Search
112 articles for “space optimization”
-
Automatic Gas Leakage Detection System
Abstract: This project report presents the design and implementation of a focused automatic gas leakage detection and ventilation system centered on the Arduino Nano microcontroller and the MQ-2 gas sensor. The primary function of the system is to detect flammable gases like LPG, propane, and methane using the MQ-2 gas sensor. This sensor continuously monitors the surrounding air for the presence of these gases. When the gas concentration crosses a predefined …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 3, 2025 · pp. 29–35 Read article
-
Designing for Indoor Air Quality: Using Plants and Ecofriendly Materials
Abstract: This study’s main objective is examining passive design techniques that optimize energy efficiency, such as natural ventilation, daylighting, and thermal insulation. It explores their potential to reduce energy consumption and enhance occupant comfort while minimizing reliance on mechanical systems. Sustainability is a key focus throughout the study, highlighting the importance of adopting sustainable practices in the design and construction industry. The research explores strategies for reducing environmental impact, minimizing waste, …
Published in International Journal of Sustainability · Vol. 2, Issue 2, 2025 · pp. 13–20 Read article
-
Exploration of Partial Order Structures in Menger Spaces Properties Characterizations and Applications
Abstract: Partial order structures play a crucial role in understanding the intricate relationships within mathematical spaces. In this paper, we delve into the realm of Menger spaces and investigate their properties through the lens of partial orders. Menger spaces, a generalization of metric spaces, possess unique characteristics that can be further elucidated by considering partial order structures. Through rigorous analysis, we explore various properties of partial order Menger spaces, including topological …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 17–22 Read article
-
Automated Machine Learning System for Model Selection and Hyperparameter Optimization
Abstract: The proliferation of machine learning applications in various scientific and industrial domains has given rise to an urgent need for developing principled, automated techniques for optimal architecture selection and hyperparameter tuning for machine learning models without human expert intervention. In this paper, we introduce the Automated Machine Learning System for Model selection and hyperparameter Optimization (AMLSMO)—a state-of-the-art, all-encompassing AutoML system that combines the power of meta-learning-based warm-starting, Bayesian Optimization with …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 15–23 Read article
-
Revolutionizing Culinary Innovation and Sustainability through Smart Kitchen Assistant
Abstract: Introducing a Smart Kitchen Assistant which revolutionizing a culinary experiences with advanced features. This innovative system integrates a precision Vegetable Cutter, optimizing meal preparation efficiency. And a Storage Space ensures organized ingredients readily available for cooking. UV Light Sterilization guarantees hygienic food preparation surfaces, enhancing safety. Additionally, integrated Solar Panels promote sustainability, reducing energy consumption and environmental impact. By seamlessly combining this technology with sustainable practices, our Smart Kitchen Assistant …
Published in Trends in Machine design · Vol. 11, Issue 3, 2024 · pp. 1–16 Read article
-
Optimization of a new Bebq2/BCP-based OLED structure for optimum performance
Abstract: Opto-electronic devices exhibit highly nonlinear current–voltage (I–V) characteristics that significantly affect charge injection, transport, and recombination, evaluating their performance remains a difficult challenge. Device optimization is a key research goal in organic light-emitting diodes (OLEDs), as the thickness and arrangement of individual functional layers greatly influence electrical and optical responses. For a suggested Bebq2/BCP-based OLED structure, this work methodically examines the movement of charge carriers, their transport behavior, and the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 13, Issue 2, 2026 Read article
-
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
-
Role of Generative AI for Advanced Shell Language Design
Abstract: This study explores the emerging field of applying Artificial Intelligence (AI), specifically generative AI, to enhance shell scripting, a crucial skill for system administration and automation. While the formal design of entirely new shell languages using AI remains a long-term prospect, the current focus is on augmenting how existing shell languages are used for improving the scripting experience. This involves leveraging AI for tasks like automated script generation, intelligent code …
Published in Journal of Advances in Shell Programming · Vol. 12, Issue 1, 2025 · pp. 22–27 Read article
-
AI-Assisted Optimization of Supersonic Airfoil Shapes Using CFD Coupling
Abstract: This paper presents a novel framework for optimizing supersonic airfoil geometries through integrated artificial intelligence and computational fluid dynamics coupling. Traditional gradient-based optimization methods for high-speed aerodynamic shapes suffer from computational expense and convergence difficulties in non-convex design spaces. The proposed methodology employs a deep neural network surrogate model trained on high-fidelity Reynolds-Averaged Navier-Stokes solutions to approximate aerodynamic performance metrics across the design space. A hybrid particle swarm-genetic algorithm searches …
Published in Journal of Aerospace Engineering & Technology · Vol. 16, Issue 1, 2026 Read article
-
Extended Fixed Point Theorems in Menger PM-Type Spaces: Generalized Auxiliary Functions and Contractivity Conditions
