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A Blockchain-based Conditional Privacy-Preserving Traffic data Sharing in Cloud

A Blockchain-based Conditional Privacy-Preserving Traffic Da...

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IEEE international conference on Communications (ICC)

作者： Jingwei Liu Gaojian Zhang Rong Sun Xiaojiang Du Mohsen Guizani Shaanxi Key Laboratory of Blockchain and Secure Computing Xidian University Xi’an China State Key Lab of ISN Xidian University Xi’an China Department of Computer and Information Sciences Temple University Philadelphia PA USA Department of Computer Science and Engineering Qatar University Doha Qatar

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

As a typical application scenarios of Internet of Things (IoT), Internet of Vehicles (IoV) is playing an important role in the field of intelligent transportation. In such a system, vehicles are allowed to collect ambient sensing data and communicate with other vehicles, roadside infrastructure, cloud server, even personal mobile smart devices in order to exchange the relevant traffic information that usually includes the owners' sensitive information, such as geographical location or personally identifiable information. However, in open network environment, different wireless communication technologies make all these information vulnerable to various attacks and compromises. The users' private information is put at the risk of leaking at any time. To address this issue, a blockchain-based privacy-preserving traffic data sharing protocol with cloud storage is proposed based on a novel heterogeneous signcryption scheme between Public Key Infrastructure (PKI) and Certificateless Cryptosystem (CLC). Through theoretical and simulation analysis in terms of security, complexity and time consumption, the proposed traffic data sharing protocol is proved to meet the security requirements of data tamper-proofing, anonymity and traceability with higher efficiency.

关键词： Cloud computing Public key Servers Transportation Protocols

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Towards Seamless Connectivity: Implementing 6G Communication Technologies In Next-Generation Networks

Towards Seamless Connectivity: Implementing 6G Communication...

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Advancement in Technology (ICONAT), international conference for

作者： K. Kalaiselvi R. Sankar S Supriya G Kaushik Hemanth Swamy M Devika Department of Data Analytics Saveetha College of Liberal Arts and Sciences SIMATS Chennai Tamilnadu India Department of Electrical and Electronics Engineering Chennai Institute of Technology Chennai Tamil Nadu India Department of Computer Science and Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Chennai Tamil Nadu India Department of Electronics and Communication Engineering MLR Institute of Technology Hyderabad India Senior Software Engineer Motorola Solutions Department of AI& DS Dhanalakshmi College of Engineering Chennai Tamil Nadu India

ISBN: (数字)9798350354171

ISBN: (纸本)9798350354188

Advanced wireless networks are essential given the increase in demand for smart services enabled by the Internet of Everything (IoE). Despite the fact that 5G networks could enable Internet of Everything (IoE)-based services, they can’t meet all of the requirements needed to create intelligent applications. In order to overcome the shortcomings of the current infrastructure, there is an increasing demand to investigate the potential of 6G wireless communication technologies. Complex network optimization problems can be resolved by integrating artificial intelligence into sixth generation networks. An increasing user base and support for large-scale data-driven applications are essential given the fast evolving 6G landscape. In addition to highlighting network needs, critical supporting technologies, and a comparison of 5G and 6G networks, this study looks at recent advancements and trends in 6G technology. The report also explores new approaches to 6G connectivity, such as edge computing, backscatter communications, AI-driven IoT networks, and holographic beamforming, all of which are meant to support intelligent communities. In order to achieve the goal of 6Gbased IoT networks, it concludes by outlining potential research avenues.

关键词： 6G mobile communication 5G mobile communication Wireless networks Complex networks Market research Communications technology Internet of Things Optimization Next generation networking Edge computing

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Image Classification using Convolution Neural Network Based Hash Encoding and Particle Swarm Optimization

Image Classification using Convolution Neural Network Based ...

