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Blockchain based emanative unassailable system: Use cases and repercussions /
International Journal of Recent Technology And Engineering, Vol.7, Issue 6S5, pp.540-543, ISSN No: 2277-3878. -
Blockchain enabled energy efficient red deer algorithm based clustering protocol for pervasive wireless sensor networks
Energy efficiency and security are considered as important issues in the design of pervasive wireless networks. Since the nodes in pervasive wireless networks are battery-operated, it becomes essential to develop an energy-efficient method to minimize energy consumption and prolong the network lifetime. This paper presents new energy-efficient and secure clustering based data transmission in pervasive wireless networks using red deer algorithm (RDA) based clustering technique with blockchain enabled secured data transmission, named as RDAC-BC. The proposed RDAC-BC technique undergoes node initialization and performs the clustering process using the RDAC technique. The clustering technique performs cluster head (CH) selection and cluster construction process is carried out. Once the CHs are chosen, blockchain enabled secure data transmission takes place among cluster members (CMs) as well as CHs. The application of RDAC and blockchain technology helps to achieve energy efficiency and security. The experimental validation of the RDAC-BC technique is assessed under several aspects and the results are compared with existing methods. The obtained results ensured that the RDAC-BC technique has shown superior results interms of energy, network lifetime, packet delivery ratio (PDR), and throughput. 2020 Elsevier Inc. -
Blockchain for customer transparency in e-commerce a survival of fittest not fastest
Blockchain has been envisioned as the most disruptive technology in the landscape of ecommerce. There has been an array of challenges for e-commerce retailers to handle like transparency, immutability, reliability and disintermediation. The paper is an attempt to understand consumer acceptance towards new technology where the primary focus would be transparency and plans for human salvation by combating the environment and ethical challenges. The study emphasises the prospective use of blockchain technology in ecommerce industry which has been coupled with the vagueness of these issues. Unified theory of acceptance and use of technology (UTAUT) has been used as the base model to understand the consumer behaviour towards using blockchain technology as a new platform with special reference to fashion apparel sector. Providing traceability of product with an objective of consumer transparency in this mould will change the way of doing online shopping and will have more onus on retailers. Copyright 2023 Inderscience Enterprises Ltd. -
Blockchain for Securing Healthcare Data Using Squirrel Search Optimization Algorithm
The Healthcare system is an organization that consists of important requirements corresponding to security and privacy, for example, protecting patients medical information from unauthorized access, communication with transport like ambulance and smart e-health monitoring. Due to lack of expert design of security protocols, the healthcare system is facing many security threats such as authenticity, data sharing, the conveying of medical data. In such situa-tion, block chain protocol is used. In this manuscript, Efficient Block chain Network for securing Healthcare data using Multi-Objective Squirrel Search Optimization Algorithm (MOSSA) is proposed to generate smart and secure Healthcare system. In this the block chain is a decentralized and the distributed ledger device that consists of various blocks linked with digital signature schemes, consensus mechanisms and chain of hashing, offers highly reliable storage capabilities. Further the block chain parameters, such as block size, transac-tion size and number of block chain channels are optimized with the help of MOSSA. With the evolution of the MOSSA provide new features for enhancing security and scalability. The simulation process is executed in the JAVA platform. The experimental result of the proposed method shows higher throughput of 26.87%, higher efficiency of 34.67%, lowest delay of 22.97%, lesser computational overhead of 37.03%, higher storage cost of 34.29% when compared to the existing method such as Block chain-ECIES-HSO, Block chain-hybrid GO-FFO, Block chain-SDN-HSO algorithm for healthcare technologies. 2022, Tech Science Press. All rights reserved. -
Blockchain Technology in the Fashion Industry: Virtual Propinquity to Business
The concept of fashion has been coupled with technology, where technology has become the protagonist. The transparency between an organization and a customer works as a catalyst, and the customer has taken a more mainstream role. With blockchain technology, companies can reconnect with customers and customers can track the journey of a product from its raw materials to the finished goods. The primary focus of the study is on services and data collected from the following sectors, namely fashion, apparel, and online platforms. The authors main goals are (1) to illustrate an overview of how big data is transforming the service industry, especially the fashion and design sector, and (2) to present various mechanisms adopted in the service industry. The study aims to investigate a model that fits through EXT-TAM and uses additional attributes of blockchain technology with a special reference to fashion apparel. The findings of this study depict a model, where PEOU, PU, and attitude are the major constructs and present a win-win scenario for both the customer and the organization. 2022 Authors. All rights reserved. -
