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***: An open data exchange for the web of things

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IEEE Annual conference on Pervasive computing and Communications Workshops (PerCom)

作者： Vipul Gupta Arshan Poursohi Poornaprajna Udupi Sun MicroSystems Laboratories Inc. Menlo Park CA USA

Tiny, wireless, sensors embedded in a large number of Internet-capable devices-smart phones, cameras, cars, toys, medical instruments, home appliances and energy meters-can generate an enormous volume of small bits of data such as temperature and humidity readings, GPS co-ordinates and energy usage. the real value of this data lies in its analysis, which can lead to significant insights and actions that enhance the health of our planet and its populations. We have developed a web-based infrastructure called *** for storing, sharing, searching, visualizing and analyzing data from heterogeneous devices and facilitating easy interaction amongst devices and end users through an open, REST-based API. this demonstration starts off with a brief walkthrough of the *** portal as we describe its data abstractions, APIs and different views, e.g. dashboard view for monitoring the health of different sensor datastreams and their access permissions and map view for geographical search. Next we show the platform's visualization capabilities, in particular LivePlots-interactive plots of different types which can be embedded into web-based applications hosted elsewhere and are rendered using the latest data from our service each time that external webpage is reloaded. We discuss data-centric collaborations and social interactions made possible by features such as tagging, searching and sharing with fine-grained privacy controls. We demonstrate notifications that are automatically generated when sensor data meeting user-specified criteria is inserted. these notifications allow the composition of ?mashups? of heterogeneous sensors and actuators (e.g. a humidity sensor from one vendor controlling a sprinkler system from another). Finally, we present our early explorations into reprogramming and remote management of devices.

关键词： Temperature sensors Humidity Data visualization Automatic control Sensor systems Wireless sensor networks Internet Cameras Instruments Home appliances

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To Track the Availability of an Unoccupied Classroom using RFID

To Track the Availability of an Unoccupied Classroom using R...

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Annual Information Technology, Electromechanical Engineering and Microelectronics conference (IEMECON)

作者： Jayasudha Koti Stan Nadar Ojas Kambli Shobha Koli Dept of Electronics and Telecommunication Engineering St Francis Institute of Technology Mumbai India

ISBN: (数字)9798350387315

ISBN: (纸本)9798350387322

Integration of Information, Communication, and Technology (ICT) in teaching learning process incorporates computer-based communication into daily instructional process in the classroom. Integration of ICT in teaching helps the students to understand and analyze the complex concepts in a simpler manner. the use of technology that supports ICT elements and components contributes to an interesting approach, effective and creative learning in students. this acts as an add on supplement to the conventional method of chalk board teaching. But fear of equipment failure is always a setback and becomes a major problem. Technical problems create a source of frustration and interruptions in the teaching learning process. In a real time, scenario one approach is to go for technical assistance to resolve and the second one is to shift to ICT enabled unoccupied classroom. If the technical issue is not resolved in the stipulated time, then the next step is to shift to the unoccupied classrooms by checking multiple classrooms physically. It’s really a time consuming and tedious process to track the unoccupied classroom and it also effects the continuity and students’ attention. In our paper an alternative solution has been addressed by integrating various technologies. the objective of the paper is to track the availability of unoccupied classroom to overcome the unpredictable circumstances in teaching learning process within a fraction of seconds by clicking the google sheet link shared with the concerned faculty members. this has been implemented by using RFID a wireless technology, Arduino UNO based on the ATmega328P microcontroller, an open-source firmware, Node MCU a low-cost open source IoT (Internet of things) Platform developed for the ESP8266 Wi-Fi chip, Arduino IDE a software application and Google Scripts as a scripting platform to enable the Google Sheets API in the Google Cloud Console. As per the knowledge of the authors the above said issue has not been addressed in

关键词： Wireless communication Cloud computing Education Microwave devices Microwave theory and techniques Software real-time systems Internet of things Wireless fidelity Radiofrequency identification

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SentiGCN: Graph Contrastive Learning for Recommendation Based on Sentiment Analysis

SentiGCN: Graph Contrastive Learning for Recommendation Base...

