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Exploration and Practice of Project-driven smart Teaching Model in the Context of Emerging Technologies

Exploration and Practice of Project-driven Smart Teaching Mo...

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2022 international conference on Education, Network and Information Technology, ICENIT 2022

作者： Hao, Juan Liu, Xiaoqun Wang, Jiao Ma, Pingyan School of Information Engineering Hebei University of Architecture Zhangjiakou China

ISBN: (纸本)9781665463072

In order to cultivate excellent university graduates with strong application ability and innovation spirit, with the background of new engineering construction and engineering certification as the opportunity, taking social demand as the guide and combining the type of application-oriented schools, taking the teaching of Computer Network course of computer-related majors as an example, fully using the project-driven teaching method, the 'Internet+' environment With the help of emerging technologies such as cloud computing and big data, we adopt the model of diversified intelligent teaching, comprehensive teacher assessment and diversified student assessment to implement the fundamental task of establishing moral education, cultivate outstanding engineers who meet the needs of society and improve students' creativity and competitiveness in the employment process. The new form of project-driven intelligent teaching system is explored in the context of emerging technologies, with a view to providing reference and learning for the reform and innovation of related teaching in domestic higher education institutions. © 2022 IEEE.

关键词： Teaching

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Edge Intelligence Based Garbage Classification Detection Method 1

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3rd EAI international conference on Edge computing and IoT, EAI ICECI 2022

作者： Zhu, Ruijia Liu, Yiwen Gao, Yanxia Shi, Yuanquan Peng, Xiaoning School of Computer and Artificial Intelligence Huaihua University Huaihua418000 China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000 China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000 China

ISBN: (数字)9783031289903

ISBN: (纸本)9783031289897

To address the problem that the classification and cleaning of garbage in city streets is always ineffective nowadays, the paper proposes a garbage detection method based on edge intelligence. The edge intelligence not only reduces the computational load of the cloud and speeds up the data transmission, but also greatly reduces the data transmission cost. First, images of city streets are collected and uploaded to the edge device via mobile devices in various locations in the city. Then, the edge server is used to temporarily store the image information, and the PeleeNet model deployed on it is used to identify and classify various kinds of garbage, and then visualize the information of each street. Finally, the street garbage information is transmitted to the cloud, which provides a detailed picture of the city’s garbage situation and facilitates city management. In this paper, the PeleeNet model is compared with ResNet, DenseNet and MobileNet models. The results show that the edge devices equipped with PeleeNet model not only have the fastest computation speed and the highest accuracy, but also occupy the least memory. It is fully demonstrated that the method studied in the paper can be applied to the problem of litter detection in urban streets. © 2023, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： smart city

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Secure and Authenticate Communication by using SoftSIM for intelligent Transportation System in smart Cities

Secure and Authenticate Communication by using SoftSIM for I...

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2020 international E- conference on data analytics, intelligent Systems and Information Security, ICDIIS 2020

作者： Yadav, Shalini Rishi, Rahul MDU Rohtak India

intelligent Transportation System is a field which is daily paving way for new technologies. Communication in vehicular devices has paved way for security breaches. Vehicle-to-everything connects each and every device to our vehicle just like Internet of Things connects everything to the internet. Everything which is connected to the internet, is prone to security attack. It is very difficult to track the source of the information. Authentication is a big issue and has to be solved. This paper has provided a cognitive approach to address this problem effectively in ITS. A softSIM- similar to the hardware SIM has been proposed. An architecture of the softSIM is designed. A novel algorithm for authenticating the on-board softSIM with the operator has been developed. The performance analysis of softSIM is compared with regular device users. The paper also incorporates future scope as well as business case of the study. The soft SIM will be part of on-board unit and shall come programmed from manufacturer side. This has provided cost effective solution and saved the space that was needed for the hardware SIM. © Published under licence by IOP Publishing Ltd.

关键词： smart city

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Measuring the Micro Deformation and Crack of Rock Surface and Make Robot intelligent Walking Path from Pulse Lidar Profiler

Measuring the Micro Deformation and Crack of Rock Surface an...

