2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)最新文献

{"title":"The Innovation of Enterprise Management Mode of Digital Economy Based on Blockchain Technology","authors":"Xiaohui Li, Hongtao Feng","doi":"10.1109/ICKECS56523.2022.10060213","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060213","url":null,"abstract":"Blockchain is becoming an important leader in a new round of technological and industrial changes. Blockchain technology is in a rapid development stage, and its application scenarios are expanding and now cover many fields. Effectively promoting the deep integration of blockchain and the real economy and promoting blockchain technology to empower the real economy has become a new engine to accelerate the transformation and upgrading of enterprises. The purpose of this paper is to study the innovation of enterprise management mode of digital economy based on blockchain technology. Integrating the principles of blockchain technology into the management activities of enterprises, the impact of blockchain technology on the management activities of e-commerce enterprises is analysed for the e-commerce industry, which is currently a relatively popular sector in the digital economy enterprises, and corresponding suggestions are put forward. By defining variables and constructing theoretical models, conducting research hypotheses on the impact of blockchain on innovation in digital economy enterprises, using questionnaires and analyzing data using SPSS and AMOS software, we obtain that the impact of blockchain on innovation in digital economy enterprises has a positive influence role, in which the integration of innovation resources plays a mediating role.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"881 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130401846","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}

{"title":"A Novel Approach of Smart Contract based Distributed Ledger Technology using Deep Learning Techniques to Secure Medical Images","authors":"Chandini A. G, P. I. Basarkod","doi":"10.1109/ICKECS56523.2022.10060828","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060828","url":null,"abstract":"Internet of Medical Things (IoMT) is on-demand research area, generally utilized in most of medical applications. Security is a challenging problem in decentralized platform while handling with medical data or images. An effective deep learning-based blockchain framework with reduced transaction cost is proposed to enhance the security of medical images in IoMT. The proposed study involves four different stages like image acquisition, encryption, optimal key generation, secured storing. The input images initially are collected in the image acquisition stage. Then, the collected medical images are encrypted using coupled map lattice (CML). This encryption process assists to preserve the input medical images from the attackers. In order to provide more confidentiality to the encrypted images, optimal keys are generated using opposition-based sparrow search optimization (O-SSO) algorithm. These encrypted images are stored using distributed ledger technology (DLT) and smart contract based blockchain technology. This blockchain technology enhances the data integrity and authenticity and allows secured transmission of medical images. After decrypting the image, the disease is diagnosed in the classification stage using proposed Recurrent Generative Neural Network (RGNN) model. The proposed study used python tool for simulation analysis and the medical images are gathered from CT images in COVID-19 dataset.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125361781","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}

{"title":"An Efficient Pelican optimization based CNN-BiLSTM to Detect and Classify 3D Objects","authors":"Ramana Rajendran, B. Murugan","doi":"10.1109/ICKECS56523.2022.10060768","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060768","url":null,"abstract":"The lack of appropriate shape representation makes it complex to recognize the 3D shapes accurately and it is a hot topic in the field of Computer Vision (CV). This paper presents a Pelican optimized Convolutional Neural Network (CNN)-Bidirectional Long Short Term Memory (BiLSTM) to recognize the different objects in a particular scene. The CNN-BilSTM architecture is formed by placing two BiLSTM architectures below the CNN network and integrating the outputs via a fully connected layer. The pelican optimization algorithm is mainly incorporated to optimize the different hyperparameters associated with the CNN-BiLSTM architecture such as number of layers, batch size, number of layers, dropout, etc. The experiments are conducted using the ScanNet dataset which comprises both 2D and 3D data along with the labeled voxels. The proposed methodology offers improved results when compared with the existing techniques in terms of confusion matrix, accuracy, precision, and recall.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"205 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131589390","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}

