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Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDFCite
Research ArticleOpen accessIn the abstractRK4 Differential Equation to improve QoS in an eUTRAN LTE Network: A Deterministic vs. Stochastic ApproachBrou Pacôme, Pandry Ghislain, Bodjré Aka Hugues Félix, Oumtanaga SouleymaneImproving Quality of Service (QoS) in an eUTRAN LTE network is essential to guarantee optimal performance in the face of dynamic variations in user traffic and radio channel interference. In this context, this paper explores the use of 4th-order Runge-Kutta differential equations (RK4) to model and optimize radio resource management, by comparing a deterministic approach, which assumes stable and predictable … …Journal of Mathematics and Statistics, Vol. 21, Issue 1 · 3 Jul 2025 · 5,877 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Plant Disease Identification Through Hyperspectral Imaging and AC-FNet FrameworkDhason Lita Pansy, Malaichamy MuraliThe precise identification of plant diseases is essential for optimizing agricultural practices. The impact of these diseases on food production often leads to significant revenue loss. Detecting diseases that primarily manifest symptoms in plant leaves has conventionally depended on visual inspection by plant pathologists. However, modern methodologies use machine learning and computer vision techniques to facilitate disease identification, thus addressing … …Journal of Computer Science, Vol. 21, Issue 5 · 21 May 2025 · 8,568 accessesView PDFCite
Research ArticleOpen accessIn the abstractStroke Risk Assessment with Classical ML MethodsMohammad Aref Alshraideh, Najwan Alshraideh, Abedalrahman Alshraideh et al.Stroke, often caused by a disruption in the supply of essential oxygen, blood, and nutrients to the brain, represents a significant global health challenge. Due to limited resources, developing countries like Ethiopia face unique obstacles in identifying and treating strokes. This study explores the potential of Machine Learning (ML) techniques to predict stroke risk and facilitate early detection and intervention. … …Journal of Computer Science, Vol. 21, Issue 1 · 18 Dec 2024 · 4,649 accessesView PDFCite
Research ArticleOpen accessIn the abstractDevelopment of Big Data Classifier for Biomedicine Early Diagnosis: An Experimental Approach Using Machine Learning MethodsMa Beth Solas Concepcion, Bobby Dioquino Gerardo, Frank Ibañez Elijorde et al.In the fast-phase world, data availability is abundant due to a rapid adaptation increase of big data technologies. Large amounts of data have been generated and collected at an unprecedented speed and scale, introducing a revolution in medical research practices for biomedicine informatics. Thus, there is an immense demand for statistically rigorous approaches, especially in the medical diagnosis discipline. Therefore, … …Journal of Computer Science, Vol. 20, Issue 4 · 1 Feb 2024 · 5,510 accessesView PDFCite
Research ArticleOpen accessIn the abstractConvolution Neural Networks of Dynamically Sized Filters with Modified Stochastic Gradient Descent Optimizer for Sound ClassificationManu Pratap Singh, Pratibha RashmiDeep Neural Networks (DNNs), specifically Convolution Neural Networks (CNNs) are found well suited to address the problem of sound classification due to their ability to capture the pattern of time and frequency domain. Mostly the convolutional neural networks are trained and tested with time-frequency patches of sound samples in the form of 2D pattern vectors. Generally, existing pre-trained convolutional neural … …Journal of Computer Science, Vol. 20, Issue 1 · 13 Dec 2023 · 5,781 accessesView PDFCite
Research ArticleOpen accessIn the abstractBi-Stable Vibration Power Generation System Using Electromagnetic Motor and Efficiency Improvement by Stochastic ResonanceWei Zhao, Yoshiro Fujiwara, Jingchao Guan et al.Research on vibration energy harvesting using stochastic resonance has become an important research topic. A vibration energy harvesting system was developed using electromagnetic motors based on an obliquely supported bistable motion model consisting of a spring mass. After formulating the motion-governing equations of the proposed vibrating system and analyzing its potential energy performance, it was demonstrated that the system exhibits … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 3 · 2 Aug 2023 · 5,734 accessesView PDFCite
Research ArticleOpen accessIn the abstractProbabilistic Mechanics of Glass Suggests a Model for COVID-19 EpidemicsGabriele Pisano, Antonio Bonati, Gianni Royer CarfagniThe presented statistical model allows us to identify the degree of development of an epidemic starting from the observation of the number of deaths in the invested region, categorized by the age of the victims. Recognition of which cases are associated with the disease is not necessary, as this results from the comparison with data on deaths in pre-epidemic conditions. … …International Journal of Structural Glass and Advanced Materials Research, Vol. 6, Issue 1 · 26 Jan 2023 · 8,910 accessesView PDFCite
Research ArticleOpen accessIn the abstractTAGN-IDC: Implicit Discrete Constraints for Tsunami Aware Graph Neural Networks in Spatial Evacuation RoutingSularno, Wendi Boy, Putri Anggraini et al.Tsunami evacuation route requires rapid identification of safe evacuation paths under dynamically changing hazard conditions. A major challenge is incorporating hard binary road-blockage constraints caused by tsunami inundation while maintaining end-to-end differentiability for deep learning models. Existing approaches commonly rely on continuous relaxations or stochastic sampling techniques, which either compromise physical feasibility or increase computational complexity. This study proposes the … …Journal of Computer Science, Vol. 22, Issue 9 · 24 Sep 2026 · 704 accessesView PDFCite
Research ArticleOpen accessIn the abstractOn the Valuation of Currency Options in Stressed MarketsAbdulnasser Hatemi-J, Youssef El-KhatibThe current article handles the valuation of currency options in the market that is suffering from a financial crisis. The standard formulas for this purpose do not perform accurately. European foreign currency exchange options for both the call and the put versions are dealt with. It is assumed that the value of the underlying asset is a stochastic process that … …Journal of Mathematics and Statistics, Vol. 17, Issue 1 · 24 Dec 2021 · 6,499 accessesView PDFCite