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A Prediction of PM2.5 Concentration Based on Temporal-Spatial Fusion Model

A Prediction of PM2.5 Concentration Based on Temporal-Spatia...

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international conference on Computational intelligence and applications (ICCIA)

作者： Sifan Su Cui Zhu Wenjun Zhu Lubuto Kaunda Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (纸本)9781538695722;9781538695715

In this paper, a temporal-spatial fusion model is proposed for PM2.5 concentration prediction. The model uses historical PM2.5 concentration and meteorological data as input of the model to make hourly predictions of PM2.5 concentration. This model consists of three parts: 1) Long short-term memory neural network predictor based on time dimension, 2) Artificial neural network predictor based on spatial dimension, 3) Model tree predictor based on temporal-spatial fusion. This method combines the forecast results of two dimensions in space and time dynamically, as the spatial and temporal correlation of data is considered. Experimental results show this model performs better than predicting from a single dimension, confirming the effectiveness of the model.

关键词： Predictive models Atmospheric modeling Artificial neural networks Neurons Data models Wind speed Correlation

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Technical Debt indication in PLC Code for automated Production Systems: Introducing a Domain Specific Static Code Analysis Tool

Technical Debt indication in PLC Code for automated Producti...

引用

3rd IFAC conference on Embedded Systems, Computational intelligence and Telematics in Control (CESCIT)

作者： Bougouffa, Safa Dong, Quang Huan Diehm, Sebastian Gemein, Fabian Vogel-Heuser, Birgit Tech Univ Munich Inst Automat & Informat Syst D-85748 Garching Germany Schneider Elect Automat GmbH Schneiderpl 1 D-97828 Marktheidenfeld Germany

Nowadays, technical debt (TD) has become a well-known metaphor signifying long-term consequences of short-term benefits in system development. Accumulating TD can cause severe maintenance effort, and thus affect the quality of the system. Identifying and managing TD through appropriate methods and tools can be a first step towards preventing TD accumulation. Static code analysis is a technique widely used to identify TD at code level in software engineering domain and various tools were developed accordingly. However, tools for identifying TD in technical systems such as automated production systems (aPS) that are mainly controlled by Programmable Logic Controller (PLC) implemented in IEC 61131-3 programming languages are rare. Therefore, this paper presents a tool that uses static code analysis with the application of software quality metrics and coding conventions enabling the PLC software developer to identify TD and evaluate it. (C) 2018, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Validation Verification Testing Evaluation of embedded systems and applications Programmable logic controllers

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Timing Analysis of the UPMSat-2 Communications Subsystem

Timing Analysis of the UPMSat-2 Communications Subsystem

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3rd IFAC conference on Embedded Systems, Computational intelligence and Telematics in Control (CESCIT)

作者： Garrido, Jorge Zamorano, Juan Alonso, Alejandro de la Puente, Juan A. Univ Politecn Madrid Informat Proc & Telecommun Ctr Grp Sistemas Tiempo Real & Arquitectura Serv Tele Madrid Spain

Communication between satellites and ground stations is a critical element of all satellite missions. Limitations in bandwidth and coverage may restrict the capability of ground operators to control the position and functionality of the satellite and to recover platform and mission data collected on board. In this context, analysing the link budgets, i.e. the amount of information that can be transmitted on each orbit, is an effective part of the system design process, providing scope for modifications before the development of the system is completed. In this paper an approach to computing link budgets based on response-time analysis is described. The analysis provides estimates of worst-case response times for on-board software tasks, which are subsequently used to compute effective link budgets. The approach has been used in the analysis of the communications subsystem of an experimental satellite mission. (C) 2018, IFAC (international Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Embedded computer control systems and applications Logical design, physical design, and implementation of embedded computer systems Micro-nano-aerospace vehicles/satellites

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Person Identification in Smart Surveillance robots using Sparse Interest Points 1

Person Identification in Smart Surveillance Robots using Spa...

