Search
134 articles for “data processing efficiency”
-
Optimizing Data Processing Efficiency in Big Data: Advanced MapReduce Algorithm Innovations
Abstract: The exponential growth of big data in recent years has created an urgent need for innovative and efficient processing frameworks capable of managing and analyzing massive and complex datasets. Among these, MapReduce has gained prominence as a powerful tool for distributed data processing due to its simplicity and scalability. However, traditional MapReduce frameworks often encounter significant limitations in terms of efficiency, scalability, and resource optimization, particularly when handling large-scale and …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 1–7 Read article
-
Implementing and Analyzing Network Commands in Cloud and Edge Computing Environments with Cisco Simulators
Abstract: The present review examines edge and cloud topologies and compares them according to latency. Instead of using distant data centers like cloud computing platforms, edge computing designs process data physically close to the source. Increased demand for Internet of Things (IoT) devices, which are growing more concerned with real-time data processing and analysis, has fueled the expansion of edge computing and cloud computing. In essence, each of these designs offers …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 62–69 Read article
-
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
-
Sky Scanners: Using satellite remote sensing to figure out what Earth is like
Abstract: Satellite remote sensing has changed the way we look at, study, and learn about the Earth changing systems. Orbiting sensors take data from many different spectral bands, giving us constant, large-scale information about land, oceans, and the atmosphere. This study discusses the fundamental concepts of satellite remote sensing, including the various types of sensors, methods for data acquisition, and techniques for interpreting images. It talks about important uses like monitoring …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 22–33 Read article
-
Importance of Thesaurus in Natural Language Processing for Scholarly Data Extraction
Abstract: The exponential growth of scholarly literature needs advanced methods for efficient data extraction and knowledge discovery. Natural Language Processing (NLP) has emerged as a crucial technology in automating the analysis and organization of academic texts. Among various linguistic resources, thesauri serve as important tool for enhancing semantic understanding by providing structured vocabularies, synonyms, and hierarchical relationships between terms. This paper examines the importance of thesauri in enhancing NLP-based scholarly data …
Published in Emerging Trends in Languages · Vol. 3, Issue 1, 2026 · pp. 19–24 Read article
-
Semantics Analysis of Expected Goals in Soccer Data Using Machine Learning
Abstract: In recent years, the increasing availability of soccer data has greatly enhanced the accuracy and depth of player performance evaluation. Soccer, being one of the most popular sports worldwide, attracts millions of fans due to its simple rules, minimal equipment requirements, and high entertainment value. However, analyzing an entire match manually can be time-consuming, leading to a growing demand for automated methods that can summarize and interpret game data efficiently. …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 31–47 Read article
-
Searching Substring in O(n) Time Complexity
Abstract: This research paper presents a highly efficient algorithm for substring search within a given string, achieving a remarkable time complexity of O(n). The proposed algorithm utilizes a two-pointer approach to compare the given string with the targeted substring. By employing string concatenation, the algorithm dynamically constructs a resultant substring during the matching process. Upon completion of character matching, the algorithm compares the resultant substring with the targeted substring and returns …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 9–15 Read article
-
Using Machine Learning for Key phrase Extraction in Digital Libraries
Abstract: Machine learning has revolutionized various aspects of information retrieval, including key phrase extraction in digital libraries. Key phrase extraction is crucial for summarizing and categorizing vast amounts of textual data, enabling efficient search and retrieval processes. This study explores the application of machine learning techniques for automatic key phrase extraction in digital libraries. We review various supervised and unsupervised learning algorithms, including deep learning models, that are employed to identify …
Published in International Journal of Cheminformatics · Vol. 1, Issue 2, 2023 · pp. 8–13 Read article
-
Light-Dark Cycle Disruption in Hypothalamus Tissue of Mus Musculus Causes Change in the Expression of Gm45928 Gene
Abstract: The majority of organisms on earth display consistent 24-hour rhythms in their physiology and behavior due to circadian biology. Light and dark cycles play a key role in setting our internal body clock, which controls things like our sleep patterns, hormone levels, body temperature, and metabolism. The disruption of the light-dark cycle has significant effects on the molecular and behavioral rhythms of the circadian clock of hypothalamus. Gm45928 is a …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 3, Issue 1, 2025 · pp. 32–46 Read article
-
Digital Frontiers in Life Sciences: The Transformative Role of Computing in Modern Biology
