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Research ArticleOpen accessEvery word in the titleOptimization of α-Glucosidase Inhibitors Recovery from Rainbow Trout Hydrolysate Using GA-BP Neural NetworkYingke Chu, Yanling Dong, Qingfeng Rong et al.To enhance the value of by-products from rainbow trout processing, the inhibition rate of α-glucosidase (AGIR) is used as indicators. Optimization of rainbow trout hydrolysate extraction by comparing Response Surface Methodology (RSM) and BP Neural Network (BPNN) models. The RSM results: the AGIR is 55.02%. BPNN models predicted the optimal extraction conditions: 51℃ for temperature,1:2.3 for solid-liquid ratio, 4.15 h … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 1,734 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFake News Detection Using Weighted Fine-Tuned BERT and Sparse Recurrent Neural NetworkAsha Kathigi, Mukta Pujar, A M S Akshatha et al.Fake news refers to misinformation or false reports shared in the form of images, articles, or videos, disguised as real news to manipulate people’s opinions. Recently, fake news and rumors have spread extensively and rapidly around the world. This has led to the production and propagation of inaccurate news articles. Therefore, it is necessary to restrict the spread of fake … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 2,087 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Fractal Fusion Driven Deep Neural Network: An Efficient Hybrid Methodology for Disease Detection and Classification in Plant LeavesDeepkiran Munjal, Mrinal Pandey, Laxman SinghPlant diseases and pest attacks are among the major issues in agriculture, which have a great impact on crop growth and yield. Early and correct detection of these diseases is vital for effective management and keeping plant health at the desired level. This research proposes a new method for detection and classification of plant diseases, the Optimized Fractional Fusion Deep … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Jan 2026 · 2,223 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComprehensive Assessment of Spatial Distribution of Road-Network Vulnerability in South AsiaPan Yuqi, Jiang Penghui, Li Manchun, Chen DengshuaiUnexpected phenomena-natural disasters, accidents and wars-can disrupt regional traffic systems because of the incapacities of road networks to sustain inflicted impacts. Therefore, the assessment of road-network vulnerability becomes integral to traffic-safety-maintenance and accident-prevention procedures. This study demonstrates the development of a comprehensive network system based on suggested improvements in node extraction, road construction and network attribution. An indicator system for … …American Journal of Environmental Sciences, Vol. 17, Issue 6 · 24 Dec 2021 · 6,446 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRandom Forests for Online Intrusion Detection in Computer NetworksHeitor Scalco Neto, Wilian Soares Lacerda, Rafael Verão FrançozoThis study proposes a methodology to build an Online Network Intrusion Detection System by using the Computational Intelligence technique called Random Forests and an API to preprocess the network packets. The experiments were carried out from two network traffic databases: The ISCX (i); and a test database (ii) created with the proposed API in our own network environment. The results … …Journal of Computer Science, Vol. 17, Issue 10 · 19 Oct 2021 · 6,955 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleFault-Tolerant Control of a Nonlinear Uncertain System: A Neural Network-Based Passive Approaches and Comparative Study with State-of-the-Art Control ApproachesSejal K. Raval, Himanshukumar Rajendrabhai Patel, Vipul A. ShahThis article suggests passive methods for designing Fault-Tolerant Control (FTC) for nonlinear uncertain systems with actuator and leak faults. To anticipate the Fault-Tolerant Control (FTC) action to overcome the actuator and leak faults, two-layer Feed-Forward Back-Propagation Neural Network (FFBPNN) and two-layer Cascade Forward Neural Network (CFNN) have been used, it will also tolerate external process additive disturbances. We employ the … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 6,736 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleAn Integrated Framework to Predict the Strength of New SMILE Using Graph Attention NetworkSandhi Kranthi Reddy, S. V. G. ReddyMachine Learning (ML) and Deep Learning (DL) have significantly advanced various fields, including healthcare, finance, autonomous systems, and scientific research. In healthcare, these technologies have been widely applied to disease prediction, such as cancer and diabetes. However, the challenge of drug resistance persists, creating a need for more effective drugs. Developing new drugs is a complex, expensive, and time-intensive process, … …Journal of Computer Science, Vol. 21, Issue 10 · 25 Nov 2025 · 2,157 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimized Feature Reduction Techniques for Enhanced Network Threat Detection in Wireless Sensor NetworksBikash Kalita, Satyajit SarmahThe security of Wireless Sensor Networks (WSNs) is currently seriously threatened by numerous threats. Consequently, a number of applications are offered to regulate data and information sharing along with the related security features that need to be maintained throughout data transfer. This study suggests an intelligent feature reduction methodology based on machine learning that uses Modified Principal Component Analysis (MPCA) … …Journal of Computer Science, Vol. 21, Issue 8 · 10 Oct 2025 · 2,290 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleRemote Sensing Image Classification Using Convolutional Neural Network (CNN) and Transfer Learning TechniquesMustafa Majeed Abd Zaid, Ahmed Abed Mohammed, Putra SumariThis study investigates the classification of aerial images depicting transmission towers, forests, farmland, and mountains. To complete the classification job, features are extracted from input photos using a Convolutional Neural Network (CNN) architecture. Then, the images are classified using Softmax. To test the model, we ran it for ten epochs using a batch size of 90, the Adam optimizer, and … …Journal of Computer Science, Vol. 21, Issue 3 · 11 Feb 2025 · 10,117 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleClassification of Arabic Comments to Detect Cyberbullying from Social Media Using Convolutional Neural Network and Meta-LearningSarah Mansour Elgaud, Mustafa Ali Abuzaraida, Abdullah AlshehabAs a result of the proliferation of social media, cyberbullying has become widespread in the Arab community on social media and cyberbullying has become a concern targeting individuals and may cause some serious side effects. The problems of Natural Language Processing (NLP) for the Arabic language and its complexity make it difficult to classify texts accurately. In recent years, deep … …Journal of Computer Science, Vol. 21, Issue 3 · 10 Feb 2025 · 6,279 accessesView PDFCite