2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)最新文献_第3页

A review of optimization method in face recognition: Comparison deep learning and non-deep learning methods 人脸识别优化方法综述:深度学习与非深度学习方法的比较

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250484

Sulis Setiowati, Zulfanahri, Eka Legya Franita, I. Ardiyanto

{"title":"A review of optimization method in face recognition: Comparison deep learning and non-deep learning methods","authors":"Sulis Setiowati, Zulfanahri, Eka Legya Franita, I. Ardiyanto","doi":"10.1109/ICITEED.2017.8250484","DOIUrl":"https://doi.org/10.1109/ICITEED.2017.8250484","url":null,"abstract":"Currently, face recognition system is growing sustainably on a larger scope. A few years ago, face recognition was used as a personal identification with a limited scope, now this technology has grown in the field of security, in terms of preventing fraudsters, criminals, and terrorists. In addition, face recognition is also used in detecting how tired a driver is, reducing the occurrence of road accidents, as well as in marketing, advertising, health, and others. Many method are developed to give the best accuracy in face recognition. Deep learning approach become trend in this field because of stunning results, and fast computation. However, the problem about accuracy, complexity, and scalability become a challenges in face recognition. This paper focus on recognizing the importance of this technology, how to achieve high accuracy with low complexity. Deep learning and non-deep learning methods are discussed and compared to analyze their advantages and disadvantages. From critical analysis using experiment with YALE dataset, non-deep learning algorithm can reach up to 90.6% for low-high complexity and 94.67% in deep learning method for low-high complexity. Genetic algorithm combining with CNN and SVM was an optimization method for overcome accuracy and complexity problems.","PeriodicalId":267403,"journal":{"name":"2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133661025","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: 22

Detection of fibrosis in liver biopsy images using multi-objective genetic programming 基于多目标遗传规划的肝活检图像纤维化检测

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250486

Purit Thong-on, U. Watchareeruetai

引用次数: 2

Automatic labeling for news article classification based on paragraph vector 基于段落向量的新闻文章分类自动标注

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250448

Taishi Saito, O. Uchida

引用次数: 3

A novel modeling approach of SVC for three-phase transient stability simulator 一种新的三相暂态稳定模拟器SVC建模方法

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250509

Pavel Y. Bannykh, P. Chusovitin, A. Pazderin

引用次数: 1

Identification of medical surgical product and object distinction using image processing 基于图像处理的医用外科产品识别与目标区分

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250452

S. Anai, M. Iwasaki, Keisuke Hano, S. Kuchii

引用次数: 1

Mobile expert systems for bamboo identification using rule based reasoning 基于规则推理的竹识别移动专家系统

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250473

E. P. Purwandari, E. Arifin, A. Yani, E. W. Winarni, Feri Noperman

{"title":"Mobile expert systems for bamboo identification using rule based reasoning","authors":"E. P. Purwandari, E. Arifin, A. Yani, E. W. Winarni, Feri Noperman","doi":"10.1109/ICITEED.2017.8250473","DOIUrl":"https://doi.org/10.1109/ICITEED.2017.8250473","url":null,"abstract":"Indonesia is tropical country which has high plant diversity including bamboo. This condition make difficult to identification process. Bamboo species in Indonesia is estimated at about 159 species out of the total 1250 species around the world. The bamboo identification method usually takes a long time, relatively expensive, complicated, and requires information from bamboo expert. By transferring the knowledge of bamboo experts in recognizing the characteristics of bamboo such as roots, shoots, stems, branches, and leaves, then identification can be done without having to bring an expert directly. Data in mobile expert system for the bamboo identification is divided into 6 morphologies, 31 feature attributes, and 188 characteristic. This system is built with rule based reasoning method that modified with greedy algorithm to compare the weight difference of bamboo species. The experiments were performed with 143 bamboo test cases have shown 100% high accuracy rate for the same system input 100%. Furthermore, the accuracy rate reaches 100% for 50% input data equal to the knowledge base and only 50% answer filled, so the user does not need to answer the whole question to get accurate identification result. This result shows that the mobile expert system for bamboo identification with rule based reasoning generated results more reliable than human expert.","PeriodicalId":267403,"journal":{"name":"2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"300 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122473826","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: 0

The improved ensemble classification technique using Wolf algorithm 改进的基于Wolf算法的集成分类技术

