Results (26)
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Keyword: AlgorithmsComparative Analysis of Scheduling Algorithms in 5G Uplink Transmission
by Maryam Imran Sheik Mamode and Tulsi Pawan Fowdur
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 41-51, 2022; DOI: 10.55708/js0105005
Abstract: 5G is the successor to 4G technology and it has enabled a new level of user experience with much greater speeds and much lower latencies. Scheduling is the method of allocating resources for transmission of data. In this paper, three scheduling algorithms have been investigated, namely Proportional Fair, Round Robin and Best CQI. An uplink… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Telecommunications (TEL))
Energy-Optimized Smart Transformers for Renewable-Rich Grids
by Sunday Omini Oboma and Edward Lambart
Journal of Engineering Research and Sciences, Volume 4, Issue 10, Page # 21-28, 2025; DOI: 10.55708/js0410003
Abstract: The accelerating and unrestrained use of energy globally raises serious concerns for the future of the planet, primarily due to the environmental devastation caused by fossil fuels. Achieving high energy efficiency in both fuel-driven and renewable energy systems is crucial for future energy optimization. Clean energy production is one of the most effective strategies to… Read More
(This article belongs to the Section Energy and Fuels (ENF))
An Optimized Algorithm for Solving the Maximum Independent Set Problem
by Hager Hussein
Journal of Engineering Research and Sciences, Volume 4, Issue 8, Page # 24-30, 2025; DOI: 10.55708/js0408003
Abstract: Software engineering plays an important role in computer science. Novel quantum algorithms can efficiently solve software-engineering problems. Not only software engineering but also many industries including logistics, finance, genomics, resource allocation, logistics, bioinformatics, mobile agents and more have optimization problems. Such problems may have long time solutions. Research has been conducted to improve the performance… Read More
(This article belongs to the Section Quantum Science and Technology (QST))
Comparative Analysis of Supervised Machine Learning Models for PCOS Prediction Using Clinical Data
by Ranyah Taha, Huda Zain El Abdin and Tala Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 16-26, 2025; DOI: 10.55708/js0406003
Abstract: Polycystic Ovary Syndrome (PCOS) is a prevalent hormonal disorder affecting women of reproductive age, commonly resulting in irregular menstrual cycles, elevated androgen levels, and the presence of polycystic ovaries. It is a major cause of infertility and is often linked with metabolic complications such as insulin resistance and obesity. Symptoms vary and may include acne,… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Fire Type Classification in the USA Using Supervised Machine Learning Techniques
by Ranyah Taha, Fuad Musleh and Abdel Rahman Musleh
Journal of Engineering Research and Sciences, Volume 4, Issue 6, Page # 1-8, 2025; DOI: 10.55708/js0406001
Abstract: Wildfires are a growing global concern, causing widespread environmental, economic, and health impacts. In the USA, fire incidents have become more frequent and intense due to factors such as climate change, prolonged droughts, and human activities. Machine learning plays a vital role in predicting and classifying fires by analyzing vast satellite and environmental datasets with… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences 2024-25 and the Section Remote Sensing (RMS))
AI-Driven Digital Transformation: Challenges and Opportunities
by Maikel Leon
Journal of Engineering Research and Sciences, Volume 4, Issue 4, Page # 8-19, 2025; DOI: 10.55708/js0404002
Abstract: This paper explores the crucial role of Artificial Intelligence (AI) in driving digital transformation across industries. It examines machine learning, deep learning, fuzzy logic, genetic algorithms, reinforcement learning, and generative AI techniques, highlighting their development, applications, and examples. Case studies showcase AI’s impact in optimizing supply chains, improving financial operations, boosting customer engagement, and revolutionizing… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2025 and the Section Artificial Intelligence – Computer Science (AIC))
A Bibliometric Analysis Review on Energy Optimization while Designing Wireless Sensor Networks
by Makwena Idah Masopoga, Mbuyu Sumbwanyambe, Zenghui Wang and Nthambeleni Reginald Netshikweta
