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432 articles for “efficiency algorithm”
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AI in Pharmacy Automation: A Review of Innovations in Robotics, Their Ethical Implications, and Impact on Workflow and Workforce
Abstract: The pharmacy profession has witnessed a paradigm shift with the integration of robotics and artificial intelligence (AI) in automation. Traditional practices that relied heavily on manual dispensing, paper documentation, and technician labor are now being augmented or replaced by robotic dispensing systems, sterile compounding machines, and predictive AI algorithms. These innovations enhance safety, improve efficiency, and reduce errors, while also raising complex ethical questions related to workforce displacement, liability, and …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 17, Issue 1, 2026 · pp. 01–07 Read article
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A Novel Approach for Design and Optimization of Slot Antenna for WLAN Applications
Abstract: The simulation, and analysis of a micro-strip fed slot antenna array intended for operation in the 2.4 GHz ISM (Industrial, Scientific, and Medical) band, which is widely used for wireless technologies such as Wi-Fi and Bluetooth. A slot antenna is a type of antenna where a slot (cut or gap) is made on a metal surface, and it radiates electromagnetic waves. Utilizing ANSOFT HFSS software, the antenna's performance is optimized, …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 1–12 Read article
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Real-Time Object Detection and Tracking in Traffic Surveillance: Implementing Algorithms That Can Process Video Streams for Immediate Traffic Monitoring
Abstract: The rapid growth in urban development and traffic congestion calls for adopting high standards of traffic surveillance systems for monitoring. This paper reviews the current advancement and future trends of real-time object detection and tracking technology and its implications for traffic surveillance. Conventional approaches to traffic monitoring can provide more or less accurate data, but they are not easily scalable and cannot cope with rapidly changing conditions typical within urban …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 18–39 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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Analysis and Design of Modern Parking Structure by Considering Optimised Bracing Systems Under the Dynamic Load
Abstract: The design and implementation of effective bracing systems are crucial for ensuring the structural stability and safety of G+10 parking buildings, particularly in regions prone to seismic and wind loads. This study evaluates and optimizes various bracing systems, including X-type, V-type, Inverted V-type, and Eccentric bracing, to determine their suitability for use in G+10 parking structures in the Chhatrapati Sambhajinagar City area. The research focuses on assessing each bracing system's …
Published in Recent Trends in Civil Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 61–76 Read article
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Entangled Shields: Securing Digital Systems in the Quantum Cryptographic Revolution
Abstract: Quantum computing utilizing principles of superposition and entanglement is poised to revolutionize the computational landscape, presenting unprecedented challenges and opportunities across various disciplines. Among these, cryptography stands at the forefront due to its reliance on computational hardness assumptions, which Quantum algorithms, such as Grover’s and Shor’s, can efficiently exploit. This study explores theoretical foundations and practical applications of quantum-safe cryptographic primitives, such as lattice-based cryptography, hash-based signature schemes, code-based systems, …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 2, 2025 · pp. 33–43 Read article
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Optimizing Economic Load Dispatch in a 10-Unit System Using the SSA Method
Abstract: The optimization of economic load dispatch (ELD) in a 10-unit power system employing the social spider algorithm (SSA) method is reported. ELD is a critical aspect of power system operation, aiming to allocate the power generation among multiple units efficiently while meeting the demand at the lowest possible cost. The SSA method, inspired by the collaborative behavior of social spiders, demonstrates its efficacy in solving optimization problems. In this research, …
Published in Trends in Electrical Engineering · Vol. 14, Issue 3, 2024 · pp. 1–13 Read article
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Solar Empowerment: A Critical Review of Intelligent Home Automation Technologies
Abstract: An innovative way to improve domestic lifestyle is with the Interactive Powered by solar energy Automated Home System, which combines smart technology with renewable energy. This system leverages solar power to sustainably meet energy needs, ensuring an eco- friendly and cost-effective solution. The heart of ISPHAS lies in its intelligent automation, seamlessly interconnecting various household devices and systems to optimize energy consumption and enhance overall efficiency. Through advanced sensors and …
Published in Journal of Nuclear Engineering & Technology · Vol. 14, Issue 1, 2024 · pp. 25–31 Read article
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Blockchain from the Cryptographic Perspective of Privacy and Anonymization for Sustainability
Abstract: This paper delves into the fascinating intersection of cryptography and blockchain technology. It explores the implementation of blockchain in cryptography, highlighting how cryptographic algorithms improve the security of blockchain systems. This paper looks at various issues such as why cryptographic methods in use with blockchain networks guarantee data security, confidentiality, and credibility. It also examines the relationship between consensus algorithms and cryptography, shedding light on how these elements work together …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 13–30 Read article
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Face Recognition Attendance System Using Local Binary Pattern Histogram Algorithm
