Article
Computer Science, Information Systems
Mahmoud Abbasi, Javier Prieto, Amin Shahraki, Juan M. Corchado
Summary: This paper introduces a blockchain-based industrial data trading system that addresses trust issues and security vulnerabilities in existing centralized data marketplaces. By decentralized storage and graph technology, it improves data integrity and query efficiency, while enhancing security standards with integrated access control. Preliminary evaluations indicate that the system has the potential to provide a more secure, transparent, auditable, and trustworthy data trading environment.
INTERNET OF THINGS
(2023)
Article
Computer Science, Information Systems
Mariem Turki, Saoussen Cheikhrouhou, Bouthaina Dammak, Mouna Baklouti, Rawya Mars, Afef Dhahbi
Summary: The public's health is reliant on a trustworthy drug supply chain, but the rising issue of drug counterfeiting has led to thousands of victims suffering from poisoning or treatment failures. This has resulted in a need for improved drug traceability in the supply chain. Existing traceability systems lack transparency, trust, and suffer from separated data storage. To address these limitations, a decentralized blockchain-based drug traceability solution is proposed in this research, providing a secure and trusted transaction history by utilizing smart contracts, decentralized off-chain storage, and blockchain Non-Fungible Tokens (NFTs) to ensure data provenance and integrity in an IoT environment. The effectiveness, cost, and security of the approach are evaluated.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2023)
Article
Computer Science, Interdisciplinary Applications
Salam Abdallah, Nishara Nizamuddin
Summary: In this paper, a blockchain-based framework for the online sale of pharmaceutical products is proposed. It eliminates intermediaries such as hospitals or pharmacies and utilizes Ethereum smart contracts to monitor interactions, track transactions, and ensure secure payment dispersal. The smart contracts also regulate the interaction between sellers and consumers, monitor IoT container status, and provide full notification to consumers. Special cases such as consumer refunds are handled to ensure the safe delivery of medicines.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Chemistry, Analytical
Qi Yao, Huajun Zhang
Summary: This paper proposes a trusted agricultural product traceability system based on the Ethereum blockchain. By employing a dual storage model of Blockchain+IPFS and a data privacy protection solution, the system addresses the issues found in traditional agricultural traceability systems and meets the requirements for efficient and feasible traceability.
Article
Green & Sustainable Science & Technology
Sumit Kumar Rana, Hee-Cheol Kim, Subhendu Kumar Pani, Sanjeev Kumar Rana, Moon-Il Joo, Arun Kumar Rana, Satyabrata Aich
Summary: With the onset of the fourth industrial revolution, digitalization of industrial processes, specifically supply chain management, is a key focus. Blockchain technology is emerging as a solution to enhance transparency and trust in digital supply chains.
Article
Computer Science, Information Systems
Rana M. Amir Latif, Muhammad Farhan, Osama Rizwan, Majid Hussain, Sohail Jabbar, Shahzad Khalid
Summary: Blockchain technology is widely used in business networks to record transactions, validate, and track assets. In the global supply chain network, different countries have various rules and operating procedures. The major issue faced is asset traceability, which is addressed by using blockchain technology to provide greater traceability. A proposed research study focuses on a commodity traceability network using blockchain technology, storing commodity history in a global database through smart contracts and creating a chain for tracing back to the source of goods.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Pratyush Kumar Patro, Raja Jayaraman, Khaled Salah, Ibrar Yaqoob
Summary: Efficient traceability management is crucial for products in the fishery supply chain, as negligence can result in food fraud. In this paper, we propose a private Ethereum blockchain-based solution that provides decentralized, transparent, traceable, secure, private, and trustworthy management for the fishery supply chain.
Article
Computer Science, Information Systems
Syada Tasmia Alvi, Mohammed Nasir Uddin, Linta Islam, Sajib Ahamed
Summary: Voting is a fundamental democratic activity, with paper balloting prone to errors and abuse. Digital voting methods, utilizing blockchain technology, aim to ensure anonymity, privacy, verifiability, integrity, security, and fairness in the voting process, with smart contracts on platforms like Ethereum 2.0 providing a safe means for voter verification and protection against fraudulent activities.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
N. Sangeeta, Seung Yeob Nam
Summary: Closed-circuit television (CCTV) cameras and black boxes are crucial for ensuring road safety and managing accidents. Visible highway surveillance cameras can encourage safe driving behavior and deter traffic violations. However, there are concerns regarding the security and integrity of data collected by CCTV and black boxes. These issues can potentially be addressed through the use of blockchain technology.
