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Traffic Sign Recognition Using distributed Ensemble Learning 4

Traffic Sign Recognition Using Distributed Ensemble Learning

引用

4th international conference on computing Methodologies and Communication, ICCMC 2020

作者： Putrevu, Satya Goutham Panda, Manoj Amrita School of Engineering Coimbatore Amrita Vishwa Vidyapeetham Department of Electronics and Communication Engineering India

ISBN: (纸本)9781728148892

Traffic sign recognition is one of the active areas of research in recent years. the automotive technology is moving towards automation in most of the aspects including traffic sign recognition. In an attempt to focus on driving and concentrate on road the driver often misses out the traffic signs, results of which may lead to catastrophic events. this can be avoided by automating the tasks of traffic sign detection and recognition. In this paper, we implement the traffic signs recognition through distributed ensemble technique (DEL), which is an efficient method to automate traffic sign detection. the primary goal of distributed ensemble learning is to decrease the complexity, reduce the training load on each model and improve the convergence. the impact of load distribution with respect to the number of workers has been studied and thereby understanding the trends of a distributed ensemble. Here we use an ensemble of CNN models to train with standard German data set. Keras is used for implementation of distributed ensemble in CNN. Detailed analysis on data distribution between workers and how it impacts the model accuracy is discussed. © 2020 ieee.

关键词： Traffic signs

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A Comparative Study of the Corpus for Story Creation System 16th

A Comparative Study of The Corpus for Story Creation System

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16th international Symposium on distributed computing and Artificial Intelligence (DCAI)

作者： Takahashi, Haruka Ueno, Miki Isahara, Hitoshi Toyohashi Univ Technol 1-1 HibarigaokaTempaku Cho Toyohashi Aichi Japan

ISBN: (纸本)9783030238872;9783030238865

In recent years, there are lots of researches to generate creations such as comics and novels by computing methods. Especially, the orders of sentences are very important for the quality of stories. thus, the aim of the researches is to construct story creation system in order to consider the flow of the story based on the sentence similarity. We suggest the possibility to create a new story by selecting sentences from exiting novels based on similarity. We indicated that the length of sentences and numbers of proper nouns tend to affect the naturalness of the created story.

关键词： Story creation system Supporting contents creation distributed representation Contents creators and artificial intelligence Searching similar sentences

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Scalable Visual Representation of sensor-Based, Nested Robot Programs 4

Scalable Visual Representation of Sensor-Based, Nested Robot...

引用

4th ieee international conference on Robotic computing (ieee IRC)

作者： Riedl, Michael Henrich, Dominik Univ Bayreuth Chair Appl Comp Sci Robot & Embedded Syst 3 Univ Str 30 D-95447 Bayreuth Germany

ISBN: (纸本)9781728152370

An easy to understand graphical representation for nested robot programs is important to allow also non-experts, who are usually unable to read source code, to understand, what a robot program is meant to do. In this paper we present a Backus-Naur form for describing sensor-based nested robot programs with a corresponding visual representation of these robot programs in the form of control flow along a timeline. To achieve this, we utilize a scalable layered representation to visualize the components of the Backus-Naur form. In addition to that, we add temporal information to the visual representation, so that the users are able to see the execution time of different parts of the program and of the program as a whole. the result of this work are two equivalent, equally powerful representations of robot programs, namely the textual representation in form of the Backus-Naur form and the scalable layered visual representation. Both can be converted into each other without loss. the evaluation shows, that the visual representation is easy to understand for non-experts and therefore suitable to use within the context of intuitive robot programming.

关键词： Graphical user interfaces Human robot interaction Robot programming Visualization

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Detection of Parcel Boxes for Pallet Unloading Using a 3D Time-of-Flight Industrial sensor 4

Detection of Parcel Boxes for Pallet Unloading Using a 3D Ti...