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Information systems and computing Technology (ISCTech), international conference on

作者： Fei Lei Qian Cao Xiaofeng Wang Dun Ao College of Artificial Intelligence and Automation Beijing University of Technology Bei Jing China

ISBN: (数字)9798350379860

ISBN: (纸本)9798350379877

Recommendation systems play a critical role in web applications (e.g. e-commerce sites, etc.), so as to alleviate data overload and suggest preferred items for users. Due to the limited interactions between users and items in real-life scenarios, contrastive learning has recently been adopted to enhance recommendation systems. However, most existing CL(Contrastive Learning)-based methods typically construct contrastive views through node or edge perturbation, which may disrupt the intrinsic semantic structure in user-item interaction graphs. And, these methods also neglect user preferences and emotional tendencies in reviews. therefore, this paper proposes a novel sentiment-aware graph contrastive learning method (SentiGCN), which can comprehensively explore information from both review content and user-item graphs. Firstly, sentiment information is extracted from reviews using Natural Language Processing (NLP) tools. then, the two graph structures integrating this information are constructed. Moreover, two contrastive strategies are designed to incorporate self-supervised signals. For the user-item interaction graph with sentiment features, a scheme involving the addition of random noise in the embedding space is applied for graph augmentation. For the item-item neighbor graph based on sentiment similarity, a cross-layer contrastive scheme is implemented to further explore the potential associations between items. Finally, extensive experiments on three datasets confirm the efficacy of SentiGCN.

关键词： Sentiment analysis Cross layer design Reviews Perturbation methods Semantics Noise Neural networks Contrastive learning Recommender systems Text processing

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Performance comparison of a platooning application using the IEEE 802.11p MAC on the control channel and a centralized MAC on a service channel

Performance comparison of a platooning application using the...

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IEEE international conference on Wireless and Mobile computing, Networking And Communications (WiMob)

作者： Annette Böhm Magnus Jonsson Elisabeth Uhlemann CERES (Centre for Research on Embedded Systems) Halmstad University Halmstad Sweden

Recent advances in cooperative driving hold the potential to significantly improve safety, comfort and efficiency on our roads. An application of particular interest is platooning of trucks, where it has been shown that keeping a minimum inter-vehicle distance results in considerably reduced fuel consumption. this, however, puts high requirements on timeliness and reliability of the underlying exchange of control messages between platoon members. the European profile of IEEE 802.11p, recently adopted by ETSI, defines two message types to this end, periodic beacons for basic cooperative awareness (CAM) and event-triggered decentralized environmental notification messages (DENM), both of which will use one common control channel. IEEE 802.11p employs a random medium access protocol, which may experience excessive delays during high network loads. To mitigate these effects, ETSI standardizes a decentralized congestion control algorithm to, e.g., lower the CAM update frequency during high loads. However, this may prevent proper functionality of a platooning application. In this paper we propose a solution that instead uses a dedicated service channel for platooning applications and compare its performance to standard-compliant IEEE 802.11p inter-platoon communication on the control channel. Service channels typically have less strict requirements on send rates, data traffic types and medium access methods. Our service channel solution combines a random access phase for DENM with a centralized, scheduled access phase for CAM. Using a service channel enables us to guarantee timely channel access for all CAM packets before a specified deadline while still being able to provide a reasonable DENM dissemination delay.

关键词： Computer aided manufacturing Vehicles real-time systems Delays Telecommunication standards Media Access Protocol Safety

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CKDNet: A Cascaded Knowledge Distillation Framework for Lightweight Stereo Matching

CKDNet: A Cascaded Knowledge Distillation Framework for Ligh...

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Intelligent computing and Human-Computer Interaction (ICHCI), international conference on

作者： Baiyu Pan Jianxing Pang Jun Cheng Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Research Insititue Ubtech Corporation Shenzhen China

ISBN: (数字)9798350368284

ISBN: (纸本)9798350368291

In this paper, we propose an efficient cascaded knowledge distillation framework which is tailored for the refinement of lightweight stereo matching network. Lightweight network is the feasible means to achieve real-time depth estimation on embedded devices, but often suffered from reduced accuracy. Despite previous attempts to enhance performance through the introduction of new modules, the resulting improvements are modest. To address this challenge, our framework integrates knowledge distillation with three models to cascaded optimize the performance of lightweight architectures. Our contributions include three folds: First, we demonstrate the effectiveness of knowledge distillation for stereo matching and its transferability across different scale models. Second, we conduct a comprehensive comparison of distillation methods and propose the cascade distillation framework to improve the accuracy of lightweight model. third, we proposed an adjustable compression module to enable flexible changes of model size by demands. through extensive experimentation and evaluation, we validate the efficacy of our approach. Our lightweight model has archived 0.87px on Sceneflow(EPE), and 2.26% on KITTI2015(D1). And only 12 ms for a single-time inference.

关键词： Training Performance evaluation Knowledge engineering Human computer interaction Accuracy Depth measurement Neural networks Estimation Computer architecture real-time systems

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Kinematic Control of a Mecanum Mobile Robot using time-Varying Model Predictive Control

Kinematic Control of a Mecanum Mobile Robot using Time-Varyi...

