Xinlu Zong, Jiayuan Du, Wei Liu, Lu Zhang, Qian Huang
{"title":"Indoor Emergency Evacuation Model Based on Artificial Bee Colony Algorithm","authors":"Xinlu Zong, Jiayuan Du, Wei Liu, Lu Zhang, Qian Huang","doi":"10.1109/IDAACS.2019.8924263","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924263","url":null,"abstract":"In order to quickly and efficiently simulate the crowd movement process under the evacuation scene, so as to reduce the casualties in emergency evacuation, this article proposes an indoor emergency evacuation model based on the improved artificial swarm algorithm. In this article, the cellular automata (CA) model is used to establish the evacuation environment, and then the artificial bee colony (ABC) algorithm is used to simulate the crowd evacuation. However, due to too many obstacles existing in the neighboring cells of some position, the individual in that position have to wait. If the distance equation is used to calculate the fitness, it may cause other individuals to choose these positions as new position and repeat the same mistake above. To reduce the occurrence of such cases, we improve the fitness function of the ABC algorithm. In the fitness function, the factors of attraction and repulsion force in social force model are introduced. And on the basis of the ABC algorithm, we propose the visual employed bee. The visual employed bee leads the onlooker bee to evacuate, so as to improve the efficiency of evacuation. The research results of this article can provide ideas for evacuation modeling and useful guidance for formulating evacuation strategies to reduce evacuation time and disaster losses.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134438402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"3D Virtual Biomimetic Network: a Topology for Resilient Intelligent Wireless Sensor Networks","authors":"Y. E. Ahmed, K. Adjallah, Magdi B.M. Amin","doi":"10.1109/IDAACS.2019.8924232","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924232","url":null,"abstract":"Wireless data communication has a key role in any updated information technology-based project. Mobility, flexibility, scalability, and easy-to-install are the main features of wireless data acquisition systems. While the limited lifetime, availability, failure risk, and reliability are still significant challenges. Inspired by the spider webs, as an attractive natural communication topology, this work proposes using the spider webs topology to design reliable and resilient, intelligent wireless sensor networks to be implemented for wireless data acquisition, aiming to provide promising solutions for such problems. The paper provides several definitions for innovated concepts and relevant notations such as the virtual thread, virtual thread thickness, virtual thread density, sensor nodes and base station deployment, data shortest path, data path resiliency, and reliability, from spider webs point of view. Then, it describes the significant research challenges to be addressed for applicable 3D Virtual spider webs. Also, it illustrates the customization approach of 3D virtual spider webs of wireless data acquisition for service, security, resources planning, and decision making.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133358398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
V. Kochan, Oleksandr Matsiuk, N. Kunanets, V. Pasichnyk, Oleksiy Roshchupkin, A. Sachenko, I. Turchenko, O. Duda, V. Semaniuk, Svitlana Romaniv
{"title":"Sensing in IoT for Smart City Systems","authors":"V. Kochan, Oleksandr Matsiuk, N. Kunanets, V. Pasichnyk, Oleksiy Roshchupkin, A. Sachenko, I. Turchenko, O. Duda, V. Semaniuk, Svitlana Romaniv","doi":"10.1109/IDAACS.2019.8924423","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924423","url":null,"abstract":"The Internet of Things (IoT) includes a large set of sensors of various physical quantities, operating principles and parameters. In this case, sensor errors are traditionally dominant in measuring channels. In this paper general methods of increasing the accuracy of sensors using neural networks are considered. Due to the generalization of properties, neural networks can significantly improve the accuracy of sensors with reduced complexity of the transition to their individual transformation functions.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"160 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125210847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
L. Moroz, V. Samotyy, Oleh Horyachyy, U. Dzelendzyak
