International Journal of Communication Networks and Information Security (IJCNIS)
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Realization of Vitality Optimization in Traditional Village Human Settlement Environment Supported by Intelligent Sensor Technology
Get PDFThe vitality of traditional villages (VTV) is a reference indicator for measuring the hollowing out of traditional villages. Human settlements in the world are based on the access and availability to the chief vitality factors of the geographical region. The traditional villages of China are the potential candidates for improving vitality optimization, as their development is still in the stage of infancy. This work proposes a framework that integrates complex subsystems of the traditional village human settlements with the vitality factors. The issues in these traditional villages are analyzed under the umbrella of social life, domestic life and agriculture, which is the primary occupation of people in traditional villages. Further, the work identifies the contemporary computing technologies and communication technologies used in various applications of intelligent sensor technology. This work associates the various subsystems of the villages, namely strategic, social, economic, resource and environment subsystem, and information subsystem, with the factors influencing dimensions of development, namely resources, service chain, sustainability, technology and institution. This framework can be further extended to include more elements of vitality factors
Analysis about the Influence of Sports Venues and Multi-event Sports in Improving the Community Perceptions throughGathering and Integration of People’s Opinion
Get PDFIn this study, we analyzed public perceptions of the National Games of China, focusing on sports event image, satisfaction, motivation, stadium atmosphere, and environmental impact. Data was collected from 715 individuals (average age 28.1) through a comprehensive questionnaire. The study revealed that the National Games were positively received, with entertainment being a major factor for attendance. The study revealed a strong link between individuals' participation in the event and their views on various aspects like the event's reputation, their own satisfaction, motivational factors, the ambiance of the stadium, and environmental considerations. It was also noted that people living closer to the stadiums perceived the National Games' societal impact more profoundly. Contrarily, no notable connection was observed between participants' gender and these aspects. These outcomes highlight the significant societal influence of major sports events like the National Games and emphasize the need for careful consideration of public opinion and environmental effects in organizing future events
Constructing a Multilingual E-Learning Ontology through Web Crawling and Scraping
Get PDFThe emergence of digital technologies has transformed the landscape of education, driving the exploration of innovative methods to improve the efficiency and effectiveness of university e- learning. This study focuses on leveraging network management principles in combination with web crawling trends to propose a novel approach: a web crawling and scraping-driven method for constructing a multilingual ontology tailored specifically for university e-learning. The primary goal of this research is to create a comprehensive and continuously updated knowledge repository by systematically gathering and extracting information from a wide range of online sources. By incorporating multilingual capabilities into the proposed ontology, the aim is to transcend language barriers and establish a globally accessible and inclusive e-learning environment. This approach recognizes the intricate relationship between technology and education, highlighting the potential of automated data retrieval and ontology construction in reshaping the future of university e-learning. This research contributes significantly to the rapidly growing field of educational technology by introducing a forward-thinking paradigm. It empowers both educators and learners with a versatile and personalized learning experience that transcends cultural and linguistic boundaries. As the digital era continues to evolve, this approach serves as a beacon of innovation, exemplifying the transformative power of integrating cutting-edge technology with pedagogical efforts. In essence, this study presents a groundbreaking approach to enhance university e- learning by harnessing the capabilities of web crawling, scraping, and multilingual ontology construction. It emphasizes the importance of adapting to the ever-evolving digital landscape to provide an inclusive and accessible education experience for learners worldwide. Ultimately, this research represents a significant step forward in the ongoing effort to revolutionize education through the integration of advanced technology and pedagogical innovation
Design and Performance Analysis of Low Latency Routing Algorithm based NoC for MPSoC