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4th ieee international conference on Robotic computing (ieee IRC)

作者： Monica, Riccardo Aleotti, Jacopo Rizzini, Dario Lodi Univ Parma Dept Engn & Architecture RIMLab Parma Italy Univ Parma CIDEA Ctr Interdipartimentale Energia & Ambiente Parma Italy

ISBN: (纸本)9781728152370

this work presents a 3D vision system for automatic detection of cardboard parcel boxes of known size, located on the top layer of a pallet of known height. An industrial Time-of-Flight (ToF) sensor is adopted that can operate in different illumination conditions thanks to the use of an infrared light source. the perception system is intended for application in industrial warehousing for end-of-line operations, like robot depalletizing. the proposed method does not assume any predefined layout of parcels and, therefore, it can work even with an incomplete layer of misaligned cardboard boxes. the developed solution first extracts all possible object hypotheses, then an optimization problem is solved, based on a genetic algorithm, to exclude conflicts. Experiments have been performed on a real dataset including complex configurations of tightly packed parcels.

关键词： Object detection Range sensing Warehouse automation

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Reducing IoT Bandwidth Requirements by Fog-Based distributed Hash Tables 4

Reducing IoT Bandwidth Requirements by Fog-Based Distributed...

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4th international conference on Cloud and Internet of things (CIoT)

作者： Rabay'a, Ahmad Kudla, Pascal Kubitza, Lukas Graffi, Kalman Schoettner, Michael Heinrich Heine Univ Dusseldorf Inst Comp Sci Dusseldorf Germany

ISBN: (纸本)9781728195414

Internet-of-things (IoT) devices often rely on cloud services for computations and data management. As the number of IoT devices is growing fast, the Internet connection to the cloud data-center can become a bottleneck regarding bandwidth and latency. Fog computing has been introduced by Cisco to address these challenges. the proposed peer-to-peer (p2p) Fog model allows fog-nodes to cooperate and reduce the bandwidth requirement to the cloud and the system as a whole. In this publication we evaluate Pastry and CAN for implementing a DHT on fog nodes compared to implementing Chord on fog nodes. the simulation shows that Pastry offers better results in terms of bandwidth consumption compared to non-cooperative Fog computing, Chord Fog, and CAN Fog models. the overall reduction in bandwidth reflects as well to reduction in costs.

关键词： Cloud computing Fog computing Internet-of-things Peer-to-peer Bandwidth Simulation

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distributed computing framework of intelligent sensor network for electric power internet of things 9

Distributed computing framework of intelligent sensor networ...

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9th ieee Joint international Information Technology and Artificial Intelligence conference, ITAIC 2020

作者： Li, Dawei Yu, Ruimo Song, Chunhe Li, Shu Jia, Gengtao Zhou, Xiaoli Start Grid Shanghai Information Telecommunication Company Shanghai200122 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

the power IoT terminal environment is complex, and current smart sensor sensors have problems such as poor networking capabilities and large processing delays, and few specific edge-side automatic networking capabilities. this paper analyzes and elaborates the distributed intelligent sensor computing framework from the perspective of edge intelligent networking, designs a computing model for intelligent sensors of power Internet of things terminals, and gives the edge-based deployment of convolutional neural network architecture, data aggregation, model training, and intelligent reasoning. Finally, the validity of the proposed framework model is verified by public sample data. © 2020 ieee.

关键词： Internet of things

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Internet of things in Smart Agriculture - Possibilities and Challenges 4

Internet of Things in Smart Agriculture - Possibilities and ...

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4th ieee international conference on Smart systems and Technologies (SST)

作者： Grgic, Kresimir Zagar, Drago Balen, Josip Vlaovic, Jelena Fac Elect Engn Comp Sci & Informat Technol Osijek Croatia

ISBN: (纸本)9781728197593

Intensive development of the Internet of things (IoT) technologies enabled different novel applications, including smart agriculture systems. Smart agriculture concept connotes modern technology-based and information-based approach to different processes in agriculture. From the technical perspective, IoT technologies represent the basis for the smart agriculture networks. the paper analyzes possible applications of agricultural sensor networks. It gives an overview of different sensor types, as well as different communication technologies suitable for the use in agricultural sensor networks. the analysis of security aspects of smart agriculture systems is given. Open problems and directions for future development are emphasized.