Journal of Engineering Research and Sciences, Volume 3, Issue 11, Page # 81-92, 2024; DOI: 10.55708/js0311007
Abstract: Energy optimisation algorithms play an essential role in reducing energy usage. Hence, it is mandatory to identify current themes and predict future research study in energy optimisation algorithms (EOAs) in wireless sensor networks (WSNs). Several reviews have been conducted on energy optimisation algorithms (EOAs) in WSNs, although many focused on narrative reviews. This study focuses… Read More
(This article belongs to the Section Electrical Engineering (ELE))
Biclustering Results Visualization of Gene Expression Data: A Review
by Haithem Aouabed, Mourad Elloumi and Fahad Algarni
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 54-68, 2024; DOI: 10.55708/js0310006
Abstract: Biclustering is a non-supervised data mining method used to analyze gene expression data by identifying groups of genes that exhibit similar patterns across specific groups of conditions. Discovering these co-expressed genes (called biclusters) can aid in understanding gene interactions in various biological contexts. Biclustering is characterized by its bi-dimensional nature, grouping both genes and conditions… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 and the Section Mathematical and Computational Biology (MCB))
On a Kernel k-Means Algorithm
by Bernd-Jürgen Falkowski*
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 37-43, 2024; DOI: 10.55708/js0310004
Abstract: This is the extended version of a paper presented at CISP-BMEI 2023. After a general introduction kernels are described by showing how they arise from considerations concerning elementary geometrical properties. They appear as generalizations of the scalarproduct that in turn is the algebraic version of length and angle. By introducing the Reproducing Kernel Hilbert Space… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
An Integrated Approach to Manage Imbalanced Datasets using PCA with Neural Networks
by Swarup Kumar Mondal and Anindya Sen
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 1-12, 2024; DOI: 10.55708/js0310001
Abstract: Imbalanced dataset handling in real time is one of the most challenging tasks in predictive modelling. This work handles the critical issues arising in imbalanced dataset with implementation of artificial neural network and deep neural network architecture. The usual machine learning algorithms fails to achieve desired throughput with certain input circumstances due to mismatched class… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 and the Section Artificial Intelligence – Computer Science (AIC))
Quantum Machine Learning on Remote Sensing Data Classification
by Yi Liu, Wendy Wang, Haibo Wang and Bahram Alidaee
Journal of Engineering Research and Sciences, Volume 2, Issue 12, Page # 23-33, 2023; DOI: 10.55708/js0212004
Abstract: Information extracted from remote sensing data can be applied to monitor the business and natural environments of a geographic area. Although a wide range of classical machine learning techniques have been utilized to obtain such information, their performance differs greatly in classification accuracy. In this study, we aim to examine whether quantum-enhanced machine learning can… Read More
(This article belongs to the Section Remote Sensing (RMS))
Imputation and Hyperparameter Optimization in Cancer Diagnosis
by Yi Liu, Wendy Wang and Haibo Wang
Journal of Engineering Research and Sciences, Volume 2, Issue 8, Page # 1-18, 2023; DOI: 10.55708/js0208001
Abstract: Cancer is one of the leading causes for death worldwide. Accurate and timely detection of cancer can save lives. As more machine learning algorithms and approaches have been applied in cancer diagnosis, there has been a need to analyze their performance. This study has compared the detection accuracy and speed of nineteen machine learning algorithms… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2023 and the Section Medical Informatics (MDI))
Classification of Rethinking Hyperspectral Images using 2D and 3D CNN with Channel and Spatial Attention: A Review
by Muhammad Ahsan Aslam, Muhammad Tariq Ali, Sunwan Nawaz, Saima Shahzadi and Muhammad Ali Fazal
Journal of Engineering Research and Sciences, Volume 2, Issue 4, Page # 22-32, 2023; DOI: 10.55708/js0204003
