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36 results for “Loss Optimization”
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Research ArticleOpen accessPhrase in the titleImplementation of Single Candidate Loss Optimization Algorithm for Loss Optimization of Bhojpuri-English Machine Translation ModelRituraj Dixit, Sarabjeet Singh Bedi, Ibrahim Aljubayri, Mohammad Zubair KhanMachine translation of low-resource Indian languages is necessary as most of the regions still know and speak their specific dialects and are still not comfortable understanding the English language. Indian languages are morphologically rich, due to which there are two big challenges, Ambiguity and Domain adaption, which are faced by researchers during the translation. Lack of data also increases the … …Journal of Computer Science, Vol. 21, Issue 5 · 17 Apr 2025 · 5,151 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleOptimization of Non-Technical Electricity Loss Detection Using Artificial Neural Networks: Case of Cameroon Distribution NetworkLekini Nkodo Claude Bernard, Bell Serge Samuel, Nyemb Nsoga Valjacques et al.Non-Technical Losses (NTL) represent a critical challenge for power utilities, particularly in developing countries. This paper proposes an unsupervised deep learning approach based on an autoencoder to detect abnormal electricity consumption patterns in the Cameroonian distribution network. The model learns normal customer behavior using historical consumption data and identifies anomalies through reconstruction error analysis. Statistical thresholds are applied to classify … …American Journal of Engineering and Applied Sciences, Vol. 19, Issue 1 · 23 Jul 2026 · 1,225 accessesView PDFCite
Research ArticleOpen accessIn the keywordsCalculation of Total Cost, Tolerance Based on Taguchi's, Asymmetric Quality Loss Function ApproachR. Sampath Kumar, N. Alagumurthi, R. RameshProblem statement: Current world market force the manufacturing sectors to develop high quality product and process design with minimum possible cost. About 80% of problems in production units may be attributed to 20% of design tolerance causes. While design typically represents the smallest actual cost elements in products (around 5%), it leverages the largest cost influence (around 70%). So design … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 4 · 31 Dec 2009 · 8,045 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrioritized Experience Replay-Based Deep Deterministic Policy Gradient for Reliable Path Selection in SDN-IoT NetworksGaurav Kumar, G. S. Girisha, N. ShamanthRouting optimization is becoming prominent in Software-Defined Networks (SDN) due to the exponential growth of network traffic demands and the requirement for Quality of Service (QoS). However, reliable routing that satisfies the QoS requirements, such as end-to-end delay, packet loss, and bandwidth, remains a difficult task in SDN. To overcome this limitation, a Deep Reinforcement Learning (DRL)-based Prioritized Experience Replay-based … …Journal of Computer Science, Vol. 22, Issue 8 · 4 Aug 2026 · 1,001 accessesView PDFCite
Research ArticleOpen accessIn the abstractFuzzyNET: A Fuzzy Logic-Based Framework for Enhancing Urban Efficiency in Smart CitiesHemant Kumar, Safdar Tanweer, Parul Agarwal et al.The smart city paradigm emphasizes the strategic use of IoT, Big Data, and digital technologies to optimize urban operations and improve service delivery for citizens. Embedding digital technologies within operational workflows is driven by the objective of improving efficiency and long-term sustainability. The core transformation is Artificial Intelligence (AI) that revolutionizes management of cities through automation and instantaneous decisions based … …Journal of Computer Science, Vol. 22, Issue 7 · 19 Jul 2026 · 820 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized YOLOv8 for Insect Detection in Agricultural Farms Using Edge Vision SystemsDeebalakshmi R., Adhithyaa S., Yoga Vignesh V., Balaji Ganesh RajagopalFarmers started to adopt smart gadgets like automated pest detection and kiosks for their work in light of the AI revolution in agriculture. These kinds of technologies help farmers identify pest infestations early, which allows the farmers to take action accordingly and prevent crop loss. This results in improvement in both yield and sustainability. However, running an advanced model such … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Jan 2026 · 2,640 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancements In Precision Agriculture: A Review on Image-Based Stress Detection and Predictive Yield Loss ModelingA. Josephine, A. SubhashiniPrecision agriculture utilizes cutting-edge technologies to maximize the management of crops, enhance utilization of resources, and maximize yield forecasting. This study critically analyzes 53 peer-reviewed articles to evaluate advancements in image-based stress detection and yield prediction techniques for precision agriculture. The review enumerates main issues, such as image-based analysis methods, different crop stress aspects (biotic, environmental, and abiotic), and remote … …Journal of Computer Science, Vol. 21, Issue 11 · 28 Dec 2025 · 2,508 accessesView PDFCite
Research ArticleOpen accessIn the abstractSelf-Supervised Contrastive Learning for Steering Angle Prediction in Autonomous Driving SimulationsMaxson Phang, Suryadiputra LiawatimenaPredicting steering angles is a crucial task in autonomous driving, with end-to-end deep learning being a widely used approach. However, such models often suffer from overfitting to learned trajectories, limiting their generalization to new data. To address this, self-supervised contrastive learning is explored as an alternative, allowing models to learn meaningful representations without labeled data. The primary objective is to … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,581 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Optimization to Trust Enhanced Secure Routing Optimization with IABC and CGWAA for MANETYuvaraja Panneer Selvam, Suganthi PerumalRouting in Mobile Ad Hoc Networks (MANET) presents significant challenges due to the dynamic nature of network topology. Optimal route selection and efficient route discovery are matched by effective routing in MANET. This study proposes a Hybrid Optimization to Trust-Enhanced Secure Routing Optimization (HO-TESRO) designed to address these challenges in IoT environments by integrating metrics such as link stability, bandwidth, … …Journal of Computer Science, Vol. 21, Issue 4 · 19 Mar 2025 · 4,983 accessesView PDFCite