Research ArticleOpen accessIn the abstractIMPROVING INDEPENDENT COMPONENT ANALYSIS USING SUPPORT VECTOR MACHINES FOR MULTIMODAL IMAGE FUSIOND. Egfin Nirmala, A. Bibin Sam Paul, V. VaidehiThe objective of this study is to combine multiple images of a scene acquired by different sensors to create a new image with all important information from the input images. Recent studies show that bases trained using Independent Component Analysis (ICA) is effective in multisensor fusion and has improved performance over traditional wavelet approaches. In the ICA based fusion, the … …Journal of Computer Science, Vol. 9, Issue 9 · 6 Aug 2013 · 7,272 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation on Score Reliability for Biometric Speaker Authentication SystemsDzati Athiar Ramli, Haryati Jaafar, Muhammad Hazim HasanProblem statement: Fusion weight tuning based on score reliability is imperative in order to ensure the performances of multibiometric systems are sustained. Approach: In this study, two variant of conditions i.e., different performances of individual subsystems and inconsistent quality of test samples are experimented to multibiometric systems. By applying multialgorithm scheme, two types of features extraction method i.e., Linear Predictive … …Journal of Computer Science, Vol. 8, Issue 9 · 16 Aug 2012 · 7,238 accessesView PDFCite
Research ArticleOpen accessIn the abstractFeature Fusion in Improving Object Class RecognitionNoridayu Manshor, Amir Rizaan Abdul Rahiman, Mandava Rajeswari, Dhanesh RamachandramProblem statement: Extraction of features in object class recognition researches previously gives attention to local features as discriminative features. This is because local features have invariant properties that are robust to viewpoints, translation and rotation. However this feature still has a limitation to represent high-level representation of objects. The problem will occur if the object is too small and do … …Journal of Computer Science, Vol. 8, Issue 8 · 24 Jul 2012 · 6,907 accessesView PDFCite
Research ArticleOpen accessIn the abstractRule Based Shallow Parser for Arabic LanguageMona Ali Mohammed, Nazlia OmarProblem statement: One of language processing approaches that compute a basic analysis of sentence structure rather than attempting full syntactic analysis is shallow syntactic parsing. It is an analysis of a sentence which identifies the constituents (noun groups, verb groups, prepositional groups), but does not specify their internal structure, nor their role in the main sentence. The only technique used … …Journal of Computer Science, Vol. 7, Issue 10 · 4 Aug 2011 · 7,183 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrediction of End-of-Life Strategies for Household Equipments Using Artificial IntelligentM. M. Noor, K. Kadirgama, Aidy Ali et al.Problem statement: Environment issue on the dumping of used household product is a big challenge nowadays. Towards green design, life cycle of a product is very crucial. This study discussed on recycling strategies which include reuse, service, remanufacture and recycle with or without disassembly by using Support Vector Machine Method (SVM). Approach: In early stage of prediction, the input parameters … …American Journal of Applied Sciences, Vol. 6, Issue 10 · 31 Oct 2009 · 7,931 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Moment Features Extraction for Recognizing Handwritten Arabic LettersGheith Abandah, Nasser AnssariProblem statement: Offline recognition of handwritten Arabic text awaits accurate recognition solutions. Most of the Arabic letters have secondary components that are important in recognizing these letters. However these components have large writing variations. We targeted enhancing the feature extraction stage in recognizing handwritten Arabic text. Approach: In this study, we proposed a novel feature extraction approach of handwritten Arabic … …Journal of Computer Science, Vol. 5, Issue 3 · 31 Mar 2009 · 7,495 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Multi Model Ensemble for Engagement PredictionFahmida Begum, K Ulaga PriyaFor intelligent educational systems, the ability to monitor and respond to student engagement in real time is essential for enhancing learning outcomes. However, existing models often lack adaptability and practical deployment potential, as they depend on single data modalities, rigid ensemble mechanisms, and post-session analysis. This study introduces an intelligent multimodal ensemble framework designed to address these challenges by predicting … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,844 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Advancements for Lung Cancer Detection: An In-Depth Review and Future ProspectsAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarLung cancer is a major cause of cancer-related mortality globally, underscoring the necessity for efficient diagnostic instruments. The review paper summarizes the role of ML and DL in detection, staging, and prognostication of lung cancer. We evaluate the relative efficacy of several models, such as CNNs, SVMs, and ensemble approaches, by analyzing publically accessible imaging and molecular information. We emphasize … …Journal of Computer Science, Vol. 22, Issue 1 · 1 Mar 2026 · 1,794 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Indoor Asset Tracking: IoT Integration and Machine Learning Approaches for Optimized PerformanceRafiq Hamadamin Maulud, Sadegh Abdollah AminifarIndoor asset tracking entails the surveillance and governance of the position and movement of tangible assets within enclosed spaces, including warehouses, hospitals, and workplaces. Indoor asset tracking systems employ technologies such as Radio Frequency Identification (RFID), Bluetooth Low Energy (BLE), Wi-Fi, and UWB (Ultra-Wideband) to deliver real-time visibility and precise placement of goods. This research introduces indoor asset tracking with … …Journal of Computer Science, Vol. 21, Issue 7 · 7 Jul 2025 · 3,733 accessesView PDFCite
Review ArticleOpen accessIn the abstractProtein Sequences Features Extraction for Predicting Beta- Turns and their Types: A ReviewMurtada Khalafallah Elbashir ElfakiBeta-turns are considered to be important secondary structure types that have essential role in molecular recognition, protein folding and stability. They represent 25% of protein structures, therefore they are the most common type of non-repetitive or tight turns structures. Their prediction is considered to be an important issue in bioinformatics and molecular biology, because it provides valuable information and inputs … …Journal of Computer Science, Vol. 15, Issue 9 · 1 Oct 2019 · 7,694 accessesView PDFCite