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564 articles for “s-multiplicative”
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SpecForesight: A Predictive Analytics Pipeline for Laptop Price Forecasting
Abstract: This paper frames laptop pricing as a supervised predictive analytics problem, transforming product specifications into feature-rich signals to forecast price with calibrated regression models and operational guardrails against drift. A structured pipeline ingests tabular listings, performs data cleaning, and engineers domain-informed features (e.g., central processing unit (CPU) family and clocks, graphics processing unit (GPU) tiering, memory/storage density, display, and touch capabilities), followed by encoding and normalization to optimize model learnability. …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 61–71 Read article
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Acoustic Sensing for City Flow: Quasi-Supervised Recognition of Sirens and Traffic for Urban Mobility Intelligence
Abstract: This paper frames environmental audio as a mobility telemetry source, extending a benchmark urban-sound corpus with transportation-critical classes—ambulance, firetruck, police, and traffic—and training spectrogram-based models under a quasi-supervised regime to support real-time city operations; leveraging 10-fold protocols, class-weighted objectives, and audiospecific augmentations (time stretch, pitch shift, SpecAugment, PatchAugment), the system benchmarks multiple CNN backbones combined with self-supervised learning paradigms enable the extraction of rich, discriminative acoustic representations, achieving strong multi-class …
Published in Trends in Electrical Engineering · Vol. 16, Issue 1, 2025 · pp. 42–50 Read article
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Challenges and Promoting Factors for Tribal Girls in Vocational Education
Abstract: This research paper purely focused on the importance of vocational education and training programs specifically for tribal girls in India with a particular objective of its role in enhancing economic independence and promoting self- sufficiency in woman. It also highlighted multiple barriers like social, cultural, administrative, and economical in accessing the vocational education which affects the participation, retention. At the same time the study positions vocational education as a transformative …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 16, Issue 1, 2026 Read article
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ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
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Assessing the Robustness of Machine Learning Models for Wireless Intrusion Detection Under Adversarial Traffic Perturbations
Abstract: As the Internet of Things (IoT) devices and wireless communication networks continue to grow rapidly, protecting systems from cyber threats has become increasingly important. Machine learning–based intrusion detection systems (IDS) have shown strong potential in detecting abnormal and malicious network activities, yet their effectiveness and resilience when facing adversarial attacks are still not sufficiently explored. This research evaluates Machine Learning (ML) models–XGBoost, random forest, and multi-layer perceptron (MLP)—in detecting attacks …
Published in International Journal of Wireless Security and Networks · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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A Mini Review of Synthesis and Applications of Functionally Graded Materials
Abstract: Material composition or microstructure varies gradually along the thickness over a specific volume in functionally graded material (FGM) that results in spatial change in properties like thermal conductivity, strength, stiffness, electrical, magnetic, and light properties, etc. Application of the concept of FGM leads to a single product that has multiple properties in it as demanded by the operational or functional requirements of the product under service conditions. It also allows …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 54–65 Read article
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Using MCDM Methods in automotive industry- A Review
Abstract: In the automobile sector, choosing the best car necessitates weighing a number of factors, including cost, fuel economy, performance, safety, and environmental impact. In order to solve complicated situations that need the simultaneous evaluation of multiple conflicting aspects, Multi-Criteria Decision Making (MCDM) procedures are essential. Among the various MCDM approaches, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and MOORA are widely recognized for their straightforward structure …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 20–26 Read article
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Passenger car fuel economy: Insights from big data analytics
Abstract: The increasing availability of real-world vehicle telematics through On-Board Diagnostics II (OBD-II) systems has enabled data-driven evaluation of passenger car fuel economy beyond conventional laboratory-based test cycles. While standardized certification procedures ensure repeatability, they often fail to capture the influence of real-world traffic conditions, driver behaviour, and transient vehicle operation. This study presents a structured Big Data Analytics (BDA) approach for analysing high-frequency OBD-II data collected from a gasoline passenger …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 8–19 Read article
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OBD-II Big Data–Driven ML and AI-Based Virtual Sensing for Fuel Economy, Component Health, and Carbon Intelligence
Abstract: The rapid growth of connected vehicles has led to the large-scale availability of high-frequency On-Board Diagnostics II (OBD-II) data; however, much of this data remains underutilised, as existing studies and commercial systems typically address fuel economy, maintenance, or emissions in isolation or rely on additional physical sensors. Such fragmented and sensor-dependent approaches limit scalability and increase system cost, particularly in high-volume and resource-constrained vehicle markets. To address this gap, this …
