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50 articles for “transformed data”
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Research ArticleOpen accessIn the keywordsFuzzy Time Series: An Application to Tourism Demand ForecastingMuhammad Hisyam Lee, Maria Elena Nor, Suhartono et al.Problem statement: Forecasting is very important in many types of organizations since predictions of future events must be incorporated into the decision-making process. In the case of tourism demand, better forecast would help directors and investors make operational, tactical and strategic decisions. Besides that, government bodies need accurate tourism demand forecasts to plan required tourism infrastructures, such as accommodation site … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,474 accessesView PDFCite
Research ArticleOpen accessIn the abstractApplying Dempster Shafer Theory and Causal Inference in Investigating Internet of Things Digital Forensic ChallengeMohamed El-Dosuky, Sherif K. Ratib et al.The rapid growth of IoT ecosystems has transformed digital forensics, creating challenges in analyzing distributed, heterogeneous, and uncertain evidence. Conventional forensic methods often struggle to handle ambiguous and conflicting IoT data, highlighting the need for robust frameworks that effectively manage uncertainty across multiple evidence sources. This research presents a hybrid forensic framework that integrates Dempster Shafer Theory (DST) for probabilistic … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 888 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Coding Schema-Based Mobile System for Children With ASD in MauritaniaCheikhne Mohamed Mahmoud Seyidi, Ahmed Mohameden, Mohamed Lamine Diakité, Mohamedade Farouk NanneChildren with Autism Spectrum Disorders (ASD) in many African countries face persistent barriers, including limited diagnostic awareness, scarce specialized resources, and the absence of educational interventions adapted to local contexts. In Mauritania, these challenges are exacerbated by the extreme centralization of autism services, with only two care centers available nationwide. Unlike existing ASD interventions that rely on imported pedagogical models … …Journal of Computer Science, Vol. 22, Issue 5 · 25 May 2026 · 1,312 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing User Satisfaction and System Trust through Gamification in E-Commerce PlatformsMontela Livanto, Viany Utami TjhinThe increasing adoption of gamification in e-commerce platforms has significantly transformed how people use, engage, and develop their trust in digital systems. Despite this, few empirical studies have so far investigated the integration of gamification with the DeLong and McLean IS Success Model to develop theories of user satisfaction and system trust in emerging markets. This study examines the influence … …Journal of Computer Science, Vol. 22, Issue 4 · 31 Mar 2026 · 1,570 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,680 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Fleet Management with GPS Data in Port Terminals: A Deep Learning Architecture for Truck Position PredictionMohammed El Karkraoui, Hicham AttariuasEffective truck fleet management in port terminals is crucial for improving operational efficiency and reducing delays. However, GPS-based positioning systems often face limitations in port environments due to signal obstructions and network issues. This study explores the utilization of advanced methods for deep learning, particularly Recurrent Neural Networks (RNNs) for predicting truck positions when GPS signals are unavailable or unreliable. … …Journal of Computer Science, Vol. 21, Issue 10 · 16 Dec 2025 · 2,271 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdaptive Data Transformation for Enhanced Clustering Performance in Diagnostic SystemsMohammed Subhi Al-BatahThis paper presents an enhanced approach to the Balanced Iterative Reducing and Clustering using Hierarchies (BIRCH) algorithm, aimed at improving clustering accuracy in medical data, specifically for breast cancer diagnosis. The proposed method introduces a modified data transformation technique to optimize the original BIRCH algorithm. This transformation refines the clustering process, resulting in significant improvements in diagnostic accuracy. The modified … …Journal of Computer Science, Vol. 21, Issue 9 · 17 Oct 2025 · 2,287 accessesView PDFCite
Research ArticleOpen accessIn the abstractBridging Innovation and Access: Randomized, Single-Dose, Open-Label, Parallel-Group Bioequivalence Study of Generic and Innovator Injection Semaglutide in IndiaMayur Madhav Mayabhate, Nitin Kapure, Akhilesh Sharma, Radhakrishna VaddemSemaglutide, a long-acting Glucagon-Like Peptide-1 (GLP-1) receptor agonist, is effective in improving glycemic control, reducing body weight, and lowering cardiovascular risk in Type 2 Diabetes Mellitus (T2DM). Limited accessibility of the innovator formulation underscores the need for bioequivalent generic alternatives. To assess the pharmacokinetic bioequivalence of a synthetic Semaglutide Injection (2 mg/1.5 mL) developed by Alkem Laboratories Ltd., India, compared … …American Journal of Pharmacology and Toxicology, Vol. 20, Issue 1 · 20 Apr 2026 · 2,626 accessesView PDFCite
Review ArticleOpen accessIn the abstractEconomic Theory and Machine Learning Integration in Asset Pricing and Portfolio Optimization: A Bibliometric Analysis and Conceptual FrameworkPatrick Kevin Aritonang, Sudarso Kaderi Wiryono, Taufik FaturohmanThe integration of Machine Learning (ML) with economic theory has transformed financial market analysis, particularly in asset pricing and portfolio optimization. This study synthesizes existing research, identifies gaps and elucidates ML's impact on enhancing economic models and strategies through a Systematic Literature Review (SLR) of 401 relevant documents using bibliometric methodology and VOS viewer. Results show an increasing trend in … …Journal of Computer Science, Vol. 20, Issue 10 · 7 Aug 2024 · 5,715 accessesView PDFCite
Research ArticleOpen accessIn the abstractGenerating IoT Specific Anomaly Datasets Using Cooja Simulator (Contiki-OS) and Performance Evaluation of Deep Learning Model Coupled with Aquila OptimizerVandana Choudhary, Sarvesh Tanwar, Tanupriya ChoudhuryIn recent times, the massive expansion of the Internet of Things (IoT) has transformed various facets of everyday life and industries. The compelling cause behind the widespread adoption of IoT is the increasing availability of affordable, compact, and energy-efficient computing devices. While these devices offer significant benefits, they also raise substantial security and privacy challenges. Consequently, safeguarding IoT networks and … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 6,850 accessesView PDFCite