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1st international conference on robotics and Smart Manufacturing (RoSMa)

作者： Vinay, A. Krishna, Sai B., V Manoj, P. N. Rao, Nishanth A. Muthy, K. N. Balasubramanya Natarajan, S. PES Univ Ctr Pattern Recognit & Machine Intelligence 100 Feet Ring RdBanashankari Stage 3 Bengaluru 560085 Karnataka India

Face recognition presents a challenging and interesting problem in the field of robotics and computer vision. robot systems which support face recognition has been vastly used for surveillance, defense etc., robots prominently rely on real time feedbacks from sensors. robots with face recognition have numerous applications such as automation process, object detection, security and surveillance, defense, autonomous vehicles etc. A robot face recognition system is a computer application used to automatically identify or verify a person from a digital image or a video frame from a video source. This is usually achieved through a comparison of selected facial features from an image and a facial database. In order to recognize a face in real time the images captured by camera have to be stored and then processed by face recognition algorithm. In the entire face recognition process, the choice of feature extractor is very important. The constraint on the feature extractor limits the accuracy. SIFT, SURF and ORB are amongst the prominent feature extractors due to their insusceptibility to constraints such as illumination, pose and scale. In this paper, we demonstrate that proposed SRP model with ORB gives better percent accuracy of around 85% after preprocessing. (C) 2018 The Authors. Published by Elsevier Ltd.

关键词： Face Recognition Feature Matching Sparse Random Projection SIFT SURF ORB FLANN

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Information Disclosure, Security, and Data Quality 1

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31st international conference on Industrial Engineering and Other applications of Applied Intelligent Systems (IEA/AIE)

作者： Zaman, A. N. K. Obimbo, Charlie Dara, Rozita A. Univ Guelph Sch Comp Sci 50 Stone Rd East Guelph ON N1G 2W1 Canada

ISBN: (数字)9783319920580

ISBN: (纸本)9783319920580;9783319920573

Data sharing is important to interested parties for mining trends and patterns in designing data-driven decision-making systems. However, sharing raw data creates severe problems like identity theft or personal information leakage such as disclosure of illness of a specific person. This study analyzed results from an Adaptive Differential Privacy (ADiffP) algorithm that satisfies e-differential privacy for publishing sanitized data. The algorithm was tested with two different data sets to measure its robustness by comparing other existing works. The results obtained from the proposed algorithm show that the sanitized data preserves the same pattern as the raw data. Additionally, classification accuracies for sanitized data are also promising.

关键词： Differential privacy Data anonymization Privacy preserving data publishing Data sanitization

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Optimization Design of the Maintenance robot with Charged Used in Substation

Optimization Design of the Maintenance Robot with Charged Us...

引用

international conference on Mechanical, Control and Computer Engineering (ICMCCE)

作者： Shungui Liu Xin Zhang Ronghui Huang Xu Dong Jian Li Qiang Chen Shenzhen Power Supply Co. Ltd Shenzhen China Shandong Luneng Intelligence Technology Co. Ltd Jinan China

With the continuous development of the society, the requirements for the power supply stability of the power grid are getting higher and higher, and users have increasingly stricter requirements for power outages. It is difficult to arrange power cuts for critical lines, and the maintenance opportunities for power outage are getting less and less. The maintenance robot is used in substations with voltage levels of 220kV and below, and electrified maintenance work is carried out on pillar insulators and other equipment in substations. The robot adopts a universal mobile chassis structure. The end of the lift platform can be equipped with different live working tools to adapt to different tasks. The engineering prototype of robot is designed and optimized combined with the problems found in the machining process based on the actual situation at the substation site. It is mainly the optimization design of the drive system of the mobile chassis of the robot, especially the optimization layout of the chassis equipment. And the optimal design of the structure of insulated lifting arm and small flying arm.

关键词： Handheld computers Erbium robots Optimization Insulation

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Area Constraint Aware Physical Unclonable Function for intelligence Module

Area Constraint Aware Physical Unclonable Function for Intel...

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international conference on Computational intelligence and applications (ICCIA)

作者： Yusuke Nozaki Masaya Yoshikawa Dept. of Information Engineering Meijo University Nagoya Japan

ISBN: (纸本)9781538695722;9781538695715

Artificial intelligence technology such as neural network (NN) is widely used in intelligence module for Internet of Things (IoT). On the other hand, the risk of illegal attacks for IoT devices is pointed out; therefore, security countermeasures such as an authentication are very important. In the field of hardware security, the physical unclonable functions (PUFs) have been attracted attention as authentication techniques to prevent the semiconductor counterfeits. However, implementation of the dedicated hardware for both of NN and PUF increases circuit area. Therefore, this study proposes a new area constraint aware PUF for intelligence module. The proposed PUF utilizes the propagation delay time from input layer to output layer of NN. To share component for operation, the proposed PUF reduces the circuit area. Experiments using a field programmable gate array evaluate circuit area and PUF performance. In the result of circuit area, the proposed PUF was smaller than the conventional PUFs was showed. Then, in the PUF performance evaluation, for steadiness, diffuseness, and uniqueness, favorable results were obtained.