Published in Journal of Automobile Engineering and Applications · Vol. 13, Issue 1, 2026 · pp. 39–50 Read article
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Factors Affecting Mammalian Embryo Culture: A Detailed Review
Abstract: Human IVF has made remarkable progress, but optimizing the in vitro environment remains essential and crucial for supporting embryo development and improving overall clinical outcomes in assisted reproductive technologies (ART). Even with advances in complex culture media, incubator design, and laboratory workflows, embryos grown outside the body are still exposed to chemical and physical stressors that can significantly affect their developmental potential. In this review, we discuss key chemical stressors, …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 4, Issue 1, 2026 Read article
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An Empirical Analysis of Cost, Time, and Quality Relationships Using Correlation and Regression Techniques
Abstract: Cost, time, and quality have been recognized as the three key dimensions that determine construction project performance and are commonly represented through the "Project Management Triangle." However, despite their theoretical linkage, there is limited empirical evidence to quantify the nature of their relationships, particularly within developing construction markets. This paper seeks to contribute to addressing this shortfall by investigating the specific influence of cost and schedule variations upon quality outcomes …
Published in Journal of Construction Engineering, Technology & Management · Vol. 16, Issue 1, 2026 · pp. 52–60 Read article
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Hybrid Graceful QoS Degradation in Distributed Operating Systems
Abstract: Maintaining Quality of Service (QoS) in distributed operating systems is a critical challenge, especially in dynamic and resource-constrained environments. Traditional QoS mechanisms often fail to adapt effectively to unforeseen failures or load spikes, leading to abrupt service disruptions. This study reviews the concept of hybrid graceful QoS degradation, a paradigm that combines multiple strategies to ensure continuous, albeit potentially reduced, service availability. By intelligently integrating techniques like resource reservation, priority-based …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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AI-Based Machine Learning Web Application Firewall (ML-WAF)
Abstract: This research investigates the use of deep learning techniques for the real-time detection of malicious activities in web traffic and proposes an intelligent, AI-driven Web Application Firewall (WAF) designed to provide automated and adaptive security. The system analyzes diverse components of HTTP requests, including request methods, URLs, headers, cookies, and payload content, to accurately identify and classify malicious behavior. The proposed model targets a wide range of common and critical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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In Vivo Biocompatibility and Interfacial Stability of Thermoplastic Polyurethanes and Nanofilled Resin Composites: A Bioanalytical Study of Polymer-Host Interactions Under Dynamic Loading
Abstract: The widespread application of thermoplastic polyurethanes (TPU) and nanofilled resin composites in biomedical devices requires rigorous assessment of their biocompatibility under mechanical stress. While nanofilled composites utilize filler particles (<100 nm) to enhance surface properties and wear resistance, the biological response to these materials in a hydrolytic, enzymatic environment remains a critical area of investigation. Objective: To analyze the in vivo bio-molecular response at the interface of TPU aligners and …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 1112–1119 Read article
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A Study on Artificial Intelligence in UI/UX Design
Abstract: User interface/user experience (UI/UX) design plays a crucial role in shaping how users interact with and perceive digital platforms, as it directly influences usability, satisfaction, and overall engagement. In today’s rapidly advancing technological era, artificial intelligence (AI) has emerged as a transformative force across multiple industries, and UI/UX design is no exception. The integration of AI into UI/UX has fundamentally changed the way digital interfaces are conceptualized, designed, and delivered …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 · pp. 46–51 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Get-Together: A Web-Based Platform for Organising, Booking, and Management of Venues, Services, Events, and Commodities
Abstract: Planning an event is often a complicated and demanding process that requires the coordination of several independent service providers, including venue managers, caterers, decorators, entertainers, musicians, vendors, and many others. Relying on traditional booking approaches usually means depending on manual communication or third-party agencies, both of which can introduce unnecessary delays, scheduling conflicts, higher costs, misunderstandings, and limited room for personalisation. This research proposes a comprehensive web-based platform designed to …
Published in Journal of Web Engineering & Technology · Vol. 13, Issue 1, 2026 · pp. 41–47 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article
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Random Forrest Based Man-in-the-Middle Attack Detection in Advanced Metering Infrastructure
Abstract: Advanced metering infrastructure (AMI) plays a central role in the operation of modern smart grid (SG) systems by enabling continuous, two-way communication between utility providers and consumers. Through this communication, AMI supports real-time monitoring, dynamic pricing, and efficient energy management. However, the same connectivity that makes AMI effective also increases its exposure to cyber threats. One of the most critical threats is the man-in-the-middle (MITM) attack, in which an attacker …
Published in Journal Of Network security · Vol. 14, Issue 1, 2026 · pp. 1–8 Read article