Article
Chemistry, Multidisciplinary
Justas Kazanavicius, Dalius Mazeika, Diana Kalibatiene
Summary: This research proposes and evaluates an approach for migrating from a monolith database to a multi-model polyglot persistence. The results show that this approach improves the quality attributes of data storage, such as consistency, understandability, availability, and portability.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Feng Ye, Xinjun Sheng, Nadia Nedjah, Jun Sun, Peng Zhang
Summary: As the need for handling data from various sources becomes crucial, managing multi-model data has become a key area of research. Striking a balance between polyglot persistence and multi-model databases is challenging. Current benchmarks are not suitable for comparing these two methods. MDBench, an end-to-end benchmark tool, is introduced to address this issue. ArangoDB excels at insertion operations of graph data, while the polyglot persistence instance is better at handling deletion operations of document data. When it comes to multi-thread and associated queries, polyglot persistence outperforms ArangoDB in execution time and resource usage. However, ArangoDB has the edge over MongoDB and Neo4j regarding reliability and availability.
JOURNAL OF DATABASE MANAGEMENT
(2023)
Article
Computer Science, Information Systems
Carlos Garcia Calatrava, Yolanda Becerra, Fernando M. Cucchietti
Summary: This paper proposes a comprehensive approach to improve the performance and efficiency of time-series databases, utilizing a polyglot-based approximation to optimize data storage while considering the characteristics of the data flow. Experimental results show that this approach outperforms mainstream time-series databases in terms of speed and performance.
Article
Computer Science, Information Systems
Beom-Heyn Kim, Young Yoon
Summary: Cloud storage services are popular among billions of users, but data consistency remains a significant concern. Relief is proposed as a solution to enable client-side data consistency verification for various consistency models. It is shown to be an efficient solution to overcome previous limitations.
Article
Computer Science, Artificial Intelligence
Tanusree Parbat, Ayantika Chatterjee
Summary: This paper focuses on the design of an encrypted database using fully homomorphic encryption (FHE) and proposes a scheme for secure modification or conditional update of the encrypted database. The proposed scheme applies Attribute-Based Access Control (ABAC) to FHE databases with minimal performance and storage overhead. It supports arbitrary secure encrypted SQL query execution with suitable access control.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
Neha Bansal, Shelly Sachdeva, Lalit K. Awasthi
Summary: Although there are many data modeling tools for relational databases, this paper focuses on data modeling for NoSQL databases. It proposes a workload-driven model for the logical schema design of a NoSQL document database, which converts the conceptual schema and application workload into a logical model for NoSQL document stores.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Luiz Henrique Zambom Santana, Ronaldo dos Santos Mello
Summary: This article surveys the usage of NoSQL databases to store large RDF graphs, discussing aspects such as model mapping, indexing, partitioning, and caching, as well as proposing a reference architecture.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2022)
Article
Computer Science, Information Systems
Lei Zhang, Ke Pang, Jiangtao Xu, Bingxin Niu
Summary: XYJSON is a data interaction transformation model that can handle all data using standard SQL syntax and JSON document data. It solves the problem of increased development workload and difficulty caused by using different control methods for different types of databases under cloud hybrid storage, by establishing a general conversion model between relational and NoSQL data.
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS
(2022)
Article
Computer Science, Information Systems
Dejan Dundjerski, Milo Tomasevic
Summary: This paper focuses on using real-world data to build an automatic database troubleshooting system, which combines comprehensive statistical data science models and an expert system for root cause analysis. Extensive evaluation studies on Azure SQL production workloads confirmed the feasibility and cost-effectiveness of this approach at the scale of the cloud.
IEEE TRANSACTIONS ON CLOUD COMPUTING
(2022)
Article
Computer Science, Hardware & Architecture
Jasper Bogaerts, Bert Lagaisse, Wouter Joosen
Summary: This paper discusses the importance of application-level access control when hardening software applications and introduces the data access middleware Sequoia, which enables attribute-based, application-level access control in data-driven applications through query rewriting. The middleware enforces external access control policies on data-focused operations and provides scalable runtime enforcement of policies for relational databases and document stores.
