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27 results for “Automated Evaluation”
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Research ArticleOpen accessPhrase in the titleAutomated Evaluation of Short Answers Using Text Similarity for the Portuguese LanguageSilvério Sirotheau, Joao C.A. dos Santos, Eloi L. Favero, Simone N. de FreitasAlong with the development of distance education, emerges the demand for virtual environments as the automated evaluation studies of essays that has already produced promising results. However, when dealing with short answers, replicating the decisions of a human grader is still a challenge, as the portability of essay evaluation techniques to short answers has not produced results with the same … …Journal of Computer Science, Vol. 15, Issue 11 · 21 Nov 2019 · 6,899 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleImplementation and Evaluation of Evolutionary Connectionist Approaches to Automated Text SummarizationUday Kulkarni, Rajesh Shardanand PrasadProblem statement: Text summarization takes care of choosing the most significant portions of text and generates coherent summaries that express the main intent of the given document. This study aims to compare the performances of the three text summarization systems developed by the authors with some of the existing Summarization systems available. These three approaches to text summarization are based … …Journal of Computer Science, Vol. 6, Issue 11 · 23 Oct 2010 · 8,489 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleEvaluation of a New Device, Automated Shower head on Water Conservation in Bath ShowersM. Shamsi, G. H.S. BonjarIn cosmopolitan areas and big cities of the world, shortage of drinking water during the peaks of consumption hours is a noticeable problem. Many people may not have piped water during these critical hours especially in summer times. To minimize this problem, an electronic control valve was designed and developed which saved about 70% of water in each showering session … …American Journal of Applied Sciences, Vol. 1, Issue 4 · 31 Dec 2004 · 7,201 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review of Artificial Intelligence and Deep Learning Approaches for Cocoa Pod Disease DetectionHenry Techie-Menson, Michael Asante, Yaw Marfo Missah et al.Cocoa pod diseases destroy an estimated 700,000 metric tons of cocoa annually, threatening 40–50 million smallholder farmers across tropical regions. Accurate field diagnosis remains constrained by symptom similarity, labour-intensive scouting, and limited specialist access in remote communities. This paper presents a PRISMA-guided systematic review of 25 peer-reviewed studies on automated cocoa pod disease detection and classification (2016–2026), addressing architectural approaches, … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 733 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetecting Novelty in Indonesian Research Grant Proposals Using Machine Learning and Natural Language ProcessingWalanstar Alimcan Sitorus, Evaristus Didik MadyatmadjaAssessing the novelty of research proposals represents a critical challenge in large-scale research grant management, particularly when the number of submitted proposals is substantial and topic diversity continues to increase. This study proposes an analytical approach to detect the novelty of Indonesian academic research proposal titles by leveraging semantic similarity based on Natural Language Processing (NLP). The CRISP-DM framework is … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Aug 2026 · 1,067 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Deep Learning Model for Evaluating Subjective Answers Based on Semantic Textual SimilaritySiddhesh Kudtarkar, Kavita ShirsatSubjective answer evaluation requires accurately identifying semantic similarities between student and reference responses. This study introduces a Hybrid Deep Learning Model (HDLM) that integrates CNN, GRU, and LSTM architectures to assess Semantic Textual Similarity (STS) more effectively. The HDLM employs two parallel branches-CNN-GRU and CNN-LSTM to capture both local syntactic features and long-range contextual dependencies, followed by Manhattan distance for … …Journal of Computer Science, Vol. 22, Issue 4 · 7 Apr 2026 · 1,690 accessesView PDFCite
Research ArticleOpen accessIn the abstractIoT-Integrated CNN Deep Learning for Automated Breast Cancer Detection and DiagnosisYamini Kalva, R. Ganesh Babu, Sindhu V. et al.Breast cancer continues to be a primary cause of death in women, requiring prompt and accurate diagnosis to enhance treatment results. Traditional diagnostic techniques depend on manual assessment, which leads to possible misclassification, significant inter-observer variability, and delays in decision-making. Current deep learning models, including CNNs, frequently experience feature loss, gradient declining and restricted adaptability to real-time data. To overcome … …Journal of Computer Science, Vol. 22, Issue 4 · 30 Mar 2026 · 1,753 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Comprehensive Review of Medical Image Denoising: Techniques, Challenges, Applications and Future DirectionsMohit Sharma, Ayush Dogra, Anita Gupta et al.The concept of noise reduction in medical images plays a vital role in improving image quality and accuracy associated with diagnosis, and facilitating reliable automated analysis. This survey presents a structured overview of medical image denoising, beginning with foundational definitions and noise models for modalities such as MRI and CT. We critically evaluate persistent gaps, including the limited generalizability of … …Journal of Computer Science, Vol. 22, Issue 3 · 28 Mar 2026 · 1,849 accessesView PDFCite
Research ArticleOpen accessIn the abstractAdvancing Stroke Lesion Segmentation With U-Net Variants: Classical, Transfer Learning, and MRI Sequence-Specific Customized ApproachesSonia Flora Panesar, Amit P. GanatraIschemic stroke, caused by restricted cerebral blood flow, is a leading cause of death and disability worldwide. Accurate segmentation of stroke lesions in MRI is essential for timely diagnosis but remains labor-intensive when done manually. This study presents a comparative evaluation of three U-Net variants for automated ischemic stroke lesion segmentation using the ISLES 2022 dataset: (1) Classical U-Net with … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,791 accessesView PDFCite
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 PDFCite