关键词： Artificial neural networks Table lookup Neurons Hamming distance Authentication Hardware

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CCDN: Checkerboard Corner Detection Network for Robust Camera Calibration 11th

CCDN: Checkerboard Corner Detection Network for Robust Camer...

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11th international conference on Intelligent robotics and applications (ICIRA)

作者： Chen, Ben Xiong, Caihua Zhang, Qi Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Inst Rehabil & Med Robot Wuhan 430074 Hubei Peoples R China

ISBN: (纸本)9783319975894;9783319975887

Aiming to improve the checkerboard corner detection robustness against the images with poor quality, such as lens distortion, extreme poses, and noise, we propose a novel detection algorithm which can maintain high accuracy on inputs under multiply scenarios without any prior knowledge of the checkerboard pattern. This whole algorithm includes a checkerboard corner detection network and some post-processing techniques. The network model is a fully convolutional network with improvements of loss function and learning rate, which can deal with the images of arbitrary size and produce correspondingly-sized output with a corner score on each pixel by efficient inference and learning. Besides, in order to remove the false positives, we employ three post-processing techniques including threshold related to maximum response, non-maximum suppression, and clustering. Evaluations on two different datasets show its superior robustness, accuracy and wide applicability in quantitative comparisons with the state-of-the-art methods, like MATE, ChESS, ROCHADE and OCamCalib.

关键词： Camera calibration Checkerboard corner detection Robustness Fully convolutional network

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Biologically Inspired Low Energy Clustering for Large Scale Wireless Sensor Networks

Biologically Inspired Low Energy Clustering for Large Scale ...

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2019 3rd international conference on Artificial intelligence, Automation and Control Technologies (AIACT 2019)

作者： Jie Zhou Mengying Xu Yi Lu College of Information Science and Technology Shihezi University

The recent technological advances in data gathering, embedded micro-devices and mobile networking has significantly advanced the applications of small-size and numerous tiny nodes. Large scale wireless sensor networks（LSWSNs） are intensively studied and used in the fields of traffic avoidance, intelligent family, medical diagnostic, environmental, multimedia surveillance, military affairs and so on. The recent success of emerging LSWSNs technology has encouraged researchers to develop new low energy clustering algorithm in this field. In LSWSNs, reducing communication energy consumption of sensor will not lead to maximize network lifetime for the total system. The low energy clustering is a typical NP-hard combinatorial optimization problem. In this paper, an immune adaptive cuckoo search algorithm（IACSA） is given to reduce total energy consumption. We first design a fitness function to evaluate energy consumption of system. The IACSA is designed to improve the energy efficiency for LSWSNs. It has the advantages of immune generator that takes into account different benefits and adaptive operator to enhance the convergence rate. Simulations are conducted to show a comparison of IACSA with the shuffled frog leaping algorithm（SFLA）, particle swarm optimization（PSO） and artificial fish swarm algorithm（AFSA）. Results show that the proposed IACSA has lower energy consumption compared to the SFLA, AFSA and PSO, which means that the proposed method reduces the energy consumption.

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Discrete Binary Cat Swarm Optimization for Scheduling Workflow applications in Cloud Systems 3

Discrete Binary Cat Swarm Optimization for Scheduling Workfl...

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3rd IEEE international conference on Computational intelligence and Communication technology (CICT)

作者： Kumar, Bhopender Kalra, Mala Singh, Poonam NITTTR Chandigarh India

ISBN: (纸本)9781509062188

There are many challenges evolved in adopting the cloud environment for scheduling workflow applications. The reason behind this is the resource heterogeneity and on-demand services offered by cloud service providers using per-per-use-model. Mapping of the distributed resources to the tasks of an application while satisfying the user's quality of service (QoS) parameters become tedious job because of heterogeneity of resources and dependent nature of the tasks. Many meta-heuristics based approaches are applied by the researchers for scheduling workflow applications to attain near optimal solution. A discrete binary cat swarm optimization (DBCSO) is proposed for scheduling workflow applications in the present work. The purpose of this algorithm is to optimize workflow schedule length also known as makespan. Scientific workflows of different sizes are evaluated with the proposed algorithm using WorkflowSim and results are compared with state-of-art algorithms. The results indicate an improvement in the performance by minimizing the makespan.

关键词： Cloud computing particle swarm optimization (PSO) workflow scheduling discrete binary cat swarm optimization (DBCSO)

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