Volume 3, Issue 10 (October 2024) - 00 Articles
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # i-i, 2024
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # i-i, 2024
by ABCÂ and DEF
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # i-i, 2024
Journal of Engineering Research and Sciences, Volume 3, Issue 8, Page # i-i, 2024
by Swarup Kumar Mondal, and Anindya Sen
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 1-14, 2024; DOI:Â 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 ratios in the sample dataset. Dealing with imbalanced dataset leads to performance degradation and interpretability issue in traditional ML architectures. For regression tasks, where the target variable is continuous, the skewed data distribution is major issue. …. Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
by Haoyuan Huang, and Rongcheng Cui
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 15-20, 2024; DOI:Â 10.55708/js0310002
Abstract: Accurate gemstone classification is critical to the gemstone and jewelry industry, and the good performance of convolutional neural networks in image processing has received wide attention in recent years. In order to better extract image content information and improve image classification accuracy, a CNNs gemstone image classification algorithm based on deep multi-feature fusion is proposed… Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
by Vaibhavi Tiwari
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 21-36, 2024; DOI:Â 10.55708/js0310003
Abstract:Â The incorporation of cutting-edge technologies like sensor networks, artificial intelligence (AI), and vehicle-to-everything (V2X) communication has hastened the rollout of autonomous vehicles (AVs), offering significant possibilities for the future of transportation. This document offers an extensive overview of AV technology, covering essential elements such as technological infrastructure, degrees of automation, cybersecurity threats, societal impacts, regulatory structures, and emerging trends. This analysis emphasizes the existing obstacles and progress within the industry by examining the activities of key entities like Tesla, Waymo, and General Motors. Additionally, a comparative examination of autonomous vehicles and drones is performed, providing distinct perspectives on possible cybersecurity vulnerabilities shared by both technologies, including GPS spoofing, jamming, and unauthorized data interception….. Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
by Bernd-Jürgen Falkowski
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 37-43, 2024; DOI:Â 10.55708/js0310004
Abstract:Â 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 it is shown how operations in a high dimensional feature space can be performed without explicitly using an embedding function (the “kernel trick”). The general section of the paper lists some kernels and sophisticated kernel clustering algorithms. Thus the continuing popularity of the k-means algorithm is probably due to its simplicity. …. Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
by Renyan Jiang, Kunpeng Zhang, Xia Xu and Yu CaoÂ
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 44-54, 2024; DOI:Â 10.55708/js0310005
Abstract: Research on repairable systems in a fleet is mainly concerned with modelling of the failure times using point processes. One important issue is to quantitatively evaluate the heterogeneity among systems, which is usually analyzed using frailty models. Recently, a fleet heterogeneity evaluation method is proposed in the literature. This method describes the heterogeneity with the relative dispersion of equivalent acceleration factors (EAFs) of systems, which is defined as the ratio of the mean times between failures (MTBFs) of a system and a reference system. A main drawback of this method is that the MTBFs of a specific system and the reference system are estimated at different times while the MTBF estimated at different time can be different…… Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
by Haithem Aouabed, Mourad Elloumi and Fahad AlgarniÂ
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 55-68, 2024; DOI:Â 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 in the same bicluster and its overlapping property, allowing genes to belong to multiple biclusters. Biclustering algorithms often produce a large number of overlapping biclusters. Visualizing these results is not a straightforward task due to the specific characteristics of biclusters….. Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
by Yuexin Liu, Amir Tofighi Zavareh and Ben ZoghiÂ
Journal of Engineering Research and Sciences, Volume 3, Issue 10, Page # 69-75, 2024; DOI:Â 10.55708/js0310007
Abstract: Mental health concerns are increasingly prevalent among university students, particularly in engineering programs where academic demands are high. This study builds upon previous work aimed at improving mental health support for engineering students through the use of machine learning (ML) and eye-tracking technology. A framework was developed to monitor mental health by analyzing eye movements and physiological data to provide personalized support based on student behavior. In this extended study, baseline data were analyzed to explore the correlations between emotions and physiological biomarkers. Key findings indicate that emotions such as Anger and Fear are positively correlated with increased physical activity, while Sadness is associated with elevated respiratory rates…. Read More
(This article belongs to the Special Issue Special Issue on Multidisciplinary Sciences and Advanced Technology 2024 & Section Biochemical Research Methods (BRM))