Blockchain with deep learning-enabled secure healthcare data transmission and diagnostic model
At these times, internet of things (IoT) technologies have become ubiquitous in the healthcare sector. Because of the increasing needs of IoT, massive quantity of patient data is being gathered and is utilized for diagnostic purposes. The recent developments of artificial intelligence (AI) and deep learning (DL) models are commonly employed to accurately identify the diseases in real-time scenarios. Despite the benefits, security, energy constraining, insufficient training data are the major issues which need to be resolved in the IoT enabled medical field. To accomplish the security, blockchain technology is recently developed which is a decentralized architecture that is widely utilized. With this motivation, this paper introduces a new blockchain with DL enabled secure medical data transmission and diagnosis (BDL-SMDTD) model. The goal of the BDL-SMDTD model is to securely transmit the medical images and diagnose the disease with maximum detection rate. The BDL-SMDTD model incorporates different stages of operations such as image acquisition, encryption, blockchain, and diagnostic process. Primarily, moth flame optimization (MFO) with elliptic curve cryptography (ECC), called MFO-ECC technique is used for the image encryption process where the optimal keys of ECC are generated using MFO algorithm. Besides, blockchain technology is utilized to store the encrypted images. Then, the diagnostic process involves histogram-based segmentation, Inception with ResNet-v2-based feature extraction, and support vector machine (SVM)-based classification. The experimental performance of the presented BDL-SMDTD technique has been validated using benchmark medical images and the resultant values highlighted the improved performance of the BDL-SMDTD technique. The proposed BDL-SMDTD model accomplished maximum classification performance with sensitivity of 96.94%, specificity of 98.36%, and accuracy of 95.29%, whereas the feature extraction is performed based on ResNet-v2 World Scientific Publishing Company. -
Blockchain-based circular economy for achieving environmental sustainability in the Indian electronic MSMEs
Purpose: The circular economy is a production and consumption model that encourages people to share, lease, reuse, repair, refurbish and recycle existing materials and products for as long as possible. The blockchain-based circular economy is being used in many industries worldwide, but Indian electronic MSMEs face many problems in adopting a blockchain-based circular economy. The research aims to discover the barriers the electronic MSMEs face in adopting a blockchain-based circular economy and pull back from achieving environmental sustainability in their operations. Design/methodology/approach: Fifteen barriers are identified from the literature review and finalized with experts' opinions. These barriers are evaluated by using interpretive structural modeling (ISM), MICMAC analysis and fuzzy TOPSIS method. Findings: Lack of support from distribution channels, lack of traceability mechanism and customer attitudes toward purchasing remanufactured goods are identified as the most critical barriers. Practical implications: The study will benchmark the electronic MSMEs in achieving environmental sustainability in the blockchain-based circular economy. Originality/value: It is a study that not only establishes a hierarchical relationship among the barriers of blockchain adoption in Indian electronic MSMEs but also verifies the results with fuzzy TOPSIS method. 2022, Emerald Publishing Limited. -
Blockchain-Based Service Oriented Privacy-Preserving Data Sharing over Distributed Data Streams in Asynchronous Environment
Innovative city applications use information and communication technologies to function various operations efficiently. The widespread use of the Internet of Things (IoT) can be viewed in several applications like smart cars, smart cities, e-commerce, and cyber-physical systems. The huge amount of data produced and transmitted by these systems is handled by cloud-based storage services, which are vulnerable to multiple threats risking the privacy and security features of the application. Cloud storage services employ encryption algorithms to ensure data confidentiality, but it fails to address the privacy issues. Apart from the privacy risks, in these systems, the identity of a user who shares and accesses the data is traceable, as it is required to verify user eligibility before providing access. Also, a vast amount of daily data is stored on a centralized system that processes service requests from multiple