2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)最新文献

{"title":"Denoising Task-Based Functional Magnetic Resonance Imaging Data Using Hybrid Deep Neural Network Model","authors":"Sahar Kashfolayat, Hamid Shiri, A. Baniasadi","doi":"10.1109/ICCNS58795.2023.10193697","DOIUrl":"https://doi.org/10.1109/ICCNS58795.2023.10193697","url":null,"abstract":"We present a hybrid deep neural network model for Denoising task-based fMRI data. This model is based on the Deep Neural Network (DNN) model [1] and improves its performance by utilizing different layers for Grey Matter and non-Grey Matter related data. The preprocessed data passes through GM and non-GM masks. Then it is fed to the network and passes through temporal filters along with an LSTM layer. The result will be classified using time-distributed fully-connected layers –since the input data is a time-series of voxel values-which have different structures for GM and non-GM input data. This hybrid mechanism helps the model to reduce the correlation between non-GM processed data and the design matrix significantly. We also increase the correlation of GM output, which is equivalent to better cost function and less noise. This new self-supervised model is tested using simulated data and the HCP database [2]. We succeed in denoising task better than the DNN model by an average of at least 4%.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124457562","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 Comparison Study of Deep Learning Algorithms for Metasurface Harvester Designs","authors":"H. A. Ajmi, M. Bait-Suwailam, L. Khriji","doi":"10.1109/ICCNS58795.2023.10193585","DOIUrl":"https://doi.org/10.1109/ICCNS58795.2023.10193585","url":null,"abstract":"The paper compares three deep learning artificial intelligence algorithms used for metasurface design. In-house design code for designing metasurface structures was developed with Python, the NumPy library. To facilitate the study, the three algorithms used are AdaBelief, Adam, and Yogi. According to the numerical comparison study, Adam has a better performance in terms of model generalization with a large dataset (in our case 7000 samples), while Adabelief and Yogi show a better performance in terms of a low dataset (in our case 4,000 samples), and Yogi has a better performance with a lower dataset correlation between the predicted performance of the energy harvester obtained from three algorithms. Yogi and Adablief performance could be improved by manipulating the hyper-parameters.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131948945","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":"Implementation of the IoT Technology in Structural Health Monitoring of Bridges: Case Study","authors":"Ahmad Elrefae, M. Alhassan, M. Issa, Layla Amaireh, Rami Mohawesh","doi":"10.1109/ICCNS58795.2023.10193185","DOIUrl":"https://doi.org/10.1109/ICCNS58795.2023.10193185","url":null,"abstract":"Bridges are regarded as the backbone of the transportation infrastructure; therefore, it is essential that bridges are sustained and kept open to traffic to avoid costly delays and road closures. The nature of fatigue loading on bridges caused by the passage of millions of automobiles and heavy trucks imposes severe loading conditions on them. This is in addition to the influence of severe environmental conditions represented mainly by temperature variations, freeze-thaw cycles, contaminated water, deicers, materials aging, and wearing. Moreover, frequent vehicle collisions on bridges may result in fires and damage to the bridge’s structural components. Structural health monitoring (SHM) of bridges is a reliable method for ensuring the integrity of the bridge and the success of systematic repairs and restorations that are typically conducted. It is an investigative technology that can detect significant problems and failure causes to take proactive measures before the occurrence of catastrophic failures. Using SHM technology, the bridge control unit and operators are immediately notified of any severe problems. The current boom in the Internet of Things (IoT) provides an ideal foundation for its integration in the SHM of bridges by enabling interconnection and continuous data-sharing among the monitored elements. A network of various types of sensors (strain gages, temperature sensors, cracks detection sensors, etc.) installed at pre-identified locations can collect and transmit data for processing by an onsite intelligent control unit. In accordance with the urgency of the bridge condition, the bridge management unit can access the control unit for routine evaluations. When bridge girders are damaged or deteriorated, it is common to reinforce them with carbon fiber-reinforced polymer (CFRP) composites. The effectiveness of this repair technique is dominantly dependent on the bond between the concrete and the CFRP composites. The SHM technology is utilized in such repair procedure to ensure that the CFRP composites are in full composite action with the structural member. This paper presents a case study of a long-term SHM with the aid of IoT technology of damaged prestressed concrete girders of a bridge repaired with CFRP composites and instrumented with multiple strain gages connected to a control unit that transmits the strain values and temperature variations to the bridge management unit for continuous assessment.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127292230","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":"On the Education Effect of CHATGPT: Is AI CHATGPT to Dominate Education Career Profession?","authors":"Yazan Al Ahmed, Abdulla Sharo","doi":"10.1109/ICCNS58795.2023.10192993","DOIUrl":"https://doi.org/10.1109/ICCNS58795.2023.10192993","url":null,"abstract":"In the year 2022, OpenAI invented a new model of ChatGPT, a Natural language processing (NLP) system that can hold natural chats while maintaining the context of the conversation. Since then, this tool has displayed numerous capabilities leading to increased research on its functionality and impacts on society. In this article, ChatGPT’s influence on university education was examined. information linking the impact and usability of ChatGPT was collected for conducting the exams, solving programming exams, and term papers by examining over 50 essay papers from learners. The essay papers were chosen from different topics. Some of the essay papers chosen are those that had been done and completed in previous academic work. Different tool misuse levels were assessed, starting from the use of it as an assistant to simplify copying its outputs. In this case, How copying and pasting material directly from ChatGPTs can affect students’ grades was deeply examined and compared since some of its answers are not termed correct. This issue is broadly discussed in this article. While it shows how this tool can be used to commit exam cheating, the article also touches on the potentially significant pros of the learning sector. For example, it might be used as help to describe challenges encountered while handling an assignment or to fasten the process of learning. The outcome showed that ChatGPT can assist scientists to generate coherent papers, accurate, informative, and systematic. This paper evaluated Artificial intelligence (AI)-generated work and actual learner-generated work and then compared the performance of each approach. This paper summarizes that new assessment formats are required to focus on critical thinking and creativity that Artificial intelligence cannot replace.