Article
Management
Pedro Azevedo, Jorge Gomes, Mario Romao
Summary: In the global marketplace, supply chains often involve multiple countries, organizations, and complex processes. This complexity makes it challenging to ensure traceability, chain of custody, and transparency, thus affecting business competitiveness. This study proposes using Blockchain to ensure chain of custody and traceability, allowing organizations to demonstrate product provenance, integrity, and compliance. By connecting Supply Chain Actors and product identifications using digital certificates, a complete traceability solution can be achieved. The study includes the design of a Public Key Infrastructure (PKI) and the development of an Ethereum Smart Contract for certificate authentication, providing decentralized and trustful assurance of provenance, chain of custody, and traceability in supply chains.
OPERATIONS MANAGEMENT RESEARCH
(2023)
Article
Agronomy
Showkat Ahmad Bhat, Nen-Fu Huang, Ishfaq Bashir Sofi, Muhammad Sultan
Summary: Modern-day agriculture supply chains have evolved into a global interconnected system, and the application of blockchain and IoT technologies can improve transparency and security, addressing issues in the agriculture supply chain.
Article
Computer Science, Information Systems
Senay A. A. Gebreab, Haya R. R. Hasan, Khaled Salah, Raja Jayaraman
Summary: Healthcare supply chains face challenges related to information integrity, traceability, and transparency of medical devices. This paper proposes a blockchain-based solution using non-fungible tokens and smart contracts to achieve reliable and efficient medical device traceability and ownership management.
Article
Computer Science, Theory & Methods
Subashini Babu, Hemavathi Devarajan
Summary: This study develops a monitoring system using blockchain technology to improve the transparency and trustworthiness of traceability data in the supply network of Non-Perishable (NP) agro goods. By utilizing the properties of blockchain technology, the system establishes a storage structure in both blockchain and IPFS for efficient information inquiry and addresses the issue of blockchain storage explosion. The findings demonstrate that the system enhances security, safeguards supply chain data, and improves throughput efficiency while reducing latency.
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2023)
Article
Food Science & Technology
Evripidis P. P. Kechagias, Sotiris P. P. Gayialis, Georgios A. A. Papadopoulos, Georgios Papoutsis
Summary: In today's era, technological revolutions have greatly impacted and will continue to change business operations. The complexity of supply chain processes has also grown with the evolution of technology. Ensuring traceability in the food industry is crucial for safety and compliance. Blockchain technology has gained attention as a potential solution to improve traceability, and this paper presents the development of a distributed application for table olives' traceability using Ethereum. The application significantly enhances product traceability, reducing time and improving data accuracy, supply chain efficiency, and compliance with international standards.
Article
Computer Science, Artificial Intelligence
Bello Musa Yakubu, Rabia Latif, Aisha Yakubu, Majid Iqbal Khan, Auwal Ibrahim Magashi
Summary: The increasing concerns about rice product safety and traceability have led to the exploration of blockchain technology in the food supply chain. This paper proposes a framework based on smart contracts that can track and monitor interactions and transactions among stakeholders in the rice supply chain, providing up-to-date information for informed decision-making.
PEERJ COMPUTER SCIENCE
(2022)
Article
Statistics & Probability
Denis A. Pustokhin, Irina V. Pustokhina, Phuoc Nguyen Dinh, Son Van Phan, Gia Nhu Nguyen, Gyanendra Prasad Joshi, K. Shankar
Summary: This paper presents a new RCAL-BiLSTM model based on ResNet and Class Attention Layer for COVID-19 diagnosis. The model incorporates bilateral filtering preprocessing, feature extraction using ResNet and Bi-LSTM, and softmax-based classification. Experimental results on the Chest-X-Ray dataset demonstrate the superior performance of the RCAL-BiLSTM model.
JOURNAL OF APPLIED STATISTICS
(2023)
Article
Computer Science, Information Systems
Romany F. Mansour, S. Abdel-Khalek, Ines Hilali-Jaghdam, Jamel Nebhen, Woong Cho, Gyanendra Prasad Joshi
Summary: This paper designs an intelligent outlier detection with machine learning empowered big data analytics (IODML-BDA) model for mobile edge computing (MEC). The model utilizes adaptive synthetic sampling-based outlier detection techniques and oppositional swallow swarm optimization-based feature selection techniques. Experimental analysis on various datasets confirms the higher accuracy of the proposed model.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Hardware & Architecture
R. Bhaskaran, P. S. Sujith Kumar, G. Shanthi, L. Raja, Gyanendra Prasad Joshi, Woong Cho
Summary: This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization (IM-EECNL) approach for real-time wireless networks. The proposed approach involves node localization and clustering to improve network performance and achieve high energy efficiency.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Article
Computer Science, Hardware & Architecture
M. Iyyappan, Arvind Kumar, Sultan Ahmad, Sudan Jha, Bader Alouffi, Abdullah Alharbi
Summary: This paper discusses the measurements of coupling and cohesion in component-based software engineering and proposes a framework for selecting suitable components using the Hexa-oval optimization algorithm. The study shows that high cohesion and low coupling contribute to better software design quality, increased reliability, and reduced system complexity.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2023)
Retraction
Computer Science, Artificial Intelligence
Sudan Jha, Eunmok Yang, Alaa Omran Almagrabi, Ali Kashif Bashir, Gyanendra Prasad Joshi
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Chemistry, Analytical
Shippu Sachdeva, Simarpreet Kaur, Romisha Arora, Manoj Sindhwani, Krishan Arora, Woong Cho, Gyanendra Prasad Joshi, Ill Chul Doo
Summary: This paper presents a 4.8 Tbps ultra-high capacity optical satellite communication system using polarization division multiplexing and twisted light beams. The system incorporates Laguerre Gaussian transverse mode profiles for OAM multiplexing and investigates the effects of receiver's digital signal processing module. The experimental results demonstrate the successful performance of the proposed system over a distance of 22,000 km, with the fundamental mode LG00 showing excellent performance.
