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68 articles for “memory efficiency”
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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
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Dynamic Skip-Layer Trees: A Novel Data Structure for Efficient Multi-level IoT Data Processing in Smart Cities
Abstract: This paper introduces dynamic skip-layer trees (DSLTs), a novel hierarchical data structure specifically designed for processing and managing multi-layered Internet of Things (IoT) sensor data in smart city environments. DSLTs extend the traditional skip list concept by incorporating dynamic layer adjustment and spatial awareness, enabling efficient querying and updates across various geographical and temporal dimensions. Our experimental results demonstrate that DSLTs achieve up to 40% faster query processing and a …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 11–21 Read article
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Implementation of the Tridiagonal Matrix Algorithm (TDMA) in C: A Practical Approach
Abstract: This paper presents a practical implementation of the tridiagonal matrix algorithm (TDMA), also known as the Thomas algorithm, using the C programming language. The TDMA is a commonly used algorithm for solving systems of linear equations where the coefficient matrix is tridiagonal. The paper draws a detailed step-by-step process of the algorithm’s development, from forward elimination to backward substitution, with a focus on minimizing computational difficulty compared to standard Gaussian …
Published in Recent Trends in Programming languages · Vol. 11, Issue 3, 2024 · pp. 36–43 Read article
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A Memory-Based Genetic Algorithm for Optimization of Power Generation in a Microgrid
Abstract: Due to advancement in power electronics field, it is becoming more feasible to integrate renewable energy into power grid. Renewable energy sources are prompting more and more small investors to invest in generation and distribution of renewable energy at microgrid level. The increased competition requires energy producers to offer energy at minimum possible cost to gain the confidence of consumers, which needs efficient methods to schedule energy generation among the …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 3, 2025 · pp. 29–38 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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A Physics-Informed Graph Neural Network Framework for Real- Time Thermal-Aware Fault Prediction and Adaptive Power Optimization in Heterogeneous System-on-Chip Architectures
Abstract: Heterogeneous System-on-Chip (SoC) architectures are increasingly adopted in edge computing, artificial intelligence, autonomous systems, and high-performance embedded platforms due to their superior computational efficiency and flexibility. However, increasing integration density and workload diversity introduce severe thermal hotspots, accelerated device degradation, and unexpected hardware faults that adversely affect system reliability and energy efficiency. This study proposes a Physics-Informed Graph Neural Network (PI-GNN) framework for real-time thermal- aware fault prediction and adaptive …
Published in Journal of VLSI Design Tools and Technology · Vol. 16, Issue 2, 2026 Read article
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An Intelligent Neural Networks Approach for Monitoring of Soilless Urban Farms
Abstract: Urban agriculture is increasingly recognized as a sustainable approach to addressing food security challenges in rapidly growing and densely populated cities. Conventional soil-based farming often faces limitations such as space scarcity, excessive water consumption, and environmental degradation. To overcome these challenges, soilless farming techniques such as hydroponics and aeroponics have gained significant attention due to their efficient utilization of space, reduced water requirements, and potential for year-round crop production. However, …
Published in Journal of Water Resource Engineering and Management · Vol. 12, Issue 3, 2025 · pp. 31–37 Read article
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Accelerating Unsupervised Feature Learning: Parallelized Training of Denoising Autoencoders
Abstract: Unsupervised representation learning has become a cornerstone of contemporary machine learning, enabling algorithms to extract informative features from un-labelled, high-dimensional data. This work investigates the efficacy of stacked denoising autoencoders (SDAEs) trained via parallelized stochastic gradient descent (SGD) as a scalable approach to feature extraction. By strategically leveraging multi-threaded computation, our study systematically examines the trade-offs between increased parallelism, training efficiency, and the preservation of model accuracy. Experiments on the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 56–64 Read article
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Dealing with Hardware of the Computers: An Analytical Study
Abstract: The evolution of computer hardware has been pivotal in shaping modern computing capabilities, impacting both personal and professional spheres. This study offers a thorough overview of essential hardware components, such as the central processing unit (CPU), memory, storage devices, motherboards, and input/output peripherals. It explores how advancements in hardware technology, such as the transition from mechanical hard drives to solid-state drives (SSD) and the development of multi-core processors, have enhanced …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 12–21 Read article
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CMOS-Based Process-Scalable Analog Circuits for Machine Learning: A Comprehensive Review and Future Directions.