IEEE TRANSACTIONS ON DEPENDABLE AND SECURE COMPUTING
(2021)
Article
Construction & Building Technology
Gokhan Demirdogen, Zeynep Isik, Yusuf Arayici
Summary: Facility management is the most costly stage in the building lifecycle of healthcare buildings. Building Information Modeling (BIM) has the potential to address the information management needs of healthcare facility management. However, its static nature hinders its use in facility management, which requires dynamic information handling. This paper aims to develop a healthcare facility management system using Big Data Analytics (BDA), BIM, and NoSQL database to enable information query and Key Performance Indicator (KPI) visualization. The findings show that the proposed system effectively enables practitioners in healthcare facility management to retrieve and analyze facility management data.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Chemistry, Analytical
Marie Mardal, Petur W. Dalsgaard, Brian S. Rasmussen, Kristian Linnet, Christian B. Mollerup
Summary: In this article, a novel data analysis strategy for liquid chromatography-high-resolution mass spectrometry (LC-HRMS) data based on structured query language database archiving is reported. The ScreenDB database was populated with parsed untargeted LC-HRMS data from forensic drug screening, allowing for long-term monitoring, retrospective data analysis, and identification of alternative analytical targets. The examples demonstrated the significant improvement ScreenDB brings to forensic services and its potential for broad applications in large-scale biomonitoring projects.
ANALYTICAL CHEMISTRY
(2023)
Article
Computer Science, Information Systems
Monther Aldwairi, Moath Jarrah, Naseem Mahasneh, Baghdad Al-khateeb
Summary: Data management systems rely on a correct design of data representation and software components. The data representation scheme plays a vital role in how the data are stored, which influences the efficiency of its processing and retrieval. The proposed graph-based approach outperforms the RDF4J framework in terms of insertion and retrieval time, according to extensive experiments using healthcare data with Neo4J, OrientDB, and RDF4J.
INFORMATION PROCESSING & MANAGEMENT
(2023)
Article
Computer Science, Hardware & Architecture
Maria Jose Suarez-Cabal, Pablo Suarez-Otero, Claudio de la Riva, Javier Tuya
Summary: Current information technologies generate large amounts of data, which are stored in NoSQL databases for management and analysis. We propose a method called MDICA to maintain data integrity in column-oriented databases and provide statements and messages to help developers avoid problems.
COMPUTER STANDARDS & INTERFACES
(2023)
Article
Computer Science, Artificial Intelligence
Daniel Bauer, Florian Froese, Luis Garces-Erice, Chris Giblin, Abdel Labbi, Zoltan A. Nagy, Niels Pardon, Sean Rooney, Peter Urbanetz, Pascal Vetsch, Andreas Wespi
Summary: Over the past three years, the authors have been operating a large-scale data processing platform on an OpenStack private cloud instance, providing analytics for a wide variety of corporate data assets to globally distributed teams. They control every layer of the stack and report their experiences in building and operating such a system, including their technical choices and how they evolved based on actual workloads.
Article
Computer Science, Information Systems
Rajendra Prasad Nayak, Srinivas Sethi, Sourav Kumar Bhoi, Kshira Sagar Sahoo, Anand Nayyar
Summary: This paper proposes a machine learning-based misbehavior detection system for cognitive software-defined multimedia vehicular networks. The system analyzes communication data and updates trust values to classify behaviors using the best machine learning algorithm. Experimental results show that the system has high detection accuracy and performs well in terms of detection time and energy consumption.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Ashish Singh, Adnan Gutub, Anand Nayyar, Muhammad Khurram Khan
Summary: In recent decades, food safety and traceability issues have become increasingly important. The establishment of a Food Safety Traceability System (FSTS) has become essential to prevent accidents and misconduct by tracing food from producer to consumer. While various technologies have been integrated into traditional food supply chain systems, they are not adequate for the current supply chain market. This paper discusses the potential of blockchain technology to overcome safety and tracking issues in FSTS implementation, providing a detailed analysis of various aspects including consensus algorithms, security attacks, and solutions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Kalyan Kumar Jena, Sourav Kumar Bhoi, Debasis Mohapatra, Chittaranjan Mallick, Kshira Sagar Sahoo, Anand Nayyar
Summary: The Internet of Medical Things (IoMT) is crucial for supporting healthcare systems. This paper proposes a machine intelligence-based model that utilizes IoMT to analyze disease images in order to detect cherry red spot (CRS) disease in the eyes. The results show that this approach achieves better detection accuracy, lower detection error, and faster processing time compared to the k-means algorithm.
Article
Engineering, Electrical & Electronic
Sandip K. Chaurasiya, Arindam Biswas, Anand Nayyar, Noor Zaman Jhanjhi, Rajib Banerjee
Summary: With the development of technology, many modern applications have been proposed on wireless sensor networks with IoT integration, but the performance of these networks is restricted due to various constraints imposed by sensor nodes, especially power limitation. This paper proposes a metaheuristic clustering scheme using differential evolution technique to address this problem. The proposed scheme achieves improved network performance by forming load-balanced clusters, providing a more scalable and adaptable network. Through simulation results and experimentation, it has been shown to outperform state-of-the-art schemes in terms of cluster formation, network lifetime, resource utilization, and throughput.
INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS
(2023)
Article
Computer Science, Information Systems
Ashima Kukkar, Rajni Mohana, Aman Sharma, Anand Nayyar, Mohd. Asif Shah
Summary: Machines are being utilized to accurately understand people's communication on social media in the age of automation. The concept of what and how people believe on social media platforms greatly influences decision-making. The use of internet and social media is growing rapidly and can be harnessed for various purposes. This study focuses on sentiment analysis based on Emotional Recognition (ER) and proposes a novel lexicon-based system that considers lengthened words as they are. The performance of the proposed system surpasses traditional systems by achieving 81% to 96% F-measure rates for all datasets.
Article
Education & Educational Research
Ashima Kukkar, Rajni Mohana, Aman Sharma, Anand Nayyar
Summary: Predicting student performance is crucial in higher education, and a novel Student Academic Performance Predicting (SAPP) system is proposed to address the existing issues and enhance prediction accuracy. The SAPP system uses a combination of 4-layer stacked LSTM network, Random Forest, and Gradient Boosting techniques to predict students' pass or fail outcomes. The system achieved a prediction accuracy of approximately 96%, which is higher than existing systems.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Computer Science, Artificial Intelligence
T. Anitha, S. Aanjankumar, S. Poonkuntran, Anand Nayyar
Summary: This paper proposes a new technique for identifying and categorizing malevolent Internet traffic in smart devices. The technique combines deep learning techniques, specifically convolutional neural networks (CNN), with long short-term memory (LSTM) to detect and categorize malevolent traffic. Our approach achieves a high traffic detection rate, accuracy, and low false acceptance rate (FAR) compared to existing methods. These outcomes highlight the superior performance and analysis of our technique, making it a valuable contribution to smart device security.
NEURAL COMPUTING & APPLICATIONS
(2023)
Correction
Multidisciplinary Sciences
Anudeep Gandam, Jagroop Singh Sidhu, Sahil Verma, N. Z. Jhanjhi, Anand Nayyar, Mohamed Abouhawwash, Yunyoung Nam
Article
Computer Science, Artificial Intelligence
Raju Pal, Mukesh Saraswat, Sandeep Kumar, Anand Nayyar, Pushpendra Kumar Rajput
Summary: This study proposes a multi-objective binary Grey wolf optimizer for optimizing the clustering centers in wireless sensor networks. By simultaneously optimizing multiple objectives, such as energy utilization and network stability, this method outperforms other state-of-the-art clustering protocols in terms of improving network performance and extending network lifetime.
Article
Education & Educational Research
Hayat Sahlaoui, El Arbi Abdellaoui Alaoui, Said Agoujil, Anand Nayyar
Summary: This study compares different variations of the Synthetic Minority Oversampling Technique (SMOTE) combined with classification algorithms to create prediction models. The results show that SMOTE with Edited Nearest Neighbors is superior, and the balanced random forest classifier performs better when using SMOTE-ENN, achieving 96% accuracy, precision, and F-value. Smote also has faster execution time. For model interpretability, combining Local Interpretable Model-agnostic Explanations (LIME) and SHapley Additive exPlanations (SHAP) provides deeper insights.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Engineering, Biomedical
L. Godlin Atlas, K. P. Arjun, K. Sampath Kumar, Rajesh Kumar Dhanaraj, Anand Nayyar
Summary: The range of diseases such as diabetes, hypertension, and vascular occlusions is increasing rapidly in modern society, leading to organ damage. Among them, eye diseases have severe impacts on vision, and early detection and treatment are necessary. Existing strategies have some setbacks, so a deep learning framework has been developed in this study to improve the prediction of retinal hemorrhage.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2024)
Article
Computer Science, Artificial Intelligence
K. Jyothsna Devi, Priyanka Singh, Muhammad Bilal, Anand Nayyar
Summary: This paper proposes a secure digital image watermarking scheme in the hybrid DWT-SVD domain, which addresses the security concerns in UAV image transmission using an adaptive scaling factor and symmetric cryptographic-based encryption method. Experimental results show that the scheme achieves high security and low computational cost.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Theory & Methods
Rajesh Ramnarayan, Rajesh Singh, Anita Gehlot, Kapil Joshi, Ashraf Osman Ibrahim, Anas W. Abulfaraj, Faisal Binzagr, Salil Bharany
Summary: The use of digital twin technologies in the hospitality industry has gained significant attention due to their effectiveness in evaluation, planning, resource utilization, and improving real-time services. These technologies improve production and customer service in the hospitality industry, creating a fast virtual world space for customers.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