Article
Green & Sustainable Science & Technology
Thavavel Vaiyapuri, Sharath Kumar Jagannathan, Mohammed Altaf Ahmed, K. C. Ramya, Gyanendra Prasad Joshi, Soojeong Lee, Gangseong Lee
Summary: The COVID-19 outbreak has caused psychological problems and led to public expression of sentiments on social networking platforms. This study presents a Marine Predator Optimization with Natural Language Processing model for sentiment analysis of Twitter data during the pandemic. The model utilizes data preprocessing, word vectors from the BERT model, and a bidirectional recurrent neural network for sentiment detection and classification, improving classification performance.
Editorial Material
Chemistry, Multidisciplinary
Bhanu Shrestha, Seongsoo Cho, Changho Seo
APPLIED SCIENCES-BASEL
(2023)
Correction
Computer Science, Information Systems
Seongsoo Cho, Bhanu Shrestha, Bashir Salah, Inam Ullah, Nermin M. Salem
Article
Medicine, General & Internal
Soojeong Lee, Gyanendra Prasad Joshi, Chang-Hwan Son, Gangseong Lee
Summary: Noninvasive blood pressure estimation is crucial for cardiovascular and hypertension patients. This paper proposes a new methodology that combines the Gaussian process with hybrid optimal feature decision (HOFD) in cuffless blood pressure estimation. The experimental results show that the proposed algorithm is very effective, with lower root mean square errors (RMSEs) for SBP and DBP compared to conventional algorithms.
Article
Mathematics
Bhargav Bhatt, Himanshu Sharma, Krishan Arora, Gyanendra Prasad Joshi, Bhanu Shrestha
Summary: Optimization is a broad field where researchers develop new algorithms to solve various problems. Grey wolf optimization is an efficient and easy-to-use algorithm, but it has drawbacks such as being stuck in local optima and having poor exploration. This paper discusses strategies to overcome these drawbacks and proposes a novel algorithm to improve the convergence rate and exploration capability.
Article
Engineering, Environmental
S. Jayakumar, S. Sudarsan, B. Sridhar, E. Parthiban, A. V. Prabhu, Sudan Jha
Summary: The adsorption of Cr6+ and Pb2+ ions in contaminated solution using a ternary blend made up of Chitosan, Nylon 6, and Polyurethane foam (CS/Ny 6/PUF) with a ratio of 2:1:1 was investigated. The blends were used as adsorbents due to their insolubility in acidic and basic mediums. The maximum adsorption of metal ions was achieved at pH 5 and followed the Freundlich model. The adsorption kinetics showed a pseudo-second-order reaction for chromium and a pseudo-first-order reaction for lead.
Article
Chemistry, Analytical
Srinivasagam Solaiappan, Bharathi Ramesh Kumar, N. Anbazhagan, Yooseung Song, Gyanendra Prasad Joshi, Woong Cho
Summary: The real-time vehicular traffic system is an essential part of the urban vehicular traffic system, providing effective traffic signal control for a complex traffic network. Coordinating vehicular traffic allows for parallel vehicle movements without accidents. This study examines vehicular traffic flow and proposes an algorithm to estimate vehicle waiting time. The effectiveness of the proposed system is verified by comparing it with a real-time vehicular traffic system experimentally and numerically.
Article
Computer Science, Information Systems
Dipen Saini, Rahul Malik, Rachit Garg, Mohammad Khalid Imam Rahmani, Md. Ezaz Ahmed, Deepak Prashar, Sudan Jha, Jabeen Nazeer, Sultan Ahmad
Summary: This study proposes a novel multimodal hybrid bioinspired model for hyperspectral image augmentation, which continuously improves classification performance through iterative learning. The model represents input images in various domains and extracts windowed feature sets via a convolutional filter. It selects high inter-class variance features and reduces intra-class variance levels for improved classification performance. The model intelligently augments the selected images and classifies them using a customized CNN classifier. Through combining these models and incremental accuracy optimizations, the proposed model improves hyperspectral classification accuracy by 10.6% and precision by 10.4% compared to standard deep learning-based augmentation techniques.