Abstract: Maintaining accurate and tamper-proof attendance records in educational and corporate environments has long been a challenge due to the limitations of manual and biometric systems. This study introduces the development and deployment of a contactless, automated attendance system that utilizes facial recognition through the local binary pattern histogram (LBPH) algorithm. The primary goal is to offer a secure and efficient substitute for conventional attendance methods by harnessing the power of …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 13, Issue 1, 2026 · pp. 29–34 Read article
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Refrigeration System Performance and Energy Optimization in Food Preservation and Cold Chain Logistics
Abstract: A vital part of the food preservation sector, refrigeration guarantees the durability, security, and quality of perishable food items in the supply chain. The food cold chain, which encompasses the refrigeration systems used during storage, transportation, and distribution, is integral to maintaining food safety and minimizing waste. However, as the global demand for food increases and sustainability concerns rise, energy consumption in refrigeration systems presents a major challenge. Efficient refrigeration …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 12, Issue 1, 2025 · pp. 22–29 Read article
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Crop Yield Prediction Using Machine Learning Algorithm Based on Climate Variables
Abstract: India's economy is based primarily on agriculture, as over 50% of the country's population depends on it for their livelihood. The long-term viability of agriculture is seriously threatened by variations in the weather, climate, and other environmental factors. Because machine learning provides tools for decision assistance in agricultural yield prediction, including guidance on which crops to plant and when to plant them during the growing season, it is essential to …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 49–52 Read article
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Novel Laplace-domain Approach to the Electromagnetic Transients in Compensated High Voltage Power Lines
Abstract: This paper addresses the simulation of the electromagnetic transients developed in high voltage power lines, which are initiated by lightning discharges. The analysis can handle both individual and simultaneous series inductive and shunt capacitive compensation types. The sizes and locations of the compensating elements are included in the analysis. The derived Laplace s-domain mathematical model applies the concept of the ABCD transmission constants representing equivalent two-port networks. Applying the relations …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 2, Issue 1, 2024 · pp. 15–21 Read article
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Data-Driven Predictive Analytics and Decision- Making in FinTech Using MongoDB and High-Throughput Data Pipelines
Abstract: This paper examines the implementation of MongoDB and high-throughput data pipelines within the financial technology (FinTech) sector to drive data-informed predictive analytics and decision-making. The study focuses on the architectural components, scalability, and challenges of integrating NoSQL databases into real-time data ingestion and analytics pipelines. The transformative potential of these technologies in modern financial systems is highlighted through practical use cases such as fraud detection, credit scoring, and personalized financial …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 1–15 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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Crime Prediction and Criminal Identification System Using Machine Learning
Abstract: Advanced machine learning and data analytics-driven crime prediction and criminal identification systems have become game-changing instruments for contemporary law enforcement. Utilizing past crime statistics, surveillance footage, and additional resources, these systems forecast criminal activity, manage resources efficiently, and improve investigation capacities. With an emphasis on their importance in enhancing public safety and lowering crime rates, this paper presents an overview of criminal identification and prediction systems. Examining the technologies and …
Published in International Journal of Electronics Automation · Vol. 2, Issue 1, 2024 · pp. 28–34 Read article
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Optimal Placement and Sizing of STATCOM for Loss Reduction and Voltage Profile Enhancement Using Genetic Algorithm
Abstract: Electric power distribution networks frequently experience significant power losses and voltage profile deterioration due to increasing load demand and inadequate reactive power compensation. This study investigates the enhancement of the Eleme distribution network in Rivers State through voltage upgrading and optimal deployment of a Static Synchronous Compensator (STATCOM). The existing network consists of a 5.56 km, 11 kV radial distribution system supplying seventeen distribution transformers with a cumulative load demand …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 2, 2026 Read article
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IoT Sensors to Monitor Pipeline Pressure and Flow Rate Combined with ML-Algorithms to Detect Leakages
Abstract: In the field of fluid mechanics, pipelines are the lifeblood of industries, transporting everything from natural gas and oil to water and chemicals. Maintaining their integrity is paramount for safety, economic efficiency, and environmental protection. Traditional leak detection methods explained in fluid mechanics can be slow, expensive, and sometimes fail to identify small leaks early enough to prevent significant damage. However, the convergence of Internet of Things (IoT) and Machine …
Published in Recent Trends in Fluid Mechanics · Vol. 12, Issue 2, 2025 · pp. 40–48 Read article
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Botnet Beacon: Unveiling Covert Networks with Advanced AI Detection Strategies
Abstract: Securing information technology systems is paramount in today's interconnected world, where the reliability and security of networks and applications are of utmost importance. In this context, the development of a Botnet Detection System (BDS) that harnesses the power of AI classification algorithms becomes a critical endeavor. The primary objective of this work is to construct a comprehensive framework for a BDS that can efficiently gather network data and subject it …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 12, Issue 2, 2024 · pp. 26–32 Read article