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647 articles for “data structures”
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Advancements in Data Structures: Bridging the Gap Between Theory and Real-world Applications
Abstract: In the rapidly advancing landscape of computer science, this study unfolds a comprehensive exploration of Data Structures, spanning from foundational principles to cutting-edge innovations. Data structures form the backbone of computational processes, and this study aims to dissect and illuminate their pivotal role. Beginning with fundamental concepts such as Arrays, Linked Lists, Stacks, and Queues, the narrative progresses to intricate structures like Trees, Graphs, and Hash Tables. Practical applications in …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Learning Data Structures: Key to Good Programming
Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article
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Emerging Trends in Data Structures for Modern Machine Learning Applications
Abstract: In the realm of machine learning, data structures play a pivotal role in facilitating efficient data manipulation, storage, and retrieval, thereby significantly impacting the performance and scalability of machine learning algorithms. In recent years, the field of machine learning has witnessed the emergence of novel data structures tailored to address scalability and efficiency challenges inherent in handling large-scale and high-dimensional data. This study provides a look at the data preprocessing, …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 1–7 Read article
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Impact of Time Complexity Using Array and Linked List in Data Structure
Abstract: Data structures are techniques for maintaining, manipulating, and storing data on a computer, enabling efficient access and modification. They support various operations, such as insertion, deletion, updating, and sorting. Examples of data structure include arrays, linked lists, graphs, heaps, stacks, and queues. Each data structure is designed to meet specific needs and solve particular problems. Typically, we identify the problem, devise a solution as an algorithm, and then write an …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 41–48 Read article
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An Investigative Study on Cache-Oblivious Data Structures
Abstract: Cache-oblivious data structures and data management systems have emerged as critical components in modern computing environments, aiming to optimize memory access patterns across different levels of the memory hierarchy without explicit knowledge of cache sizes or configurations. This study presents an overview of cache-oblivious techniques, including adaptive data structures, compression, parallel processing, and security considerations. The workexplores future directions in cache-oblivious systems, such as non-volatile memory support, graph processing, edge …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 2, 2023 · pp. 33–37 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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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
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Array-Linked Data Structure: Introducing a Hybrid Model of Memory Management and Faster and Easier Insertion and Reallocation Procedures
Abstract: Here, I have introduced a new data structure titled “Array-Linked Data Structure”. It incorporates a hybrid model of memory allocation, introducing a new insertion procedure in an existing data structure which is faster than that for arrays. It also offers O(c) access time where c is a constant. The access time is worse than O(1) for an array but still better than that for a linked list since the index …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 1–11 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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Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems
Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …
Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article
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Rainwater Measuring Algorithm in O(1) Time Complexity
Abstract: The Rain Terraces Time Complexity Data Structure Algorithm (RTTCDSA) introduces a novel method for managing temporal data efficiently, inspired by the natural flow of rainwater on terraced landscapes. This study presents the conceptual framework and implementation details of RTTCDSA, which leverages principles of temporal dynamics and landscape morphology to organize and query temporal data with optimal time complexity. RTTCDSA employs a hierarchical structure akin to terraced landscapes, facilitating rapid traversal …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 1, 2024 · pp. 26–32 Read article
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Combining Unstructured and Structured Clinical Data in a Hybrid Transformer Model to Enhance Cardiovascular Analytics and Clinical Decision- Making
Abstract: Since cardiovascular disease (CVD) continues to be a major global cause of morbidity and mortality, early and accurate risk prediction is essential for prompt intervention and individualized treatment. This study introduces a new hybrid transformer-based model that combines unstructured clinical narratives, structured data, and customized lifestyle characteristics. A comprehensive understanding of disease progression is made possible by the model's ability to capture contextual, temporal, and patient- specific insights through the …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 4, Issue 1, 2026 · pp. 30–37 Read article
