical Methods in Medicine     Open Access   (Followers: 2)
Computational and Mathematical Organization Theory     Hybrid Journal   (Followers: 1)
Computational and Structural Biotechnology Journal     Open Access   (Followers: 1)
Computational and Theoretical Chemistry     Hybrid Journal   (Followers: 11)
Computational Astrophysics and Cosmology     Open Access   (Followers: 6)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 13)
Computational Biology Journal     Open Access   (Followers: 6)
Computational Brain & Behavior     Hybrid Journal   (Followers: 1)
Computational Chemistry     Open Access   (Followers: 3)
Computational Communication Research     Open Access   (Followers: 1)
Computational Complexity     Hybrid Journal   (Followers: 5)
Computational Condensed Matter     Open Access   (Followers: 1)

        1 2 3 4 5 6 7 | Last

Similar Journals
Journal Cover
Applied Computer Systems
Number of Followers: 6  

  This is an Open Access Journal Open Access journal
ISSN (Print) 2255-8683 - ISSN (Online) 2255-8691
Published by Sciendo Homepage  [370 journals]
  • Real-Time Identification from Gait Features Using Cascade Voting Method

    • Abstract: There are several biometric methods for identification. These are generally classified under two main groups as physiological and behavioural biometric methods. Recently, methods using behavioural biometric features have gained popularity. Identification made using gait pattern is also one of these methods. The present study proposes a machine learning based system performing identification in real time via gait features using a Kinect device. The data set is composed of 23 individuals’ skeleton model data obtained by the authors. From these data, 147 handcrafted features have been extracted. Deep Neural Network (DNN), Random Forest (RF), Gradient Boosting (GB), XG-Boost (XGB) and K-Nearest Neighbour (KNN) classifiers have been trained with these features. Furthermore, the output of these five machine learning models has been combined with a voting approach. The highest classification has been obtained with 97.5 % accuracy via a voting approach. The classification accuracies of the RF, DNN, XGB, GB and KNN classifiers are 95 %, 87.5 %, 85 %, 80 % and 65 %, respectively. The classification accuracy obtained via a voting approach is higher than in the previous studies. The developed system successfully performs real-time identification.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Text Tone Determination Using Fuzzy Logic

    • Abstract: The study proposes the text tone detection system based on sentiment dictionaries and fuzzy rules. Computer analysis of texts from different sources has been performed in emotional categories: anger, anticipation, disgust, fear, joy, sadness, surprise and trust. A synonym dictionary has been used to expand the vocabulary. To increase the accuracy and validity of sentiment analysis, the authors of the study have used coefficients that take into account different emotional loads of words of various parts of speech and the action of intensifying or softening adverbs. A quantitative value of the text tone has been obtained as a result of an aggregation of normalized data on all emotional categories by the fuzzy inference methods. It has been found that emotional words have a greater impact on the text tone value in the case of analysis of short messages. The proposed approach makes it possible to contribute to all emotional categories in the final text evaluation.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Curriculum Learning for Age Estimation from Brain MRI

    • Abstract: Age estimation from brain MRI has proved to be considerably helpful in early diagnosis of diseases such as Alzheimer’s and Parkinson’s. In this study, curriculum learning effect on age estimation models was measured using a brain MRI dataset consisting of normal and anomaly data. Three different strategies were selected and compared using 3D Convolutional Neural Networks as the Deep Learning architecture. The strategies were as follows: (1) model training performed only on normal data, (2) model training performed on the entire dataset, (3) model training performed on normal data first and then further training on the entire dataset as per curriculum learning. The results showed that curriculum learning improved results by 20 % compared to traditional training strategies. These results suggested that in age estimation tasks datasets consisting of anomaly data could also be utilized to improve performance.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Solution to On-line vs On-site Work Efficiency Analysis on the Example of
           Engineering System Designer Work

