Y. Matsumura, Ayumu Kobayashi, Kiyotaka Sugiyama, T. Pataky, T. Yasuda, K. Ohkura, Bill Sellers
{"title":"A (μ, λ) evolutionary and particle swarm hybrid algorithm, with an application to dinosaur gait optimization","authors":"Y. Matsumura, Ayumu Kobayashi, Kiyotaka Sugiyama, T. Pataky, T. Yasuda, K. Ohkura, Bill Sellers","doi":"10.1109/IWCIA.2013.6624791","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624791","url":null,"abstract":"A hybrid evolutionary algorithm based on (μ, λ) evolutionary algorithms and particle swarm optimization is proposed for the numerical optimization problems. In order to find out the performance of the hybrid, the computer experiment is tested on dinosaur's gait generation problem. Experimental results show that hybrid optimization finds maximum fitness and is faster in the first phase.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115788410","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":"An estimation of favorite value in emotion generating calculation by Fuzzy Petri Net","authors":"T. Ichimura, Kousuke Tanabe","doi":"10.1109/IWCIA.2013.6624777","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624777","url":null,"abstract":"Emotion Generating Calculations (EGC) method based on the Emotion Eliciting Condition Theory can decide whether an event arouses pleasure or not and quantify the degree under the event. An event in the form of Case Frame representation is classified into 12 types of calculations. However, the weak point in EGC is Favorite Value (FV) as the personal taste information. In order to improve the problem, this paper challenges to establish a learning method to learn speaker's taste information from dialog. Especially, the learning method employs Fuzzy Petri Net to find an appropriate FV to a word which has the unknown FV. This paper discusses the effective learning method to improve a weak point of EGC when a missing value of FV exists.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125752719","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":"Meta-heuristic algorithms applied to the optimization of type-1 and type 2 TSK fuzzy logic systems for sea water level prediction","authors":"Nguyen Cong Long, P. Meesad","doi":"10.1109/IWCIA.2013.6624787","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624787","url":null,"abstract":"This paper describes an approach using Firefly Algorithm, Particle Swarm Optimization and Genetic Algorithm to optimize the parameters of Takagi-Sugeno-Kang (TSK) fuzzy logic system (both type-1 and type-2) in order to find the optimal fuzzy logic system for sea water level prediction. The obtained results of the simulations performed are compared among these optimization algorithms in order to find which one is the best optimization algorithm for sea water level prediction.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125832498","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":"Dependent input neuron selection in contradiction resolution","authors":"R. Kamimura","doi":"10.1109/IWCIA.2013.6624781","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624781","url":null,"abstract":"In this paper, we propose a new type of information theoretic method called “dependent input neuron selection” in the framework of contradiction resolution. In contradiction resolution, a neuron fires without considering other neurons (self-evaluation), and at the same time the neuron's firing rate is determined by other neurons (outer-evaluation). If there exists contradiction between self and outer-evaluation, the contradiction should be reduced as much as possible. Roughly speaking, outer-evaluation corresponds to cooperation between neurons in the self-organizing maps. Thus, contradiction resolution can be applied to the production of self-organizing maps. In this contradiction resolution, we introduce dependent input neuron selection. The importance of neurons is determined by the degree of matching between neurons. A limited number of best-matching input neurons participate in processing input patterns. We applied the method to the CO2 production. Experimental results showed that prediction performance was much improved by choosing the appropriate number of input neurons. In addition, better prediction performance was accompanied by reasonably small quantization and topographic errors. The results suggest a possibility of contradiction resolution to produce networks with higher prediction performance and better topological properties.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131571542","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":"Detecting electrical stimulation of cortical mapping from recorded awake surgery sounds","authors":"Toshihiko Nishimura, T. Nagao","doi":"10.1109/IWCIA.2013.6624794","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624794","url":null,"abstract":"Recently the surgical operation is recorded by the video camera and the sound recorder, so a number of intraoperative records are stored. There are, however, no indexes for searching surgical events, so these intraoperative records are not exploited sufficiently for analysis of surgical procedures. In our study, we target the records of awake surgery performed in the Intelligent Operating Theater of Tokyo Women's Medical University by using Intraoperative Examination Monitor for Awake Surgery(IEMAS) system. There are a number of useful intraoperative records of surgical procedures. In this paper, we propose an automatic indexing method for electrical stimulation of corical mapping which is of paramount importance in awake surgery. The electric sounds are output from the instrument while the surgeon performs direct electrical stimulation of cortical area. It is, therefore, possible to index automatically to detect these sounds. The power of this sound is, however, weak because the instrument is located aside from the sound recorder. We adopt short-term autocorrelation analysis for detection of the signals and dynamic thresholding for indexing electrical stimulation automatically. In the experiment, we applied the proposed indexing method for actual intraoperative records. The proposed approach is able to index the surgical events successfully.