{"title":"Algorithms for Calculating the Square Root and Inverse Square Root Based on the Second-Order Householder's Method","authors":"L. Moroz, V. Samotyy, Oleh Horyachyy, U. Dzelendzyak","doi":"10.1109/IDAACS.2019.8924302","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924302","url":null,"abstract":"This article proposes a set of algorithms for calculating the square root and inverse square root for normalized single and double precision floating-point numbers. They are based on the combination of the Householder's method of cubic convergence and the Newton-Raphson method of quadratic convergence using the magic constant to obtain the initial approximation. The advantage of the algorithms is to increase the accuracy of calculations of these functions without the use of division operation and lookup tables.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134140878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kyryll Udod, V. Kushnarenko, S. Wesner, V. Svjatnyj
{"title":"Preservation System for Scientific Experiments in High Performance Computing: Challenges and Proposed Concept","authors":"Kyryll Udod, V. Kushnarenko, S. Wesner, V. Svjatnyj","doi":"10.1109/IDAACS.2019.8924459","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924459","url":null,"abstract":"Continuously growing amount of research experiments using High Performance Computing (HPC) leads to the questions of research data management and in particular how to preserve a scientific experiment including all related data for long term for its future reproduction. This paper covers some challenges and possible solutions related to the preservation of scientific experiments on HPC systems and represents a concept of the preservation system for HPC computations. Storage of the experiment itself with some related data is not only enough for its future reproduction, especially in the long term. For that case preservation of the whole experiment's environment (operating system, used libraries, environment variables, input data, etc.) via containerization technology (e.g. using Docker, Singularity) is proposed. This approach allows to preserve the entire environment, but is not always possible on every HPC system because of security issues. And it also leaves a question, how to deal with commercial software that was used within the experiment. As a possible solution we propose to run a preservation process outside of the computing system on the web-server and to replace all commercial software inside the created experiment's image with open source analogues that should allow future reproduction of the experiment without any legal issues. The prototype of such a system was developed, the paper provides the scheme of the system, its main features and describes the first experimental results and further research steps.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133913524","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Z. Ye, Ye Cao, Aixin Zhang, Can Jin, L. Ma, Xiang Hu, Jiwei Hu
{"title":"An Image Enhancement Optimization Method Based on Differential Evolution Algorithm and Cuckoo Search Through Serial Coupled Mode","authors":"Z. Ye, Ye Cao, Aixin Zhang, Can Jin, L. Ma, Xiang Hu, Jiwei Hu","doi":"10.1109/IDAACS.2019.8924343","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924343","url":null,"abstract":"Image enhancement based on Beta function is a widely used method for it is able to fit multiple transformation curves, which is a significant step for image analysis. The key step for the method is to find the appropriate parameters to determine the grayscale transformation function. However, it needs a lot of time to seek applicable parameters when enumeration is used and random optimization algorithms often have failures within a limited time and are prone to fall into the local optimum. In order to solve the problems a serial coupled mode of stochastic optimization algorithms is investigated in the paper. According to the model, the differential evolution algorithm and cuckoo search algorithm are tried in image enhancement through serial coupling mode and compared with the traditional optimization algorithm. The experimental results reveals that the proposed approach is feasible and the performance is more balanced, which has a good performance on the image enhancement.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132670732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mauricio Postigo-Málaga, Luis Porras Figueroa, J. Chilo
{"title":"Low Cost Outdoors WSN Parking System for Metropolitan Areas Based on RSS","authors":"Mauricio Postigo-Málaga, Luis Porras Figueroa, J. Chilo","doi":"10.1109/IDAACS.2019.8924422","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924422","url":null,"abstract":"Finding a free parking space in the metropolitan areas during rush hour is time consuming and it leads to traffic congestions and air pollution. Wireless Sensor Network (WSN) can be used to obtain information related to the parking condition requiring very little installation and maintenance costs. In this work, we present the design and implementation of an outdoor parking system based on Wireless Sensor Networks (WSNs), received signal strength (RSS) and pattern recognition algorithms to effectively find free parking spaces. Simulation and experiment results show good performance in the verification of the parking system. XBee-PRO 900HP-S3B modules with high performance and low power consumption were used. These modules support the IEEE-802.15.4 protocol for communication in the 900 MHz band and can be configured in different network topologies. The received signal strength (RSS) was measured to form fingerprints for the parking spaces availability (busy or vacant). Kalman filters were implemented to improve RSS which varies due to the effects of short-term fading. The parking spaces availability was evaluated with different classification algorithms in the WEKA environment with results up to 85%.