    • Abstract: Day-to-day working activities have been heavily altered by COVID-19 pandemic, forcing a transition from traditional on-site work to on-line telework across the whole world. It has become much harder to efficiently organise, guide and evaluate employee’s work. There are different factors that can influence “work from home” quality, and many of these affect such work negatively. A set of relevant methods and tools should be developed which could improve this situation. The goal of the study is to summarise related background of this problem and to propose an approach to overcoming this problem. To achieve the goal, design engineer’s work is evaluated in an appropriate environment (e.g., AutoCAD, etc.) using automated analysis and visualization of IS auditing data.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Academic Performance Modelling with Machine Learning Based on Cognitive
           and Non-Cognitive Features

    • Abstract: The academic performance of students is essential for academic progression at all levels of education. However, the availability of several cognitive and non-cognitive factors that influence students’ academic performance makes it challenging for academic authorities to use conventional analytical tools to extract hidden knowledge in educational data. Therefore, Educational Data Mining (EDM) requires computational techniques to simplify planning and determining students who might be at risk of failing or dropping from school due to academic performance, thus helping resolve student retention. The paper studies several cognitive and non-cognitive factors such as academic, demographic, social and behavioural and their effect on student academic performance using machine learning algorithms. Heterogenous lazy and eager machine learning classifiers, including Decision Tree (DT), K-Nearest-Neighbour (KNN), Artificial Neural Network (ANN), Logistic Regression (LR), Random Forest (RF), AdaBoost and Support Vector Machine (SVM) were adopted and training was performed based on k-fold (k = 10) and leave-one-out cross-validation. We evaluated their predictive performance using well-known evaluation metrics like Area under Curve (AUC), F-1 score, Precision, Accuracy, Kappa, Matthew’s correlation coefficient (MCC) and Recall. The study outcome shows that Student Absence Days (SAD) are the most significant predictor of students’ academic performance. In terms of prediction accuracy and AUC, the RF (Acc = 0.771, AUC = 0.903), LR (Acc = 0.779, AUC = 0.90) and ANN (Acc = 0.760, AUC = 0.895) outperformed all other algorithms (KNN (Acc = 0.638, AUC = 0.826), SVM (Acc = 0.727, AUC = 0.80), DT (Acc = 0.733, AUC = 0.876) and AdaBoost (Acc = 0.748, AUC = 0.808)), making them more suitable for predicting students’ academic performance.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • The Process of Data Validation and Formatting for an Event-Based Vision
           Dataset in Agricultural Environments

    • Abstract: In this paper, we describe our team’s data processing practice for an event-based camera dataset. In addition to the event-based camera data, the Agri-EBV dataset contains data from LIDAR, RGB, depth cameras, temperature, moisture, and atmospheric pressure sensors. We describe data transfer from a platform, automatic and manual validation of data quality, conversions to multiple formats, and structuring of the final data. Accurate time offset estimation between sensors achieved in the dataset uses IMU data generated by purposeful movements of the sensor platform. Therefore, we also outline partitioning of the data and time alignment calculation during post-processing.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Determining and Measuring the Amount of Region Having COVID-19 on Lung
           Images

    • Abstract: It is important to know how much the lungs are affected in the course of the disease in patients with COVID-19. Detecting infected tissues on CT lung images not only helps diagnose the disease but also helps measure the severity of the disease. In this paper, using the hybrid artificial intelligence-based segmentation method, which we call TA-Segnet, it has been revealed how the region with COVID-19 affects the lung on 2D CT images. A hybrid convolutional neural network-based segmentation method (TA-Segnet) has been developed for this process. We use “COVID-19 CT Lung and Infection Segmentation Dataset” and “COVID-19 CT Segmentation Dataset” to evaluate TA-SegNET. At first, the tissues with COVID-19 on each lung image are determined, then the measurements obtained are evaluated according to the parameters of Accuracy, Dice, Jaccard, Mean Square Error, Mutual Information and Cross-correlation. Accuracy, Dice, Jaccard, Mean Square Error, Mutual Information and Cross-correlation values for data set-1 are 98.63 %, 0.95, 0.919, 0.139, 0.51, and 0.904, respectively. For data set-2, these parameters are 98.57 %, 0.958, 0.992, 0.0088, 0.565 and 0.8995, respectively. Second, the ratio of COVID-19 regions relative to the lung region on CT images is determined. This ratio is compared with the values in the original data set. The results obtained show that such an artificial intelligence-based method during the pandemic period will help prioritize and automate the diagnosis of COVID-19 patients.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Time Series Forecasting of Mobile Robot Motion Sensors Using LSTM Networks

