2015 SAI Intelligent Systems Conference (IntelliSys)最新文献_第3页

PSO-PD fuzzy control of distillation column 精馏塔PSO-PD模糊控制

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361194

Yousif Al-Dunainawi, M. Abbod

引用次数: 3

Object recognition in assembly assisted by augmented reality system 增强现实系统辅助装配中的物体识别

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361172

Anderson Nishihara, J. Okamoto

{"title":"Object recognition in assembly assisted by augmented reality system","authors":"Anderson Nishihara, J. Okamoto","doi":"10.1109/INTELLISYS.2015.7361172","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361172","url":null,"abstract":"Assembly processes for simple toys or complex machines require instructions to be executed. Traditionally, these instructions are written in the form of paper or digital manuals. These manuals contain descriptive text, photos or diagrams to guide the assembly sequence from the beginning to the final state. To change this paradigm, an augmented reality system is proposed to guide users in assembly tasks. The system recognizes each piece to be assembled through image processing techniques and guides the piece placement with graphic signs. Still, the system checks if the pieces are properly assembled and alerts the user when the assembly has been finished. In the field of assembly assisted by augmented reality systems, many works use some kind of customized device, such as head mounted displays (HMD). Additionally, markers are commonly used to track camera position and to identify assembly parts. These two features restrict the spread of the technology whence, in this work, customized devices and markers to track and identify parts are not used and all the processing is executed on embedded software in an off-the-shelf device without the need of communication with other computers to offload image processing. In this work we present the current results of the proposed system's object recognition process. The implemented object recognition subsystem is part of a system called A3R (Assembly Assisted by Augmented Reality).","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117026582","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}

引用次数: 17

Energy optimization in wireless sensor networks based on genetic algorithms 基于遗传算法的无线传感器网络能量优化

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361182

Ángela Rodríguez, P. Falcarin, Armando Ordóñez

引用次数: 6

Integrated CAD/CAPP/CAM and ANN in sheet metal punching and nippling operations 集成CAD/CAPP/CAM和ANN在钣金冲压和压紧操作

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361210

Amal A Mohamed, A. Barakat, M. Etman, H. Hussein

{"title":"Integrated CAD/CAPP/CAM and ANN in sheet metal punching and nippling operations","authors":"Amal A Mohamed, A. Barakat, M. Etman, H. Hussein","doi":"10.1109/INTELLISYS.2015.7361210","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361210","url":null,"abstract":"The integration between CAD and CAM is vital to the competitiveness between the manufacturing companies and their rapid respond ability to market changes. The integration is an entrance to the world of digital manufacturing and the computer integrated manufacturing \"CIM\". The CIM construction is based on a group of links. The process planning activates is represent as one of this CIM links. The present work aims to integrate CAD, CAPP and CAM to obtain a solution for automated process planning for sheet metal parts. The integration is accomplished by using CREO software as a CAD system in sheet metal, building a knowledge base and generating CAPP program to select optimum cutting parameters using artificial Neural Network. The output is then taken from CAD file and operations schedule from CAPP file to extract tool path program for selected machine tool (CAM). A case study for a sheet metal part is proposed to demonstrate the system procedure and its applicability. It can be concluded that the integrated system decreases the errors which may creep into process and save the extra efforts spent with separate systems. The system makes use of the interaction and consulting capabilities of human experts, also it may be used for other future applications to obtain intelligent CAPP for various parts.","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127227345","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}

引用次数: 1

Relation mining using cross correlation of multi domain social networks 基于互相关的多领域社交网络关系挖掘

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361250

Fozia Noor, Asadullah Shah, S. Khan

{"title":"Relation mining using cross correlation of multi domain social networks","authors":"Fozia Noor, Asadullah Shah, S. Khan","doi":"10.1109/INTELLISYS.2015.7361250","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361250","url":null,"abstract":"Social network analysis has emerged as an important research area in intelligence analysis to facilitate decision-maker in more informed decisions. With the passage of time social network services are increasingly being used in legal and criminal investigations including understanding and tracking of dark networks, i.e., illegal and covert networks. Criminal organizations are well-suited to be studied using social network analysis as they consist of networks of individuals that span countries and continents using false identities over different networks to remain anonymous. There is a need to recognize the criminals carrying different fake identities to correctly track their immoral activities. This research article is focusing on devising a method which can be used to identify group of people i.e. criminal, terrorist or friends on different Social networks by analyzing patterns and performing correlations across different social network systems. Data integration using cross correlation is used to merge entities to form single fused networks. This single fused network also estimate the intensity of relationship between individuals in general networks based on the number of networks they are connected. To best of our knowledge no such studies is done in the social network analysis, therefore this method is unique and offers innovations in making effective use of presence of people in different networks.","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124970490","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}

引用次数: 2

Robust algorithm of multi-source data analysis for evaluation of social vulnerability in risk assessment tasks 多源数据分析鲁棒算法用于风险评估任务中的社会脆弱性评估

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361256

Y. Kostyuchenko, Ivan Kopachevsky, D. Movchan, Yulia Bilous

引用次数: 8

A neural network model of Caenorhabditis elegans and simulation of chemotaxis-related information processing in the neural network 秀丽隐杆线虫的神经网络模型及神经网络中趋化相关信息处理的模拟

