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Unmanned Surface Vehicle with Drown Map System

Unmanned Surface Vehicle with Drown Map System

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international symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Saad Al-Dakheel Sibel Tariyan Ozyer Faruk Can Ozdemir Altug Karadag Mahmood Al-Tekreeti Computer Engineeering Çankaya University Ankara Turkey Rakun Company Ankara Turkey Electronic and Communication Engineering Ankara Turkey

The drowning cases that are happened whether in sea or ocean specially increasing cases among refugees requires to employ the advanced technology and tools to encounter this problem. Internet of Things (IoT) and cloud computing techniques will be applied in marine sector to address the problems of drowning. Internet of things that represented in sensors, actuators...etc. generate a vast number of data that globally known as a Big data, due to the limited storage and processing of the physical units with the big number of data, a cloud computing is adopted to solve this problem. In this paper, an Unmanned Surface Vehicle (USV) contains GPS and Force Sensitive Resistor (FSR) sensors will be built to discover the location and approximate number of people exposed to drowning. In addition to USV, a real-time map system will be carried out to display this information. All the data and information that generating from the sensors and map system will be stored in a cloud in real-time. This work is a part of the research and development project which is accepted in Turkey Government with the collaboration of the University and Industry.

关键词： Global Positioning System Cloud computing Servers Force Real-time systems sensor systems

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Research on Topology Control Algorithm in Heterogeneous wireless sensor networks Based on the Game Theory 18

Research on Topology Control Algorithm in Heterogeneous wire...

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3rd international Conference on Intelligent information processing (ICIIP)

作者： Deng Yun Zhang Qingjun Cheng Xiaohui Guilin Univ Technol Coll Informat Sci & Engn Guilin 541004 Guangxi Peoples R China

ISBN: (纸本)9781450364966

Given that the selfish behavior performed by saving energy when the nodes of heterogeneous sensor network is transmitting data, the decline or even rejection in providing data forward services for the neighbor nodes, and the consequence of decline or even paralysis of network communication capability, we put forward a game theory-based topology control algorithm(GTTCA) of heterogeneous wireless sensor network after making consideration for the effects that nodes' transmission power and residual energy exert on the sensor network topology. We also design a revenue function related to transmission power, residual energy and the degree of participation (the possibility nodes participating in transmitting data services). The constant game between network nodes and the adjustment in transmission power is to select the strategy maximizing the revenue function to construct the optimal path with the neighbor nodes. By theoretical analysis, after a period of time, the function converges to a stable state, namely, Nash equilibrium state. Through stimulation experiment, compared with the existing algorithm, the one in this paper is able to efficiently adjust the transmission power of nodes, balance the network energy consumption, and to some extent, prolong the life cycle of network.

关键词： Heterogeneous wireless sensor network game theory topology residual energy the degree of participation

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Temperature and Humidity Detection System of Communication System Based on Raspberry Pi 3

Temperature and Humidity Detection System of Communication S...

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3rd international Conference on Intelligent Transportation, Big Data and Smart City, ICITBS 2018

作者： Luo, Qian Xie, Min China Satellite Maritime Tracking and Control Department Jiangyin China

ISBN: (纸本)9781538642016

Temperature and humidity information is an important quality index of communication system. A temperature and humidity sensor network is constructed based on Raspberry Pi development platform and temperature and humidity sensor. The temperature and humidity sensor network can monitor the temperature and humidity of the communication system, and then transmit the measured parameters to the remote server in time by IP network, and carry out the corresponding data processing, which can realize the basic security protection of the communication system. © 2018 IEEE.

关键词： sensor networks

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23rd international Computer symposium, ICS 2018

23rd International Computer Symposium, ICS 2018

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23rd international Computer symposium, ICS 2018

ISBN: (纸本)9789811391897

The proceedings contain 85 papers. The special focus in this conference is on Computer symposium. The topics include: An Adaptive Tai-Chi-Chuan AR Guiding System Based on Speed Estimation of Movement;multi-view Community Detection in Facebook Public Pages;supervised Representation Hash Codes Learning;the Bread Recognition System with Logistic Regression;recognition and Counting of Motorcycles by Fusing Support Vector Machine and Deep Learning;an Efficient Event Detection Through Background Subtraction and Deep Convolutional Nets;Light-Weight DCNN for Face Tracking;3D Facade Reconstruction Using the Fusion of Images and LiDAR: A Review;an Application of Detecting Cryptomeria Damage by Squirrels Using Aerial Images;Local Dimming Design for LCD Backlight;clothing Classification with Multi-attribute Using Convolutional Neural Network;color Video and Convolutional Neural networks Deep Learning Based Real-Time Agtron Baking Level Estimation Method;deep Virtual Try-on with Clothes Transform;scene Recognition via Bi-enhanced Knowledge Space Learning;a Hybrid Methodology of Effective Text-Similarity Evaluation;research on Passenger Carrying Capacity of Taichung City Bus with Big Data of Electronic Ticket Transactions: A Case Study of Route 151;the Ridership Analysis on Inter-County/City Service for the Case Study of Taichung City Bus System;An Enhanced Pre-processing and Nonlinear Regression Based Approach for Failure Detection of PV System;evaluation of Performance Improvement by Cleaning on Photovoltaic Systems;egoStellar: Visual Analysis of Anomalous Communication Behaviors from Egocentric Perspective;robot Localization Using Zigbee Nodes;visual Analysis for Online Communities Exploration Based on Social Data;forecasting Monthly Average of Taiwan Stock Exchange Index;auto-scaling in Kubernetes-Based Fog Computing Platform.