Abstract: Background: Fixed point theory in probabilistic metric spaces, particularly Menger spaces, has been a subject of intensive research due to its applications in nonlinear analysis and mathematical modeling. Traditional approaches often impose restrictive constraints on the defining properties of Menger spaces and limit the class of auxiliary functions in contractivity conditions Methods: We extend recent fixed point theorems in Menger spaces by: (1) introducing the notion of Menger PM-type spaces …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 3, 2025 · pp. 1–6 Read article
-
Role of Reinforcement Learning in Improvement of Semiconductor Doping
Abstract: The semiconductor industry faces increasing challenges in achieving optimal doping profiles as device dimensions shrink and performance requirements intensify. Traditional doping optimization methods, while effective, often struggle with the complex, multi-dimensional parameter spaces characteristic of modern semiconductor manufacturing. This study explores the transformative role of reinforcement learning (RL) in improving semiconductor doping processes, examining how RL algorithms can autonomously optimize doping parameters to enhance device performance, reduce manufacturing costs, and …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 23–34 Read article
-
Firefly Algorithm–Based Optimization of Processing Parameters for Enhanced Performance of Polymer Composite Materials
Abstract: Polymer composite materials are extensively used in aerospace, automotive, and oil & gas applications due to their high strength-to-weight ratio and design flexibility. However, achieving optimal mechanical and thermal performance strongly depends on precise control of processing parameters such as curing temperature, energy consumption, and material utilization. Conventional trial-and-error approaches often lead to excessive energy usage, non-uniform curing, and sub-optimal composite properties. To address these challenges, this paper proposes an …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 90–107 Read article
-
Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
-
Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article
-
AI-Driven Topology Optimization of Woven Fiber-Reinforced Composite Chassis Structures for Electric Vehicles Under Crash Loading
Abstract: The structural design of an electric vehicle (EV) chassis represents a unique engineering challenge to achieve minimal weight while meeting occupants' safety requirements during high-energy crash conditions without compromise to the battery housing's integrity or the geometrical constraints of the electric powertrain package. In this paper, a single framework is proposed to integrate physics-based artificial intelligence (AI) surrogate models using PINNs, CNN-accelerated topology optimization, and FEA to design woven fiber-reinforced …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 72–89 Read article
-
New Ideas in Quantum RF
Abstract: Quantum RF Innovations is leading the way in next-generation wireless technologies by connecting old radio frequency systems with new quantum- enabled solutions. Our goal is to change the way signals are processed, communicated, and sensed by using advanced quantum principles and cutting- edge RF engineering. We are creating a new class of devices and systems that can achieve ultra-low-noise signal amplification, unprecedented spectrum control, and quantum-secured communication through interdisciplinary research …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
-
Prevention of Water Overflows and Leakages at MPCOE Campus
Abstract: Water is one of the fundamental necessities of human life, essential for a wide range of daily activities. People rely on water for drinking, cleaning, cooking, irrigation, and industrial processes. To meet these needs, water is often pumped from ground storage to overhead tanks. However, the use of non-automated switches to operate pumping machines can lead to significant issues, such as water overflow and unnecessary electricity consumption. The proposed system …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 1, 2025 · pp. 43–51 Read article
-
New trends in Radio Frequency design and making things smaller
Abstract: Recent improvements in wireless communication, the Internet of Things (IoT), and 5G/6G networks have made people want small, powerful radio frequency (RF) equipment. With an emphasis on how developments in materials engineering, circuit architecture, and packaging technologies are redefining RF system integration, this article offers a thorough evaluation of current developments in RF downsizing. System-on-Chip (SoC), System-in-Package (SiP), and Antenna-in-Package (AiP) ideas, which allow tightly integrated RF front-ends with enhanced …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 28–34 Read article
-
AI-Driven Multi-Objective Optimization of Conductive Polymer Composites for High-Performance Flexible Electronics
Abstract: The development of conductive polymer composites (CPCs) is critical for advancing flexible and wearable electronic technologies. However, the conventional trial-and-error approach to material formulation is time-consuming and often inefficient due to the high-dimensional nature of the design space. This study introduces a novel AI-driven framework that integrates machine learning (ML) with multi-objective optimization to accelerate the discovery of high-performance CPCs. A dataset of 1,000 experimentally reported formulations was compiled, capturing …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 734–745 Read article
-
Comparison of Models of Machine Learning and Hyperparameter optimization methods on various datasets
Abstract: The most likely phase in achieving powerful and robust machine learning models is probably the hyperparameters tuning step. The traditional exhaustive methods of search (Grid Search and others) ensure that the search space is covered, but are computationally very inexpensive; random search is less expensive and can still miss good regions; and lastly, the modern model-based and population-based methods (Bayesian Optimization, Tree-structured Parzen Estimator (TPE), Genetic Algorithms) are thought to …
Published in Recent Trends in Programming languages · Vol. 13, Issue 1, 2026 Read article