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ASSESSING OF FOREST STRUCTURE USING EARTH OBSERVATION DATA: ACASE STUDY IN MUNESSA FOREST, OROMIA REGION, ETHIOPIA
Abstract: Forest structure is essential for estimating forest-related carbon emissions, analyzing forest degradation, and quantifying the effectiveness of forest restoration initiatives. However, forest structure quantification is only limited to the specific area of interest without considering the whole forest coverage. Remote sensing data can easily deliver a large area to assess forest structure. Therefore, this study aims to assess forest structure of Munessa Natural Forest by integrating satellite based light detection …
Published in International Journal of Land Read article
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Assessing of Forest Structure Using Earth Observation Data: A Case Study in Munessa Forest, Oromia Region, Ethiopia
Abstract: Understanding forest structure is crucial for estimating carbon emissions associated with forests, assessing forest degradation, and evaluating the success of forest restoration efforts. However, forest structure quantification is limited to the area of interest without considering the whole forest coverage. Forest structure may be easily assessed over a wide area using data from remote sensing. Thus, by combining ground observation with satellite-based light detection and ranging (LiDAR) and Sentinel 2 …
Published in International Journal of Land · Vol. 2, Issue 1, 2025 · pp. 28–37 Read article
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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
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Intrinsic Evaluation of Graph Embeddings: Assessing Clustering and Community Detection Performance
Abstract: This paper presents an intrinsic evaluation of some graph embedding techniques on clustering and community detection tasks. We analyze a diverse set of embedding methods, ranging from traditional techniques such as Laplacian eigenmaps to more recent approaches like graph autoencoders, high-order proximity preserved embedding (HOPE), and graph attention network (GAT), using two widely studied datasets, Cora and CiteSeer. Our evaluation relies on two main metrics: Silhouette score with respect to …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 3, Issue 1, 2025 · pp. 40–48 Read article
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TensorFlow-Based Big Data Analytics for IoT Networks: A Study
Abstract: Internet of Things (IoT) has exploded in recent years, connecting billions of devices generating massive amounts of data. This deluge presents both a significant opportunity and a considerable challenge. While the potential insights hidden within this data are transformative, customary data processing techniques frequently fall short when handled with the velocity, volume, and variety of IoT-generated data. This is where Big Data technologies step in, offering the tools and infrastructure …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 31–38 Read article
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Time Series Forecasting Based on PyAF and fbProphet
Abstract: Time series forecasting is the technique of predicting future events using previous data. Time series data includes information that is collected and recorded at regular intervals, such as daily stock prices, monthly sales figures, or hourly temperature readings. The purpose of time series forecasting is to use previous data to create accurate forecasts about the future values of a given variable. This can be beneficial for a range of applications, …
Published in International Journal of Information Security Engineering · Vol. 1, Issue 1, 2023 · pp. 32–36 Read article
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The Molecular Structure of Chemical Compounds by using Quantitative Calculations in Chemistry
Abstract: Computational chemistry has its roots in the early attempts of theoretical physicists, beginning in 1928, to solve the Schrödinger equation using mechanical calculating machines. These calculations verified that the solutions of the Schrödinger equation quantitatively reproduced experimentally observed properties of simple systems such as the helium atom and the hydrogen molecule. These approximate solutions of larger systems and exact solutions of simple model problems allowed chemists and physicists to provide …
Published in Journal of Catalyst & Catalysis · Vol. 12, Issue 2, 2025 · pp. 01–08 Read article
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Recent Developments in Structural Genomics: Uncovering Cellular Functions
Abstract: Structural genomics has become a groundbreaking field for understanding cellular functions by revealing the three-dimensional structures of proteins and other biomolecules. This field combines advanced methods like X-ray crystallography, nuclear magnetic resonance spectroscopy, cryo-electron microscopy, and computational modeling to explore the molecular structure and behavior of cellular components. Recent advances have significantly accelerated the pace of structure determination, bolstered by high-throughput methods and artificial intelligence tools like AlphaFold. These developments …
Published in International Journal of Cell Biology and Cellular Functions · Vol. 2, Issue 2, 2024 · pp. 30–35 Read article