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2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)最新文献

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Face recognition: A multivariate mutual information based approach 人脸识别:一种基于多元互信息的方法
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175979
Hammad Dilpazir, H. Mahmood, M. Zia, Hafiz Malik
{"title":"Face recognition: A multivariate mutual information based approach","authors":"Hammad Dilpazir, H. Mahmood, M. Zia, Hafiz Malik","doi":"10.1109/CYBConf.2015.7175979","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175979","url":null,"abstract":"A method based on multivariate mutual information (MMI) is proposed for face recognition. Unlike the existing frameworks, the proposed method is not hindered by rigorous computation for feature extraction and learning spaces. The proposed method uses information-theoretic framework for face recognition. The training set is used to estimate the underlying joint and marginal densities, which are utilized to calculate the mutual information. The mutual information for each pixel value is used to highlight the regions, that correspond to maximum information that are used for face recognition process. Performance of the proposed method is evaluated on two image datasets. The recognition performance of the proposed method is also compared with existing principal component analysis (PCA) based face recognition algorithms.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125048071","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: 3
Linguistic variable elimination for a heart failure dataset 心力衰竭数据集的语言变量消除
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175931
J. Bohacik, K. Matiaško, Miroslav Benedikovic
{"title":"Linguistic variable elimination for a heart failure dataset","authors":"J. Bohacik, K. Matiaško, Miroslav Benedikovic","doi":"10.1109/CYBConf.2015.7175931","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175931","url":null,"abstract":"Patients with heart failure often suffer disabling symptoms. In addition to these symptoms, half of all patients diagnosed with heart failure die within four years. The prevalence of heart failure is currently about 2%-3% of the adult population and it is expected to grow. It is interesting to predict if a patient with heart failure dies soon so that life-threatening situations and costs are minimized. In this paper, a data mining method for discovering fuzzy rules with different truth level thresholds in linguistic variable elimination for prediction of death on the basis of data available in hospitals is presented. Cognitive uncertainties are taken into consideration through the use of fuzzy sets, membership functions and membership degrees. The accuracy of the prediction of the death for a patient with heart failure and the interpretability of fuzzy rules are discussed. Our study shows, in comparison to other data mining methods, that it is useful for this type of prediction.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123837106","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
Framework for ontology evolution based on a multi-attribute alignment method 基于多属性对齐方法的本体演化框架
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175915
Marcin Pietranik, N. Nguyen
{"title":"Framework for ontology evolution based on a multi-attribute alignment method","authors":"Marcin Pietranik, N. Nguyen","doi":"10.1109/CYBConf.2015.7175915","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175915","url":null,"abstract":"In this paper we want to investigate how to measure changes that occur when ontologies evolve in time. In the modern semantic online environments users cannot assume that initially created ontologies will remain static throughout the whole lifespan of particular application. Moreover, alignments originally established between such ontologies can become stale and invalid when certain changes have been applied to maintained ontologies. Therefore, such mappings should evolve in parallel. These issues raise some important questions: How to express changes introduced to ontologies? When the revalidation of alignments should occur? Is it necessary to relaunch an alignment procedure for the whole ontologies or is it possible to check and adjust only small fragments of mappings affected by applied modifications?","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122530554","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: 4
Traditional and self-adaptive differential evolution for the p-median problem p中值问题的传统和自适应差分进化
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175950
P. Krömer, J. Platoš, V. Snás̃el
{"title":"Traditional and self-adaptive differential evolution for the p-median problem","authors":"P. Krömer, J. Platoš, V. Snás̃el","doi":"10.1109/CYBConf.2015.7175950","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175950","url":null,"abstract":"The p-median problem is an established combinatorial optimization problem with several alternative formulations and a number of real-world applications in areas such as operational research and planning. It has been also used as a testbed for many heuristic and metaheuristic optimization algorithms. Recently, it was shown that a simple, traditional, variant of the differential evolution algorithm is able to solve certain p-median problem instances on a competitive level. This work compares the performance of the traditional differential evolution with two adaptive variants of this algorithm on several well-known p-median problem instances.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"192 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116403564","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
Face 3D biometrics goes mobile: Searching for applications of portable depth sensor in face recognition 人脸三维生物识别走向移动:探索便携式深度传感器在人脸识别中的应用
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175983
Weronika Gutfeter, A. Pacut
{"title":"Face 3D biometrics goes mobile: Searching for applications of portable depth sensor in face recognition","authors":"Weronika Gutfeter, A. Pacut","doi":"10.1109/CYBConf.2015.7175983","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175983","url":null,"abstract":"This paper presents an acquisition procedure and method of processing spatial images for face recognition with the use of a novel type of scanning device, namely mobile depth sensor Structure. Depth sensors, often called RGBD cameras, are able to deliver 3D images with a frame rate 30-60 frames per second, however they have relatively low resolution and a high level of noise. This kind of data is compared here with a high quality scans enrolled by the structural light scanner, for which the acquisition time is approximately 1.5 s for a single image, and which - because of its size - cannot be classified as a portable device. The purpose of this work was to find the method that will allow us to extract spatial features from mobile data sources analyzed here only in a static context. We transform the 3D data into local surface features and then into vectors of unified length by use of the Moving Least Squares method applied to a predefined grid of points on a reference cylinder. The feature matrices were calculated for various image features, and used in PCA analysis. Finally, the verification errors were calculated and compared to those obtained for stationary devices. The results show that single-image mobile sensor images lead to the results inferior to those of stationary sensors. However, we suggest a dynamic depth stream processing as the next step in the evolution of the described method. The presented results show that by including multi-frame processing into our method, it is likely to gain the accuracy similar to those obtained for a stationary device under controlled laboratory conditions.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127574587","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: 4
