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1975 articles for “font meta- data” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
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Strategies to Avoid Illegal Data Access
Abstract: For companies of all sizes, data security is a top priority. The chance of unauthorized data access increases as technology develops. To prevent unwanted access to their data, businesses must be proactive. This study examines technology solutions, personnel training, and policy enforcement as methods to prevent unauthorized data access. Data may be protected from illegal access using technological solutions like firewalls, intrusion detection systems, and encryption. Intrusion detection systems notify …
Published in Journal of Communication Engineering & Systems · Vol. 12, Issue 3, 2022 · pp. 29–40 Read article
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Big Data: A Survey Paper on Big Data Technologies
Abstract: AbstractThere are many Big Data technologies that have been making an impact on the new technology stacks for handling Big Data, but Apache Hadoop is one technology that has been the darling of Big Data talk. Hadoop is an open-source platform for storage and processing of diverse data types that enables data-driven enterprises to rapidly derive the complete value from all their data. A plethora of Big Data Analytics technologies …
Published in Journal of Computer Technology & Applications · Vol. 11, Issue 3, 2020 · pp. 1–7 Read article
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Font-Based Text Steganography for Covert Communication in Devanagari Script: A Review (2020–2026)
Abstract: Steganography hides the fact that a communication exists rather than merely safeguarding its content. Text is the most challenging of all steganographic media because it contains the least redundancy and is the most sensitive to changes. Devanagari script, with its conjunct consonants, ligatures, matras, and non-linear glyph construction, makes these difficulties even harder, rendering rendering-dependent and OCR- based steganographic methods largely ineffective. This paper presents a systematic review of text …
Published in Emerging Trends in Languages · Vol. 3, Issue 2, 2026 · pp. 22–33 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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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
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From Differential Equations to Data Science: A Survey on Analytical Methods in Contemporary Problems
Abstract: The integration of differential equations and data science methods represents a dynamic and evolving approach to solving contemporary challenges across a wide range of disciplines, including engineering, physics, biology, economics, and finance. Differential equations have long served as fundamental tools for modeling continuous systems and processes, offering powerful insights into the behavior of natural and man-made phenomena. For example, they describe how heat diffuses through materials, how populations grow in …
Published in Recent Trends in Mathematics · Vol. 2, Issue 2, 2025 · pp. 1–6 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Study Of Uber-Related Data Using Machine Learning
Abstract: This paper describes the operation of the machine learning algorithm used in the Uber database, which contains data generated by the Uber Movement for a few locations in Hyderabad and the big apple City. Uber is known as a peer-to-peer program. This program connects you to the nearest drivers available to take you to your destination. This database includes Uber capture data with information such as time, ride date additional …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 9, Issue 2, 2022 · pp. 1–6 Read article
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Hybrid Deduplication for Secure Data Sharing Using Erasure Techniques and HIDC
Abstract: Data deduplication has an important role in reducing storage consumption to make it affordable to manage in today’s explosive data growth. To overcome the problems occurring in the cloud a system is proposed, in which History Aware Inline De-duplication algorithm for checking duplicity of data before uploading it on the server is used. MD5 algorithm is used to generate the hash value of the data. Also, erasure coding is used …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 3, 2017 · pp. 34–39 Read article
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A Unique Insight on Detoxification and Inactivation of Metal Toxicity in Herbal-Metal Preparations in Siddha System
Abstract: Metal chelating property of various time tested siddha herbs were tested individually vis a vis Phyllanthus emblica, Embelia ribes, Elettaria cardamomum, Withania somnifera, Corollocarpus epigaeus, Centella asiatica, Celastrus paniculatus, Smilax chinensis, Psoralea corylifolia, Solanum trilobatum and Indigofera aspalathoides. Most of the plants showed metal chelating effect suggesting their role in in-activating metal toxicity. Use of these herbs along with metal preparation may offer some value in reducing toxicity due to …
Published in Research & Reviews : A Journal of Unani, Siddha and Homeopathy · Vol. 2, Issue 2, 2015 · pp. 13–17 Read article
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An Overview of Privacy-Preserving Data Encryption Techniques in Mobile Cloud Computing for Big Data
Abstract: With the introduction of mobile cloud computing (MCC), data processing, storage, and sharing have undergone a radical transformation that has greatly improved organizational effectiveness and quality of life. But there are also serious worries about data security and privacy due to the increasing usage of mobile devices and cloud computing, particularly when managing large amounts of data from many sources like sensors and cellphones. The privacy issues surrounding MCC are …