users, posing considerable risks to the system's stability during peak periods. To address these challenges faced during the data sharing process in a centralized system, Service Oriented Privacy-Preserving Data Sharing (SOPPDS) platform based on a blockchain framework is proposed. The modified Key Policy-Attribute-based Encryption (MKP-ABE) technique is applied to securely share the data between the service owners and the service consumers. It was evident from the performance evaluation of the proposed SOPPDS platform that the encryption process takes lesser time than the decryption process. Also, the cryptographic operations performed on the prime order sets exhibited increased latency and computational cost. It was observed that comparatively, cryptographic operations performed on composite order sets could overcome the issues in prime order sets. SOPPDS platform works well in preserving the users' privacy, ensuring anonymity in the data sharing process, and maintaining the confidentiality of the data shared in the system. 2023, Ismail Saritas. All rights reserved. -
Blocking intrusion logic using optimized multi-head convolution in wireless sensor network
Wireless sensor nodes (WSN) combine sensing and communication capabilities in the smallest sensor network component. Sensor nodes have basic networking capabilities, such as wireless connection with other nodes, data storage, and a microcontroller to do basic processing. The intrusion detection problem is well analyzed and there exist numerous techniques to solve this issue but suffer will poor intrusion detection accuracy and a higher false alarm ratio. To overcome this challenge, a novel Intrusion Detection via Salp Swarm Optimization based Deep Learning Algorithm (ID-SODA) has been proposed which classifies intrusion node and non-intrusion node. The proposed ID-SODA technique uses the k-means clustering algorithm to perform clustering. The Salp Swarm Optimization (SSO) technique takes into residual energy, distance, and cost while choosing the cluster head selection (CHS). The CHS is given the input to a multi-head convolutional neural network (MHCNN), which will classify into intrusion node and non-intrusion node. The performance analysis of the suggested ID-SODA is evaluated based on the parameters like accuracy, precision, F1 score, detection rate, recall, false alarm rate, and false negative rate. The suggested ID-SODA achieves an accuracy range of 98.95%. The result shows that the suggested ID-SODA improves the overall accuracy better than 6.56%, 2.94%, and 2.95% in SMOTE, SLGBM, and GWOSVM-IDS respectively. 2023 - IOS Press. All rights reserved. -
Blowing Your Own Trumpet: How to Increase the Online Visibility of Your Publication?
After seeing ones manuscript in the print form in a journal, the author feels a sense of elation which is indescribable. However, if one really want peers and other researchers to take note of the work, some more effort is needed. With the massive increase in the number of biomedical journals in print supplemented by another large chunk onlinequite a few published papers remain unread by majority of the readers. The availability of social sites, persistent identifiers, and manuscript-sharing sites has simplified the job of increasing the impact of an article. We herein share some of these tricks-of-the-trade. 2018, Indian Academy of Pediatrics. -
Blue ocean marketing- A promising strategy /
Vol. 7 No. 1 (2013) ISSN: 2278-5612 -
Bob Dylan: Poet of disruption, dissonance and an aesthetic of dissent
This paper is a brief study of the pivotal figure of folk rock, Bob Dylan. Acclaimed as a songwriter and singer, he was also the poetic voice of the counter culture of the nineteen sixties in America. The counter culture sought to unseat the mainstream establishment that seemed obsessed with war, conservative ideals and religious nationalism. Dylan burst onto this scene 'already a legend' and 'the unwashed phenomenon' (Baez, 1975) projecting the image of the original vagabond and troubadour. A glance at a selection of some of his best known lyrics disabuses one of the notions of his being uninitiated into the discourse of philosophy and literature. He draws freely on and engages with ideas from texts that are sometimes even obscure. The Nobel he was awarded in October 2016 recognized his art for evolving new modes of poetic expression. This paper studies Dylan, the performer and the writer who has masterfully disrupted most accepted literary modes using the dissonance-rich space of Rock music while retaining some of the traditional forms of poetic utterance. AesthetixMS 2016. -
Body image issues and self-concept dilemmas in adolescents living with thalassemia
