There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it...
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There are an increasing number of Narrow Band IoT devices being manufactured as the technology behind them develops *** high co‐channel interference and signal attenuation seen in edge Narrow Band IoT devices make it challenging to guarantee the service quality of these *** maximise the data rate fairness of Narrow Band IoT devices,a multi‐dimensional indoor localisation model is devised,consisting of transmission power,data scheduling,and time slot scheduling,based on a network model that employs non‐orthogonal multiple access via a *** on this network model,the optimisation goal of Narrow Band IoT device data rate ratio fairness is first established by the authors,while taking into account the Narrow Band IoT network:The multidimensional indoor localisation optimisation model of equipment tends to minimize data rate,energy constraints and EH relay energy and data buffer constraints,data scheduling and time slot *** a result,each Narrow Band IoT device's data rate needs are met while the network's overall performance is *** investigate the model's potential for convex optimisation and offer an algorithm for optimising the distribution of multiple resources using the KKT *** current work primarily considers the NOMA Narrow Band IoT network under a single EH ***,the growth of Narrow Band IoT devices also leads to a rise in co‐channel interference,which impacts NOMA's performance *** simulation,the proposed approach is successfully *** improvements have boosted the network's energy efficiency by 44.1%,data rate proportional fairness by 11.9%,and spectrum efficiency by 55.4%.
The Internet of Things (IoT) and Machine-to-Machine (M2M) communication have connected devices, enabling major advances in various fields. The priority now is secure and efficient management of these interconnected sy...
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ISBN:
(纸本)9798400709418
The Internet of Things (IoT) and Machine-to-Machine (M2M) communication have connected devices, enabling major advances in various fields. The priority now is secure and efficient management of these interconnected systems. IoT ecosystems need access control to manage interactions. Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), Policy-Based Access Control (PBAC), and Context-Based Access Control (CBAC) are examined in the context of Industrial IoT (IIoT) in this paper. Intelligent manufacturing and anticipatory maintenance are among the many opportunities created by IoT and IIoT rapid growth. However, these advances present new security and access control challenges. Access control is essential for managing user, device, and application authorization in complex, interconnected environments. Our goal is to analyze their suitability, pros, and cons in industrial settings where strict access control is needed to ensure system safety, confidentiality, and efficiency. The IIoT case study implementation of these access control mechanisms is the focus of this paper. We examine an IIoT scenario in which a manufacturing plant has a network of machinery, sensors, and control systems. The case study shows how RBAC, ABAC, PBAC, and CBAC apply pragmatically. We evaluate their ability to manage access to critical machinery, data, and devices. We analyze and compare these access control mechanisms within the IIoT framework to determine the best one for the industrial environment, taking into account scalability, security, real-time decision making, and industrial process complexity. This paper examines access control mechanisms and practical observations from a real-world IIoT case study to improve IIoT security discussions. The findings can help IIoT practitioners, researchers, and decision-makers choose access control solutions. Industrial operations can become safer and more efficient.
With the large-scale deployment and use of biometrics technology, the security threats of a biometric system are also increasing. The presentation attack (PA) is typical;an imposter spoofs legitimate users’ biometric...
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The human body is composed of cells, and each cell has a variety of components. Cancer is one of the most serious illnesses in the world and is a leading cause of India's death rate. Breast cancer is frequently di...
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Biomedical image processing is widely utilized for disease detection and classification of biomedical *** color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and ...
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Biomedical image processing is widely utilized for disease detection and classification of biomedical *** color image analysis is an effective and non-invasive tool for carrying out secondary detection at anytime and *** removing the qualitative aspect,tongue images are quantitatively inspected,proposing a novel disease classification model in an automated way is *** article introduces a novel political optimizer with deep learning enabled tongue color image analysis(PODL-TCIA)*** presented PODL-TCIA model purposes to detect the occurrence of the disease by examining the color of the *** attain this,the PODL-TCIA model initially performs image pre-processing to enhance medical image *** by,Inception with ResNet-v2 model is employed for feature ***,political optimizer(PO)with twin support vector machine(TSVM)model is exploited for image classification process,shows the novelty of the *** design of PO algorithm assists in the optimal parameter selection of the TSVM *** ensuring the enhanced outcomes of the PODL-TCIA model,a wide-ranging experimental analysis was applied and the outcomes reported the betterment of the PODL-TCIA model over the recent approaches.
Manpower shortage is a global phenomenon which causes much trouble, especially retailers. In retail stores, the labors are the major cost. Unmanned stores could reduce labors and it can also increase the profit of ret...
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This research proposes a system for detecting plagiarism in academic submissions. The system utilizes advanced text comparison algorithms to identify instances of plagiarism, ensuring academic integrity and promoting ...
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ISBN:
(数字)9798350377972
ISBN:
(纸本)9798350377989
This research proposes a system for detecting plagiarism in academic submissions. The system utilizes advanced text comparison algorithms to identify instances of plagiarism, ensuring academic integrity and promoting a culture of originality among students. By providing educators with a tool to efficiently detect plagiarism, this system aims to streamline the evaluation process and enhance the overall learning experience for students. This system has the potential to significantly reduce plagiarism incidents and foster a more ethical and productive academic environment.
Protein-protein interactions are of great significance for human to understand the functional mechanisms of *** the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)dat...
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Protein-protein interactions are of great significance for human to understand the functional mechanisms of *** the rapid development of high-throughput genomic technologies,massive protein-protein interaction(PPI)data have been generated,making it very difficult to analyze them *** address this problem,this paper presents a distributed framework by reimplementing one of state-of-the-art algorithms,i.e.,CoFex,using *** do so,an in-depth analysis of its limitations is conducted from the perspectives of efficiency and memory consumption when applying it for large-scale PPI data analysis and *** solutions are then devised to overcome these *** particular,we adopt a novel tree-based data structure to reduce the heavy memory consumption caused by the huge sequence information of *** that,its procedure is modified by following the MapReduce framework to take the prediction task distributively.A series of extensive experiments have been conducted to evaluate the performance of our framework in terms of both efficiency and *** results well demonstrate that the proposed framework can considerably improve its computational efficiency by more than two orders of magnitude while retaining the same high accuracy.
The health and social implications of pandemic epidemics are substantial. Accurate forecasting and management of such epidemics are of utmost importance to lessen the blow of such epidemics. To tackle this pressing pr...
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The self-driving cars have increased the need for better intelligent transportation systems. To facilitate the usage of these automated vehicles, very efficient real-time data monitoring in the network is required in ...
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