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221 results for “Value of Information”
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Research ArticleOpen accessIn the abstractUltrasound-Assisted Enzymatic Extraction of Polysaccharides from Waste Corn Bract: Process Optimization, Characterization, Antioxidant and Anti-Diabetic PotentialsYihui Liu, Yayi Li, Na Niu et al.Corn bract is the main agricultural waste of corn production and processing. Little information is focused on its value-added utilization. In the present study, the Ultrasound-Assisted Enzymatic Extraction (UAEE) was used for the first time to extract Corn Bract Polysaccharides (CBPs). The optimum conditions of UAEE for CBPs extraction were: Cellulase amount of 0.7%, enzymolysis for 58 min, and ultrasound … …American Journal of Biochemistry and Biotechnology, Vol. 18, Issue 2 · 28 Jun 2022 · 6,126 accessesView PDFCite
Research ArticleOpen accessIn the abstractImplementing a Hybrid VMD–BiTCN–BiGRU Architecture With Intelligent Optimization for Agricultural Commodity Price Prognostication in Gujarat MarketsJignesh Hirapara, Ratnesh Kumar Namdeo, Ankit Kumar Dubey et al.In the agricultural sector, the prices of pulses require adequate forecasting to plan farming activities, store and market, and guide policy-making. However, the pulse price series is highly volatile, seasonal, nonstationary, and nonlinear, and thus conventional linear time series models are not necessarily very effective. In the suggested framework, the raw price data series is decomposed using Variational Mode Decomposition … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Aug 2026 · 1,021 accessesView PDFCite
Research ArticleOpen accessIn the abstractForecasting Corporate Financial Distress Using Explainable Machine Learning: Implications for Risk Management TechnologyKanjana Hinthaw, Warawut NarkbunnumFinancial distress prediction is a critical task in financial risk management, yet it remains challenging due to class imbalance, complex financial structures, and limited model interpretability. This study develops an integrated machine learning framework that combines feature selection, class imbalance handling, threshold optimization, and Explainable Artificial Intelligence (XAI) to improve both predictive performance and decision-making reliability. Using a dataset of … …Journal of Computer Science, Vol. 22, Issue 7 · 22 Jul 2026 · 1,130 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplication of Machine Learning for the Detection of Depression and Mindfulness as a Mitigation MethodSantiago Domingo Moquillaza Henriquez, Liliana Ruth Huamán Rondón et al.Depression is a global mental health problem with various causes. Nowadays, with Artificial Intelligence, it can be predicted in order to take preventive measures, whether at a psychotherapeutic or pharmacological level. This research, based on a survey conducted, detects depression using logistic regression with a 91% fit to the ROC-AUC model, accuracy of 0.839188, precision 0.851354. In addition, a study … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,216 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Sentiment-Aware Hybrid Ensemble Clustering Framework for Social Network Content Analysis and Community DiscoveryDhimesh Pravinbhai Parmar, Paresh TannaSocial media stages produce huge volumes of short, familiar, and sentiment-rich content that offerings significant encounter for community discovery and thematic analysis. Traditional clustering approach struggle with sparsity, noise, and limited surroundings information present in such texts. To address these limitations, this study introduces a sentiment-aware hybrid ensemble clustering framework designed openly for social network content analysis. The planned method … …Journal of Computer Science, Vol. 22, Issue 5 · 26 May 2026 · 1,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractFrom Digital Engagement to Social Welfare: Measuring the Impact of the mSmart Application in a Developing RegionHendro Nindito, Evaristus Didik Madyatmadja, Siti Elda Hierra, MaryaniThe mSmart platform, introduced as a pilot initiative in Labuan Bajo, Indonesia, was developed to strengthen community participation in local digital services. This study explores the extent to which the application delivers social value to its users and the broader community. Guided by the Information Systems Success Model (ISSM) and the WebQual framework, the research focuses on three main factors: … …Journal of Computer Science, Vol. 22, Issue 5 · 25 May 2026 · 1,228 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized XGBoost for Ethereum Fraud Detection: A Cost-Sensitive ApproachSupriya P., Rubah Sheriff, Shreya Padaki et al.In today’s technologically advancing world, many fields from finance to healthcare and education are shifting toward a digital and decentralized format. A significant transformation is underway with the currency of the masses. Blockchain-based cryptocurrencies like Bitcoin and Ethereum allow users to generate fungible tokens anonymously through smart contracts. However, these features also facilitate illicit transactions and cybercrimes like fraud, phishing, … …Journal of Computer Science, Vol. 21, Issue 12 · 10 Jan 2026 · 2,770 accessesView PDFCite
Research ArticleOpen accessIn the abstractGender Classification from Face and Eyes Images Using Deep Learning AlgorithmZahraa Salam Abu Ghrban, Nidhal Khdhair EL AbbadiGender classification provides additional information about the individual’s identity, which is crucial in surveillance, smart interface, and smart advertising, it is a very important aspect of face analysis that has piqued the interest of researchers in areas such as demographic information collection, surveillance, human-computer interaction, marketing intelligence, security, etc. Usually, facial images are used to extract features for classification. This … …Journal of Computer Science, Vol. 19, Issue 3 · 24 Feb 2023 · 6,937 accessesView PDFCite
Research ArticleOpen accessIn the abstractUnsupervised Cosegmentation Model based on Saliency Detection and Optimized Hue Saturation Value Features of SuperpixelsRasha Shoitan, Mona M. MoussaSegmenting out the foreground from a single image remains a challenge in computer vision. Image co-segmentation has been used recently to alleviate the single image segmentation by exploiting the information of the common object to be segmented from a group of images having the same object. This research proposes an unsupervised co-segmentation technique based on saliency detection and optimized features … …Journal of Computer Science, Vol. 17, Issue 7 · 3 Aug 2021 · 7,003 accessesView PDFCite