    • Abstract: Deep neural networks are a tool for acquiring an approximation of the robot mathematical model without available information about its parameters. This paper compares the LSTM, stacked LSTM and phased LSTM architectures for time series forecasting. In this paper, motion sensor data from mobile robot driving episodes are used as the experimental data. From the experiment, the models show better results for short-term prediction, where the LSTM stacked model slightly outperforms the other two models. Finally, the predicted and actual trajectories of the robot are compared.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Evaluation of Fingerprint Selection Algorithms for Two-Stage Plagiarism
           Detection

    • Abstract: Generally, the process of plagiarism detection can be divided into two main stages: source retrieval and text alignment. The paper evaluates and compares effectiveness of five fingerprint selection algorithms used during the source retrieval stage: Every p-th, 0 mod p, Winnowing, Frequency-biased Winnowing (FBW) and Modified FBW (MFBW). The algorithms are evaluated on a dataset containing plagiarism cases in Bachelor and Master Theses written in English in the field of computer science. The best performance is reached by 0 mod p, Winnowing and MFBW. For these algorithms, reduction of fingerprint size from 100 % to about 20 % kept the effectiveness at approximately the same level. Moreover, MFBW sends overall fewer document pairs to the text alignment stage, thus also reducing the computational cost of the process. The software developed for this study is freely available at the author’s website http://www.cs.rtu.lv/jekabsons/.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Adversarial Attacks and Defense Technologies on Autonomous Vehicles: A
           Review

    • Abstract: In recent years, various domains have been influenced by the rapid growth of machine learning. Autonomous driving is an area that has tremendously developed in parallel with the advancement of machine learning. In autonomous vehicles, various machine learning components are used such as traffic lights recognition, traffic sign recognition, limiting speed and pathfinding. For most of these components, computer vision technologies with deep learning such as object detection, semantic segmentation and image classification are used. However, these machine learning models are vulnerable to targeted tensor perturbations called adversarial attacks, which limit the performance of the applications. Therefore, implementing defense models against adversarial attacks has become an increasingly critical research area. The paper aims at summarising the latest adversarial attacks and defense models introduced in the field of autonomous driving with machine learning technologies up until mid-2021.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • A Cognitive Rail Track Breakage Detection System Using Artificial Neural
           Network

    • Abstract: Rail track breakages represent broken structures consisting of rail track on the railroad. The traditional methods for detecting this problem have proven unproductive. The safe operation of rail transportation needs to be frequently monitored because of the level of trust people have in it and to ensure adequate maintenance strategy and protection of human lives and properties. This paper presents an automatic deep learning method using an improved fully Convolutional Neural Network (FCN) model based on U-Net architecture to detect and segment cracks on rail track images. An approach to evaluating the extent of damage on rail tracks is also proposed to aid efficient rail track maintenance. The model performance is evaluated using precision, recall, F1-Score, and Mean Intersection over Union (MIoU). The results obtained from the extensive analysis show U-Net capability to extract meaningful features for accurate crack detection and segmentation.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Distance Sensor and Wheel Encoder Sensor Fusion Method for Gyroscope
           Calibration

