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Research ArticleOpen accessIn the abstractMachine Learning Oceanographic Data for Prediction of the Potential of Marine ResourcesDenny Arbahri, Oky Dwi Nurhayati, Imam MuditaMarine data and information are very important for human survival, therefore this data and information is attractive to investors because of the potential economic value. This data and information has been difficult to obtain, the solution to overcome this is by analyzing oceanographic data for 2009-2019 collected from the marine database belonging to the Agency for the Study and Application … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,975 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparative Analysis of Five Decomposition Techniques for Monthly Rainfall Time Series from 1991 to 2020 in Guinea (West Africa)Noukpo Médard Agbazo, Oumar Keita, Alpha Oumar Baldé et al.The selection of an optimal time series decomposition’ technique is crucial for enhancing rainfall prediction by using sophisticated methods as deep learning hybrid approaches. This study evaluates the effectiveness of five times series decomposition techniques in analyzing monthly rainfall datasets across Guinea geographical regions (Lower-Guinea (Boké, Conakry, Kindia), Middle-Guinea (Labé, Mamou), Upper-Guinea (Faranah, Kankan) and Forest-Guinea (Nzérékoré)) and identifies the … …American Journal of Applied Sciences, Vol. 22, Issue 1 · 27 Jan 2026 · 3,047 accessesView PDFCite
Research ArticleOpen accessIn the abstractMultimedia Image Retrieval Using Novel Modelling of Combined Binary Patterns with Reduced DimensionsM. Geetha Yadav, SP. ChokkalingamAdvancements in computer vision have transformed image retrieval. However, many existing systems struggle to bridge the semantic gap between low-level features and high-level user expectations. This study proposed a new approach that combines texture and colour features to enhance retrieval accuracy and user satisfaction. The proposed method employs the HSV colour model to extract colour features, focusing on dominant features … …Journal of Computer Science, Vol. 21, Issue 4 · 14 Apr 2025 · 5,224 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Support and Resistance Indicators for Stock Market with Fibonacci Sequence in Long Short-Term MemoryThambusamy Velmurugan, Thiruvalluvan IndhumathyPredictive data analytics is a branch of data analytics where models are designed that effectively interpret; anticipate outcomes by analyzing present data to make predictions about future. One of the major attributes for prediction is time and there have been a considerable number of time series analytical models that are used for forecasting. Long Short-Term Memory (LSTM) is a deep … …Journal of Computer Science, Vol. 16, Issue 10 · 28 Oct 2020 · 7,323 accessesView PDFCite
Research ArticleOpen accessIn the abstractONCODIAG Select and Test (ST) Algorithm: An Approximate Clinical Reasoning Model for Diagnosing and Monitoring Breast CancerO.N. Oyelade, A.A. Obiniyi, S.B. JunaiduClinical reasoning involves coordinated thinking strategies targeted at gathering and analyzing relevant information to arrive at a high-quality clinical solution to patients' medical problems. The correctness and proper choice of clinical reasoning approach chosen by a clinician or machine affect the accuracy and acceptability of the diagnosis; moreover, another challenge that usually surfaces during clinical reasoning is the burden of … …Current Research in Bioinformatics, Vol. 9, Issue 1 · 22 Feb 2020 · 8,942 accessesView PDFCite
Review ArticleOpen accessIn the abstractHybrid Machine Learning Framework with Data Analytics Model for Privacy-Preserved Intelligent Predictive Maintenance in Healthcare IoTArun Ganji, D. Usha, P.S. RajakumarFederated Learning (FL) is a cutting-edge approach for developing machine learning (ML) models using distributed datasets while preserving data privacy and ownership. FL is particularly suited for Internet of Things (IoT) networks due to its decentralized nature, which supports In-Edge AI and maintains data locality. However, FL's complexity poses challenges in analyzing system health, making it crucial to develop robust … …Journal of Computer Science, Vol. 21, Issue 1 · 30 Nov 2024 · 5,830 accessesView PDFCite
Research ArticleOpen accessIn the abstractEpileptic Seizure Detection Using Integrated Decomposed Features from EEG SignalShupta Das, Suraiya Akter Mumu, M. A. H. Akhand, Md Abdus Samad KamalThe root cause of the seizure is a sudden abnormal excessive electrical discharge in the brain and it is an Epileptic Seizure (ES) when such abnormal electrical activity arises particularly for epilepsy. Recognizing ES is crucial for effective treatment as it often repeats and can lead to serious outcomes. Since epilepsy is a neurological issue, detecting ES by analyzing brain … …Journal of Computer Science, Vol. 20, Issue 10 · 8 Aug 2024 · 4,850 accessesView PDFCite
Research ArticleOpen accessIn the abstractDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,264 accessesView PDFCite
Research ArticleOpen accessIn the abstractModeling User Experience in Delivery Applications Using the Design Thinking Method and System Usability ScaleKevin Christianto, Aziza Chakir, Johanes Fernandes Andry et al.Technological developments bring comfort and ease to users in accessing applications. Companies need to design systems that are centered on human needs to create technology that is competitive in the market, especially in the field of expeditions. The problem that arises in the sea cargo expedition company is that master data recording is still done manually, which has an impact … …Journal of Computer Science, Vol. 20, Issue 7 · 17 Apr 2024 · 6,006 accessesView PDFCite
Research ArticleOpen accessIn the abstractDirect Sequence and Frequency Hopping Signals Classification Based on Co-Occurrence Matrix and Clustering TechniquesHaidy S. Fouad, Hend A. Elsayed, Shawkat K. GirgisSpread Spectrum techniques (SS) were first developed for military applications, but currently, they have commercial applications. SS provides secure communication and allows multiple accesses for same radio spectrum. So, most Wireless Local Area Network (WLAN) systems use it, as do Cognitive Radios (CR), space systems and Global Positioning Systems (GPS). Direct Sequence Spread Spectrum (DSSS) and frequency hopped spread spectrum … …Journal of Computer Science, Vol. 15, Issue 1 · 10 Jan 2019 · 8,214 accessesView PDFCite