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RSI/ISM international conference on Robotics and Mechatronics (ICROM)

作者： Seyed Ali Shahzadeh Fazeli Sohrab Allahyari Arman Gholibeikian S. Ali A. Moosavian Dept. of Mechanical Engineering Advanced Robotics & Automated Systems (ARAS) Laboratory Center of Excellence in Robotics & Control K. N. Toosi University of Technology Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

Mecanum wheeled mobile robots have increasingly caught researchers' attention due to their wide range of applications and higher maneuverability. However, their complex structure makes their trajectory tracking and control problem more challenging. this paper presents a cascaded controller for trajectory tracking of a four-wheel Mecanum mobile robot. the cascaded controller consists of a linear time-varying model predictive controller (LTV-MPC) and an inner PID controller. the proposed controller does not require the system's dynamics model. To this end, the linear time-varying error model used to design the MPC is obtained from the robot's kinematics model. the angular velocities obtained from the predictive controller are then mapped into the required commands for the DC motors using a PID controller. the PID controller is fine-tuned considering the motor's dead zone using the Genetic Algorithm. Simulations and experimental results demonstrate the superiority of the cascaded controller over the regular LTV-MPC. the proposed algorithm can also be used for other real-time implementations of robotic tasks.

关键词： Trajectory tracking System dynamics Robot kinematics Predictive models DC motors Angular velocity real-time systems Mobile robots Voltage control Genetic algorithms

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Obstacles and Opportunities Provided using the Impact of Fifth-Generation Networks on Cybersecurity

Obstacles and Opportunities Provided using the Impact of Fif...

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Annual Information Technology, Electromechanical Engineering and Microelectronics conference (IEMECON)

作者： Mani Gopalsamy P. Deepalakshmi Senior Cybersecurity Specialist Coolsoft Louisville KY Kalasalingam Academy of Research and Education Tamil Nadu India

ISBN: (数字)9798350387315

ISBN: (纸本)9798350387322

Communication, data access, and our interactions with the digital world are all going to undergo a sea change as a result of the introduction of fifth-generation (5G) networks. through its promise of faster speed, decreased latency, and wider connection, fifth-generation wireless (5G) technology is positioned to enable a wide range of applications, ranging from improved mobile broadband to the Internet of things (IoT). When it comes to cybersecurity, however, this technological leap also brings with it a new set of challenges and opportunities. As the landscape of cyber threats continues to grow, it is necessary to reevaluate the security measures that are currently in place. this is because 5G networks are becoming the backbone of vital infrastructure and enable the proliferation of connected devices. In this study, the influence of 5G networks on cybersecurity is investigated, with a particular emphasis placed on the challenges and opportunities that are brought about by this revolutionary technology. An examination of the architectural and operational changes that 5G brings about, such as network slicing, software-defined networking (SDN), and network function virtualisation (NFV), as well as the consequences these changes have for security, is the first step in this exploration. We then proceed to conduct an analysis of the various vulnerabilities that 5G networks may reveal, which includes the possibility of additional attack surfaces, the risk of assaults on supply chains, and the difficulties associated with securing a diversified ecosystem of Internet of things devices. In addition to this, we explore the prospects that 5G networks bring for the optimisation of cybersecurity. the capacity to implement more advanced security procedures, the possibility of real-time threat detection and response, and the facilitation of secure, high-speed data transfer for security applications are some of the benefits this technology offers. When it comes to improving securit

关键词： Industries 5G mobile communication Network slicing Supply chains Ecosystems Machine learning real-time systems Internet of things Stakeholders Computer security

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Integrated Hierarchical Attention-Convolutional Temporal Network (HACTNet) and Dynamic Hybrid Neuro-Fuzzy Decision Network (DHNFD-Net) for Robotic Automation-Enabled Prediction of Breast Cancer Histological Subtypes and Lymph Node Involvement

Integrated Hierarchical Attention-Convolutional Temporal Net...

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Intelligent systems and embedded Design (ISED), international conference on

作者： thirusubramanian Ganesan Mohanarangan Veerappermal Devarajan Akhil Raj Gaius Yallamelli Vijaykumar Mamidala Rama Krishna Mani Kanta Yalla Gobinath C Jyotiranjan Swain Cognizant Technology Solutions Texas USA Ernst & Young (EY) Sacramento USA Amazon Web Services Inc Seattle USA Conga (Apttus) Broomfield CO USA Amazon Web Services Seattle USA School of Comuting and Information Technology REVA University Bangalore