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data analytics for Business and Industry: Way Towards a Sustainable Economy (ICDABI), international conference on

作者： Sameer I. Ali Al-Janabi Sufyan T. Faraj Al-Janabi Belal Al-Khateeb College of Computer Science and IT University of Anbar Ramadi Iraq

ISBN: (数字)9781728196756

ISBN: (纸本)9781728196763

Image Retrieval (IR) has become one of the main problems facing computer society recently. To increase computing similarities between images, hashing approaches have become the focus of many programmers. Indeed, in the past few years, Deep Learning (DL) has been considered as a backbone for image analysis using Convolutional Neural Networks (CNNs). This paper aims to design and implement a high-performance image classifier that can be used in several applications such as intelligent vehicles, face recognition, marketing, and many others. This work considers experimentation to find the sequential model's best configuration for classifying images. The best performance has been obtained from two layers' architecture; the first layer consists of 128 nodes, and the second layer is composed of 32 nodes, where the accuracy reached up to 0.9012. The proposed classifier has been achieved using CNN and the data extracted from the CIFAR-10 dataset by the inception model, which are called the Transfer Values (TRVs). Indeed, the Particle Swarm Optimization (PSO) algorithm is used to reduce the TRVs. In this respect, the work focus is to reduce the TRVs to obtain high-performance image classifier models. Indeed, the PSO algorithm has been enhanced by using the crossover technique from genetic algorithms. This led to a reduction of the complexity of models in terms of the number of parameters used and the execution time.

关键词： Training Predictive models Image retrieval data models Visualization Classification algorithms TV

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Research on smart party building identity online based on blockchain 2020

Research on smart party building identity online based on bl...

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Proceedings of the 2020 international conference on Cyberspace Innovation of Advanced Technologies

作者： Qubo Yang Xiaobing Zhu Organization Department of Party Committee Wuhan Donghu University Wuhan China School of computer science Wuhan Donghu University Wuhan China

ISBN: (纸本)9781450387828

Under the background of 5g mobile communication technology, artificial intelligence technology will drive the upgrading and innovation of Party building. Key technologies such as blockchain, big data, Internet of things, virtual reality, cloud computing and other key technologies will realize the precision of Party building information, the intellectualization of Party building environment, the situational scene of Party member education and the efficient communication between the party and the masses, and construct a new mode of intelligent party building from the four dimensions of technical environment, Party member's own development, intelligent work and intelligent learning. Changing the thinking, tamping the hardware, defining the position and perfecting the mechanism are the important guarantee for the construction of the new mode of the wisdom party construction.

关键词： Blockchain

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IoT-Enabled Automated Radish Care System: intelligent Detection and Response for Watering and Sunlight Needs

IoT-Enabled Automated Radish Care System: Intelligent Detect...

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international conference on Communication and Electronics Systems (ICCES)

作者： Nathaniel R. Macaranas Joseph Andrei A. Mandariaga Carlos Miguel D. Pablo Raymund M. Dioses Joseph Darwin C. Co Mark Anthony S. Mercado College of Information Systems and Technology Management Pamantasan ng Lungsod ng Maynila Manila Philippines

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377989

One of the critical issues, both in households and agriculture, is the ability to take care of radish plants due to their complexity. Traditional techniques, on the other hand, have problems such as inconsistent monitoring, high labor costs, wastage of resources, and improper timing of harvesting. Nowadays, sensor-based monitoring and automated irrigation systems are examples of novel methods that have tried to solve these problems but are mostly poorly integrated and do not respond smartly. In this paper, an intelligent system and an IoT-based system for the automated care of radish vegetables where the system can detect and watering the plants or exposing them to sunlight whenever need arises is presented. Proposed solutions to the challenges are based on modern aggregate sensor technology and automatic control, cloud communication, and predictive analysis. The system smartly incorporates multiple environmental sensors networks, data storage, and analytics in the cloud, and takes advantage of pre-energy for automated operations to ensure proper care of plants with little human input and resource usage. PlanterBot, a mobile app, allows users to control and monitor system activities remotely, integrating machine learning to perform pre-harvest assessments. Evaluation using ISO/IEC 25010 standards showed excellent performance in all targeted Functional Suitability (1.32), Usability (1.31), Reliability (1.40), and Performance Efficiency (1.37). The findings prove that the current device is functional in solving the existing problems while developing the concept of smart farming.

关键词： Temperature sensors Performance evaluation Temperature measurement Cloud computing Moisture Humidity Mobile applications Predictive analytics Usability Monitoring

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A Diverse Biases Non-negative Latent Factorization of Tensors Model for Dynamic Network Link Prediction

A Diverse Biases Non-negative Latent Factorization of Tensor...