Thalassemia, a genetic blood disorder, involves an inability to produce sufficient hemoglobin and comprises two types: alpha thalassemia and beta thalassemia. Beta thalassemias immediate treatment measures include frequent blood transmissions, stem cell and bone marrow transplants; all capable of altering an individuals idea of body image, self-concept, growth, and socialization, resulting in several emotional, psychological, and behavioral concerns. This study aimed at comprehending the dilemmas of body image and self-concept encountered by adolescents with thalassemia, particularly the resulting influence on physical development and socialization. Using the phenomenological interpretivism approach of qualitative research, data was collected using purposive-convenient sampling from 11 adolescents, both boys and girls ranging from ages 12 to 18, living with thalassemia and undergoing treatment. The research highlights adolescent concerns with body image, specifically with complexion, facial features, being either underweight or overweight, all amalgamating into a self-concept dilemma. Moreover, results point to the significant influence of experiences with family, peers, educational institutions, and hospital staff. Therapeutic attention, through regular screening and counselling, should be provided to adolescent thalassemia patients to address the psychological aspects of the chronic illness. 2021 Informa UK Limited, trading as Taylor & Francis Group. -
Bombay High Court (re)assures that copyright registration is not required to remedy infringement
Sanjay Soya Private Limited v. Narayani Trading Company, Interim Application (L) No. 5011 of 2020 and Commercial IP Suit No. 2 of 2021, High Court of Bombay, Maharashtra, judgment of 9 March 2021, by Mr. Justice G.S. Patel The Bombay High Court, in the case of Sanjay Soya Private Limited v. Narayani Trading Company, held that copyright registration is not a prerequisite to claiming relief in copyright infringement cases. The judgment clarifies the dubiety created previously by a contrary judicial opinion and aligns the Indian position with international copyright principles. 2021 The Author(s) 2021. Published by Oxford University Press. All rights reserved. -
Boosting enabled efficient machine learning technique for accurate prediction of crop yield towards precision agriculture
Due to the limited availability of natural resources, it is essential that agricultural productivity keep pace with population growth. Despite unfavorable weather circumstances, this project's major objective is to boost production. As a consequence of technological advancements in agriculture, precision farming as a way for enhancing crop yields is gaining appeal and becoming more prevalent. When it comes to predicting future data, machine learning employs a number of methods, including the creation of models and the acquisition of prediction rules based on past data. In this manuscript, we examine various techniques to machine learning, as well as an automated agricultural yield projection model based on selecting the most relevant features. For the purpose of selecting features, the Grey Level Co-occurrence Matrix method is utilised. For classification, we make use of the AdaBoost Decision Tree, Artificial Neural Network (ANN), and K-Nearest Neighbour (KNN) algorithms. The data set that was used in this study is simply a compilation of information about a variety of topics, including yield, pesticide use, rainfall, and average temperature. This data collection consists of 33 characteristics or qualities in total. The crops soya beans, maze, potato, rice, paddy, wheat, and sorghum are included in this data collection. This data collection was made possible through the collaboration of the Food and Agriculture Organisation (FAO) and the World Data Bank, both of which make their data available to the public. The AdaBoost decision tree has achieved the highest level of accuracy possible when used to anticipate agricultural yield. Both the accuracy rate and the recall rate are quite high at 99 percent. The Author(s) 2024. -
Boosting productive capacity in OECD countries: Unveiling the roles of geopolitical risk and globalization
This study examines the intertwined effects of geopolitical risk and globalization on productive capacity (the measure of economic cycles) in 20 Organisation for Economic Cooperation and Development (OECD) countries from 2000 to 2021. The panel threshold regression and Driscoll-Kraay standard error estimations highlight the positive impact of globalization on productive capacity. Still, they are underscored by the negative effect of geopolitical risk. The study also unveils a synergistic relationship, demonstrating that the combined influence of globalization and geopolitical risk can amplify productive capacity under specific conditions. Government effectiveness and innovation have positive effects on productive capacities. These findings underscore the need for balanced policies that leverage global economic integration while ensuring geopolitical stability, and offering nuanced insights to guide strategic decision-making for sustained economic cycles. 2024 Elsevier Inc. -
Boosting Surface Coverage of CO Intermediates through Multimetallic Interface Interactions for Efficient CO2 Electrochemical Reduction