ISBN: (数字)9798331522612

ISBN: (纸本)9798331522629

the model proposed in this work involves the usage of Hierarchical Attention Convolutional Temporal Network(HACTNet) and Dynamic Hybrid Neuro-Fuzzy Decision Network (DHNFD-Net) for its computational methodologies to automate breast cancer histological subtype and lymph node involvement predictions. Feature extraction and neural networks with fuzzy logic rules are designed to be highly invariant to P300 activity, which leads to highly accurate prognostic and diagnostic rule generation along with robotic automation in an integrated solution. Breast cancer is the leading cause of death worldwide, necessitating better diagnostics and personalised therapy. Build HACTNet and extract spatial-temporal features effectively. Apply DHNFD-Net for interpretable and knew perception-based decision-making. It is necessary to turn to AI as the conventional methods of pesticides are less precise, Less Explainable, and Less Scalable. Integrate these models into a robotic automation framework for real-time diagnostics. the latter includes hierarchical attention, convolutional layers for ACTNet, and neural networks with fuzzy logic for interpretable lymph node predictions of DHNFD-Net. the integrated system automates picture processing, categorization, and decision-making. this system provides 96% classification accuracy, 0.95 interpretability, 95% sensitivity and 65 images/second scalability. Inference latency has been reduced to 110 ms, ensuring real-time applicability. A proposed methodology recommends a uniform, interpretable, and scalable diagnostic framework for breast cancer, opening a wide-field vista apart all over the current methods of obtaining more significant accuracy and efficiency, thus allowing precision, real-time application, and clinical decision-making skills(Graphics-Breast cancer diagnostic framework).

关键词： Fuzzy logic Accuracy Automation Decision making Neural networks Feature extraction Breast cancer real-time systems Transient analysis Lymph nodes

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Static Modeling of A Soft Robotic Manipulator Using Neural Networks and Computer Vision Techniques

Static Modeling of A Soft Robotic Manipulator Using Neural N...

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RSI/ISM international conference on Robotics and Mechatronics (ICROM)

作者： Ali Shojaeezadeh Pouya Firuzy Rad Hamed Ghafarirad Mechanical Engineering Department Amirkabir University of Technology (Tehran Polytechnic) Tehran Iran

ISBN: (数字)9798331529734

ISBN: (纸本)9798331529741

this research explores the static modeling of a planar soft robotic arm composed of two parallel silicon-based actuators using neural networks. Soft robots, characterized by their pliable structure and pneumatic actuation, present challenges in traditional control and modeling due to their nonlinear behavior and material flexibility. Conventional methods often fail to accurately predict their motion, especially under varying internal pressures and structural imperfections. In contrast, neural network-based approaches offer robust solutions by effectively capturing these complexities through data-driven techniques. Utilizing a Levenberg-Marquardt algorithm for training, this study develops a neural network model that predicts the 2D spatial position of the robotic arm's end-effector based on input pressure variables. Experimental data, obtained via image processing techniques for precise position tracking, informs the model's training and validation phases. Results demonstrate high accuracy in predicting end-effector positions, validated by low mean squared errors and high coefficients of determination. this approach not only advances static modeling capabilities for soft robotic systems but also lays groundwork for future dynamic modeling and real-time control applications.

关键词： Training Actuators Computational modeling Neural networks Soft robotics Predictive models Pneumatic systems End effectors real-time systems Long short term memory

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FPGA implementation of 2D cross-correlation for real-time 3D tracking of deformable surfaces

FPGA implementation of 2D cross-correlation for real-time 3D...

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international conference on Image and Vision computing New Zealand, IVCNZ

作者： Amir HajiRassouliha thiranja P. Babarenda Gamage Matthew D. Parker Martyn P. Nash Andrew J. Taberner Poul M. F. Nielsen Auckland Bioengineering Institute The University of Auckland Auckland Auckland NZ The University of Auckland Department of Engineering Science Auckland New Zealand

3D surface measurements have many industrial and medical applications. We have previously used 3D surface deformation and tracking to identify mechanical properties of the skin. To be able to detect dynamic changes in the surface of the skin we need to have a real-time 3D measurement system. A significant portion of the computation time for tracking the changes is spent during 2D cross-correlation of surface images. this study focuses on improving cross-correlation speed by taking advantage of parallel computation in field programmable gate arrays (FPGAs). We have implemented variable size 2D cross-correlation computations using the Xilinx System Generator tool in the Virtex-6 LX240T FPGA. We have also proposed a hierarchical approach for finding the cross-correlation peak in order to efficiently use our method for different image sizes. Furthermore, the use of RAM blocks instead of shift registers in our design has lowered the resource requirements compared with other FPGA implementations. Preliminary results for our special design indicate better than 200 times speed up compared with a PC with an Intel Xeon E5620 CPU (2.4 GHz clock speed, 4 cores and 8 threads) and 12 GB DDR3 RAM and also 190 times speed up in comparison to an NVidia GForce GT 525M as the graphics processing unit (GPU).

关键词： Field programmable gate arrays Random access memory three-dimensional displays real-time systems Clocks Graphics processing units Synchronization

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