Position estimation at zero speed for PMSM using probabilistic neural network 基于概率神经网络的永磁同步电机零转速位置估计
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175972
K. Urbanski
{"title":"Position estimation at zero speed for PMSM using probabilistic neural network","authors":"K. Urbanski","doi":"10.1109/CYBConf.2015.7175972","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175972","url":null,"abstract":"The paper presents a method for estimating the shaft position of a synchronous motor with permanent magnets (PMSM) for the zero and very low speed range. The method is based on the analysis of the high frequency currents, which are induced by the additional test voltage in a stationary coordinate system associated with the stator. Although this method involves the identification of currents hodograph, the method does not need to calculate the current ellipse position. Presented method involves a comparison of obtained shape to the reference pattern using probabilistic neural network (PNN). The method can achieve satisfactory accuracy in a case the high asymmetry of the inductance, as well as in the case of small values of the inductance asymmetry ratio, also in the case of a high level of noise.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133692959","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
Network resource allocation in distributed systems: A global optimization framework 分布式系统中的网络资源分配:一个全局优化框架
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175944
Z. Wesołowski
{"title":"Network resource allocation in distributed systems: A global optimization framework","authors":"Z. Wesołowski","doi":"10.1109/CYBConf.2015.7175944","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175944","url":null,"abstract":"The paper proposes a global optimization approach to the network resource allocation problem, where the objective is to maximize the overall data flow through a shared network. In the proposed approach, the utility functions of agents may have different forms, which allows a more realistic modeling of phenomena occurring in computer networks. To solve the optimization problem, a modified gradient projection method has been applied.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116374895","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: 4
A forecasting method based on extrema mean empirical mode decomposition and wavelet neural network 基于极值均值经验模态分解和小波神经网络的预测方法
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175963
Jianjia Pan, Xianwei Zheng, Lina Yang, Yulong Wang, Haoliang Yuan, Yuanyan Tang
{"title":"A forecasting method based on extrema mean empirical mode decomposition and wavelet neural network","authors":"Jianjia Pan, Xianwei Zheng, Lina Yang, Yulong Wang, Haoliang Yuan, Yuanyan Tang","doi":"10.1109/CYBConf.2015.7175963","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175963","url":null,"abstract":"Time series forecasting is a widely and important research area in signal processing and machine learning. With the development of the artificial intelligence (AI), more and more AI technologies are used in time series forecasting. Multi-layer network structure has been widely used for forecasting problems. In this paper, based on a data-driven and adaptive method, extrema mean empirical mode decomposition, we proposed a decomposition-forecasting-ensemble approach to time series forecasting. Experimental result shows the prediction result by proposed models are better than original signal and EMD based models.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115249154","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
Extreme learning machine for function approximation - interval problem of input weights and biases 函数逼近的极限学习机——输入权值和偏差的区间问题
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175907
Grzegorz Dudek
{"title":"Extreme learning machine for function approximation - interval problem of input weights and biases","authors":"Grzegorz Dudek","doi":"10.1109/CYBConf.2015.7175907","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175907","url":null,"abstract":"In this article the approximation capability of the extreme learning machine is studied. Specifically the impact of the range from which the input weights and biases are randomly generated on the fitted curve complexity is analyzed. The guidance for how to generate the input weights and biases to get good performance in approximation of the functions of one variable is provided.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115342913","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
Standardization in IRIS diagnosis IRIS诊断的标准化
2015 IEEE 2nd International Conference on Cybernetics (CYBCONF) Pub Date : 2015-06-24 DOI: 10.1109/CYBConf.2015.7175934
P. Perner
{"title":"Standardization in IRIS diagnosis","authors":"P. Perner","doi":"10.1109/CYBConf.2015.7175934","DOIUrl":"https://doi.org/10.1109/CYBConf.2015.7175934","url":null,"abstract":"Molecular image-based techniques are widely used in medicine to detect specific diseases. The analysis of the eye plays an important role in order to detect specific diseases. Eye background analysis is used in order to detect certain forms of diabetes and others diseases. In the alternative medicine plays the diagnosis of the iris an important role. One understands by iris diagnosis (Iridology) the investigation and analysis of the colored part of the eye, the iris, to discover factors which play an important role for the prevention and treatment of illnesses, but al-so for the preservation of an optimum health. Although alternative practitioner describe substantial success with the iris diagnosis. The conventional medicine is not convinced of the diagnosis method. A big drawback of the method is the subjective interpretation of what is seen in the iris image. An automatic system would pave the way for much wider use of the iris diagnosis for the diagnosis of illnesses and for the purpose of individual health protection. With this paper we de-scribe our work towards an automatic iris diagnosis system. We describe the image acquisition and the problems with it. Different ways of image acquisition and image preprocessing are explained. We describe the image analysis method for the detection of the iris. This method is based on our novel case-based object recognition and case mining method. Results for the recognition of the iris are given. We describe how to detect the pupil and not wanted lamp spots. We explain how to recognize orange blue spots in the iris and match them against the topological map of the iris. Finally, we give an outlook for further work.","PeriodicalId":177233,"journal":{"name":"2015 IEEE 2nd International Conference on Cybernetics (CYBCONF)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128062170","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: 4
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