    • Abstract: MEMS gyroscopes are widely used as an alternative to the more expensive industrial IMUs. The instability of the lower cost MEMS gyroscopes creates a large demand for calibration algorithms. This paper provides an overview of existing calibration methods and describes the various types of errors found in gyroscope data. The proposed calibration method for gyroscope constants provides higher accuracy than datasheet constants. Furthermore, we show that using a different constant for each direction provides even higher accuracy.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Solution to Analysis of IT System User Behaviour Using AI/ML Algorithms

    • Abstract: Insufficient user involvement, lack of user feedback, incomplete and changing user requirements are some of the critical reasons for the difficulty of IS usage, which could potentially reduce the number of customers. Under the previous authors’ research, the method for analysing the behaviour of IT system users was developed, which was intended to improve the usability of the system and thus could increase the efficiency of business processes. The developed method is based on the use of graph searching algo rithms, Markov chains and Machine Learning approach. This paper focuses on detailing of method output data in the context of definition of their importance based on expert evaluation and demonstration of visual presentation of different UX analysis situations. The paper briefly reminds the essence of the method, including both the input and output data sets, and, with the help of experts, evaluates the expected result in the context of their importance in UX analysis. It also introduces visualization prototype developed to obtain the output data, which allows verifying the input/output data transformation possibilities and expected data acquisition potential.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Fog Computing Algorithms: A Survey and Research Opportunities

    • Abstract: The classic Internet of Things-Cloud Computing model faces challenges like high response latency, high bandwidth consumption, and high storage requirement with increasing velocity and volume of generated data. Fog computing offers better services to end users by bringing processing, storage, and networking closer to them. Recently, there has been significant research addressing architectural and algorithmic aspects of fog computing. In the existing literature, a systematic study of architectural designs is widely conducted for various applications. Algorithms are seldom examined. Algorithms play a crucial role in fog computing. This survey aims to performing a comparative study of existing algorithms. The study also presents a systematic classification of the current fog computing algorithms and highlights the key challenges and research issues associated with them.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Evaluation of Word Embedding Models in Latvian NLP Tasks Based on Publicly
           Available Corpora

    • Abstract: Nowadays, natural language processing (NLP) is increasingly relaying on pre-trained word embeddings for use in various tasks. However, there is little research devoted to Latvian – a language that is much more morphologically complex than English. In this study, several experiments were carried out in three NLP tasks on four different methods of creating word embeddings: word2vec, fastText, Structured Skip-Gram and ngram2vec. The obtained results can serve as a baseline for future research on the Latvian language in NLP. The main conclusions are the following: First, in the part-of-speech task, using a training corpus 46 times smaller than in a previous study, the accuracy was 91.4 % (versus 98.3 % in the previous study). Second, fastText demonstrated the overall best effectiveness. Third, the best results for all methods were observed for embeddings with a dimension size of 200. Finally, word lemmatization generally did not improve results.
      PubDate: Thu, 30 Dec 2021 00:00:00 GMT
       
  • Expert Survey on Current Trends in Agile, Disciplined and Hybrid Practices
           for Software Development

    • Abstract: Every software development company makes software development based on a specific approach. There are a number of approaches to software development, both disciplined and agile. Each approach includes a set of different activities. Sometimes, the specific nature of a company’s work requires a specific approach, but the need to make work more efficient, faster and better requires implementing activities of other approaches. Then hybrid software development approaches come in. The paper presents an expert survey to examine the most important software development activities, the combinations of development approaches that are used in software development processes and the way of upgrading existing approaches. The evaluated activities of software development process are classified according to their nature – whether they correspond with a team, organisation, documentation, development, and testing. The conclusions are also made on the practices that are required most – disciplined, Agile or hybrid.
      PubDate: Fri, 04 Jun 2021 00:00:00 GMT
       
  • VP-RDF: An RDF Based Framework to Introduce the Viewpoint in the
           Description of Resources