Get PDFThe Network on Chip is appropriate where System-on-Chip technology is scalable and adaptable. The Network on Chip is a new communication architecture with a number of benefits, including scalability, flexibility, and reusability, for applications built on Multiprocessor System on a Chip (MPSoC). However, the design of efficient NoC fabric with high performance is critically complex because of its architectural parameters. Identifying a suitable scheduling algorithm to resolve arbitration among ports to obtain high-speed data transfer in the router is one of the most significant phases while designing a Network on chip based Multiprocessor System on a Chip. Low latency, throughput, space utilization, energy consumption, and reliability for Network on chip fabric are all determined by the router. The performance of the NoC system is hampered by the deadlock issues that plague conventional routing algorithms. This work develops a novel routing algorithm to address the deadlock problem. In this paper, a deterministic shortest path deadlock-free routing method is developed based on the analysis of the Turn Model. In the 2D-mesh structure, the algorithm uses separate routing methods for the odd and even columns. This minimizes the number of paths for a single channel, congestion, and latency. Two test scenarios—one with and one without a load test—were used to evaluate the proposed model. For a zero-load network, three clock cycles are utilized to transfer the packets. For the load network, five clocks are utilized to transfer the packets. The latency is measured for both cases without load and with load test and the corresponding latency is 3ns and 7ns respectively.The proposed method has an 18.57Mbps throughput. The area and power utilization for the proposed method are 69% (IO utilization) and 0.128W respectively. In order to validate the proposed method, the latency is compared with existing work and 50% latency is reduced both with and without congestion load
A Broadband Meta surface Based MIMO Antenna with High Gain and Isolation For 5G Millimeter Wave Applications
Get PDFThis paper proposes a Broadband Meta surface-based MIMO Antenna with High Gain and Isolation For 5G Millimeter applications. A single antenna is transformed into an array configuration to improve gain. As a result, each MIMO antenna is made up of a 1x2 element array supplied by a concurrent feedline. A 9x6 Split Ring Resonator (SRR) elongated cell is stacked above the antenna to improve gain and eliminate the coupling effects between the MIMO components. The substrate Rogers 5880 with a thickness of 0.787mm and 1.6mm is used for the antenna and meta surface. Furthermore, antenna performance is assessed using S-parameters, MIMO characteristics, and radiation patterns. The final designed antenna supports 5G applications by embracing the mm-wave frequency spectrum at Ka-band, there is a noticeable increase in gain. In addition, once the meta surface is introduced, there is an improvement in isolation. 
Edge Computing in Centralized Data Server Deployment for Network Qos and Latency Improvement for Virtualization Environment
Get PDFWith the advancement of Internet of Things (IoT), the network devices seem to be raising, and the cloud data centre load also raises; certain delay-sensitive services are not responded to promptly which leads to a reduced quality of service (QoS). The technique of resource estimation could offer the appropriate source for users through analyses of load of resource itself. Thus, the prediction of resource QoS was important to user fulfillment and task allotment in edge computing. This study develops a new manta ray foraging optimization with backpropagation neural network (MRFO-BPNN) model for resource estimation using quality of service (QoS) in the edge computing platform. Primarily, the MRFO-BPNN model makes use of BPNN algorithm for the estimation of resources in edge computing. Besides, the parameters relevant to the BPNN model are adjusted effectually by the use of MRFO algorithm. Moreover, an objective function is derived for the MRFO algorithm for the investigation of load state changes and choosing proper ones. To facilitate the enhanced performance of the MRFO-BPNN model, a widespread experimental analysis is made. The comprehensive comparison study highlighted the excellency of the MRFO-BPNN model
AI Techniques for Efficient Healthcare Systems in ECG Wave Based Cardiac Disease Detection by High Performance Modelling
Get PDFHeart disease (HD) is extremely lethal by nature and claims a disproportionately large number of lives worldwide. Early and reliable detection techniques are necessary to prevent fatalities from HD. Clinical test results, electrocardiogram (ECG) signal, the heart sound signal, impedance cardiography (ICG), magnetic resonance imaging, and computer tomography (CT) can all be used to determine whether an individual has HD. This research propose novel technique in efficient healthcare system by ECG wave based cardiac disease detection using deep learning architecture with high performance modelling. Here the input is collected as ECG waves which has been processed and obtained as ECG wave fragments. This ECG fragment features has been extracted using deep belief kernel principal neural network. Based on this extracted features the patients 3D heart image has been collected and classified using deep quantum multilayer convolutional neural networks. Here the experimental analysis has been carried out in terms of accuracy, precision, recall, F-score, SNR, RMSE. Proposed technique attained accuracy of 95%, precision of 81%, recall of 69%, F-1score of 73%, SNR of 59% and RMSE of 62%.  