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2020 international conference on Modeling, Big data analytics and Simulation, MBDAS 2020

作者： Zhou, Tao Tao, Li School of Mechanical Engineering Jiangsu Ocean University Liangyungang Jiangsu222005 China

Derived from accumulated lidar point cloud, 3D model building appears to be a crucial technology for autonomous navigation of car. In this paper, we present a method of monitoring rock wall cracks and micro rock top displacement of underground tunnel by using pulse lidar profiler, so as to achieve the purpose of timely and real-time early warning. With the help of the Internet of things, cloud data and fog computing, the pulse lidar profiler is regarded as an extended terminal of cloud computing. It performs many tasks such as daily contour data and key electronic equipment monitoring status data recording, danger alarm calculation and emergency situation uploading to the cloud database. © Published under licence by IOP Publishing Ltd.

关键词： Optical radar

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The Current Situations of Mobile Assisted Language Learning

The Current Situations of Mobile Assisted Language Learning

引用

international conference on Machine Learning and Big data analytics for IoT Security and Privacy, SPIoT 2020

作者： Ma, Guihua Xi’an International University Xi’an710077 China

ISBN: (纸本)9783030627454

The pervasive use of mobile devices has profoundly influenced people’s life style and leaning style. Currently, it is pretty popular to use smart phones, IPADs, or PCs to have language learning. Mobile assisted language learning (MALL) makes it possible for language learning to occur at any time and place, and it can also compensate the interactive, cooperative and authentic learning environment which is often lack in tradition foreign language learning classroom. The paper mainly discussed the current situation of MALL and its application in the foreign language learning and teaching by summarizing the definition, characteristics, merits and flaws of MALL. It concluded that foreign language teachers should fully consider the functions and advantages of different mobile devices and design appropriate tasks according to learners’ cognitive level and foreign language proficiency in order to simulate learners’ interest in MALL and also encourage learners to develop their own learning strategies in MALL so as to promote their independent and autonomous learning ability. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computer aided instruction

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Healthcare analytics: overcoming the barriers to health information using machine learning algorithms

Healthcare analytics: overcoming the barriers to health info...

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international conference on Image Processing and Capsule Networks, ICIPCN 2020

作者： Veena, A. Gowrishankar, S. Department of Computer Science and Engineering Dr. Ambedkar Institute of Technology Bengaluru560056 India Affiliated to VTU Belagavi590018 India

ISBN: (纸本)9783030518585

In recent years, the data processed by the healthcare domain is increasing at an unprecedented rate accompanied by rich knowledge for medical research but low information has led to Healthcare analytics. Healthcare analytics collects the data from a myriad of areas such as clinicians, hospitals, government agencies, health insurance, pharmaceutical, and biotechnology agencies and allows for the examination of trends and patterns in various healthcare data. Based on this pattern, healthcare analytics determines how healthcare can be upgraded while constraining exorbitant spending. The retrieval of a pattern from healthcare data pertinent to the healthcare application and input to the Machine Learning algorithm is decided based on the data features. Feature selection approaches are developed to choose a subset of features that explain the details to achieve a more appropriate and compact depiction of the knowledge available. This paper summarizes Feature Selection algorithms and presents the challenges involved in healthcare data and also present an abstract architecture of data analytics in healthcare domain. Various algorithms and techniques in machine learning are compared and classified based on the applications of Healthcare analytics. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： data analytics

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Towards Trajectory Prediction-Based UAV Deployment in smart Transportation Systems

Towards Trajectory Prediction-Based UAV Deployment in Smart ...

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international conference on Computer Communications and Networks (ICCCN)

作者： Fan Liang Xing Liu Nuri Alperen Kose Kubra Gundogan Wei Yu Dept. of Computer Science Sam Houston State University USA Dept. of Computer and Information Sciences Towson University USA