Abstract: It has been demonstrated that 3D Convolutional Neural Networks (CNN) are an effective technique for classifying hyperspectral images (HSI). Conventional 3D CNNs produce too many parameters to extract the spectral-spatial properties of HSIs. A channel service module and a spatial service module are utilized to optimize characteristic maps and enhance sorting performance in order to… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Graph-based Tool for Bandwidth Estimation, Health Monitoring and Update Planning in Broadband Networks
by Gian Paolo Jesi and Andrea Odorizzi
Journal of Engineering Research and Sciences, Volume 2, Issue 4, Page # 1-13, 2023; DOI: 10.55708/js0204001
Abstract: This paper focuses on the genesis and evolution of our specific Company tool. It is aimed to tackle the problem of verifying the health status and availability of residual bandwidth between any node over the Lepida ScpA broadband network. In fact, there must be a correspondence between active contractual obligations signed by local network operators… Read More
(This article belongs to the Special Issue on Special Issue on Computing, Engineering and Sciences 2023-23 and the Section Telecommunications (TEL))
Real-Time Acquisition and Classification of Electrocardiogram Signal
by Sheikh Md. Rabiul Islam, Akram Hossain and Asif Abdullah
Journal of Engineering Research and Sciences, Volume 1, Issue 11, Page # 8-15, 2022; DOI: 10.55708/js0111002
Abstract: Cardiovascular disease (CVD) is the leading cause of death. The transition in cardiovascular disease threatens the economies of the less developed world. An electrocardiogram (ECG) machine is a device that checks the patient's heart rhythm and electrical activity. ECG signals give crucial information about the heart and numerous cardiac problems, such as coronary artery disease,… Read More
(This article belongs to the Section Biomedical Engineering (BIE))
Hybrid Frameworks for the Multi-objective Optimization of Distributed Generation Units and Custom Power Devices with Simultaneous Distribution Network Reconfiguration
by Pamela Ramsami and Robert Tat Fung Ah King
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 186-197, 2022; DOI: 10.55708/js0105020
Abstract: The increased penetration of renewable energy sources in the distribution system affects the stability and efficiency of the system. To account for the intermittent nature of these sources, distribution network reconfiguration and the integration of custom power devices are important. This paper aims to identify the optimum location of photovoltaic systems and unified power quality… Read More
(This article belongs to the Section Electronic Engineering (EEE))
Competency Manifestation Clues within Interactions in Computer Mediated Communication
by Hocine Merzouki, Nada Matta, Hassan Atifi and Francois Rauscher
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 167-178, 2022; DOI: 10.55708/js0105018
Abstract: The notion of competence is multidimensional and polysemic. Several definitions of this notion are present in the literature according to disciplines such as industry, sociology, management, psychology, etc. It often refers to the experience, knowledge, abilities, skills, behaviors, and attitudes that allow valuable action in a workplace. Beyond its intrinsic value for the individual, competence… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Interdisciplinary Applications – Computer Science (IAC))
Offline Signature Verification based on Edge Histogram using Support Vector Machine
by Sunil Kumar Dyavaranahalli Sannappa, Kiran, Sudheesh Kannur Vasudeva Rao and Yashwanth Jagadeesh
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 160-166, 2022; DOI: 10.55708/js0105017
Abstract: Investigation on verification of offline signature has explored a huge sort of techniques on more than one signature datasets, which can be amassed beneath managed conditions. However, these records will not necessarily reflect the characteristics of the signatures in some useful use cases. In this work, introduced a novel feature representation technique called edge histogram… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Interdisciplinary Applications – Computer Science (IAC))
Machine Learning Aided Depression Detection in Community Dwellers
by Vijay Kumar, Muskan Khajuria and Anshu Singh
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 17-24, 2022; DOI: 10.55708/js0105002
Abstract: Depression is a mental condition that can have serious negative effects on an individual’s thoughts and nd health problems that could lead to grave heart diseases. Depression detection has become necessary in community dwellers considering the lifestyle being followed. Here we use NHANES dataset to compare the performance of various machine learning algorithms in depression… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Ideas at the Basis of Development of Software for Specific Nuclear Reactor Safety and Design
