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325 results for “Objective Model”
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Research ArticleOpen accessIn the abstractCybersecurity Mechanism for Automatic Detection of IoT Intrusions Using Machine LearningCheikhane Seyed, MBaye Kebe, Mohamed El Moustapha El Arby et al.This article proposes an ML-based cyber security mechanism to optimize intrusion detection that attacks internet objects (IoT). Our approach consists of bringing together several learning methods namely supervised learning, unsupervised learning and reinforcement learning within the same Canvas. The objective is to choose among them the most optimal for classifying and predicting attacks while minimizing the impact linked to the … …Journal of Computer Science, Vol. 20, Issue 1 · 11 Dec 2023 · 6,186 accessesView PDFCite
Research ArticleOpen accessIn the abstractLiDAR-Based Obstacle Detection and Avoidance for Navigation and Control of an Unmanned Ground Robot Using Model Predictive ControlSai Charan Dekkata, Sun Yi, M. A. Muktadir, Selorm GarfoUnmanned Ground Vehicles (UGVs) have, as of late, been utilized in a wide assortment of utilizations because of their flexibility, diminished expense, and quick response, among other benefits. Search and Rescue (SAR) is quite possibly the most conspicuous zones for the work of UGVs instead of a monitored mission, mainly due to its impediments on the expenses, human resources, and … …Journal of Mechatronics and Robotics, Vol. 7, Issue 1 · 30 Mar 2023 · 8,219 accessesView PDFCite
Research ArticleOpen accessIn the abstractStochastic and Deterministic Mathematical Modeling and Simulation to Evaluate the Novel COVID-19 Pandemic Control MeasuresEva Gupta, Nand Jee Kanu, Amartya Munot et al.Background: In India, the novel Coronavirus Disease (COVID-19) epidemic has grown to 17,00000 cases and around 38,000 deaths up to 30th July, 2020. The impacts of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic in India were studied using modified age-structured stochastic and deterministic mathematical models. Methods: A compartmental susceptible (S)-infected (symptomatic) (IS) infected (asymptomatic) (IN) recovered (R) i.e., … …American Journal of Infectious Diseases, Vol. 16, Issue 4 · 20 Nov 2020 · 8,461 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn Integrative Model for the Study of Attitudes Towards Statistics, Part 1: Establishing the Conceptual ModelMatus Ericka, Matus Lorena, Rodríguez Lucas, de Tristán SvetlanaWe propose a model to study attitudes towardsstatistics in higher education teachers. In the literature, there is a host ofscientific articles aimed at developing and applying measurement instrumentswhose psychometric characteristics are generally statistically acceptable.However, publications on the structure of attitudes and their relationship withteaching are relatively scarce-especially those dedicated to statistics inhigher education. Based on the system of attitudes proposed … …Journal of Social Sciences, Vol. 18, Issue 1 · 19 Sep 2022 · 5,901 accessesView PDFCite
Research ArticleOpen accessIn the abstractFlock Optimization Algorithm-Based Deep Learning Model for Diabetic Disease Detection ImprovementDivager Balasubramaniyan, Nor Azura Husin, Norwati Mustapha et al.Worldwide, 422 million people suffer from diabetic disease, and 1.5 million die yearly. Diabetes is a threat to people who still fail to cure or maintain it, so it is challenging to predict this disease accurately. The existing systems face data over-fitting issues, convergence problems, non-converging optimization complex predictions, and latent and predominant feature extraction. These issues affect the system's … …Journal of Computer Science, Vol. 20, Issue 2 · 8 Jan 2024 · 5,216 accessesView PDFCite
Research ArticleOpen accessIn the abstractActive Reset and Scheduling in Fault-Tolerant Quantum-Classical Cloud ComputingMohamed El-DosukyQuantum-classical cloud computing refers to a hybrid computing model that integrates quantum computing with classical computing resources, typically hosted on the cloud. The objective of this paper is threefold: First, to scrutinize the computing paradigm of quantum-classical cloud computing; second, to study the three pillars of the underpinning techniques: Active reset, scheduling, and fault tolerance; third, to demonstrate the realization … …Journal of Computer Science, Vol. 22, Issue 7 · 1 Sep 2026 · 775 accessesView PDFCite
Research ArticleOpen accessIn the abstractCharacterization of the Changes in Opened Sufu Bottles During Storage with Mathematical ModelJingJing Liang, Dawei Li, Ruiqin Shi et al.Artificial Neural Network (ANN) is a type of nonlinear empirical model, which can clarify the complex relation between the inputs and outputs that allows it to approximate any nonlinear function for making predictions. The objective of this study is to monitor the Biogenic Amines (BAs) content and selected physicochemical properties of sufu (a traditional Chinese fermented soybean product) along time. … …American Journal of Biochemistry and Biotechnology, Vol. 14, Issue 4 · 12 Dec 2018 · 9,357 accessesView PDFCite
Research ArticleOpen accessIn the abstractChilled Water VAV System Optimization and Modeling Using Artificial Neural NetworksRand Talib, Nabil Nassif, Maya Arida, Taher Abu-LebdehIn 2016, It was estimated that about 40% of total U.S. energy consumption was consumed by the residential and commercial sectors. According to EIA, in 2009, the energy consumption in U.S. homes was 48% which was down from 58% in 1993 (Residential Energy Consumption Survey (RECS). The development of building energy savings methods and models becomes apparently more necessary for … …Energy Research Journal, Vol. 9, Issue 1 · 6 Feb 2019 · 6,452 accessesView PDFCite
Research ArticleOpen accessIn the abstractSelf-Supervised Contrastive Learning for Steering Angle Prediction in Autonomous Driving SimulationsMaxson Phang, Suryadiputra LiawatimenaPredicting steering angles is a crucial task in autonomous driving, with end-to-end deep learning being a widely used approach. However, such models often suffer from overfitting to learned trajectories, limiting their generalization to new data. To address this, self-supervised contrastive learning is explored as an alternative, allowing models to learn meaningful representations without labeled data. The primary objective is to … …Journal of Computer Science, Vol. 21, Issue 9 · 20 Oct 2025 · 2,588 accessesView PDFCite
Research ArticleOpen accessIn the abstractModern Metaheuristic with Multi-Objective Formulation for the Variable Selection ProblemLauro Cassio Martins de Paula, Anderson da Silva Soares, Telma Woerle Soares et al.The development of efficient algorithms for variable selection becomes important to deal with large and complex datasets. Most works in quantitative chemical analysis have used Genetic Algorithms (GAs) as a reference method to select variables. On the other hand, new advances in metaheuristic techniques provide novel possibilities in this task Moreover, the application of Multi-Objective Optimization (MOO) may significantly contribute … …Journal of Computer Science, Vol. 13, Issue 11 · 20 Nov 2017 · 7,668 accessesView PDFCite