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14 articles for “rewards system”
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CredBud: The Ultimate Student Platform
Abstract: In the rapidly evolving educational landscape, effective management of student performance, attendance, and engagement is essential for fostering accountability, motivation, and academic growth. Addressing the limitations of traditional methods, CredBud introduces an innovative digital platform designed to revolutionize academic management. This secure, user-friendly ecosystem empowers both students and faculty to enhance efficiency and collaboration. CredBud’s key features include a credit allocation and grading system to monitor academic progress, a theoretical …
Published in Journal of Microcontroller Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 1–9 Read article
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Design of Scrap Collection and Reward Machine Using Verilog HDL
Abstract: The growing amount of waste produced in urban environments has led to a demand for effective and automated recycling solutions. In this paper, a scrap collection and reward machine is designed and implemented using the Verilog Hardware Description Language (HDL). The proposed system is developed to provide a reliable and automated approach for managing recyclable materials while motivating users through a reward-based mechanism. The design includes scrap input interfaces, a …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 37–45 Read article
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Presenting the Model and Prioritization of Lean Production Success Drivers (Case study: Iran Khodro Company)
Abstract: The purpose of the current research is to present a model and prioritize the drivers of lean production success (case study: Iran Khodro Company). The statistical population and statistical sample of this study consists of 20 experts (managers) of Iran Khodro production department. In this research, first, the most important key success factors of lean production were determined using the validity technique of the content validity ratio, then the interpretative …
Published in International Journal of Sustainability · Vol. 1, Issue 1, 2024 · pp. 30–42 Read article
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Exploring Technologies for Extractive Text Summarization: A Review of Transformer and Reinforcement Learning Models
Abstract: In recent years, the size of information on the Internet has increased exponentially. Therefore, a solution is needed to transform large amounts of raw data into useful information the human brain can understand. Automatic Text Summarization (ATS) is a part of Natural Language Processing (NLP) that aims to take long texts and shorten them, keeping the most important information in a clear and easy-to-understand way. This research report explores methods …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 1–6 Read article
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AI-Based Software-Defined Satellite in Decision Making: A Study
Abstract: For decades, satellites have been a vital infrastructure, relaying communication signals, observing Earth's climate, and providing critical navigation data. However, the traditional model of satellite operation is often rigid and reactive, relying heavily on pre-programmed instructions and ground-based control. This limits their flexibility and responsiveness in a rapidly changing environment. Enter software-defined satellites (SDS), and now, the game-changer: artificial intelligence (AI). Imagine a satellite that can independently analyze its surroundings, …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 63–72 Read article
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Innovative Wireless Charging Solutions for Electric Vehicles
Abstract: As the automotive industry's future arises, electric vehicles (EVs) are at the forefront of zero-emission transportation technology. Although conventional plug-in charging stations are widely utilized, wireless power transfer (WPT) is an alternative. WPT may be used as either dynamic charging equipment for moving cars or static charging systems for parked cars. This study addresses the distinction between plug-in and wireless charging, the mechanics of wireless charging, various kinds of charging …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 2, Issue 1, 2024 · pp. 11–17 Read article
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Automating Compiler Optimization: A Machine Learning Approach
Abstract: This study reports on an ML-based approach to compiler optimization, complementing traditional optimization methods that rely strongly on hand-tuned settings. Compiler optimization plays a key role in performance-speedup and energy optimization of complex contemporary software systems. However, the traditional approach to optimizer settings involves laborious, error-prone, and scale-insensitive human-in-the-loop intervention, especially in the complex and high-demand environments in which today's computing application thrives. By integrating RL and GA, we can …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 12–16 Read article
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IoT-Based Smart Waste Tracking & System for Monitoring
Abstract: In an era of rapid urban growth—driven by continued population growth and greater waste dispersion due to unregulated disposal practices by all citizens—a major challenge is emerging in the effective management of solid waste in urban environments. This project proposes a solution to this challenge: a Smart Waste Tracking & System for Monitoring. In this system, every household is provided with an RFID card, which they must use each time …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 4, Issue 2, 2026 Read article
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DC Motor Control using Deep Reinforcement Learning for Enhanced Robustness and Precision
Abstract: DC motors remain the workhorse of industrial automation and mobile robotics, but achieving simultaneous high-speed transient response and negligible steady-state error under variable load conditions continues to challenge classical Proportional-Integral-Derivative (PID) controllers. These model-dependent systems often require extensive tuning and struggle to maintain optimal performance when confronted with parametric uncertainties, non-linear friction, or sudden voltage fluctuations. This study presents a novel, model-free control paradigm utilizing Deep Reinforcement Learning (DRL)—specifically, a …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 3, Issue 2, 2025 · pp. 22–29 Read article
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Predictive Learning Powered by AI and Sophisticated Student Engagement Techniques
Abstract: The contemporary landscape of education has witnessed a paradigm shift in integrating advanced technologies that have revolutionized the learning experience. Innovative methodologies have emerged to address longstanding challenges, such as enhancing student engagement, accurately predicting academic performance, and personalizing the learning journey. However, despite the numerous benefits that technology brings to education, there remains a crucial hurdle - sustaining student motivation and engagement. Traditional teaching methodologies often struggle to generate …
Published in International Journal of Behavioral Sciences · Vol. 3, Issue 1, 2026 · pp. 127–140 Read article
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Adaptive Task Scheduling And Resource Optimization Using Ai Middleware
Abstract: Modern distributed and heterogeneous computing systems face significant challenges in dealing with dynamically changing workloads, resource fragmentation, and changing latencies; existing traditional, or rule-based, schedulers are no longer useful in achieving the best system performance. Such limitations highlight the importance of the adaptive scheduling paradigms that are able to learn, to forecast and reaction to the real red conditions in the system. The middleware of artificial-intelligence is also an attractive …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 Read article
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Matching Minutiae Fingerprint Q-Learning Approach for Detail Coordination: Identifiable Mark Point
Abstract: The use of fingerprints for high-precision recognition and identification of people is one of the most reliable biometric symbols because it is non-invasive. In this paper, we propose an innovative approach to detect details on low contrast resolution image quality of fingerprint images. Existing algorithms are not very susceptible to sound and image excellence due to the lack of level of intensity. We recommend a reliable route to find fingerprints …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 1–15 Read article
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Horticulture As an Avenue of Sustainable Agriculture in India
Abstract: In the face of climate change, soil degradation, and population pressure, sustainable agriculture has become a necessity for India. Within this broader framework, horticulture which includes the cultivation of fruits, vegetables, spices, plantation crops, flowers, and medicinal plants has emerged as a key pillar of sustainable agricultural practices. With its potential to ensure food and nutritional security, enhance rural livelihoods, and contribute to ecological balance, horticulture holds a strategic position …
Published in International Journal of Trends in Horticulture · Vol. 2, Issue 2, 2025 · pp. 20–28 Read article
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Machine Learning Based Optimization of Polymer Structure Property Relationships in Composite Material Systems
Abstract: In modern engineering applications, polymer-based composite materials have garnered a lot of attention because of their lightweight nature, high strength-to-weight ratio, and changing physical features. In order to maximize the relationships between polymer structure and properties in composite materials, this study suggests a strategy based on reinforcement learning (RL). The research utilized the Polymer Composite Properties Dataset, which contains 12,700 records associated with polymer matrices, reinforcement fillers, interfacial bonding characteristics, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 242–255 Read article