Search
1885 articles for “data processing’s” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
-
A Novel Secure Cloud Storage Solution: Combining AES-OTP, RSA, and Time-Limited Access Control with Adaptive Key Management
Abstract: The reliance of cloud computing on the data processing and storage structure creates serious security risks. Ensuring availability, security, and integrity of data in cloud settings becomes a challenge for both the individual and the enterprise. This paper will, therefore, introduce a novel Hybrid Cryptographic Framework that combines RSA, One-Time Pad (OTP), and AES as a means of enhancing data security in cloud storage. It employs RSA for secure key …
Published in Current Trends in Signal Processing · Vol. 14, Issue 3, 2024 · pp. 11–20 Read article
-
Develop the Design of Sustainable Polymer Materials: Applying Reinforcement Learning, IoT-Enabled Monitoring, and Data-Driven Manufacturing Approaches
Abstract: Sustainable polymer materials development is a must due to resource constraints, environmental concerns, and the demand for designed materials with high performance. When it comes to material optimization, energy utilization, process unpredictability, and lifecycle sustainability, traditional polymer production methods have their challenges. Reinforcement Learning (RL), Internet of Things (IoT) monitoring, and data-driven production are utilized in the design and manufacturing of sustainable polymer materials. It is recommended to use Internet …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 1207–1231 Read article
-
Edge Computing in IoT: Challenges and Opportunities for Engineers
Abstract: The internet of things (IoT) has revolutionized how we interact with our environment, collect data, and make decisions. However, the exponential growth of IoT devices has led to significant challenges in data processing, latency, and bandwidth usage. Edge computing provides an effective solution to these issues by bringing computation and data storage nearer to the source of data generation. This paper provides a comprehensive exploration of the challenges and opportunities …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 3, 2024 · pp. 14–19 Read article
-
Scheduling in Hadoop Cluster: A Review
Abstract: AbstractData generated by almost everything is electronically stored in the units of exabyte or zetabyte known as big data. For big data processing, Hadoop is considered as best choice. There are lots of challenges like storage, processing and resource allocation on the basis of job deadlines, QoS, budget, network bandwidth and data transmission. In order to solve these problems, various scheduling algorithms have been developed. These scheduling algorithms are classified …
Published in Journal of Advanced Database Management & Systems · Vol. 4, Issue 3, 2017 · pp. 26–31 Read article
-
Hadoop Yarn Big Data: Review Paper
Abstract: AbstractYARN, yet another resource negotiator is a large-scale, distributed operating system for big data applications and software rewrite that is capable of decoupling MapReduce's resource management and scheduling capabilities from the data processing component. In this study we have briefly described the evolution of YARN for big data analysis from the year 2017 to the recent times. Keywords: Apache HADOOP, HDFS, MapReduce, Apache Samza, Apache Flink
Published in Journal of Advanced Database Management & Systems · Vol. 7, Issue 3, 2020 · pp. 18–26 Read article
-
Next-Generation Satellite Remote Sensing: Innovations, Applications, and Future Prospects
Abstract: Advances in satellite remote sensing have revolutionized our ability to monitor, analyze, and understand the Earth's environment across various scales. Over the past few decades, the field has seen remarkable progress in sensor technology, data processing techniques, and analytical methodologies. Modern satellites now provide high-resolution imagery and multi-spectral data, enabling enhanced monitoring of land cover, atmospheric conditions, oceanic dynamics, and natural disasters. These advancements have facilitated improvements in climate change …
Published in International Journal of Satellite Remote Sensing · Vol. 3, Issue 1, 2025 · pp. 37–62 Read article
-
Smart Cardiazmo Implemented Using Internet of Things
Abstract: In this research, we present a system that uses sensors to identify a person's heart rate utilizing heartbeat sensing even if they are at home. The idea is to detect a heart attack early enough that the patient can receive medical help within the first few hours. As a result, his or her chances of survival are considerably increased. Here we use the AD8232 sensor for the cardiography of the …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 3, 2021 · pp. 35–48 Read article
-
A Study on Privacy Preserving Techniques in Data Mining
Abstract: Data Mining (DM) is the technique of examining data from specific summarizing and perspectives the outcome as useful information. It has been describing as "the non-trivial procedure of new, potentially helpful and ultimately conceivable patterns and identifying valid in data". The word “Knowledge” in KDD submits to the discovery of example which is removing since the processed data. Preserving privacy is becoming a key apprehension as personal data is publicly …
Published in Journal of Operating Systems Development & Trends · Vol. 5, Issue 2, 2018 · pp. 18–23 Read article
-
Automating time based Household electricity Bill Calculations for Efficient Budgeting
Abstract: Recurrent household expenses must be precisely, in time, and openly tracked to make efficient household budgeting. Conventional monthly billing performance tends to delay the financial information, which results in the inefficient cash flow management and inability to modify short-term expenditure patterns. The proposed research is a system to automatize the calculation of household bills per week in order to deliver more frequent and practical insights into the household spending habits. …
Published in International Journal of Electrical Power and Machine Systems · Vol. 4, Issue 1, 2026 · pp. 1–16 Read article
-
Innovative Approaches to Reducing Data Traffic in IoT Networks Using Deep Learning and Compressive Sensing
Abstract: The exponential growth of internet of things (IoT) devices has posed unprecedented challenges in managing the massive data generated by real-time monitoring, automation, and analytics. Existing network infrastructures lack scalability, bandwidth, and suffer from latency problems, further making data transmission less efficient. This study surveys innovative approaches using deep learning and compressive sensing to reduce IoT data traffic. Deep learning is able to upgrade data processing by means of very …
Published in International Journal of Satellite Remote Sensing · Vol. 2, Issue 2, 2024 · pp. 46–62 Read article
-
Building a Modern Land Registration System: Leveraging Node.js and React.js for Efficiency, Security and Scalability