by Viacheslav Sergeevich Okunev
Journal of Engineering Research and Sciences, Volume 1, Issue 5, Page # 01-16, 2022; DOI: 10.55708/js0105001
Abstract: The main goal of the work was the development of software and codes for the design of new generation nuclear reactors. The problem is solved by the example of fast reactors with a liquid metal coolant. The problem is solved within the framework of system analysis methods and operations drawing methods. Three groups of methods… Read More
(This article belongs to the Section Nuclear Science and Technology (NST))
An Extreme Learning Machine for Blood Pressure Waveform Estimation using the Photoplethysmography Signal
by Gonzalo Tapia, Rodrigo Salas, Matías Salinas, Carolina Saavedra, Alejandro Veloz, Alexis Arriola, Steren Chabert and Antonio Glaría
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 161-174, 2022; DOI: 10.55708/js0104018
Abstract: Pressure (BP) waveform is a result of the response of the arteries to the blood ejectionproduced by tant indicator of the state of the cardiovascular system. Currently, its measurement is performed invasively in critically ill patients who need a continuous and real time monitoring of their treatment response, however, it is possible to measure the… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Medical Informatics (MDI))
Evolutionary Learning of Fuzzy Rules and Application to Forecasting Environmental Impact on Plant Growth
by Chris Nikolopoulos and Ryan Koralik
Journal of Engineering Research and Sciences, Volume 1, Issue 4, Page # 48-53, 2022; DOI: 10.55708/js0104006
Abstract: Prediction of plant growth and yield is one of the essential tasks that enables growers of food and agricultural products to effectively manage their crops. In this paper, a hybrid evolutionary/fuzzy machine learning approach is introduced where a genetic algorithm is deployed to learn the optimum membership functions of relevant fuzzy sets and a knowledge… Read More
(This article belongs to the Section Artificial Intelligence – Computer Science (AIC))
Bearing Fault Diagnosis Based on Ensemble Depth Explainable Encoder Classification Model with Arithmetic Optimized Tuning
by Kaibi Zhang, Yanyan Wang and Hongchun Qu
Journal of Engineering Research and Sciences, Volume 1, Issue 3, Page # 81-97, 2022; DOI: 10.55708/js0103009
Abstract: In a dynamic and complex bearing operating environment, current auto-encoder-based deep models for fault diagnosis are having difficulties in adaptation, which usually leads to a decline in accuracy. Besides, the opaqueness of the decision process by such deep models might reduce the reliability of the diagnostic results, which is not conducive to the subsequent optimization… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Artificial Intelligence – Computer Science (AIC))
Distributed Approach for the Indoor Deployment of Wireless Connected Objects by the Hybridization of the Voronoi Diagram and the Genetic Algorithm
by Wajih Abdallah, Sami Mnasri and Thierry Val
Journal of Engineering Research and Sciences, Volume 1, Issue 2, Page # 10-23, 2022; DOI: 10.55708/js0102002
Abstract: IoT data collection networks have recently become one of the important research areas due to their fundamental role and wide application in many domains. The establishment of networks of objects is based essentially on the deployment of connected objects to process the collected data and transmit them to the various locations. Subsequently, a large number… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Interdisciplinary Applications – Computer Science (IAC))
Neural Networks and Digital Arts: Some Reflections
by Rômulo Augusto Vieira Costa and Flávio Luiz Schiavoni
Journal of Engineering Research and Sciences, Volume 1, Issue 1, Page # 10-18, 2022; DOI: 10.55708/js0101002
Abstract: The Constant advancement in the area of machine learning has unified some areas that until then di a of computing with the arts in general. With the emergence of digital art, people have become increasingly interested in the development of expressive techniques and algorithms for creating works of art, whether in the form of music,… Read More
(This article belongs to the Special Issue on Special Issue on Multidisciplinary Sciences and Advanced Technology 2022 and the Section Artificial Intelligence – Computer Science (AIC))