Given the inherent challenges of the CO2 electroreduction (CO2ER) reaction, solely from CO2 and H2O, it is desirable to develop selective product formation pathways. This can be achieved by designing multimetallic nanocomposites that provide optimal CO coverage, allowing for tunability in the product formation. In this work, Ag and Zn codoped-SrTiO3 (ZAST) composite immobilized carbon black (CB)-modified GCE working electrode (ZAST@CB/GCE) was developed for the electrochemical conversion of CO2 to multicarbon products. The complete reaction was carried out in a CO2-saturated aqueous system of 0.5 M KHCO3 electrolyte. A potential-dependent product selectivity was suggested based on the NMR results, wherein raising the potential value enhanced the formation of liquid products such as acetone and alcohols while suppressing competitive HER. The total Faradaic efficiency for liquid products reached an impressive 97% at a potential of ?0.6 V vs. RHE. This represents a significant advancement in acetone production pathways and valorization of CO2ER technology. 2025 American Chemical Society. -
Border Collie Optimization
In recent times, several metaheuristic algorithms have been proposed for solving real world optimization problems. In this paper, a new metaheuristic algorithm, called the Border Collie Optimization is introduced. The algorithm is developed by mimicking the sheep herding styles of Border Collie dogs. The Border Collie's unique herding style from the front as well as from the sides is adopted successfully in this paper. In this algorithm, the entire population is divided into two parts viz., dogs and sheep. This is done to equally focus on both exploration and exploitation of the search space. The Border Collie utilizes a predatory move called eyeing. This technique of the dogs is utilized to prevent the algorithm from getting stuck into local optima. A sensitivity analysis of the proposed algorithm has been carried out using the Sobol's sensitivity indices with the Sobol g-function for tuning of parameters. The proposed algorithm is applied on thirty-five benchmark functions. The proposed algorithm provides very competitive results, when compared with seven state-of-the-art algorithms like Ant Colony optimization, Differential algorithm, Genetic algorithm, Grey-wolf optimizer, Harris Hawk optimization, Particle Swarm optimization and Whale optimization algorithm. The performance of the proposed algorithm is analytically and visually tested by different methods to judge its supremacy. Finally, the statistical significance of the proposed algorithm is established by comparing it with other algorithms by employing Kruskal-Wallis test and Friedman test. 2013 IEEE. -
Border Region Railway Development in Sino- Indian Geopolitical Competition
India and China share about 3,488 km long International Boundary, which has three sectors: Western, Middle and Eastern. The Eastern sector comprises two Northeastern states, that is, Arunachal Pradesh measuring 1,124 kms and Sikkim measuring 219 kms, respectively. Due to recent changes in the geopolitical relationship with China, border management and transport infrastructure development have occupied centre stage. In recent years, the Government of India has taken initiatives to develop railway infrastructure in Northeast India. The study will focus on the role of railway transportation in Sino-Indian geopolitical competition. The study is based on secondary data collected from the office of General Manager, Northeast Frontier Railway, the Census of India and reports of Memorandums of Understanding between India and China. The study reveals that railway infrastructure along the border creates geo-psychological pressures on both countries, influencing the divergent geopolitical relationship between India and China. Railway diplomacy is a tool kit of critical geopolitics which reveals the contours of geopolitical competition in borderlands. 2023 Indian Council of World Affairs(ICWA). -
Bougainvillea glabra-mediated synthesis of Zr?O and chitosan-coated zirconium oxide nanoparticles: Multifunctional antibacterial and anticancer agents with enhanced biocompatibility
The effectiveness and safety of nanomaterials (NMs) are essential for their use in healthcare. This study focuses on creating NPs with multifunctional antibacterial and anticancer properties to combat bacterial infections and cancer disease more effectively than traditional antibiotics. This study investigates the synthesis of Zr3O and chitosan (ch) coated zirconium oxide nanoparticles (chZrO NPs) using Bougainvillea glabra (B. glabra) plant extract through a green, one-pot precipitation method. The synthesized NPs were analyzed using various techniques. Their antibacterial properties are attributed to the production of reactive oxygen species (ROS), influenced by their size, large surface area, oxygen vacancies, ion release, and diffusion capabilities. The chZrO NPs showed superior antibacterial activity compared to Zr3O and chitosan alone, with effective inhibition against both Gram-positive bacteria (S. aureus and B. subtilis) and Gram-negative bacteria (E. coli and P. aeruginosa). Additionally, anticancer studies of chZrO NPs demonstrated significant activity against colon cancer HCT116 cells with C50 values of 4.98 ?g/mL compared to chitosan and Zr3O with 9.62, 6.69 ?g/mL, while biocompatibility tests on L929 cells confirmed their safety showing 93 % cell viability compared to ch and Zr3O. These findings suggest that chZrO NPs are promising candidates for future use in clinical and healthcare applications. 2025 Elsevier B.V.