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78 articles for “long-term performance”
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Research ArticleOpen accessEvery word in the titleThe Effects of Short or Long Term FGA Treatment with or without eCG on Reproductive Performance of Ewes Bred Out-of-seasonMustafa Q. Husein, Mohammed M. Ababneh, Dia S. Abu-RumanThe objective was to evaluate the effects of intravaginal FGA sponges inserted for 4 or 12 days with or without eCG on reproductive performance of ewes out-of-season. Forty-eight anestrous ewes were assigned in equal numbers to four treatments in a 2x2 factorial design. Ewes were administered with FGA sponges on May 17 for 12 days (12-day-FGA-eCG and 12-day-FGA groups, n= … …American Journal of Animal and Veterinary Sciences, Vol. 2, Issue 1 · 31 Mar 2007 · 7,485 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite
Research ArticleOpen accessIn the keywordsPerformance Assessment and Monitoring of a Permeable Reactive Barrier for the Remediation of a Contaminated SiteValerio Zolla, Rajandrea Sethi, Antonio Di MolfettaThe present study illustrates the long-term monitoring plan carried out in order to investigate the performance of a zero-valent iron permeable reactive barrier (PRB) at a chlorinated solvents’ site. The cleanup intervention has been undertaken at an industrial landfill located near the city of Turin (Italy) and represents the first full-scale application of this technology in Italy. The monitoring plan … …American Journal of Environmental Sciences, Vol. 3, Issue 3 · 30 Sep 2007 · 7,438 accessesView PDFCite
Research ArticleOpen accessIn the abstractGait Analysis Combining Sports Biomechanics and ImagingChao ZhuAiming at the problems of marker positioning error, soft tissue interference, and insufficient personalized modeling ability in traditional gait analysis, this study proposes a gait assessment method that integrates sports biomechanics and multimodal imaging analysis. Firstly, based on the public OU-ISIR gait database, a Convolutional Neural Network (CNN) is used to extract the key gait features in the human silhouette … …American Journal of Biochemistry and Biotechnology, Vol. 22, Issue 2 · 20 Jul 2026 · 850 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 abstractDeep Learning Models for Predicting Stock Closing Prices in the Saudi Stock MarketAreej Alhumaidi, Hoda A. AbdelhafezFinancial time series data are inherently volatile and nonlinear, presenting considerable challenges in accurately forecasting stock market trends. This study aims to predict the closing prices of companies listed on the Saudi stock market by analyzing historical data spanning from 2013 to 2023. To this end, four deep learning models were employed-Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), Gated Recurrent … …Journal of Computer Science, Vol. 22, Issue 4 · 22 Apr 2026 · 1,355 accessesView PDFCite
Research ArticleOpen accessIn the abstractProductivity and Energy Efficiency of Hybrid Sorrel (Rumex tianschanicus × Rumex patientia) Under Various Mowing and Fertilization RegimesAltinay Naziulovna Kukusheva, Ainagul Balgauovna Kaliyeva, Zarina Mukhtarovna Sergazinova et al.Hybrid sorrel (Rumex patientia × Rumex tianschanicus) is a multi-purpose crop that serves as both a fodder source and a potential biofuel feedstock. Despite growing interest in perennial forage and energy crops, limited information is available on the performance of hybrid sorrel (Rumex tianschanicus × Rumex patientia) under varying mowing and fertilization regimes, particularly in continental climates. This study aimed … …OnLine Journal of Biological Sciences, Vol. 26, Issue 1 · 1 Apr 2026 · 1,396 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of a Machine Learning Based Mobile and Web Crop Recommendation System for Precision Farming in WardhaAishwarya Kadu, KTV ReddyAgricultural productivity is crucial for economic growth of a nation, especially for countries like India which is highly dependent on agriculture. This study addresses the need for cutting-edge technology to enhance crop productivity by proposing a Mobile/Web-based precision farming system. Leveraging Machine Learning (ML) algorithms, the proposed system recommends optimal crops based on several factors such as environmental parameters (Nitrogen … …Journal of Computer Science, Vol. 22, Issue 3 · 20 Mar 2026 · 1,660 accessesView PDFCite
Research ArticleOpen accessIn the abstractEdge Computing Enabled Human Activity Recognition (ECEHAR) Using LSTM and CNNSuresh Kumar, M Y. Mohamed ParveesHuman Activity Recognition (HAR) is an important research area for various application domains such as healthcare, gaming, telemonitoring, and sports. However, executing HAR algorithms on remote servers or in the cloud have challenges in terms of high latency, increased bandwidth demand, and high energy consumption. Moving the computation to edge-assisted HAR is more effective and flexible solution to address the … …Journal of Computer Science, Vol. 22, Issue 3 · 6 Mar 2026 · 1,578 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Dynamic Lifelong Learning Network for Real-Time Stock Prediction With Reinforcement TuningTalent Mawere, Selvaraj Rajalakshmi, Venu Madhav Kuthadi, Otlhapile DinakanyaneCompanies and investors require accurate market forecasting to make more informed decisions. Traditional methods for predicting stock market performance have become less useful considering the dynamic and volatile nature that characterizes stock markets today. In this paper, we propose an innovative Dynamic Lifelong Learning Network for stock market prediction. The model incorporates a hybrid convolutional long short-term memory with an … …Journal of Computer Science, Vol. 22, Issue 2 · 20 Feb 2026 · 1,822 accessesView PDFCite