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361212

K. Sakamoto, Z. Soh, Michiyo Suzuki, Y. Kurita, T. Tsuji

{"title":"A neural network model of Caenorhabditis elegans and simulation of chemotaxis-related information processing in the neural network","authors":"K. Sakamoto, Z. Soh, Michiyo Suzuki, Y. Kurita, T. Tsuji","doi":"10.1109/INTELLISYS.2015.7361212","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361212","url":null,"abstract":"The nematode Caenorhabditis elegans (C. elegans) is a simple multi-cellular organism consisting of around 1,000 cells including 302 neurons, and is the only creature whose connectome has been fully mapped. For these reasons, (C. elegans) is ideal for studying information-processing mechanisms embedded in the neural network. This paper proposes a neural network model of C. elegans with the actual neural structure preserved to simulate the organism's attraction to sodium chloride (NaCl). To implement attractant behavior, the organism's neural network must calculate the temporal and spatial gradients of NaCl concentration; however, the mechanism behind this complex information processing in the worm's neural network has not yet been fully elucidated. As a first step to analyze the information processing mechanism, the parameters of the neural network model were adjusted using the backpropagation through time (BPTT) algorithm, and the neural network model was verified for its ability to generate temporal and spatial gradients. Simulation for neuron ablation experiment was then carried out, and the results exhibited same trends as the biological experiment indicating that our approach can be used to predict the results of biological experiments, and can therefore be used as a tool to provide guidelines for such experiments.","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129720457","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}

引用次数: 1

Hierarchical organization with a cross layers using smart sensors for intelligent cities 使用智能传感器的跨层分层组织用于智能城市

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361178

B. Imen, Pr Abdellaoui Mahmoud

{"title":"Hierarchical organization with a cross layers using smart sensors for intelligent cities","authors":"B. Imen, Pr Abdellaoui Mahmoud","doi":"10.1109/INTELLISYS.2015.7361178","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361178","url":null,"abstract":"To build intelligent cities with providing comfortable life, we use smart sensors. So, we have to protect these sensors form deterioration by using energy conservation techniques to extend their lifetime. In this work we concentrate in the problem of energy conservation and life expectancy of smart sensors; because, they are not refillable by micro-piles. To solve the problem of limitation of the network regarding energy resources, our approach is based on a combination between several existing mechanisms of energy saving by addressing more particularly on the data routing. The existing routing protocol ZRP cannot resist in large scale (because it isn't an adapted protocol for WSN). To overcome this limit, our approach consists in improving this protocol with the aim of having the best answers for the requirements of WSN by the introduction of hierarchical organization based on the crossing between different layers, to obtain the proposed protocol H-ZRP. We have been used NS2 for simulation. Our proposal approach offered the best performances and more reliability than at the loss packets rate, deadline from start to finish, and transmission rate.","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"14 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113972093","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}

引用次数: 8

Discovering hotspots: A placement strategy for Wi-Fi based trajectory monitoring within buildings 发现热点:建筑物内基于Wi-Fi轨迹监控的放置策略

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361169

Lorenz Schauer

{"title":"Discovering hotspots: A placement strategy for Wi-Fi based trajectory monitoring within buildings","authors":"Lorenz Schauer","doi":"10.1109/INTELLISYS.2015.7361169","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361169","url":null,"abstract":"In the last decade, Wi-Fi based trajectory monitoring has gathered high interest in the scientific and commercial world, due to the increased usage of Wi-Fi capable mobile devices. A lot of work can be found where monitor nodes are placed in an area of interest capturing Wi-Fi signals from passing phones. However, the deployment of such nodes is often inefficient, expressed by a low ratio between monitored trajectories and the amount of installed nodes. Hence, finding an optimal setting of node positions is an essential and challenging task. In this paper, a systematic solution for this variant of the NP-hard art gallery problem is investigated. The idea is to set monitor nodes only on places (hotspots), where most of the human paths can be tracked. For the discovery of such hotspots, three novel approaches are presented working on simulated user traces based on an extended pathway mobility model, and a given plant layout. The results of each approach are evaluated in terms of quality for Wi-Fi based trajectory monitoring using different parameters and settings. The evaluation indicates that the proposed methods show different potentials and limitations. Overall, they return a reliable setting of hotspots compared to a completely random selection of an equal amount of node positions and, thus, they serve as a systematic and sophisticated placement strategy.","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116444957","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}

引用次数: 2

ANN-based prediction of cementation factor in carbonate reservoir 基于神经网络的碳酸盐岩储层胶结系数预测

2015 SAI Intelligent Systems Conference (IntelliSys) Pub Date : 2015-12-21 DOI: 10.1109/INTELLISYS.2015.7361214

F. Kadhim, A. Samsuri, Yousif Al-Dunainawi

{"title":"ANN-based prediction of cementation factor in carbonate reservoir","authors":"F. Kadhim, A. Samsuri, Yousif Al-Dunainawi","doi":"10.1109/INTELLISYS.2015.7361214","DOIUrl":"https://doi.org/10.1109/INTELLISYS.2015.7361214","url":null,"abstract":"Since carbonate reservoirs are a heterogeneous in nature, therefore the behaviour of petrophysical properties of these reservoirs is a highly nonlinear. There is no close conventional statistical model can describe the behaviour of the relation between cementation factor and rock properties. Artificial Neural Network technique is used in many applications to predict variable that usually cannot be measured in linear modelling. Depending on well logs data, the Interactive Petrophysics software had been used to calculate the petrophysical properties of studied oilfield. In this study, the data sets used for training and testing neural network are provided from well number three of Nasiriya oilfield in the south of Iraq. The neural network model was trained using two different training algorithms; Gradient Descent with Momentum and Levenberg - Marquardt. Porosity, permeability and resistivity formation factor relationships to cementation factor are proposed using artificial neural network model. An efficient performance of excellent prediction of cementation factor has been obtained with less than (1*10-4) mean square error (MSE).","PeriodicalId":121474,"journal":{"name":"2015 SAI Intelligent Systems Conference (IntelliSys)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126971598","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}

引用次数: 6