Abstract: Analog computing techniques are gaining attention for machine learning (ML) applications due to their ability to reduce computational complexity. Continuous operations such as addition and subtraction offer a simpler and more efficient approach compared to probabilistic product decoding, which can be sensitive to noise and inconsistent measurements. This paper presents a simulated VLSI implementation of a broadcast edge connection, independent of the MOS component model, along with experimental results. The …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 8–17 Read article
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Development of Self-Healing Circuit Boards Using Shape Memory Polymer Composites
Abstract: This study investigates the influence of temperature, humidity, and nanofiller type on the electrical and structural performance of advanced polymer nanocomposites for self-healing circuit applications. Particular attention was given to conductivity retention and the morphological behavior of carbon nanotubes (CNTs), graphene, and silver nanoparticles (AgNPs). Results show that conductivity decreased under elevated thermal–humidity conditions, reflecting the role of environmental stress in material degradation. Among the tested systems, AgNP-based composites achieved …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 746–770 Read article
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AI Powered Fault Detection in DC Motor using STM32
Abstract: This work presents the design and implementation of an embedded artificial intelligence system for real-time fault detection in a direct current (DC) motor using the STM32 Nucleo- F411RE microcontroller. The objective of the study is to develop a low-cost and efficient predictive maintenance solution capable of identifying abnormal motor behavior at an early stage. Vibration and temperature signals are acquired using an MPU6050 sensor and processed directly on the microcontroller …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 1, 2026 · pp. 39–49 Read article
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Machine Learning Revolutionizing Server Management and Performance
Abstract: The modern data center is a complex and dynamic environment, grappling with ever-increasing workloads, stringent performance demands, and the constant pressure for cost optimization. As such, applying machine learning (ML) directly to the server infrastructure offers a powerful avenue for achieving advanced automation, resource optimization, and proactive problem resolution. This article explores the transformative potential of integrating machine learning into server systems, leveraging insights gleaned from the abstract and conclusion …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 36–44 Read article
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4D Printing in Drug Delivery: Application of Shape- Morphing Materials in Controlled Drug Release
Abstract: Four-dimensional printing technology has transformed the pharmaceutical landscape, offering unprecedented opportunities for innovation in drug development and delivery. This emerging technology enables the creation of complex geometries and customized structures, facilitating the design of personalized medications tailored to individual patient needs. Personalized dosing and drug release profiles, customized pill shapes and sizes for improved swallowability. Enhanced drug solubility and bioavailability, rapid prototyping and testing of pharmaceutical products. Development of complex …
Published in Trends in Drug Delivery · Vol. 12, Issue 3, 2025 · pp. 08–16 Read article
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Multi-Parameter Biomedical Sensor-Based Mental State Classification Using EEG And Deep Learning Techniques
Abstract: With mental health concerns becoming increasingly widespread, there is a strong need for systems that can monitor conditions like stress, anxiety, and fatigue in a continuous and non- invasive manner. This research proposes a novel multi-parameter biomedical sensing framework for mental state classification by integrating electroencephalography (EEG) signals with physiological parameters, including body temperature acquired using LM35 sensors, heart rate from pulse sensors, and blood oxygen saturation (SpO₂) measurements. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 2, 2026 Read article
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Quantum Error Correction on Cryptography
Abstract: This article introduces novel concepts in quantum error correction and cryptography. It explores “approximate quantum error correction” (AQEC), which relaxes the requirement for perfect error correction in quantum systems. AQEC specializes in creating codes tailored to specific types of noise models. The study establishes a universal, near-optimal recovery map for AQEC, simplifying the identification of effective approximate codes. In the realm of noisy-storage cryptography, the research envisions secure two-party cryptographic …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 18–23 Read article
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Human Skin Abnormality Detection with Process Similarity Criteria Fit Machine Learning Method
Abstract: This method presents a machine learning method that satisfies the defined conditions for healthy waterside beach activities. The boundary conditions of the normal and abnormal radiation spaces were formulated. The objectives of using a Regression Polynomial with Process Similarity Criteria Fit for skin temperature prediction are justified by the analysis of the existing analytical and machine learning approaches. An algorithm for skin temperature prediction using the theories of similarity criteria …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 2, 2024 · pp. 17–24 Read article
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IoT-Enabled Monitoring of AC Condensate Water for Quality Assessment and Early Detection of HVAC System Health
Abstract: The shortage of water and expensive reactive maintenance of HVAC are major problems in the modern building management. The paper introduces an Internet of Things (IoT)-enabled air conditioning (AC) condensate to water resource (predictive maintenance) and sustainable water reuse. The nature of our approach defines the quality of the condensate water at the baseline and indicates that it contains low levels of total dissolved solids (TDS) and has almost neutral …
Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 1, 2026 · pp. 25–35 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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Building Scalable Microservices with Micronaut, Kotlin, and AWS DynamoDB: A Comprehensive Architecture Study
Abstract: The evolution of enterprise software has trended steadily toward microservice architectures due to their inherent scalability and resilience advantages over monolithic systems. This research explores a comprehensive implementation approach using Micronaut, an innovative JVM-based framework specifically designed for resource-efficient microservices. The study combines Micronaut with Kotlin programming language and leverages AWS DynamoDB as a scalable NoSQL persistence layer, with Apache Kafka providing event-driven communication capabilities. We explore the critical role …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 2, 2025 · pp. 40–57 Read article