BP Neural Network for the Preservation and Identification of Service Quality in the Cold Chain Logistics of Agricultural Products
Get PDFWireless communication transmission in the cold chain logistics of agricultural products plays an essential role in food preservation and is also the premise of transportation services and product quality assurance. Currently, the construction of the Internet of Things and 4G wireless network communication network promotes the development of cold chain logistics of agricultural products. In the process of 4G wireless network communication, it contains massive amounts of information, such as location and cargo identification, resulting in problems such as delay and data loss in wireless communication and seriously affecting the preservation effect of agricultural products. Therefore, this paper proposes a 4G wireless network optimisation method based on BP neural network to detect problems such as cold chain transportation and agricultural product preservation and verify the final optimisation effect. The calculation results show that the combination of the BP neural network and 4G wireless network can improve the information recognition effect in cold chain transportation, accurately determine the location, freshness, service evaluation and other information, and realise the optimisation of wireless information network transmission. The overall optimisation rate is more than 90%. Therefore, the method proposed in this paper can meet the needs of cold chain logistics and transportation of agricultural products
NewEdge Machine Learning Approach to Distributed Clo ud Workload Forecasting and Resource Provisioning
No full textNowadays, geo-appropriated cloud server farms (Geo-2DCs) havespread and facilitated a great many cloud administrations. Thereare a number of benefits to Geo-2DCs, but they also encountersignificant challenges. One such difficulty is dynamic assetscalability, which places a premium on responsibilitydetermination. However, the complexity of arrangement tools isgreatly increased by the extremely powerful and unique nature ofcloud workloads and conditions. For conduct exhibiting andforecast multi-dimensional performance metrics, compartmentorganization frameworks also use AI calculations. In addition, theevolving duties in complicated contexts may influence the characterof asset provisioning decisions. This research presents a newmethod for haze registration called IFFCOPFC, which stands forImproved Fuzzy Fertilization based Clustering with optimalPollination Flower Calculation. The asset credits are continuouslynormalized at the previous step. The flexibility of asset looking isseverely restricted after the creation of fuzzy grouping using OPFfor the purpose of allocating assets. Last but not least, a systembased on advanced fuzzy grouping is now in place for the assetprovisioning computation. Two benchmark datasets, Iris and Wine,were used to test the proposed IFFCOPFC model. Because itprovides the highest levels of customer satisfaction and practicalasset provisioning, the IFFCOPFC model has proven to be morebeneficial to clients than the considered options
Digital Engraving and Art Design Analysis Based on Spatial Expression Techniques
Get PDFAiming at the problems of poor transmission effect and serious data loss in digital engraving, this paper puts forward a digital modeling model from the perspective of spatial expression. First, in-depth analysis of the original digital art design can not solve the problem of digital carving accuracy, and analysis of the reasons for the poor calculation accuracy of digital carving. Using wireless network technology and WIFI technology to obtain digital information of digital engraving, through the Internet design scheme statistics, according to the digital features to judge the form and result of engraving, remove irrelevant spatial information. Then, according to the Internet data monitoring, the change rate and engraving method of the engraving data are calculated, and compared with the actual engraving requirements, the parameters and indicators of digital art design are adjusted. MATLAB simulation test analysis shows that in the case of wireless communication and Internet monitoring, the digital engraving model of spatial expression technique can improve the accuracy of artistic design, and the accuracy rate is greater than the actual design requirements. According to the design requirements of different wireless networks and network communications, the time and compliance rate of digital engraving can meet the needs of artistic design