2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)最新文献_第3页

Investigation and Designing for Network Congestion Detection and Prevention in DTN DTN网络拥塞检测与预防的研究与设计

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574694

D. Tomar, Megha Kamble

{"title":"Investigation and Designing for Network Congestion Detection and Prevention in DTN","authors":"D. Tomar, Megha Kamble","doi":"10.1109/CICN51697.2021.9574694","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574694","url":null,"abstract":"Nowadays higher demands of lightweight mobile devices for monitoring critical situation such as weather, tsunami, earth quick and rural area where direct communication not possible. Those area DTN mobile communications play important role to provide message exchange between devices through limited capacity (channel, memory, processing). Due to exhaustive demand of DTN mobile communication, concurrently multiple nodes exchange the message from one location to another through lightweight capable node that arises the problem of congestion, in this paper investigate various existing approach to resolve the network related issue to enhance the performance of delay tolerant network (DTN). Those existing approach give the roadmap to further enhancement of DTN network for smooth working in real time communication in rural area where disseminated connectivity. In the paper we also design new congestion detection and prevention method using collaborative methodologies such as input and output dependency retrieval, energy utilization and fuzzy rule definition and provide lightweight solution to the DTN for improving the efficiency of network where nodes are configure in limited capacity. In future we analyse those work through the network simulator −2 and measure the performance of the network.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130050456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Construction and Application of An English-Chinese Corpus of Academic Formulaic language 英汉学术公式化语料库的构建与应用

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574687

F. Meng, Wenhui Wang, Songbin Bao

引用次数: 0

Performance Evaluation and Analysis of an WoC Based Inter Satellite Link over the Low Earth Orbit 基于WoC的近地轨道星间链路性能评价与分析

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574683

G. Soni

{"title":"Performance Evaluation and Analysis of an WoC Based Inter Satellite Link over the Low Earth Orbit","authors":"G. Soni","doi":"10.1109/CICN51697.2021.9574683","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574683","url":null,"abstract":"The various advanced applications of 5G based wireless communications include autonomous self-driven cars, telemedicine, smart spaces (e.g., home, office, etc.), sensor networks, high speed trains, smart cities, and many more [9]. For such data intensive wireless communications, only radio frequency (RF) based wireless systems cannot meet the desired demands because RF band is susceptible to interference, has limited capacity, and requires a heavy license fee to use the spectrum [10]. Hence, other portions of the electromagnetic (EM) spectrum and new technologies are required to be considered for fulfilling the demands of wireless communication systems in the near future. One such alternative solution is Free Space Optics (FSO) which is an optical wireless communication (OWC) based technology. The FSO not only has many advantages but also hampered by some atmospheric conditions, which degrades the link performance. This paper reviews the FSO link design and effect of different atmospheric condition like- fog, scintillation, turbulence, rain etc. This paper studies the system performance of an optical ISL which is proposed between satellites over Low Earth Orbit (LEO). In this study, the proposed link is simulated to obtain the maximum allowable data rate and minimum bit error rate over different distances. The system performance is improved by investigating its dependency on the photo detector type, operating wavelength, transmitted optical power, RZ and NRZ schemes.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122261591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Design and Implementation of Intelligent Garbage Classification System Based on Artificial Intelligence Technology 基于人工智能技术的智能垃圾分类系统设计与实现

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574675

Daheng Lin, Zhenglu Chen, Mengmeng Wang, Jiale Zhang, Xinxin Zhou

{"title":"Design and Implementation of Intelligent Garbage Classification System Based on Artificial Intelligence Technology","authors":"Daheng Lin, Zhenglu Chen, Mengmeng Wang, Jiale Zhang, Xinxin Zhou","doi":"10.1109/CICN51697.2021.9574675","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574675","url":null,"abstract":"In order to help users to correctly classify garbage and achieve better utilization of garbage resources, this article proposes an intelligent garbage classification system, which includes a cloud server, intelligent classification garbage bins, and mobile smart ends. Using cloud computing, artificial intelligence, image processing, Raspberry Pi design, WeChat mini-program and other technologies, the intelligent classification garbage bin realizes three working modes: manual classification, automatic classification, and compression. In the automatic classification mode, the intelligent classification garbage bin firstly preprocesses the collected garbage images, then uploads the main garbage images to the cloud server for classification, and finally uses the garbage position information provided by the resistive screen on the carrying platform to adjust in real time garbage delivery posture, put the garbage into corresponding part of the garbage bin to prevent the garbage from falling accidentally. The mobile smart end implements multiple functions, for instance, tracing the results of garbage disposal. It has been thoroughly tested that the accuracy of this system for automatic classification reaches 92%, providing a simple and feasible solution for garbage classification.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128520551","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hybrid Model based on Support Vector Machine and Principal Component Analysis Applied to Arterial Hypertension Detection 基于支持向量机和主成分分析的混合模型在高血压检测中的应用

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574662

Antony B. Almonacid, Ciro Rodríguez, Yuri Pomachagua, Diego Rodriguez

引用次数: 2

Transfer Learning based Detection of Pneumonia from Chest X-Ray Images 基于迁移学习的胸部x线图像肺炎检测

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574689

Sai Dheeraj Gummadi, Yeswanth Vootla, Anirban Ghosh, Peddisetty Naga Kartheek, Anjan Krishna Kandimalla