{"title":"Application of Machine Learning Algorithms in Project Economics Review","authors":"Chenhong Zheng, Mengzhe Liu, Y. Wang, Cong Zeng","doi":"10.1109/ICKECS56523.2022.10060452","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060452","url":null,"abstract":"In order to solve the problem that the traditional query based on secondary retrieval is too rigid so as to automatically filter out valuable target documents, and repeated queries consume a lot of time, an intelligent interactive information retrieval process and processing flow for fund project document queries is proposed. Based on the feedback information of users evaluating project documents, ID3 algorithm, CLCC algorithm and SVM classification function are used to learn the potential intention and target of users' query respectively, and the learned rule knowledge or classification function is applied to support the project document query. The experimental computations and analysis are conducted for the query of project documents in a fund review management as an example. The results show that the number of project documents read and evaluated by the user in each interactive query loop is no more than 5% of the total number of documents returned from the previous query or 20 items, and together with the project documents already read and evaluated, they constitute the set of machine learning samples. The maximum number of interactive query cycle is set to 5. Among the three machine learning methods, ID3 also shows good prediction performance when post-processing algorithm is used. ID3 generates a decision tree with large width and small height. CLCC algorithm is better than ID3 algorithm, mainly because the rule post-processing of CLCC is more flexible, and the generated concept rules contain more merge rules and each merge rule is shorter. The SVM method has the best prediction performance, mainly because the project document keyword vectors are all continuous real values. It is concluded that the fund project intelligent interactive information retrieval process and processing flow accurately describes the potential query intention and target of user evaluation project documents, and establishes a user query project document classification learning knowledge base system, thus realizing the knowledge-based project document query support.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127736493","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}

{"title":"Related Problems of Coverage and Interference Coexistence in Rail Transit Communication System","authors":"Wu Shuang, Yao Tong","doi":"10.1109/ICKECS56523.2022.10059587","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10059587","url":null,"abstract":"In recent years, China's urbanization scale process and urban rail transit line planning and development are obvious to all. However, there are still serious problems such as urban congestion and lack of carrying capacity of urban vehicles, which are also important factors hindering the development of urban transportation. The development of urban rail transit can not only open up the situation of urban ground transportation, but also create favorable conditions for the three-dimensional development of the city and provide efficient guarantee for the modernization of the city and the comprehensive coverage of the transportation network. Coverage is the area where signals can be received. Interference means that two or more signals attempt to be received at the same time, so they cannot be received. The results of coverage and interference will vary depending on the location of the receiver, but in general, if there are no obstacles between the transmitter and the receiver, all areas within a certain radius (e.g. 30 miles) should have good coverage. If there are obstacles, such as hills or buildings.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133360636","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}

{"title":"Data Classification Algorithm Based on Association Rules from the Perspective of Data Mining","authors":"Hongxing Liu, Qijiang Shu, Hongyan Xiong, Yuzhu Yang","doi":"10.1109/ICKECS56523.2022.10060274","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060274","url":null,"abstract":"Association rules(AR) are a common data classification method. It can create more value by studying how to better mine user information and establish connections between these large number(LR) of reusable objects. For better studying the data classification algorithm, this paper studies from the perspective of data mining. This paper mainly discusses and studies some common data mining technologies, and designs a method to deal with related events based on learning rules to solve the problems in practical applications. The experimental data shows that when the number of concurrent users increases, the time of different algorithms also increases, but the time spent in data mining is less than 2 minutes. It shows that the data classification algorithm under the data mining can play a certain role.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"371 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113986830","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}

{"title":"Optimization System Design of Building Internal Structure Based on Multi-Objective Evolutionary Algorithm","authors":"Dong-Sheng Xu, Yishuang Liu","doi":"10.1109/ICKECS56523.2022.10060372","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060372","url":null,"abstract":"With the rapid development of China's construction industry, there are inevitably many problems in the construction process, such as unreasonable internal structure and incomplete equipment. In order to solve these problems, it is also proposed to better promote social and economic benefits and the improvement of people's living standards. This paper takes large capacity computer as the main research object to solve the optimization engineering design and calculation analysis of multi-objective evolutionary algorithm. The main content of the research is to realize the optimization of the internal structure of construction enterprises based on multi-objective evolutionary algorithm technology, maximize the efficiency in construction engineering by using genetic algorithm, and establish a mathematical model combining particle swarm intelligence theory. Finally, the model is tested. The test results show that the interior structure optimization system based on multi-objective evolutionary algorithm has short running time, low delay time and high compatibility rate. This shows that the performance of the system is excellent and meets the user's requirements.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115224712","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}

