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60 articles for “memory optimization”
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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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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 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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Cross-layer Solutions in WSN Routing: A Review
Abstract: WSN is a less infrastructure wireless network which is embedded with large number of Sensor Nodes (SN). Its ad-hoc manner of device distribution allows it to monitor conditions under physical and environmental scenarios. Typically, SNs in WSN are installed in a specified geographical location to monitor required information. Due to SNs’ self-configuring ability, the exploitation of target is simpler. Though, its functioning is limited with factors such as energy efficiency, …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 26–36 Read article
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Electroconvulsive Therapy in the Management of Schizophrenia: A Systematic Review in Emergency Nursing Practice
Abstract: Electroconvulsive therapy (ECT) is a well-established treatment for various psychiatric disorders, including schizophrenia, particularly in cases where patients are resistant to conventional treatments. Schizophrenia, a chronic and severe psychiatric disorder, often presents with a combination of positive symptoms (such as hallucinations and delusions), negative symptoms (such as social withdrawal and emotional blunting), and cognitive impairments. While antipsychotic medications are the primary treatment, approximately 20–30% of individuals with schizophrenia do not …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 43–48 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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Comparison of Various Load Balancing Algorithms in Cloud Computing
Abstract: The components associated with distributed computing are customers, datacenter and appropriated server. One of the principal issuesin distributed computing isload adjusting. Adjusting the heap intends to circulate the outstanding task at hand among a few hubs uniformly so no single hub will be over- burden. Burden can be of any kind that is it very well may be CPU load, memory limit or system load. Right now, introduced a design …
Published in Recent Trends in Parallel Computing Read article
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Optimized Sentiment Analysis Through TextBlob and Hybrid RNN Models
Abstract: In today’s world, analyzing people’s feelings from what they write online has become very important. This is because there is a large amount of content created by users. To make this analysis accurate and fast, we present a method. This method uses a mix of two approaches: one that looks up words in a dictionary and another that uses computer learning. TextBlob is an affordable tool for getting an initial …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 29–28 Read article
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Spintronic Logic Circuits for Ultrafast Processing
Abstract: Spintronic logic has emerged as one of the most promising post-CMOS paradigms capable of addressing the speed, density, and energy challenges of deeply scaled silicon technologies. By relying on the intrinsic properties of electron spin and magnetization dynamics, spintronic devices—particularly Magnetic Tunnel Junctions (MTJs), Spin-Transfer Torque (STT), and Spin–Orbit Torque (SOT) structures—enable ultrafast, non-volatile data processing with significantly reduced energy consumption. Despite remarkable device-level advancements, circuit- level realization of high-speed, …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 35–43 Read article
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Advancements in Agricultural Forecasting: A Review of Machine Learning Based Crop Yield Prediction
Abstract: Agricultural productivity plays a critical role in global food security, and accurate crop yield prediction is essential for optimizing resource allocation and decision-making in farming. The rapid advancements in Machine Learning (ML) and Deep Learning(DL)have transformed agricultural forecasting, enabling data-driven approaches for crop prediction. This review paper provides a comprehensive analysis of various ML and DL techniques applied in crop yield forecast, highlighting the ineffectiveness, challenges, and future directions. The …
Published in Research & Reviews : Journal of Agricultural Science and Technology · Vol. 14, Issue 3, 2025 · pp. 32–38 Read article
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The Impact of Nutrition on Sports Performance and Academic Success: A Study Among University Athletes – Eastern Technical University of Sierra Leone
Abstract: University athletes operate within dual-performance environments that require simultaneous academic and athletic excellence. Nutrition plays a critical role in supporting both physiological performance and cognitive functioning; however, limited empirical work has examined its combined influence on athletic and academic outcomes within university athlete populations, particularly in low-resource contexts. This study aimed to investigate the relationship between nutritional practices, sports performance, and academic achievement among university athletes at the Eastern Technical …
Published in Research & Reviews : Journal of Food Science & Technology · Vol. 15, Issue 1, 2026 · pp. 16–27 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
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Study and analysis of the Double Data Rate SDRAM Controller for High-speed Interfacing with Processing Device
Abstract: A real-time embedded system must now manage many programs running concurrently. Increased Data Rate Because of its burst access, speed, and pipeline features, synchronous DRAM is a typical memory-building material. DDR transfers are performed using synchronous dynamic access memory. The memory controller must be set with a pipelined design for various applications and systems to perform effectively. The purpose of this study is to design a DRAM controller that will …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 1, 2024 · pp. 8–13 Read article
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Performance Comparison of Noise-Tolerant, High- Performance CMOS Domino Logic Configurations
Abstract: In high-performance VLSI chip design, domino logic configuration is often preferred over static logic due to its faster operation and smaller area footprint, especially in deep submicron (DSM) technology. However, DSM noise has become a significant challenge in domino-based circuits, leading to compromises in the reliability and signal integrity of integrated circuits (ICs). The switching threshold of domino logic, defined as the input voltage level at which the gate output …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 35–50 Read article
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Enhancing Data Processing and Storage in Computing Environments: A Survey on the Use of NVMe SSDs
Abstract: In the current era of fast pace technological growth, the efficiency of data processing and storage systems has become a key factor of various computing environments. This survey explores the transformative role of Non-Volatile Memory Express (NVMe) Solid-State Drives (SSDs) across different domains, including Big Data processing, Cloud Computing, High Performance Computing (HPC), and containerized applications. The motivation behind this comprehensive review is to understand how NVMe SSDs, known for …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 01–21 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Lyapunov-Stable Adaptive Fractional-Order Interval Type-2 Fuzzy Control for Robust Anti-Lock Braking Under Uncertain Road Adhesion Conditions
Abstract: This paper proposes a Lyapunov-stable Adaptive Fractional-Order Interval Type-2 Fuzzy Logic Controller (FO-IT2FLC) for robust anti-lock braking system (ABS) control under nonlinear vehicle dynamics and uncertain road adhesion conditions. The proposed framework integrates fractional-order error dynamics to capture memory-dependent tire–road interaction, interval Type-2 fuzzy inference to model uncertainty via footprint-of-uncertainty representation, and a Lyapunov-based adaptive learning mechanism for real-time parameter tuning. A rigorous stability proof guarantees boundedness of all closed-loop …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Polymeric Materials in Assistive Devices for Cerebral Palsy: Advances and Applications
Abstract: The neurological condition known as cerebral palsy (CP) impairs muscle coordination and movement often necessitating assistive devices for mobility, support, and rehabilitation. These devices are crucial for enhancing CP patients' quality of life by boosting their independence, comfort, and overall functionality. Recent advancements in polymer chemistry have revolutionized the development of assistive devices, offering enhanced flexibility, durability, and biocompatibility. The integration of polymeric materials in orthotic supports, adaptive braces, and …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 316–322 Read article
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High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article