{"title":"Transfer Learning based Detection of Pneumonia from Chest X-Ray Images","authors":"Sai Dheeraj Gummadi, Yeswanth Vootla, Anirban Ghosh, Peddisetty Naga Kartheek, Anjan Krishna Kandimalla","doi":"10.1109/CICN51697.2021.9574689","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574689","url":null,"abstract":"Pneumonia is an inflammatory condition affecting the small air sacs known as the alveoli present in the lungs. Despite the availability of vaccines for certain types it is known to be one of the leading causes of death across all age groups around the world. Chest X-Ray (CXR) images, blood test or sputum culture are standard techniques primarily used by doctors to confirm their diagnosis but is prone to human error due to huge imbalance between number of potential patients and doctors. Deep learning based computer aided technology with reasonably good accuracy and precision can aid the doctors by eliminating the benign cases. In this paper, a transfer learning based convolutional neural network (CNN) architectures is proposed for classifying CXR images into healthy and pneumonia affected with high accuracy and precision. The proposed method uses three different transfer learning architectures, viz. VGG - 16, VGG - 19 and Inception Resnet V2 for comparison and is found to provide best results with VGG - 19 architecture. An accuracy of 95.82% with 98.55% precision, 96.20% specificity and 95.67% sensitivity are obtained with the help of VGG-19 which is superior to any existing solution known to the authors.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121842660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Establish Program WCET and Energy Consumption Prediction Model Based on L-M Algorithm 建立了基于L-M算法的程序WCET和能耗预测模型

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574681

Fanqi Meng, Haochen Sun, Jingdong Wang

{"title":"Establish Program WCET and Energy Consumption Prediction Model Based on L-M Algorithm","authors":"Fanqi Meng, Haochen Sun, Jingdong Wang","doi":"10.1109/CICN51697.2021.9574681","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574681","url":null,"abstract":"In some hard real-time systems, the system has high requirements for program execution time and energy consumption. If the program runs overtime or the energy is exhausted in advance, it will have a significant impact on system security. In order to be able to more accurately predict the WCET and energy consumption of the program and provide support for the subsequent search for the best optimization method that optimizes WCET and the average execution time at the same time, this paper gives a set of feasible methods that can predict the worst execution time and average execution time of the program. On the basis of existing research, the static method of program execution time estimation is integrated with the dynamic method, and the WCET and energy consumption of the program are estimated using the sample program features such as dynamic instruction features, and the L-M (Levenberg-Marquardt) algorithm is used to train neural network. And compared with the traditional regression algorithm, add quantitative indicators and verify the feasibility of the method. The method in this paper can make an accurate prediction of the execution time of the program. The research is helpful to the follow-up development of this field and provides a useful reference and reference for the further optimization of the program.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"30 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117275215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Performance Investigation of the Free Space Optics Link based Communication using DOE scheme at 1550nm 1550nm下基于自由空间光链路的DOE通信性能研究

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574663

G. Soni

{"title":"Performance Investigation of the Free Space Optics Link based Communication using DOE scheme at 1550nm","authors":"G. Soni","doi":"10.1109/CICN51697.2021.9574663","DOIUrl":"https://doi.org/10.1109/CICN51697.2021.9574663","url":null,"abstract":"FSO is a terrestrial OWC system used for point-to-point communication and operates at near infrared (IR) frequencies (750–1600 nm). It is a laser driven Communication based on line of sight (LOS) enabling technology for the transmission and reception of information carrying light signals through the atmosphere. For the same, it uses light sources and light detectors, i.e., laser diodes and photodiodes, respectively. The real motive behind using FSO is to do away with the cost, time, and effort in laying fiber optic cables without adversely impacting high data rates for transmitting voice, image, text, video, or any other file. In recent years, Free space based optical communication has developed and grown rapidly and has been widely used in applications like satellite laser based communication, radar detection, and other fields. Space optical communication based system includes a TX-RX antenna system and a coupling system. The research of space optical communication system often separates the antenna systems and the coupling system for discussion. When analyzing TX-RX antenna systems, geometric optics is generally used. Based on ancient diffraction theory, the performance of space optical communication systems consisting of a transmitter antenna, receiver antenna, and fiber coupling based systems are analyzed. Besides, several practical situations are also considered such as the defocusing of the TX-RX antenna and the deviation of the fiber. The longer or greater the transmission distance, the greater the effect of diffraction. When the transmission distance is short, the defocusing of the primary mirror will help it improve the transmission efficiency of the given system.","PeriodicalId":224313,"journal":{"name":"2021 13th International Conference on Computational Intelligence and Communication Networks (CICN)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127289858","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chicken Swarm Optimization Algorithm Based on Adaptive Dynamic Distribution 基于自适应动态分布的鸡群优化算法

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574678

Xinxin Zhou, Zhirui Gao, Xueting Yi, Daheng Lin

引用次数: 1

Business Intelligence Tools Implementing in the Field of Electrical Industry 商业智能工具在电气工业领域的实现

2021 13th International Conference on Computational Intelligence and Communication Networks (CICN) Pub Date : 2021-09-22 DOI: 10.1109/CICN51697.2021.9574665

Juan Carlos Rivera Rado, C. Rodriguez

引用次数: 1