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Research ArticleOpen accessIn the keywordsBitrate Scalability for Multi-Pulse Based Code Excited Linear Prediction Speech CoderSuphattharachai Chomphan, Chutarat ChompunthProblem statement: The bitrate scalability is an important functionality that is defined in the Moving Picture Expert Group (MPEG-4) requirements. Since the traffic in a communication network varies with time, the capability of varying the bitrate of a speech coder is needed. Approach: This study proposes an approach to vary the bitrate by using a bitrate scalable tool which is … …American Journal of Applied Sciences, Vol. 9, Issue 3 · 14 Jan 2012 · 7,035 accessesView PDFCite
Research ArticleOpen accessIn the keywordsThe New Reality of Competing: Strategic Marketing Intelligence and the Assessment of the Business Transformational Model PropositionNurhan Papatya, Gurcan PapatyaProblem statement: The study contains "Strategic Marketing Intelligence (SMI)" contents and formation which are directed to the business’s permanent and continuous priority and the investigation of "transformational model proposition", designing bases, the thought of transformation to core competence and proposed model’s applicability and advantages. Approach: This study is handled as a qualitative assessment related to restricting content of the concepts … …American Journal of Economics and Business Administration, Vol. 3, Issue 3 · 20 Sep 2011 · 7,529 accessesView PDFCite
Research ArticleOpen accessIn the keywordsOptimization of Coaching Using Six SigmaDumitru Colibaba-Evulet, Andrei EvuletProblem statement: In today’s sports world, coaching and training methods are the subject of intensive competition amongst rivals. Innovative technologies, methodologies and preparation methods are employed to achieve a sustainable competitive advantage. Effective performance measurement, statistical analysis and data based decision taking have been identified as key elements towards efficient performance management. The statistical approach has been emphasized in order … …Journal of Social Sciences, Vol. 7, Issue 3 · 16 Jul 2011 · 8,054 accessesView PDFCite
Research ArticleOpen accessIn the keywordsTonal Language Speech Compression Based on a Bitrate Scalable Multi-Pulse Based Code Excited Linear Prediction CoderSuphattharachai ChomphanProblem statement: Speech compression is an important issue in the modern digital speech communication. The functionality of bitrates scalability also plays significant role, since the capacity of communication system varies all the time. When considering tonal speech, such as Thai, tone plays important role on the naturalness and the intelligibility of the speech, it must be treated appropriately. Therefore these … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 6,810 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 349 accessesView PDFCite
Research ArticleOpen accessIn the abstractEffectual Deep Learning Based Digital Image Forgery Detection Model Using Ameliorate CNN, VGG 16 and VGG 19 for Copy Move and Image Splicing Classification With Enhanced PerformancePreeti Dhiman, Usha ChauhanIn this research, a pioneer passive approach for detecting and localizing tampering in images is proposed. In the past, image forgeries have created a huge impact in the world. Developments of various image processing technologies made it easier to tamper images with the objective to cover up or hide a significant feature in an image. In some situation, such as … …Journal of Computer Science, Vol. 22, Issue 10 · 3 Oct 2026 · 568 accessesView PDFCite
Research ArticleOpen accessIn the abstractUMPM-Net: A Multimodal Deep Learning Framework for Colorectal Cancer PrognosisK. Muthuchamy, S K. Piramu PreethikaColorectal cancer (CRC) is one of the most common cancers worldwide, for which early prediction of patient outcomes is important for personalised treatment planning and to improve survival. However, current prediction systems are limited in the fact that they are based on single-modality data and cannot capture the complex interactions between clinical, imaging, and genomic factors. To overcome these shortcomings, … …Journal of Computer Science, Vol. 22, Issue 9 · 20 Sep 2026 · 613 accessesView PDFCite
Research ArticleOpen accessIn the abstractHMA-RAG: A Hierarchical Memory Augmented Retrieval Augmented Generation Framework for Fake News DetectionAfnan Altarjami, Sawsan AlshattnawiExisting methods for detecting fake news, such as traditional machine learning and transformer-based models, often work as separate classifiers that do not use outside evidence, historical knowledge, or ways to make the results easier to understand. This paper presents a framework that combines retrieval augmentation and hierarchical memory to overcome three primary constraints: Insufficient external evidence, the absence of memory, … …Journal of Computer Science, Vol. 22, Issue 9 · 7 Sep 2026 · 735 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Data Mining Driven Framework for Image-Based Crop Stress Analysis Using IPCA, FP-Growth, ConvLSTM, and Sequential ModelsA. Josephine, A. SubhashiniDetecting crop stress before it becomes serious has a major impact on the food supply. It helps in avoiding the loss of crops, increases productivity and helps farmers to practice precision farming. Most technologies today are designed specifically to either detect crop stress or to predict how well the crop will grow. Many of the technologies do not combine the … …Journal of Computer Science, Vol. 22, Issue 8 · 21 Aug 2026 · 922 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