Abstract: Land registration systems are critical for safeguarding property ownership and enabling efficient real estate transactions. However, traditional systems often suffer from inefficiencies, including lengthy processing times, susceptibility to fraud, and limited accessibility. This study proposes a modernized Land Registration System (LRS) leveraging Node.js for backend development and React.js for frontend design to address these challenges. The system integrates real-time data processing, automated document verification, and role-based access control (RBAC) to …
Published in Recent Trends in Programming languages · Vol. 12, Issue 2, 2025 · pp. 1–6 Read article
-
Distributed Data Mining Cloud Based System
Abstract: When traditional data mining systems are used for cloud computing, there are performance bottlenecks and scalability difficulties. In this study, it states that a data mining platform is directly based on the cloud computing. As compared with the traditional data mining systems, the platform is highly scalable, with massive data processing capabilities, service-oriented and low hardware costs. The platform can support the design and application of various distributed data mining …
Published in Journal of Operating Systems Development & Trends · Vol. 5, Issue 3, 2018 · pp. 10–14 Read article
-
ML Model Comparison for Sentiment Analysis Across Diverse Datasets
Abstract: Analyzing sentiment is crucial for understanding public opinion on various issues in marketing, politics, and social sciences. This study compares the performance of seven different machine learning algorithms for sentiment classification, focusing on their effectiveness, accuracy, and complexity. The research is conducted on a pre-processed dataset with balanced text samples, utilizing feature extraction methods such as Term Frequency-Inverse Document Frequency (TF-IDF). The performance assessment criteria consist of accuracy, precision, recall, …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 26–33 Read article
-
A Study on The Impact of Artificial Intelligence in Pharmaceuticals
Abstract: The main goal of artificial intelligence (AI) is to create intelligent modeling, which facilitates knowledge imagination, problem-solving, and decision-making. AI is becoming more and more significant in several pharmacy domains, including polypharmacology, hospital pharmacy, drug discovery, and drug delivery formulation development. Various types of artificial neural networks (ANNs), including deep neural networks (DNNs) and recurrent neural networks (RNNs), are utilized in the development of drug delivery formulations and in drug …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 1, 2025 · pp. 24–32 Read article
-
Analysis of Color and Particulate Depolarization Ratio Profiles for Aerosols using CALIPSO Level 2 Data
Abstract: Aerosols have an important impact on Earth’s climate system by absorbing, scattering and modifying cloud properties. There are many sources of aerosols; both natural and resulting from human activities with widely varying distribution both in space and time. In addition to aerosol columnar spatio-temporal variation, the vertical profile temporal studies provide valuable inputs to various climatic models and radiative transfer studies. This study focuses on the analysis of color ratio …
Published in Journal of Remote Sensing & GIS · Vol. 6, Issue 2, 2015 · pp. 1–5 Read article
-
Server Based Operating System (OS) Research Direction for Future Smart World Using Internet of Things
Abstract: AbstractCommunication and data processing over Internet has become a research issue to the researchers of Internet of Things (IoT). Cloud computing is already familiar at present. Cloud computing offers servers, storage, databases, networking, software, analytics and more, over the Internet (“the cloud”). Companies offering these computing services over Internet (“the cloud”) and typically, charge for cloud computing services based on usage, similar to how you are billed for water or …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 2, 2017 · pp. 26–32 Read article
-
The Convergence of AI and Composites - A Review Anchored in Patent Trends
Abstract: The integration of artificial intelligence (AI) and machine learning (ML) techniques is revolutionizing the design, analysis, and optimization of polymer (PC/FRP), metal (MC), and ceramic matrix composites (CC). Techniques such as artificial neural networks (ANN), deep learning (DL), genetic algorithms (GA), and physics-informed machine learning (PIML) are employed to enhance property estimation, process optimization, and predictive modeling. These AI-driven frameworks enable virtual testing, application-specific material design, and real-time decision-making, while …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 182–198 Read article
-
IoT Based Wireless Data Monitoring System with TFT LCD
Abstract: This study introduces the design, development, and implementation of an Internet of Things (IoT)-based wireless data monitoring system that utilizes a Thin-Film Transistor Liquid Crystal Display (TFT LCD) for real-time visualization. The system is engineered to collect, transmit, and display sensor data wirelessly, making it suitable for a range of practical applications such as industrial automation, healthcare monitoring, and environmental observation. The key goal of this work is to enhance …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 10–18 Read article
-
Big Data Analytics for Effective Decision Making in Business Intelligence
Abstract: In this study, we explore the significance of Big Data Analytics (BDA) in enhancing decision-making processes within Business Intelligence (BI) frameworks. It involves processing vast volumes of data from various sources, enabling businesses to identify patterns, trends, and correlations that were previously unnoticed. This analytical power enhances strategic planning, customer understanding, operational efficiency, and competitive advantage. Through advanced algorithms and machine learning techniques, businesses can predict future trends, optimize operations, …
Published in Journal of Advanced Database Management & Systems · Vol. 11, Issue 1, 2024 · pp. 23–28 Read article
-
Develop a Data Science Approach for Optimizing Energy Consumption
Abstract: Optimizing energy consumption has become a critical challenge in the era of sustainability and increasing energy demand. Efficient energy management is essential to address environmental concerns, reduce costs, and ensure resource availability for future generations. This project leverages data science techniques to evaluate and improve energy consumption across diverse sectors, including residential, industrial, and commercial domains. By integrating advanced analytics, machine learning models, and real-time data processing, the project aims …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 31–44 Read article