Research ArticleOpen accessIn the abstractEffects of Fertilization Frequency and Amount on the Chemometric Characteristics, Physiology, and Yield of Tomato Under Substrate CultivationEnling Ji, Qianqian Di, Qingjie Du et al.This study examined the effects of fertilization frequency and quantity on growth, yield, and quality of tomatoes under substrate cultivation. A factorial experiment evaluated two fertilization frequencies (every 5 or 10 days) and three fertilization levels (15.69, 31.38, or 62.76 kg·ha⁻¹), along with an unfertilized control. Plants were assessed for growth and development, photosynthetic pigment content, gas exchange parameters, nutrient … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 16 Feb 2026 · 1,718 accessesView PDFCite
Research ArticleOpen accessIn the abstractComplex SQL-NoSQL Query Translation for Data Lake ManagementNurhadi, Rabiah Abdul Kadir, Ely Salwana Mat SurinA data lake refers to an extremely large data resource or repository. Data lakes store large amounts of data and use advanced analytics to pair data from multiple sources with different types of structured, semi-structured, and unstructured information. NoSQL databases such as Mongodb, Redis, Neo4j, and Cassandra are nontabular and they store data differently rather than use relational tables. NoSQL … …Journal of Computer Science, Vol. 18, Issue 12 · 19 Dec 2022 · 9,281 accessesView PDFCite
Review ArticleOpen accessIn the abstractReview of Fault Tolerance, Replication, and Fragmentation in Grid-Cloud Distributed SystemsMohammed Adam Kunna Azrag et al.The study investigates key aspects of data management in distributed systems, focusing on fragmentation, replication and fault tolerance. With the increasing complexity of modern applications, efficient data handling across multiple nodes has become critical. The study begins by reviewing existing literature and moves on to analyze fragmentation techniques, evaluating their role in optimizing performance and resource utilization. Replication methods are … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,803 accessesView PDFCite
Research ArticleOpen accessIn the abstractAnalysis of the Operation of DC Interconnected Households PV under Weather ConditionsGilbert Ngoma, Maryse Dadina Nkoua Ngavouka et al.Installing Photovoltaic (PV) systems is becoming a viable solution for rural areas, with an innovative approach consisting of interconnecting autonomous PV-powered households. This study analyses the performance of interconnected autonomous PV households under different weather conditions using the Matlab Simulink R2016a software. Over and above this interconnection analysis, in this study, a new mathematical model to predict PV power is … …American Journal of Engineering and Applied Sciences, Vol. 18, Issue 1 · 4 Jan 2025 · 6,213 accessesView PDFCite
Research ArticleOpen accessIn the abstractCooling Load Prediction in the Under-Actuated Zone with Multilayer Perceptron Artificial Neural NetworkYaddarabullah, Aedah Abd Rahman, Amna SaadThis study focuses on addressing the challenge of predicting cooling loads in under-actuated zones, where the variability in occupant behavior, environmental conditions, and electronic usage creates complex dynamics. Traditional models like Support Vector Regression (SVR) and E-Lastic-Net (ELN) often struggle to capture these non-linear relationships, leading to inefficient Heating, Ventilation, and Air Conditioning (HVAC) management and increased energy consumption. To … …Journal of Computer Science, Vol. 21, Issue 3 · 27 Jan 2025 · 5,306 accessesView PDFCite
Research ArticleOpen accessIn the abstractMachine Learning Based Prediction of Catch Yields in Small Scale FisheriesEpifelward Niño Olaivar Amora, Patrick D. CernaSmall-scale fisheries are critical for food security and livelihoods but increasingly face threats from overfishing and environmental change. This study employed machine learning to predict catch yields in Cogtong Bay, Philippines, using 3,478 records collected in 2020–2021 that included species, gear, location, season, and weather data. Models developed in Python with scikit-learn and XGBoost compared Random Forest (RF), Extreme Gradient … …Journal of Computer Science, Vol. 22, Issue 8 · 24 Aug 2026 · 1,117 accessesView PDFCite
Research ArticleOpen accessIn the abstractBlockchain-Enabled Privacy-Preserving Access Control for Electronic Health Records Using Smart ContractsG. Bhanu Prasad, M. Venkateswara RaoElectronic medical records are crucial for providing high-quality healthcare, but they also raise serious privacy and security issues. Traditional centralised storage systems are vulnerable to manipulation, hacking, and illegal access. This study suggests a smart contract-based blockchain architecture that provides decentralised, unaltered, and privacy-preserving access control for EMRs. The model integrates cryptographic techniques like AES-256 encryption and SHA-256 hashing for … …Journal of Computer Science, Vol. 22, Issue 6 · 22 Jun 2026 · 1,313 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Based Smart Hydroponic System for Nutrient Management Using Predictive Machine Learning AlgorithmsPalash Gourshettiwar, K. T. V. ReddyHydroponics, an efficient cultivation method, benefits significantly from the precision and adaptability that Machine Learning (ML) algorithms can offer, along with the real-time monitoring facilitated by the devices using the Internet of Things (IoT). This study summarises the latest research and discusses how Machine Learning and the IoT work together, focusing on nutrient optimization, plant development, and resource efficiency. The … …Journal of Computer Science, Vol. 22, Issue 3 · 11 Mar 2026 · 3,056 accessesView PDFCite