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Closed-loop Analysis with Incremental Backstepping Controller considering Measurement Bias 21

Closed-loop Analysis with Incremental Backstepping Controlle...

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21st international-Federation-of-Automatic-Control (IFAC) symposium on Automatic Control in Aerospace (ACA)

作者： Jeon, Byoung-Ju Seo, Min-Guk Shin, Hyo-Sang Tsourdos, Antonios Cranfield Univ Sch Aerosp Transport & Mfg Coll Rd Cranfield Beds England

In this paper, closed loop system characteristics with an incremental backstepping controller are investigated through theoretical analysis when both measurement biases and model uncertainties exist. Incremental backstepping algorithm is proposed in previous studies to reduce model dependency of classical backstepping algorithm with additional measurements about state derivatives and control surface deflection angles. This research enables to have following critical understandings especially about the effects of biases on these additional measurements to system characteristics with incremental backstepping method. First, these biases do not affect a characteristic equation, so they do not have any influence about a condition for absolute stability. Second, these biases cause a steady state error, and model uncertainty in control effectiveness information starts to have an impact to it when these biases are additionally considered. Copyright (C) 2019. The Authors. Published by Elsevier Ltd. All rights reserved.

关键词： Backstepping control Incremental backstepping control Closed-loop analysis Measurement bias Model uncertainty Model-based approach sensor-based approach

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Performance Analysis of Between Software Defined Wireless Network and Mobile Ad Hoc Network Under DoS Attack

Performance Analysis of Between Software Defined Wireless Ne...

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international symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Hüseyin POLAT Onur POLAT Esra SÖĞÜT O. Ayhan ErdEM Department of Computer Engineering Gazi University Ankara Turkey

The traditional network used today is unable to meet the increasing needs of technology in terms of management, scaling, and performance criteria. Major developments in information and communication technologies show that the traditional network structure is quite lacking in meeting the current requirements. In order to solve these problems, Software Defined Network (SDN) is capable of responding as it, is flexible, easier to manage and offers a new structure. Software Defined networks have many advantages over traditional network structure. However, it also brings along many security threats due to its new architecture. For example, the DoS attack, which overloads the controller's processing and communication capacity in the SDN structure, is a significant threat. Mobile Ad Hoc Network (MANET), which is one of the wireless network technologies, is different from SDN technology. MANET is exposed to various attacks such as DoS due to its security vulnerabilities. The aim of the study is to reveal the security problems in SDN structure presented with a new understanding. This is based on the currently used network structures such as MANET. The study consists of two parts. First, DoS attacks against the SDN controller were performed. Different SDN controllers were used for more accurate results. Second, MANET was established and DoS attacks against this network were performed. Different MANET routing protocols were used for more accurate results. According to the scenario, attacks were performed and the performance values of the networks were tested. The reason for using two different networks in this study is to compare the performance values of these networks at the time of attack. According to the test results, both networks were adversely affected by the attacks. It was observed that network performance decreased in MANET structure but there was no network interruption. The SDN controller becomes dysfunctional and collapses as a result of the attack. While the inno

关键词： Mobile ad hoc networks Computer architecture Security Bandwidth Software defined networking Wireless networks IEEE Sections

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Extraction of Numerical data from Categorical Data Set and Artificial Neural networks

Extraction of Numerical data from Categorical Data Set and A...

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international symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Ahmet Hıfzı Bacaksız Eren Esgin AI Birimi MBIS Ar-Ge Merkezi İstanbul Türkiye

In this study, the need for numerical data which is required for the machine learning techniques is considered. In order to classify a categorical data by multilayer perceptron, which is one of the well-known artificial neural network structure, the content of the data is digitalized. While the numerical equivalent of the data content is created at categorical level, the protection of the information it carries has been an important issue in terms of achieving effective results and has been studied a lot. Here, a binary-defined transformation is applied to the categorical data. Afterwards, a guide vector is implemented to protect the relation at its own business context. The guide vector implicitly conserves positional relation of the corresponding dataset at the categorical level. Hence, a significant dimensional reduction is accomplished in this new dataset obtained after the digitalization of the original dataset. The classification performance of newly extracted features is validated with multilayer perceptron structure and successful results are observed. In this study, the actual data extracted from the enterprise resource planning (ERP) system is used as the main data source. The underlying methods of modeling and data processing are implemented in MATLAB and Python programming languages.