$A$ smart transportation system (i.e., intelligent transportation system) refers to a transportation critical infrastructure system that integrates advanced technologies (e.g., networking, distributed computing, big data analytics, etc.) to improve the efficiency, safety, and sustainability of the transportation system. However, the rapid increase in the number of vehicles on roads and significant fluctuations in the flow of traffic can cause the coverage holes of Road Side Units (RSUs) and local traffic overload in smart transportation systems, which can negatively affect the performance of systems and causes accidents. To address these issues, deploying Unmanned Aerial Vehicles (UAVs) as mobile RSUs is a viable approach. Nonetheless, how to deploy UAVs to the optimal position in the smart transportation system remains an unsolved issue. This paper proposes a Vehicle Trajectory-based Dynamic UAV Deployment Algorithm (VTUDA). The VTUDA utilizes vehicle trajectory prediction information to improve the efficiency of UAV deployment. First, we deploy a distributed Seq2Seq-GRU model to the UAVs and train the model. We leverage the well-trained model to predict vehicle trajectory. VTUDA then uses the predicted information to make informed decisions on the optimal location to position the UAVs. Further-more, VTUDA considers both the condition of communication channels and energy consumption during the deployment process to ensure that UAVs are deployed to optimal positions. Our experimental results confirm that the proposed VTUDA can effectively improve the deployment of UAVs. The experimental results also demonstrate that VTUDA can significantly enhance vehicle access and communication quality between vehicles and UAVs.

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data analytics Based Multimodal System for Fracture Identification and Verification in CBIR Domain

Data Analytics Based Multimodal System for Fracture Identifi...

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international conference on intelligent Manufacturing and Energy Sustainability, ICIMES 2020

作者： Manjula Gururaj Rao, H. Nagaraja, G.S. JAIN University Bangalore India R V College of Engineering Bangalore India

ISBN: (纸本)9789813344426

Bone fracture is a typical human challenge related to excessive stress being forced on bone or simple mistakes occur in the bone as a result of the osteoporosis and malignancy of the body. Precise analysis of bone fracture is also a significant feature of the medical profession. X-ray/CT-scans are used in this study to assess bone fracturing. False and misjudging of fracture detection can happen to reduce this and to help or assist the doctor, we propose multimodal integrated techniques to identify the fracture. In this paper, it elaborates the different combination and integrations of fracture identification and detection methods to identify and detect the area of the fracture. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： data analytics

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A Method of Flow Compensation Incentive based on Q-Learning for User Privacy Protection 18

A Method of Flow Compensation Incentive based on Q-Learning ...

引用

18th IEEE international conference on Mobile Ad hoc and smart Systems (IEEE MASS)

作者： Chen, Lu Zhang, Degan Zhang, Jie Zhang, Ting Fan, Hongrui Du, Jinyu Tianjin Univ Technol Minist Educ Key Lab Comp Vis & Syst Tianjin Key Lab Intelligent Comp & Novel Software Tianjin Peoples R China Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing Peoples R China Tianjin Univ Sport Sch Sports Econ & Management Tianjin Peoples R China

ISBN: (纸本)9781665449359

To solve the incentive problem for MCS (Mobile Crowdsensing) users based on privacy protection, we proposed an incentive method of flow compensation for the privacy protection of users and designed a system model which combined MCS with MEC (Mobile Edge computing). The EC (Edge Center) uploaded the perception results to the MCS diminishing MCS's overhead. We also designed an incentive model based on Q-Learning algorithm for privacy protection of user data, which can reduce the incentive expenditure and improve users' enthusiasm for participation. Compared with the existing incentive method based on privacy protection, our method improves the perceptual result precision, decreases MCS cloud overhead, and declines flow compensation cost.

关键词： mobile crowdsensing mobile edge computing privacy protection incentive strategy machine learning

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Temporal Modeling of On-Street Parking data for Detection of Parking Violation in smart Cities 8th

Temporal Modeling of On-Street Parking Data for Detection of...

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8th international conference on Frontiers of intelligent computing: Theory and Applications, FICTA 2020

作者： Sahoo, Shiv Kumar Panigrahi, Niranjan Mohapatra, Debasis Panda, Asutosh Sinha, Arvind Parala Maharaja Engineering College BerhampurOdisha India National Institute of Technology RaipurChhattisgarh India

ISBN: (纸本)9789811557873

With the increase in number of vehicles, the requirement of intelligent parking management is indispensable in smart cities. One of the major requirements in smart parking system is handling parking violations efficiently. The parking violation generally includes parking beyond allowed time. To detect parking violations and to manage it efficiently, the parking data collected through field sensor devices need to be analyzed intensively and thoroughly. To this end, this paper has presented temporal analysis of on-street parking data of Melbourne city and proposed a novel mathematical model and curve-fitting algorithm using quasi-Newton method to detect parking violation. The proposed model is validated with real dataset through simulation with a sum of squared error of 4.888 × 10- 7. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Curve fitting

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