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153 results for “random process”
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Research ArticleOpen accessIn the abstractDrawdown and Drawup of Bi-Directional Grid Constrained Stochastic ProcessesAldo Taranto, Shahjahan KhanThe Grid Trading Problem (GTP) of mathematical finance, used in portfolio loss minimization, generalized dynamic hedging and algorithmic trading, is researched by examining the impact of the drawdown and drawup of discrete random walks and of Itô diffusions on the Bi-Directional Grid Constrained (BGC) stochastic process for profit Pt and equity Et over time. A comprehensive Discrete Difference Equation (DDE) … …Journal of Mathematics and Statistics, Vol. 16, Issue 1 · 14 Sep 2020 · 9,158 accessesView PDFCite
Review ArticleOpen accessIn the abstractHuman Activity Recognition at the Edge: A Systematic Review of Machine Learning Models, Deployment Constraints, and Latency Energy Accuracy Trade offsJose Antonio Rojas Guillén, Wini Ebelin Quispe Bautista, Arturo Gamarra MorenoHuman Activity Recognition (HAR) has become a key component of intelligent healthcare monitoring, assisted living, sports analytics, smart environments, and wearable computing. However, the migration of HAR models from cloud-centered architectures to edge, embedded, mobile, and wearable platforms introduces constraints related to computational capacity, memory footprint, battery consumption, inference time, and real-time responsiveness. This study presents a systematic literature review … …Journal of Computer Science, Vol. 22, Issue 8 · 7 Sep 2026 · 601 accessesView PDFCite
Research ArticleOpen accessIn the abstractCardiovascular Disease Prediction using Various Machine Learning AlgorithmsDebabrata Swain, Badal Parmar, Hansal Shah et al.Almostone-third of all deaths caused around the world were caused due tocardiovascular diseases. Even if death was not the result, much cost isincurred during the treatment of such diseases. But much of these deaths andtreatments could have been prevented with prior action. Advance knowledge ofthe symptoms and consequently proper care can lead us to avoid such diseases.Thus, current research proposes … …Journal of Computer Science, Vol. 18, Issue 10 · 13 Oct 2022 · 9,402 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,661 accessesView PDFCite
Research ArticleOpen accessIn the abstractLarge Deviation, Basic Information Theory for Wireless Sensor NetworksKwabena Doku-AmponsahIn this research paper, we establish Shannon-McMillan-Breiman Theorem for Wireless Sensor Networks modelled as Coloured Geometric Random Networks. For, large n we show that a Wireless Sensor Network consisting of n sensors in [0; 1]d linked by an expected number of edges of order n log n can be transmitted by approximately [n(log n)2 πd/2/(d/2)!] H bits, where H is … …Journal of Mathematics and Statistics, Vol. 13, Issue 4 · 20 Oct 2017 · 7,123 accessesView PDFCite
Research ArticleOpen accessIn the abstractComparison Between Selective Sampling and Random Undersampling for Classification of Customer Defection Using Support Vector MachineHeri Kuswanto, Yogi Sarumaha, Hayato OhwadaQuality of a product determines the customer loyalty and it can be measured by conducting a survey. Company ‘X’ that sells three kinds of product (low, medium and high price) collected very large dataset through an online survey and recorded customer defection and their characteristic. The measured variables are Update Accumulation, Product Price, Customer Type, Delivery Status and Customer Defection. … …Journal of Computer Science, Vol. 13, Issue 8 · 16 Aug 2017 · 7,272 accessesView PDFCite
Research ArticleOpen accessIn the abstractRandom Forest Classification and Support Vector Machine for Detecting Epilepsyusing Electroencephalograph RecordsHeri Kuswanto, Mutiah Salamah, Muhammad Idrus FachruddinComplexity in data structure has led to the rapid development of computational statistics methods. Machine learning approaches have been introduced and applied to solve complex problems in many fields. This paper applies two common machine learning approaches, Random Forest (RF) and Support Vector Machine (SVM), in the detection of epilepsy. The diagnosis of epilepsy can usually only be made when … …American Journal of Applied Sciences, Vol. 14, Issue 5 · 4 May 2017 · 8,141 accessesView PDFCite
Research ArticleOpen accessIn the abstractAccessing the Appropriateness of a Spatial Regression Using Generalized (h1h2-)Slepian Random FieldWayan Somayasa, Jamhir Safani, La Ode Ngkoimani, Muhamad Zamrun F.In this study we derived asymptotic goodness-of-fit test (model check) for spatial regression where the critical region as well as the p-value of the tests are approximated based on the distribution of a type of the integral functional of the generalized (h1h2-)-Slepian field and the set-indexed Gaussian white noise. Such random fields are obtained as the limit process of the … …Journal of Mathematics and Statistics, Vol. 13, Issue 2 · 2 May 2017 · 7,364 accessesView PDFCite
Research ArticleOpen accessIn the abstractCapsule Defect Detection and Classification Using Enhanced MobileNet ModelWenqing Bian, Yongzhi Huang, Baolian Shan, Yanting ChangThe quality of capsules has a direct impact on human health. However, defects inevitably arise during the capsule manufacturing process, and manual sorting is required. Most studies on capsule defects focus on detecting surface imperfections and those on internal capsule defects remain relatively limited. This study classifies four types of capsules using the deep learning model MobileNet, aiming to accurately … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 5 Nov 2024 · 5,205 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Method for Fast and Robust Intensity Based 2D/3D Registration in Differentiable FrameworkAgung Alfiansyah, Izzati Muhimmah, Arif Sasongko et al.This study introduces an innovative intensity-based registration method designed to align 3D image data volumes, such as Computed Tomography (CT), with 2D data, such as X-ray images, a crucial component of intra-operative navigation in image-guided surgery. Leveraging advanced autodifferentiable reconstruction techniques based on the GPU-accelerated Siddon algorithm, the proposed approach facilitates the generation of differentiable Digitally Reconstructed Radiographs (DRRs), enabling … …Journal of Computer Science, Vol. 20, Issue 12 · 24 Oct 2024 · 4,825 accessesView PDFCite