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IEEE international conference on Networking, Sensing and Control

作者： Xuke Wu Hang Gou Hao Wu Juan Wang Minzhi Chen Siyu Lai Computer School China West Normal University Nanchong China Computer School of China West Normal University Nanchong Sichuan China University of Chinese Academy of Sciences Beijing China Chongqing Engineering Research Center of Big Data Application for Smart Cities and Chongqing Key Laboratory of Big Data and Intelligent Computing Chongqing Institute of Green and Intelligent Technology Chinese Academy of Sciences Chongqing China North Sichuan Medical College Nanchong China Medical College Nanchong Sichuan China

ISBN: (数字)9781728168555

ISBN: (纸本)9781728168562

Dynamic networks vary over time, making it vital to capture networks temporal patterns for predicting missing links with high accuracy. A biased non-negative latent factorization of tensors (BNLFT) model is very effective in extracting such patterns from dynamic data. However, a BNLFT model only integrates single bias, which cannot adequately represents the volatility of the dynamic data. To address this issue, this paper presents a Diverse Biases Non-negative Latent Factorization of Tensors (DBNT) model for accurate prediction of missing links in dynamic networks. Meanwhile, for further prediction accuracy improvement, the preprocessing bias is integrated into the DBNT model. Empirical studies on two dynamic networks datasets from real applications show that compared with state of the art predictors, a DBNT model achieves higher prediction accuracy.

关键词： Tensors conferences Predictive models data models Sensors data mining

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Internet of Things based smart window and Temperature Monitoring System

Internet of Things based Smart window and Temperature Monito...

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international conference on Advanced computing and Communication Systems (ICACCS)

作者： Sudha Mercy S. A. Sivasubramanian Bhuvan B. Natesh J.M. Mathana Jerald Vinfrank J. G. Lokesh Jeppiaar Institute of Technology India Chennai Institute of Technology India

ISBN: (数字)9781728151977

ISBN: (纸本)9781728151984

Due to the movement of India to intelligent City, many of the processes have been already made automatic in various sectors like Industries, Hospitals even in Homes. Thus smart window is an automatic as well as manual operation for windows in Houses, Industries, Schools, Hospitals, Orphanages, etc. This Prototype will use IoT to sense the temperature of a closed environment continuously and adjust the Temperature of that closed Environment by opening or closing the window. This process will update the data gathered for the temperature and upload it to a dedicated server so that we can easily monitor the temperature in a closed environment remotely. This process can also be controlled Manually (by using the application) by sending a message to the device to Open/Close the window remotely. If both the temperature (Inside & outside the room) is not suitable for the room temperature, then the appliances like Air conditioning, Fan, etc. will automatically start operating to adjust the room temperature. Additionally, this process will sense the environment for movements in other unoccupied rooms. So if there are no movements in the room then the appliances operating in that room will automatically be turned off. Similarly, if persons who are walking to that room, automatically the appliances in that room will automatically be turned on. Thus this operation will help us to maintain the temperature level in a closed environment and it is possible to launch the intelligent window operation with no human power.

关键词： Temperature sensors Microsoft Windows Temperature control Temperature measurement Internet of Things Brushless motors Monitoring

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ARPDR: An Accurate and Robust Pedestrian Dead Reckoning System for Indoor Localization on Handheld smartphones

ARPDR: An Accurate and Robust Pedestrian Dead Reckoning Syst...

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2020 IEEE/RSJ international conference on intelligent Robots and Systems (IROS)

作者： Xiaoqiang Teng Pengfei Xu Deke Guo Yulan Guo Runbo Hu Hua Chai Didi Chuxing College of System Engineering National University of Defense Technology Changsha P. R. China College of Electronic Science and Technology National University of Defense Technology Changsha P. R. China

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

The proliferation of mobile computing has prompted Pedestrian Dead Reckoning (PDR) to be one of the most attractive and promising indoor localization techniques for ubiquitous applications. The existing PDR approaches either suffer position drifts caused by accumulative errors or are sensitive to various users. This paper presents ARPDR, an accurate and robust PDR approach to improve the accuracy and robustness of indoor localization methods. Particularly, we propose a novel step counting algorithm based on motion models by deeply exploiting inertial sensor data. We then combine step counting with adaptive thresholding to personalize the PDR system for different users. Furthermore, we propose a novel stride-heading model with a deep neural network to predict stride lengths and walking orientations, thus the displacement errors are significantly reduced. Extensive experiments on public datasets demonstrate that ARPDR outperforms the state-of-the-art PDR methods.

