43 results for “Conventional Extraction”

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Research ArticleOpen accessIn the keywordsAn Investigation on the Systems of Collecting and Extracting Greywater from Surface Water and WastewaterSaeid Eslamian, Mohammad Abdolhoseini, Kaveh Ostad-Ali-Askari, Vijay P. SinghLack of water resources, on the one hand and degradation of the quality of available resources; on the other hand, raise serious concerns about water supply. Limited water resources in some areas necessitate planning for use of unconventional resources, such as: Unconventional and recyclable water resources, which should be used optimally. Therefore, there is an increasing need for use of … …American Journal of Engineering and Applied Sciences, Vol. 14, Issue 2 · 7 Jun 2021 · 6,439 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsComparative Extraction of Pectic and Polyphenols from Mexican Lime Pomace and BagasseDaniela Sanchez-Aldana, Cristobal Noe Aguilar, Guadalupe Virginia Nevarez-Moorillon, Juan Carlos Contreras EsquivelMexican lime bagasse and pomace are rich in pectin and they also represent an important source of value-added compounds such as polyphenols. Two different options for the combined recovery of pectin and phenolic compounds from Mexican lime bagasse and pomace, two byproducts of industrial lime processing, were developed. Conventional and microwave-assisted extraction methods were used. All pectic extracts presented a … …American Journal of Agricultural and Biological Sciences, Vol. 8, Issue 4 · 29 Oct 2013 · 7,804 accessesView PDF Cite

Research ArticleOpen accessIn the abstractIncorporation of Modified Region Growing into FCM Clustering for Extraction of Tumors in MR ImagesLovepreet Singh Brar, Jaget Singh, Bhawana Agrawal et al.Due to the tremendous growth of medical Magnetic Resonance (MR) images, it becomes an essential requirement for an automated extraction of diagnostically salient parts of the images to refine the transmission and storage process. Research method: This paper proposes an automated unsupervised machine learning segmentation technique named fuzzy c-means clustering based on modified region growing algorithm (RG-FCM) for the extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,477 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Deep Learning Approach for Telugu Domain Identification with Multichannel LSTM-CNNBuddha Hari Kumar, Chitra Perumal, Inakoti Ramesh Raja et al.The vast growth of textual data has ushered into the limelight, a plethora of applications in information retrieval and natural language processing (NLP). Proper extraction of information from text is heavily dependent on recognizing the thematic content, which becomes crucial in the tasks of document summarization, information extraction, question answering, machine translation, and sentiment analysis. The great complexity of this … …Journal of Computer Science, Vol. 21, Issue 9 · 26 Nov 2025 · 2,395 accessesView PDF Cite

Research ArticleOpen accessIn the abstractPredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAI-Based Feature Extraction Approaches for Dual Modalities of Autism Spectrum Disorder NeuroimagesMeenakshi Malviya, Chandra J, Nagendra NHigh-dimensional data, lower detection accuracy, susceptibility to manual errors, and the requirement of clinical experts are some drawbacks of conventional classification models available for Autism Spectrum Disorder (ASD) detection. To address these challenges and explore the affiliated information from advanced imaging modalities such as Magnetic Resonance Imaging (MRI) in structural MRI (sMRI) and resting state-functional MRI (rs-fMRI), the study applied … …Journal of Computer Science, Vol. 20, Issue 11 · 28 Sep 2024 · 5,087 accessesView PDF Cite

Research ArticleOpen accessIn the abstractProtective Role of Ganoderma lucidum Polysaccharides Against Stress Induced by Heavy Metals in Caenorhabditis elegansHuixiu Ma, Dehui Dai, Guicai Chen, Weilian HuAli, H., Khan, E., & Ilahi, I. (2019). Environmental Chemistry and Ecotoxicology of Hazardous Heavy Metals: Environmental Persistence, Toxicity, and Bioaccumulation. Journal of Chemistry, 2019, 6730305. https://doi.org/10.1155/2019/6730305 Aljerf, L., & Aljerf, N. (2023). Food products quality and nutrition in relation to public. Balancing health and disease. Progress in Nutrition, 25(1), e2023024. https://doi.org/10.23751/pn.v25i1.13928 Aljerf, L., Williams, M., Ajong, A. B., Onydinma, … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 2 · 18 May 2024 · 6,947 accessesView PDF Cite

Research ArticleOpen accessIn the abstractCustomized Named Entity Recognition Using Bert for the Social Learning Management System Platform CourseNetworkingKayal Padmanandam, KVN Sunitha, Behafarid Mohammad Jafari et al.Named Entity Recognition (NER) is an information extraction task and one of the most researched applications to extract knowledge from massive data. Conventional NER systems identify predefined entities like name, person, location, organization, time, etc. However, there is a limitation to identifying user-defined entities that are specific to an application. This challenge introduces the concept of customized NER. For instance, … …Journal of Computer Science, Vol. 20, Issue 1 · 15 Dec 2023 · 6,985 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEnhancing Kidney Stone Detection Accuracy Using Image Processing and a Hybrid Convolutional Deep Belief NetworkGeetha M. N, Barkathulla A, S. Nandhini Devi et al.Automated CKD is a rapidly expanding non-communicable ailment that significantly contributes to global mortality and morbidity. CKD impacts more than 10% of the worldwide population, leading to millions of deaths annually. This paper proposes an enhanced deep learning model for renal disease detection that integrates convolutional and involution layers to enhance classification accuracy. CKD is a worldwide health issue characterised … …Journal of Computer Science, Vol. 22, Issue 10 · 9 Oct 2026 · 749 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid BiGRU-BiLSTM Model for Real-Time ECG Arrhythmia Detection Using Wearable SensorsPrem Narayan Singh, Rajendra Prasad MahapatraAccurate and real-time detection of cardiac arrhythmias is essential for timely medical intervention. Advances in wearable devices and deep learning have made it feasible to continuously monitor electrocardiogram (ECG) signals, facilitating early identification of abnormal heart rhythms. For arrhythmia detection, this study presents a hybrid deep learning architecture combining Bidirectional Gated Recurrent Units (Bi-GRU) and Bidirectional Long Short-Term Memory (Bi-LSTM). … …Journal of Computer Science, Vol. 22, Issue 5 · 5 Jun 2026 · 1,331 accessesView PDF Cite