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250494

Duangjai Jitkongchuen, W. Paireekreng

{"title":"The improved ensemble classification technique using Wolf algorithm","authors":"Duangjai Jitkongchuen, W. Paireekreng","doi":"10.1109/ICITEED.2017.8250494","DOIUrl":"https://doi.org/10.1109/ICITEED.2017.8250494","url":null,"abstract":"The rise of data mining leads to the data-oriented society and focusing on data analytics. Several classification techniques have been investigated to find the optimized model for data prediction. This includes the enhancing the performance of the model. Grey Wolf Optimizer is the one of novel approach to solve NP-hard problems. However, the algorithm address the general situation. To solve the customized situation, the adapted algorithm needs to be explored. This research proposes the Ensemble Featured-Wolf (EF-Wolf) algorithm which includes the feature selection stage and implements ensemble technique to optimize the function selection problem in classification. The number of the packs of the wolf can help to select the most optimized functions to selection the most relevant features in the dataset. In addition, the packs ensemble of the relevant features can determine the feature selection of the dataset. The experiment shows the comparison among classification techniques with binary and multiclass datasets. The results show that EF-Wolf 5-pack mostly performs better results in terms of accuracy rate compared to other techniques.","PeriodicalId":267403,"journal":{"name":"2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129987784","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: 0

Development of an IoT device for monitoring electrical energy consumption 开发用于监测电能消耗的物联网设备

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250475

Siriwat Wasoontarajaroen, Khwanchai Pawasan, Vithaya Chamnanphrai

引用次数: 21

Optimal allocation of distributed generation with FACTS controller for electrical power loss reduction using genetic algorithm 基于遗传算法的分布式发电FACTS控制器优化分配

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250468

Sattawat Burana, P. Thararak, P. Jirapong, Kannathat Mansuwan

{"title":"Optimal allocation of distributed generation with FACTS controller for electrical power loss reduction using genetic algorithm","authors":"Sattawat Burana, P. Thararak, P. Jirapong, Kannathat Mansuwan","doi":"10.1109/ICITEED.2017.8250468","DOIUrl":"https://doi.org/10.1109/ICITEED.2017.8250468","url":null,"abstract":"Distributed generation (DG) and flexible alternating current transmission systems (FACTS) can be used to increase the efficiency and enhance power generation of distribution systems. However, the installation of DG with FACTS at inappropriate allocations can result in negative impacts. In this paper, a new DG with FACTS allocation planning tool is proposed for determining the optimal location and sizing of DG with FACTS to reduce power losses. The optimal power flow (OPF) with DG and FACTS is formulated as a minimization problem of system power losses subjected to system constraints such as the grid code from Provincial Electricity Authority (PEA) of Thailand, loading limits, generation limits, and voltage limits. DG and FACTS used in this experiment are a synchronous generator and static var compensator (SVC), respectively. Genetic algorithm (GA) implemented by an m-file script in MATLAB is used for the optimization technique. Consequently, evaluation of load flow solutions and objective functions in each generation of GA are determined using DIgSILENT Programing Language (DPL) script in DIgSILENT software. An existing 22 kV distribution system from PEA is used as a test system. The practical system data from a geographic information system (GIS) database are imported for the planning tool. The obtained simulation results show that the optimal allocation of DG with FACTS using proposed tool results in system power loss reduction, line loading and voltage profile improvement.","PeriodicalId":267403,"journal":{"name":"2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132130367","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

A publish subscribe based middleware for enabling real time web access on constrained device 一个基于发布订阅的中间件，用于在受限设备上实现实时web访问

2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE) Pub Date : 2017-10-01 DOI: 10.1109/ICITEED.2017.8250510

A. Bhawiyuga, Dany P Kartikasari, Eko Sakti Pramukantoro

{"title":"A publish subscribe based middleware for enabling real time web access on constrained device","authors":"A. Bhawiyuga, Dany P Kartikasari, Eko Sakti Pramukantoro","doi":"10.1109/ICITEED.2017.8250510","DOIUrl":"https://doi.org/10.1109/ICITEED.2017.8250510","url":null,"abstract":"In IoT world, web platform can be one of the promising interoperability enabler platform due to its massive success in current internet era. In order to integrate the web and IoT, a middleware with efficient communication architecture is required. In this paper, we designed and implemented publish subscribe based middleware for enabling real time web access on constrained device. The proposed system consists of three components : the sensor-actuator equipped device and its web based client counterpart acting as both publisher/subscriber, and MQTT broker. In order to send its sensing data to user, each device periodically publish a message with specific topic. In another side, user subscribe to that topic for getting the latest data from a device. The similar natures are applied for communication in reverse direction i.e. the user giving command to device. For enabling web access to the system, web based client utilize MQTT through websocket protocol to communicate with broker while the device utilize MQTT on top of pure TCP/IP stack to reduce the communication overhead. From the functional and performance testing we conclude that the proposed system is able to bridge the communication between web based client to the device with reasonable performance.","PeriodicalId":267403,"journal":{"name":"2017 9th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124980147","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: 7