关键词： Location awareness Adaptation models Dead reckoning Handheld computers Robustness smart phones Mobile computing

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Harnessing AI for Effective Distance Learning: Teachers’ Perspectives on COVID-19's Impact on Education

Harnessing AI for Effective Distance Learning: Teachers’ Pe...

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intelligent computing, Communication, Networking and Services (ICCNS), international conference on

作者： Firas Tayseer Ayasrah Khaleel Alarabi Jihan Yousef Aprilla Fortuna Dony Novaliendry Hanan Nassar Aljermawi College of Education Humanities and Science Al Ain University Al Ain UAE Faculty of Engineering Universitas Negeri Padang Padang Indonesia Pendidikan Teknik Informatika Universitas Negeri Padang Padang Indonesia Educational college Taibah University Saudi Arabia

ISBN: (数字)9798350354690

ISBN: (纸本)9798350354706

The COVID-19 epidemic has caused significant modifications to the education sector, especially concerning the implementation of distance learning as an online learning modality technique, providing substantial obstacles for students and educators throughout the globe. Within these changing surroundings, implementing artificial intelligence (AI) throughout online courses of study has emerged as an achievable strategy to enhance creativity and effectiveness. powered by artificial intelligence, chat tools provide smooth interaction among educators and students, and based on artificial intelligence, analytics enable vital information into the results of student learning and progress, which enables data-driven decisions to improve instructional methods. However, notwithstanding the possible positive effects of AI for distant learning, issues remain, especially the need for educators to get additional instruction and the requirement to address biases in AI techniques. Understanding teachers' perspectives is vital for efficiently incorporating AI into distant instructional settings. At the same time, ongoing investigation into AI's implications for classroom procedures and outcomes for learners remains essential for shaping the coming years of education. In light of these considerations, this study seems to be about educators' engagement with distance learning during COVID-19-induced closures of classrooms, demonstrating obstacles to utilizing online resources and emphasizing the importance of grasping students’ perspectives to refine educational strategies during digitization.

关键词： COVID-19 Computer aided instruction Pandemics Navigation Education Learning (artificial intelligence) Grasping Stakeholders Artificial intelligence smart phones

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Trust Management in Cyber Physical System using Blockchain

Trust Management in Cyber Physical System using Blockchain

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international conference on computing and Networking Technology (ICCNT)

作者： Bhabendu Kumar Mohanta Utkalika Satapathy Meenu Rani Dey Soumyashree S. Panda Debasish Jena IIIT Bhubaneshwar Odisha India IIT Guwahati Assam

ISBN: (数字)9781728168517

ISBN: (纸本)9781728168524

Cyber-physical Systems (CPS) are reshaping the way of interaction with the physical world. Moreover, the true potential of CPS will be realized when a decentralized approach will be taken into account. Blockchain is an up-and-coming technology which can establish trust in CPS, where participants do not trust each other. Blockchain applications eliminate the middle man to provide trust and making the processes more efficient & cheaper. It's decentralized nature and cryptographic algorithm make it immune to attack and becomes a secure technology. When the data is stored on the blockchain it becomes immutable, ensuring trust in data. Nevertheless, this does not guarantee the trustworthiness of the device which is generating the data. We propose a blockchain-based signature storage solution to ensure trust among the participants which is further applicable to a diverse range of blockchain-based CPS applications. We have implemented our system using the Ethereum network and Docker Tools. Our proposed solution guarantees security properties i.e. device identification, authentication, integrity, and non-repudiation. Also, it reduces the storage space and storage cost than the traditional usage of blockchain in CPS.

关键词： Blockchain smart contracts Internet of Things Bitcoin Reliability intelligent sensors Authentication

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