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123988830","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":"Early discovery of chronic non-attenders by using NFC attendance management system","authors":"T. Ichimura, Shin Kamada","doi":"10.1109/IWCIA.2013.6624813","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624813","url":null,"abstract":"Near Field Communication (NFC) standards cover communications protocols and data exchange formats. They are based on existing radio-frequency identification (RFID) standards. In Japan, Felica card is a popular way to identify the unique ID. Recently, the attendance management system (AMS) with RFID technology has been developed as a part of Smart University, which is the educational infrastructure using high technologies, such as ICT. However, the reader/writer for Felica is too expensive to build the AMS. NFC technology includes not only Felica but other type of IC chips. The Android OS 2.3 and the later can provide access to NFC functionality. Therefore, we developed AMS for university with NFC on Nexus 7. Because Nexus 7 is a low cost smart tablet, a teacher can determine to use familiarly. Especially, this paper describes the method of early discovery for chronic non-attenders by using the AMS system on 2 or more Nexus 7 which is connected each other via peer-to-peer communication. The attendance situation collected from different Nexus 7 is merged into a SQLite file and then, the document is reported to operate with the trunk system in educational affairs section.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"69 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124282228","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}
H. Katagiri, Takeshi Uno, Kosuke Kato, H. Tsuda, H. Tsubaki
{"title":"An interactive multiobjective programming approach to tour route planning problems","authors":"H. Katagiri, Takeshi Uno, Kosuke Kato, H. Tsuda, H. Tsubaki","doi":"10.1109/IWCIA.2013.6624807","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624807","url":null,"abstract":"This article considers tour route planning problems to find an optimal tour route in sightseeing. Tour routes are optimized in terms of two types of criteria. The first optimization criterion is to maximize the sum of values of places a tourist visits, namely, the sum of the values of sightseeing spots, restaurants and hotels. The second optimization criterion is to minimize the tiredness caused by moving from place to place, which is dependent on means of transportation. This paper provides a problem formulation of a tour route planning problem as a multiobjective mixed 0-1 programming problem in which the number of constraints is a polynomial order of the number of places possible to visit or stay. An interactive algorithm is provided in order to find a satisficing solution reflecting tourist's preferences.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122177053","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}
Tomohiro Hayashida, I. Nishizaki, Tsubasa Matsumoto
{"title":"Structural optimization of neural network for data prediction using dimensional compression and tabu search","authors":"Tomohiro Hayashida, I. Nishizaki, Tsubasa Matsumoto","doi":"10.1109/IWCIA.2013.6624790","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624790","url":null,"abstract":"In the traditional procedures, data classification with a high degree of accuracy by neural networks requires heuristic structural optimization by using expert knowledge. However, the optimization procedure takes an immense amount of time and effort. Additionally, high-dimensional data is difficult to classify for many analysts, thus, it would appears that accuracy of data classification grows higher by proper selection and dimensional compression of input data. This study suggests new procedure for data classification by using neural networks. For dimensional compression of input data, the suggested procedure uses sandglass type neural networks, and tabu search algorithms are applied for input data selection and structural optimization of union between a sandglass type and a feedforward neural networks.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"191 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123264436","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":"Stereo vision for the measurement of turning tool size","authors":"Pei-Ju Chiang, Geng-Hao Ping","doi":"10.1109/IWCIA.2013.6624809","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624809","url":null,"abstract":"During computer numerical control (CNC) machining, interference and collisions can occur due to discrepancies between simulations and actual operating conditions, which can result in time loss and increased costs. The aim of this study was to measure the size of the tools used in CNC machines using automatic sensors in order to determine whether discrepancies exist between simulations and actual machining resulting from human negligence. Using a 3D stereo vision system, we obtained images of turning tools and extracted the required information related to tool features through image processing. Epipolar geometry was applied to simplify the dimensions of the feature search, and the theory and methods of object reconstruction in stereo vision systems were used to obtain the size of the turning tool.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128591496","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":"Harmonic filters planning of system for specially connected transformers using PSO-NTVE method","authors":"Ying-Pin Chang","doi":"10.1109/IWCIA.2013.6624775","DOIUrl":"https://doi.org/10.1109/IWCIA.2013.6624775","url":null,"abstract":"This paper is used to investigate the harmonic filters planning of a power system with three-phase to two-phase specially connected transformers. A particle swarm optimization method with nonlinear time-varying evolution (PSO-NTVE) is employed in the planning of large-scale passive harmonic filters. The objective is to minimize the cost of the filter, the filters loss, the total harmonic distortion of currents and voltages at each bus simultaneously. The reactive power compensation and constraints of individual harmonics are also considered. Three design cases are compared to demonstrate the design results. The study results shows that the scheme type of three-phase to two-phase specially connected transformers have significant effects on the harmonic distribution. The phase B of VV connection scheme has reduced 3rd order harmonic distortion, the Scott and Le Blanc connection scheme batter than VV connection scheme for improved harmonic distortion, and the many typical passive filters structure batter than one typical filter. From the results of the illustrative examples, the feasibility of the PSO-NTVE to design an optimal passive harmonic filter is verified.","PeriodicalId":257474,"journal":{"name":"2013 IEEE 6th International Workshop on Computational Intelligence and Applications (IWCIA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117068628","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}