{"title":"Construction of a Learning Engagement Evaluation Model Based on Multi-modal Data Fusion","authors":"Jing Chen, P. D.","doi":"10.1109/ICKECS56523.2022.10060326","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060326","url":null,"abstract":"Learning engagement has become an important indicator affecting learning outcome in universities. It can not only reflect learners' learning process, but also fully resonate “learner-centered” educational concept. Accurate evaluation of learning engagement is an important task. Multi-modal data fusion can extract and fuse dynamic and multi-dimensional input, which is of great value in characterizing learners' learning process. But there are some problems in traditional evaluation methods, such as poor real-time evaluation, low evaluation effect of single modal data, and social approval response bias. Based on multi-modal data fusion, an evaluation model of learners' engagement was constructed and its predictive effect was verified. In this study, OpenCV region extraction method was applied and an automatic evaluation method was proposed based on multi-modal data fusion calculation. Questionnaires were collected to explore factors impacting learning engagement from university students in mainland China. Results showed (a) the evaluation model of learning engagement, i.e., behavioral engagement, cognitive engagement and emotional engagement has good reliability and validity; (b) It demonstrates that learner engagement has a significant predictive effect on academic achievement. The study finds that improving learning engagement will significantly improve learners' overall academic gains and the learning engagement evaluation model can accurately assess learning engagement.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115377297","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}

{"title":"Comparison on Blockchain-based Intrusion Detection Systems for Internet of Things","authors":"Daniel Mago Vistro, Muhammad Kamran Abid, Mughees Ahmad, Mubashir Ali, Jawad Hassan, Akhlaq Younas","doi":"10.1109/ICKECS56523.2022.10060383","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060383","url":null,"abstract":"The Internet of Things (IoT) is a cutting-edge concept that unites the Internet with actual physical objects from a variety of industries, such as home automation, manufacturing, human health, and environmental monitoring. Users are now able to use gadgets with Internet access for routine tasks. Along with many advantages, IoT also presents a number of security-related difficulties. The security of the IoT network has grown in importance as the popularity of the Internet of Things increases daily. An IoT network is more secure thanks to encryption and authentication, yet it can be challenging to defend IoT devices from online threats. Cyberattacks on the Internet of Things system not only result in data loss, but they also have the potential to bring the entire system to a standstill. The performance of the network can be negatively impacted by hostile activities, which are easily detected by intrusion detection systems (IDS). To safeguard IoT systems, an efficient intrusion detection system (IDS) is required. Another cutting-edge technology that helps security systems counter the most recent threats is blockchain. In this post, we analysed state-of-the-art blockchain-based intrusion detection methods for Internet of Things devices. New advancements to alleviate security threats are also listed in a table. Finally, we list the major questions brought on by the current restrictions.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"204 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115571609","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}

{"title":"MRI Image Enhancement for Brain Tumor Detection using Hybridization of Contrast Enhancement Techniques","authors":"Deena Abin, Govind Mudavadkar, Rakesh Minase, Mridul Handoo, R. Kumawat","doi":"10.1109/ICKECS56523.2022.10060125","DOIUrl":"https://doi.org/10.1109/ICKECS56523.2022.10060125","url":null,"abstract":"Magnetic Resonance Imaging also known as MRI is a significant technology used in medical image processing that provides important information on the structure of human soft tissue. As MRI is used to diagnose numerous brain-related severe illnesses, such as brain tumors and spinal cord tumors, image enhancement of the collected brain images is considered to be important by a large number of medical researchers and doctors. Despite the progress of technology, every image has some deficiencies, such as noise, low contrast, low brightness. To solve these issues related to MRI images, various histogram equalization techniques for example HE, CLAHE, BBHE, DSIHE, RMSHE, and Fuzzification and their hybridizations are applied to different MRI images. Metrics such as entropy, PIQE, and BRISQUE are used to evaluate the findings.","PeriodicalId":171432,"journal":{"name":"2022 International Conference on Knowledge Engineering and Communication Systems (ICKES)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114530813","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}