关键词： internet of things smart agriculture wireless sensor network

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Research on Fault Prediction and Diagnosis of Superconducting System Based on Deep Learning

Research on Fault Prediction and Diagnosis of Superconductin...

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ieee international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Zhang Xize Xie Wei Zheng Jian Zong Xihua Jiao Ting Zhang Dayi Shanghai International Superconducting Science and Technology Co. Ltd. Shanghai China State Grid Shanghai Municipal Electric Power Company Shanghai China Shanghai Electric Cable Research Institute Co. Ltd. Shanghai China

ISBN: (纸本)9781665428408

distributed sensors are indispensable for collecting and controlling the necessary physical quantities in increasingly complex superconducting systems. they provide a reference for the monitoring and maintenance of the system status. With the continuous increase of system complexity, traditional maintenance strategies are difficult to directly apply to highly coupled superconducting systems. In order to make a more accurate assessment of the health status of the superconducting system and take full advantages of deep learning in tasks such as time series prediction, fault detection and diagnosis, we use a deep neural network to explore the time series prediction task with data collected by the superconducting system sensors. Combined with the network residual structure, the performance of the neural network is improved effectively. At the meantime, in order to solve the problem of extremely unbalanced positive and negative samples in the sensor data recording in the superconducting system, TIMEGAN is used to expand the samples. the experiment showed that the presented superconducting fault prediction and diagnosis system in the paper is effective and efficient.

关键词： Deep learning Electrical engineering Fault detection Time series analysis Neural networks Maintenance engineering sensor systems

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An Overview of Routing Techniques in WSNs 4

An Overview of Routing Techniques in WSNs

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4th international conference on Intelligent computing in Data Sciences (ICDS)

作者： Moundounga, Anselme Russel Affane Satori, Hassan Satori, Khalid Sidi Mohammed Ben Abdallah Univ Fac Sci Dhar Mahraz Dept Math & Comp Sci Fes Morocco

ISBN: (纸本)9781728180847

the rapid progress of wireless technology constraint scholars for working hard to propose advanced methods and techniques to contribute and solve the most common issues of wireless sensor networks. these sensor networks are, generally a set of huge sensor nodes that work with limited resources, batteries lifetime, storage capability, and are generally deployed in regions where human access is often impossible. In this work, we analyze and describe commonly routing techniques and adapted algorithms take out of machine learning designed for wireless sensor networks. We aim to give readers a global view and up-to-date vision of the actual proposed techniques and bring an overview of them. We explore commonly routing mechanisms recently proposed and the popular routing protocols are treated. We target to help better acknowledgment and understanding of the current routing protocols for wireless sensor networks that can be dealt with to further research.

关键词： Wireless sensor Network(s) Node(s) Routing Protocol Algorithm Energy Consumption

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Context-Aware Anomaly Detection for the distributed Data Validation Network in Industry 4.0 Environments

Context-Aware Anomaly Detection for the Distributed Data Val...

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4th World conference on Smart Trends in systems, Security and Sustainability (WorldS4)

作者： Wallis, Kevin Schillinger, Fabian Backmund, Elias Reich, Christoph Schindelhauer, Christian Univ Appl Sci Furtwangen Furtwangen Germany Univ Freiburg Freiburg Germany

ISBN: (数字)9781728168234

ISBN: (纸本)9781728168234

In the Industry 4.0 context, especially when considering large factories producing costly goods, monitoring sensor values is important to ensure high quality. this reduces large costs for mending faulty products or recall of those. Different approaches are used to ensure efficient monitoring and validation of sensor values. the distributed Data Validation Network (DDVN) can remove single points of failure. Still, not every anomaly in the validation procedure means that errors or attacks have occurred. Oilier reasons like maintenance procedures, updates of firmware, or changed materials can lead to False-Positive (FP) or False-Negative (FN) detection of errors. To reduce these, we incorporate context information in the validation procedure. Further, we show how the appropriate context information is selected and used on a real machine data set.

关键词： Anomaly Detection Context-Awareness distributed Data Validation Network Industry 4.0

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