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125405798","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":"Target-Based Versus Customer-Based Genetic Algorithms and Matrix Factorization Recommender Systems","authors":"Y. Kilani, M. Sullabi, A. Alsarhan","doi":"10.1109/ICCNS58795.2023.10193537","DOIUrl":"https://doi.org/10.1109/ICCNS58795.2023.10193537","url":null,"abstract":"Recommender systems (RS) are a practical choice to help the customers choose the targets (i.e. book, restaurant, movie, TV, mobile phone, etc) they like in a short time. Collaborative filtering (CF) and matrix factorization (MF) techniques are common methods that are used in the RSs. The CF technique considers the rates of the customers to the targets. It recommends targets I for customer x if I have been rated high by similar customers to x. The MF technique splits the rating matrix into two matrices, customer-factor and factor-target, such that their targets nearly obtains the rating matrix. Navgaran RS (NRS) is a RS that uses the genetic algorithms (GA) to predict the uknown entries in the customer-factor and factor-target matrices in order to make recommendation for the active customer (i.e. the customer who wants recommendation). NLM is a GA-based CF RS that hybridizes both the neighbourhood and the latent factor models to predict targets for the active customers. NLM is a customer-based RS and improved NRS. In our project, we have modified NLM to make it target-based instead of being customer-based. We show that our new RS, NLMu, outperforms NLM and NRS in solving some instances.We experimentally used the datasets: MovieLens, FilmTrust, and CiaoDVD. We show that NLMu has better precision value than NRS in MovieLens. It is faster and has less error than NRS and NLM in FilmTrust, and it is faster and has less error than NRS in CiaoDVD.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126508854","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":"Keynote Speech 4: Digital Transition in Precision Agriculture","authors":"S. Sendra","doi":"10.1109/mcna59361.2023.10185764","DOIUrl":"https://doi.org/10.1109/mcna59361.2023.10185764","url":null,"abstract":"Digital agriculture is revolutionizing the global agricultural sector, aiming to optimize productivity, enhance competitiveness, and mitigate the negative effects on the environment. Precision agriculture, on one hand, is increasingly being adopted in larger areas, while the process of digital transition involves monitoring crops and incorporating artificial intelligence and other technologies to enable more efficient management practices. Therefore, it is crucial to showcase the manifold benefits of digitalization to farmers, ensuring the development of a sustainable and competitive agricultural sector. Furthermore, obtaining accurate and up-to-date information about farming sites offers significant advantages to researchers, the educational community, and even promotes the emergence of agricultural tourism. This speech aims to explore diverse approaches that facilitate the adoption of digitalization in agriculture. Disruptive technologies such as Low Power Wireless Area Networks (LPWAN) can be combined with other established short-range wireless technologies within a heterogeneous network. Additionally, the integration of multispectral images, 3D point-cloud maps, and AI-powered algorithms capable of processing massive amounts of data (AI and Big Data) can create a comprehensive system that enhances vital aspects such as the sustainability of agricultural activities, reduction in the utilization of natural resources, and increased public awareness of these issues. The exchange of knowledge between farmers and experts will yield valuable recommendations to support their transition to more ecologically sustainable farming practices.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125869076","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":"BioTrak: A Blockchain-based Platform for Food Chain Logistics Traceability","authors":"Alessia Spitalleri, I. Kavasidis, Vincenzo Cartelli, Raffaele Mineo, Francesco Rundo, S. Palazzo, C. Spampinato, D. Giordano","doi":"10.1109/ICCNS58795.2023.10193341","DOIUrl":"https://doi.org/10.1109/ICCNS58795.2023.10193341","url":null,"abstract":"The food supply chain, following its globalization, has become very complex. Such complexities, introduce factors that influence adversely the quality of intermediate and final products. Strict constraints regarding parameters such as maintenance temperatures and transportation times must be respected in order to ensure top quality and reduce to a minimum the detrimental effects to public health. This is a multi-factorial endeavor and all of the involved stakeholders must accept and manage the logistics burden to achieve the best possible results.However, such burden comes together with additional complexities and costs regarding data storage, business process management and company specific standard operating procedures and as such, automated methods must be devised to reduce the impact of such intrusive operations.For the above reasons, in this paper we present BioTrak: a platform capable of registering and visualizing the whole chain of transformation and transportation processes including the monitoring of cold chain logistics of food ingredients starting from the raw material producers until the final product arrives to the end-consumer.The platform includes Business Process Modelling methods to aid food supply chain stakeholders to optimize their processes and also integrates a blockchain for guaranteeing the integrity, transparency and accountability of the data.","PeriodicalId":158016,"journal":{"name":"2023 International Conference on Intelligent Computing, Communication, Networking and Services (ICCNS)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116228662","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}