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  • Security and Privacy in 5G Internet of Vehicles (IoV) Environment
  • Abstract Modern vehicles are equipped with sensors, communication, and computation units that make them capable of providing monitoring services and analysis of real-time traffic information to improve road safety. The main aim of communication in vehicular networks is to achieve an autonomous driving environment that is accident-free alongside increasing road use quality. However, the demanding specifications such as high data rate, low latency, and high reliability in vehicular networks make 5G an emerging solution for addressing the current vehicular network challenges. In the 5G IoV environment, various technologies and models are deployed, making the environment open to attacks such as Sybil,…
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  • Fusion of Internal Similarity to Improve the Accuracy of Recommendation Algorithm
  • Abstract Collaborative filtering algorithms (CF) and mass diffusion (MD) algorithms have been successfully applied to recommender systems for years and can solve the problem of information overload. However, both algorithms suffer from data sparsity, and both tend to recommend popular products, which have poor diversity and are not suitable for real life. In this paper, we propose a user internal similarity-based recommendation algorithm (UISRC). UISRC first calculates the item-item similarity matrix and calculates the average similarity between items purchased by each user as the user’s internal similarity. The internal similarity of users is combined to modify the recommendation score to make…
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  • Development of a Module for Measuring Electrical Variables in Power Transformers Based in IoT, to Manage and Monitoring by Telemetry Mechanism
  • Abstract This work shows the development of a module that performs measurements of electrical variables in a low voltage power transformer. These variables are sent by means of the IEEE802.11 standard, connecting to a database stored in the cloud; associating with the meter IoT concepts, this to allow a client to perform an analysis, monitoring and management of their electrical network. For the construction of this module, non-invasive current sensors connected to a three-phase meter are used and a communication card is used that allows data to be extracted from the meter and sent to the cloud database. This module, to…
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  • Multi-Classification Network for Identifying COVID-19 Cases Using Deep Convolutional Neural Networks
  • Abstract The novel coronavirus 2019 (COVID-19) rapidly spreading around the world and turns into a pandemic situation, consequently, detecting the coronavirus (COVID-19) affected patients are now the most critical task for medical specialists. The deficiency of medical testing kits leading to huge complexity in detecting COVID-19 patients worldwide, resulting in the number of infected cases is expanding. Therefore, a significant study is necessary about detecting COVID-19 patients using an automated diagnosis method, which hinders the spreading of coronavirus. In this paper, the study suggests a Deep Convolutional Neural Network-based multi-classification framework (COVMCNet) using eight different pre-trained architectures such as VGG16, VGG19,…
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  • A Novel Integrated Machine & Business Intelligence Framework for Sensor Data Analysis
  • Abstract Increased smart devices in various industries are creating numerous sensors in each of the equipment prompting the need for methods and models for sensor data. Current research proposes a systematic approach to analyze the data generated from sensors attached to industrial equipment. The methodology involves data cleaning, preprocessing, basics statistics, outlier, and anomaly detection. Present study presents the prediction of RUL by using various Machine Learning models like Regression, Polynomial Regression, Random Forest, Decision Tree, XG Boost. Hyper Parameter Optimization is performed to find the optimal parameters for each variable. In each of the model for RUL prediction RMSE, MAE…
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  • Review of Internet of Things in Different Sectors: Recent Advances, Technologies, and Challenges
  • Abstract Human beings and their activities are now connected through Internet of Things (IoT) with the evolution of wireless communication technologies. IoT is becoming popular and its usage is immensely increasing among various sectors. In this research paper, a comprehensive review has been conducted by considering recent and important literature review on IoT applications being operated in three major sectors. The three sectors studied are health, sports and transportation and logistics. Paper explored that with the help of IoT techniques, different miniature sized devices are invented which can record various parameters of human body, wearables devices have been invented which are…
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  • An Overview of the Miniaturization and Endurance for Wearable Devices
  • Abstract The miniaturization and endurance of wearable devices have been the research direction for a long time. With the development of nanotechnology and the emergence of microelectronics products, people have explored many new strategies that may be applied to wearable devices. In this overview, we will summarize the recent research of wearable devices in these two directions, and summarize some available related technologies.
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  • Study on Optimization of Urban Rail Train Operation Control Curve Based on Improved Multi-Objective Genetic Algorithm
  • Abstract A multi-objective improved genetic algorithm is constructed to solve the train operation simulation model of urban rail train and find the optimal operation curve. In the train control system, the conversion point of operating mode is the basic of gene encoding and the chromosome composed of multiple genes represents a control scheme, and the initial population can be formed by the way. The fitness function can be designed by the design requirements of the train control stop error, time error and energy consumption. the effectiveness of new individual can be ensured by checking the validity of the original individual when…
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  • An Optimization Scheme for Task Offloading and Resource Allocation in Vehicle Edge Networks
  • Abstract The vehicle edge network (VEN) has become a new research hotspot in the Internet of Things (IOT). However, many new delays are generated during the vehicle offloading the task to the edge server, which will greatly reduce the quality of service (QOS) provided by the vehicle edge network. To solve this problem, this paper proposes an evolutionary algorithm-based (EA) task offloading and resource allocation scheme. First, the delay of offloading task to the edge server is generally defined, then the mathematical model of problem is given. Finally, the objective function is optimized by evolutionary algorithm, and the optimal solution is…
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  • KNEMAG: Key Node Estimation Mechanism Based on Attack Graph for IoT Security
  • Abstract With the rapid development and widespread application of the IoT, the at-tacks against IoT vulnerabilities have become more complex and diverse. Most of the previous research focused on node vulnerability and its risk analysis. There is little information available about the importance of the location of the node in the system. Therefore, an estimation mechanism is proposed to assess the key node of the IoT system. The estimation of the key node includes two parts: one is the utilization relationship between nodes, and the other is the impact on the system after the node is conquered. We use the node…
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  •   Views:764       Downloads:466        Download PDF
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