关键词： Data models Econometrics Mathematical model Feature extraction Matlab Reactive power Machine learning

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An Adaptive Scheme for Two-stage Multi-hypothesis Prediction 3

An Adaptive Scheme for Two-stage Multi-hypothesis Prediction

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IEEE 3rd international Conference on Signal and Image processing (ICSIP)

作者： Chen, Can Hou, Shiming Zhou, Chao Ding, Fei Zhang, Dengyin Nanjing Univ Posts & Telecommun Nanjing Jiangsu Peoples R China

ISBN: (纸本)9781538663967

Existing two-stage multi-hypothesis reconstruction (2sMHR) schemes deploy a pixel-domain multi-hypothesis (MH) prediction after a measurement-domain recovery to break the limit of flexibility in reconstruction. However, these schemes for 2sMHR are sensitive to different types of videos because they select reference frames non-adaptively in pixel-domain recovery. To address this problem, we propose an adaptive scheme for 2sMHR in which we hold the assumption that the most accurate reference frame has the most significant weight. Specifically, we firstly integrate candidate reference frames into the same hypothesis set and utilize L1 norm to select the preferred frame as the reference to execute a secondary reconstruction. Simulation results demonstrate that the proposed scheme outperforms the state-of-the-art schemes in terms of stability.

关键词： distributed compressed video sensing (DCVS) multi-hypothesis (MH) prediction secondary reconstruction wireless video sensor networks (WVSN)

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3D Convolutional Neural networks for Diagnosis of Alzheimer's Disease via Structural MRI

3D Convolutional Neural Networks for Diagnosis of Alzheimer'...

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Annual IEEE symposium on Computer-Based Medical Systems

作者： Ekin Yagis Luca Citi Stefano Diciotti Chiara Marzi Selamawet Workalemahu Atnafu Alba G. Seco De Herrera Computer Science and Electrical Engineering (CSEE) University of Essex Colchester United Kingdom Department of Electrical Electronic and Information Engineering “Guglielmo Marconi” University of Bologna Bologna Italy University of Bologna Bologna Italy University of Essex Colchester UK

ISBN: (数字)9781728194295

ISBN: (纸本)9781728194301

Alzheimer's Disease (AD) is a widespread neurodegenerative disease caused by structural changes in the brain and leads to deterioration of cognitive functions. Patients usually experience diagnostic symptoms at later stages after irreversible neural damage occurs. Therefore, early detection of AD is crucial to start treatments to decelerate the progress of the disease and to maximize patients' quality of life. With the rapid advances in machine learning and scanning, early detection of AD may be possible via computer-assisted systems using neuroimaging data. Among all, deep learning utilizing magnetic resonance imaging (MRI) has become a prominent tool due to its capability to extract high-level features through local connectivity, weight sharing, and spatial invariance. This paper describes our investigation of the classification accuracy based on two publicly available data sets, namely, ADNI and OASIS, by building a 3D VGG variant convolutional network (CNN). We used 3D models to avoid information loss, which occurs during the process of slicing 3D MRI into 2D images and analyzing them by 2D convolutional filters. We also conducted a pre-processing of the data to enhance the effectiveness and classification performance of the model. The proposed model achieved 73.4% classification accuracy on ADNI and 69.9% on OASIS dataset with 5-fold cross-validation (CV), outperforming 2D network models.

关键词： Magnetic resonance imaging Three-dimensional displays Dementia Two dimensional displays Feature extraction Data models

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Poster Abstract: An Automated Real-time and Affordable Airborne Pollen Sensing System

Poster Abstract: An Automated Real-time and Affordable Airbo...

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international symposium on information processing in sensor networks (IPSN)

作者： Nam Cao Olga Saukh Lothar Thiele Institute of Technical Informatics Graz University of Technology ETH Zurich Computer Engineering and Networks Lab

ISBN: (纸本)9781728107271

In this paper, we present the design of our prototype of an automated real-time and affordable pollen sensing system. The design consists of three main subsystems: (1) a trap with automatic filtering, (2) a particle concentration system, and (3) a digital microscope with autofocus. The prototype shows effective particle gathering, filtering and concentration in a tiny sized area. As a result, we reduce particle loss and improve image quality taken by the optical system when searching and autofocusing on pollen grains. Our first prototype collects raw time-stamped data and transmits these to the backend server where we plan to run the detection and classification algorithms to extract accurate pollen counts from microscopic images. The key advantage of processing images at the backend is that we let the experts undertake corrective actions and help the system learn to detect and classify pollen using state-of-the-art interactive imitation learning algorithms. The final model can then run locally on embedded hardware.

关键词： Microscopy Prototypes Cyclones sensors Real-time systems Filtering Image resolution

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