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132716193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Can Jin, Z. Ye, Lingyu Yan, Ye Cao, Aixin Zhang, L. Ma, Xiang Hu, Jiwei Hu
{"title":"Image Segmentation Using Fuzzy C-means Optimized by Ant Lion Optimization","authors":"Can Jin, Z. Ye, Lingyu Yan, Ye Cao, Aixin Zhang, L. Ma, Xiang Hu, Jiwei Hu","doi":"10.1109/IDAACS.2019.8924420","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924420","url":null,"abstract":"Image segmentation is the indispensable part in the field of computer vision. There are tremendous methods for handling this task such as Otsu-thresholding and Fuzzy C-means (FCM). However, the segmentation results of the images are occasionally unsatisfactory due to the presence of noise. In this paper, two kinds of spatial information consisting of the relative position information and the intensity information of the neighborhood pixels in an image are taken into consideration in constructing the objective function in FCM. Moreover, Ant Lion Optimization, one of the recently proposed optimization algorithms is utilized to optimize the relevant index. Bioinspired ALO has the robust ability to find optimal parameters in search spaces. So the proposed approach to image segmentation based on Fuzzy C-Means (FCM) and Ant Lion Optimization (ALO) may alleviate this problem to a certain degree. A series of experimental validation has been implemented for demonstrating the performance of the proposed approach in the end of the paper.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132731385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mircea Stefan Simoiu, V. Calofir, I. Fagarasan, Cristina Nichiforov
{"title":"eLearning Remote Simulator for Implementing Control Systems - A Case Study on a DC Motor","authors":"Mircea Stefan Simoiu, V. Calofir, I. Fagarasan, Cristina Nichiforov","doi":"10.1109/IDAACS.2019.8924324","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924324","url":null,"abstract":"In control systems, regarding the teaching process, practical aspects are equally important as theoretical aspects. Students should conduct experiments to test the robustness, stability and quality of the designed control systems or control algorithms. Unfortunately, having a modern, equipped laboratory available for all students often implies having to support big acquisition and maintenance costs. In this context, the paper proposes a remote eLearning system, capable of simulating processes and implementing control systems. The solution is developed as an open architecture, in a flexible and cost efficient manner. The goal of the project is to help create a context where students can remotely simulate and implement control systems during classes, from their assigned laboratory computer. The paper also includes a case study on a permanent magnet DC motor as an example for validating the capabilities of the proposed solution.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"244 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132943667","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xinlu Zong, Lu Zhang, Jiayuan Du, Liu Wei, Qian Huang
{"title":"Abnormal Event Detection in Video Based on SVDD","authors":"Xinlu Zong, Lu Zhang, Jiayuan Du, Liu Wei, Qian Huang","doi":"10.1109/IDAACS.2019.8924464","DOIUrl":"https://doi.org/10.1109/IDAACS.2019.8924464","url":null,"abstract":"Abnormal event detection, as a hot research field in intelligent video monitoring system, has attracted many researchers' attention in recent years. In order to overcome the shortcomings of the semi-supervised model, namely the training sample is difficult to contain all possible situations, leading to the occurrence of error detection, we propose a method based on support vector data description (SVDD). The principle of the method is to train the model with normal data and abnormal data respectively to obtain two SVDD models, and then judge whether there are abnormal events according to the results of the two models. This method has been tested by existing data sets and achieved good results.","PeriodicalId":415006,"journal":{"name":"2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114369283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}