Abstract: The integration of computers in the biological sciences has revolutionized research and experimentation, facilitating advancements in areas such as genomics, bioinformatics, systems biology, and ecological modeling. The ability to process vast amounts of biological data efficiently has transformed how scientists study complex biological systems and phenomena. Computational tools enable the analysis of DNA sequences, protein structures, metabolic pathways, and ecological dynamics, which were previously beyond the reach of traditional laboratory …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 Read article
-
Data Representation and Abstraction in Computer Systems: An Interactive Study
Abstract: Data abstraction simplifies data, while data representation stores or encodes it. Data abstraction in programming involves constructing a data type that hides data representation. This lets consumers concentrate on the data’s primary features rather than its implementation. Data abstraction is common in object-oriented programming and database administration. Computers store data in binary format. The smallest binary unit is a bit, or “binary digit”. Bytes typically have eight bits. Data abstraction …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 22–31 Read article
-
Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
-
Industry 4.0 and Smart Supply Chains: Transforming Supply Chain Processes for Enhanced Efficiency and Sustainability
Abstract: The fourth industrial revolution, or Industry 4.0, is an important transformation in how industries function via the use of cutting-edge digital technology. Supply chain management is being substantially altered by integrating technologies like blockchain, big data, automated processes, artificial intelligence, and the internet of things into typical operations of the supply chain. With the help of these technologies, corporations can design intelligent supply chains that are more effective, flexible, and …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 1, 2025 · pp. 36–41 Read article
-
Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
-
Webpage Extraction and Retrieval Chatbot
Abstract: Web scraping is a fundamental technique for automating data extraction in big data applications. While multiple implementations exist, few leverage Python’s Beautiful Soup library for efficient and structured data retrieval. This project aims to develop a web scraper and retrieval system that extracts relevant information from web pages, stores it in a vector database (Milvus), and enables intelligent querying using semantic search and generative AI. The system is designed to …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
-
The Role of Artificial Intelligence in Enhancing Athlete Performance and Training Strategies
Abstract: Artificial Intelligence (AI) is transforming modern sports by improving athlete performance, training methods, and decision-making processes. The integration of AI technologies such as machine learning, data analytics, wearable sensors, and computer vision has enabled coaches and sports scientists to analyze large amounts of performance data with greater accuracy and efficiency. Athletes' physiological indicators, movement patterns, injury risks, and recuperation processes are all monitored by these technology. Training regimens can therefore …
Published in Recent Trends in Sports · Vol. 3, Issue 2, 2026 · pp. 1–7 Read article
-
Deep Learning Enhanced Compressive Sensing for Wireless IoT Data Optimization and Weather Monitoring.
Abstract: This research explores the application of deep learning and compressive sensing in order to optimize data traffic in non-orthogonal multiple access (NOMA)-based wireless internet of things (IoT) networks and weather monitoring. Such a framework would be very effective and overcome pilot attacks and reconstruction losses for secure data transmission. In this regard, a strong communication model has been adopted based on power-domain NOMA for simultaneous wireless transmission by multiple IoT …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 20–36 Read article
-
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
-
Effects of Cluster Computing on Big Data Analysis and Network Topology
Abstract: The rapid expansion of big data has posed substantial difficulties for conventional computing systems. As a result, cluster computing has grown to be a potent method for effective large data processing. Cluster computing involves multiple interconnected nodes functioning as a unified system, pooling together their processing, storage, and memory resources. These nodes are typically connected through high-speed networks such as ethernet or InfiniBand, facilitating efficient data sharing and communication among …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 1, Issue 1, 2023 · pp. 31–39 Read article
-
Bayesian Optimization–Driven Operating Parameter Tuning for Maximizing Methane Yield in Anaerobic Digestion
Abstract: To achieve maximum methane production in an anaerobic digestion (AD) process, a combination of various operational parameters must be tuned nonlinearly in the digestion ecosystem. The conventional trial and error optimization methods are slow, resource consuming, and in most instances, cannot model the intricate parameter interaction in biogas production. The current work introduces a Bayesian Optimization-based model to optimize the set of conditions to maximize the level of methane produced …
Published in International Journal of Energy and Thermal Applications · Vol. 4, Issue 1, 2026 · pp. 1–8 Read article