    • Abstract: The description of resources and their relationships is an essential task on the web. Generally, the web users do not share the same interests and viewpoints. Each user wants that the web provides data and information according to their interests and specialty. The existing query languages, which allow querying data on the web, cannot take into consideration the viewpoint of the user. We propose introducing the viewpoint in the description of the resources. The Resource Description Framework (RDF) represents a common framework to share data and describe resources. In this study, we aim at introducing the notion of the viewpoint in the RDF. Therefore, we propose a View-Point Resource Description Framework (VP-RDF) as an extension of RDF by adding new elements. The existing query languages (e.g., SPARQL) can query the VP-RDF graphs and provide the user with data and information according to their interests and specialty. Therefore, VP-RDF can be useful in intelligent systems on the web.
      PubDate: Fri, 04 Jun 2021 00:00:00 GMT
       
  • Real-Time Turkish Sign Language Recognition Using Cascade Voting Approach
           with Handcrafted Features

    • Abstract: In this study, a machine learning-based system, which recognises the Turkish sign language person-independent in real-time, was developed. A leap motion sensor was used to obtain raw data from individuals. Then, handcraft features were extracted by using Euclidean distance on the raw data. Handcraft features include finger-to-finger, finger -to-palm, finger -to-wrist bone, palm-to-palm and wrist-to-wrist distances. LR, k-NN, RF, DNN, ANN single classifiers were trained using the handcraft features. Cascade voting approach was applied with two-step voting. The first voting was applied for each classifier’s final prediction. Then, the second voting, which voted the prediction of all classifiers at the final decision stage, was applied to improve the performance of the proposed system. The proposed system was tested in real-time by an individual whose hand data were not involved in the training dataset. According to the results, the proposed system presents 100 % value of accuracy in the classification of one hand letters. Besides, the recognition accuracy ratio of the system is 100 % on the two hands letters, except “J” and “H” letters. The recognition accuracy rates were 80 % and 90 %, respectively for “J” and “H” letters. Overall, the cascade voting approach presented a high average classification performance with 98.97 % value of accuracy. The proposed system enables Turkish sign language recognition with high accuracy rates in real time.
      PubDate: Fri, 04 Jun 2021 00:00:00 GMT
       
  • Evaluating the Impact of Design Pattern Usage on Energy Consumption of
           Applications for Mobile Platform

    • Abstract: Energy efficiency in mobile computing is really an important issue these days. Owing to the popularity and prevalence of Android operating system among the people, a great number of Android smartphone applications have been developed and proliferated by the software developers. While developing these applications, developers have to keep energy consumption factor in mind, as the efficiency of an application is largely affected by it. Thus, designers and programmers endeavour to choose the best designing approaches to develop energy-efficient applications. It is imperative to assist the programmers in choosing appropriate techniques and strategies to manage power consumption. In the present research, we have investigated the effect of Android application design on its energy utilisation. For this purpose, we have practically implemented design patterns on two Android applications and evaluated their energy consumption before and after implementing these patterns. We have modelled the high-level design of these two Android applications by using software design patterns in such a way as to abate their energy requirement. We have also checked how the quality, maintainability, and efficiency of code are affected by these design patterns. The outcomes of the research can facilitate programmers to utilise these details while developing energy efficient solutions.
      PubDate: Fri, 04 Jun 2021 00:00:00 GMT
       
  • Mapping of Source and Target Data for Application to Machine Learning
           Driven Discovery of IS Usability Problems

    • Abstract: Improving IS (Information System) end-user experience is one of the most important tasks in the analysis of end-users behaviour, evaluation and identification of its improvement potential. However, the application of Machine Learning methods for the UX (User Experience) usability and effic iency improvement is not widely researched. In the context of the usability analysis, the information about behaviour of end-users could be used as an input, while in the output data the focus should be made on non-trivial or difficult attention-grabbing events and scenarios. The goal of this paper is to identify which data potentially can serve as an input for Machine Learning methods (and accordingly graph theory, transformation methods, etc.), to define dependency between these data and desired output, which can help to apply Machine Learning / graph algorithms to user activity records.
      PubDate: Fri, 04 Jun 2021 00:00:00 GMT
       
 
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