Published in Recent Trends in Electronics Communication Systems · Vol. 12, Issue 1, 2025 · pp. 1–7 Read article
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Optimization of Helical Spring Weight using Meta-heuristic Algorithms
Abstract: Optimization is the act of obtaining the best results under given circumstances. A mathematical theory of optimization is highly in use and is being applied to design where design function can be expressed mathematically. Many techniques like Linear Programming, Branch & Bound technique, Dynamic Programming methods are available to solve optimization problems. But these conventional Methods suffer from certain drawbacks like sticking at suboptimal solution, inefficiency in handling problems having …
Published in Trends in Machine design · Vol. 5, Issue 2, 2018 · pp. 21–28 Read article
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A Short Survey of Data Compression Techniques for Column Oriented Databases
Abstract: AbstractColumn oriented data-stores has all values of a single column stored as a row followed by all values of the next column. Such way of storing records helps in data compression since values of the same column are of the similar type and may repeat. This paper surveys the various data compression techniques in column oriented databases. Data compression is efficiently used to save storage space and network bandwidth. It …
Published in Current Trends in Information Technology · Vol. 3, Issue 2, 2013 · pp. 1–6 Read article
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Study of Various Forecasting Models for Time Series Data Using Stochastic Processes
Abstract: The data which is in time stamped format is called as time series data. The time series data is everywhere, for example, weather data, stock market data, health care data, sensor data, network data, sales data and many more. Time series have various components due to which the time series data became complex. Trend, seasonality, cyclical, and irregularities, these are different components. As everyone is interested to know about future. …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 2, 2021 · pp. 26–32 Read article
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Visual Analytics with Machine Learning for Data-Driven Investigations of Product State Transmission in Production System
Abstract: In recent years, the significance of effectiveness and productivity has grown. Furthermore, the industry has been able to improve production system performance thanks to advances in processing power and advanced analytics. A better understanding of intermediate product stages is therefore required to take the relevant measures. To highlight the importance of this field of study, a study on data-driven probabilistic ML algorithms and their real-time applications to smart energy systems …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 2, 2022 · pp. 1–7 Read article
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Metabolites in Modern Medicine: Decoding the Future of Health and Diseases
Abstract: The end products of many metabolic processes in cells are called metabolites. Each reaction contributes a specific metabolite. Metabolites act as fingerprints of on-going biological processes. Constant changes in cellular composition due to both environmental and internal factors. By analysing the types and presence of metabolites, scientists can effectively reconstruct the inner workings of a cell or organism. In the past, analysing metabolites was a slow and tedious process, often …
Published in Emerging Trends in Metabolites · Vol. 1, Issue 2, 2024 · pp. 1–13 Read article
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Database Security and Integrity: Ensuring Reliable and Secure Data Management
Abstract: This paper explores the critical aspects of database security and integrity, addressing major threats and presenting strategies to mitigate these risks. Emphasizing the importance of secure and reliable data management, the paper reviews historical perspectives, current trends, key challenges, and future directions in the field. The research underscores the necessity of robust security measures and integrity controls to maintain the trustworthiness and reliability of databases, which are pivotal in supporting …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Big Data, Big Impact: The Role of Analytics in Modern Business
Abstract: In modern business, “Big Data” signifies the vast amount of data collected from various sources, and “Big Data Analytics” refers to the process of analyzing this data to extract valuable insights, enabling companies to make data-driven decisions, optimize operations, better understand customers, and ultimately gain a competitive edge by identifying trends, patterns, and opportunities that might otherwise be missed. This study analyzes large datasets, by which businesses can gain deeper …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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Design and Performance Assessment of Light Weight Data Security System for Secure Data Transmission in IoT
Abstract: The Internet of Things (IoT) is expected to provide an interface for future technologies’ small processing tools. It is expected to provide more communication data and information security can risky. Data pinnacles and information security can be a risk. This size of the gadget in this engineering is essentially little, low power utilization. Many rounds of encryption are essentially a misuse of requirements Gadget vitality. Less convoluted calculation, be that …
Published in Journal Of Network security Read article