• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.2
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• pp.7-12
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• 2009

The new approach was proposed which uses feature extraction based on fuzzy integral in the process of face verification using morphological shape decomposition. The centre of area was used with image pixels related with structure element and its weight in an attempt to consider neighborhood information. Therefore the morphological operators were defined for feature extraction. And then the number of decomposition images were more about 4 times than the conventional. Finally in the simulations with the extractions for face verification it was proved that the approach in this paper was even more good than the conventional in stability of feature extraction and threshold value.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.137-144
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• 2010

Cyber lectures have been popular with students as they are more accessible. In this thesis we also created a personal identification confirmation system with RFID as it is quite difficult to confirm who is taking a lecture. In the process of developing the confirmation system, an algorithm enabling real-time identification confirmation, as well as interactive virtual questioning system, was also developed. After the computer simulation test we proved the duplex on-line lecturing system is more effective than the current one-way cyber lecturing system which does not take into consideration students with less/no degree of understanding.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.254-261
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• 2016

The present research paper is devoted to solving an urgent problem, i.e., the energy saving and energy efficiency of buildings. A rapid settlement method and experimental control of the energy conservation based on the specific characteristics of the thermal energy consumption for the heating and ventilation of the buildings, and as well as the rapid development of wireless sensor networks, can be used in a variety of monitoring parameters in our daily lives. Today's world has become quite advanced with smart appliances and devices such as laptops, tablets, TVs, and smartphones with various functions, and their use has increased significantly in our day-to-day lives. In this case, the most important role is played by a wireless sensor network with its development and use in heterogeneous areas and in several different contexts. The fields of home automation, process management, and health management systems make extensive use of wireless sensor networks. In this paper, we explore the main factors of the microclimate in an indoor environment. We control the temperature humidity, and other factors remotely using sensors and Internet-of-Things technologies.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.246-253
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• 2016

Infrared (IR) imaging has been researched for various applications such as surveillance. IR radiation has the capability to detect thermal characteristics of objects under low-light conditions. However, automatic segmentation for finding the object of interest would be challenging since the IR detector often provides the low spatial and contrast resolution image without color and texture information. Another hindrance is that the image can be degraded by noise and clutters. This paper proposes multi-level segmentation for extracting regions of interest (ROIs) and objects of interest (OOIs) in the IR scene. Each level of the multi-level segmentation is composed of a k-means clustering algorithm, an expectation-maximization (EM) algorithm, and a decision process. The k-means clustering initializes the parameters of the Gaussian mixture model (GMM), and the EM algorithm estimates those parameters iteratively. During the multi-level segmentation, the area extracted at one level becomes the input to the next level segmentation. Thus, the segmentation is consecutively performed narrowing the area to be processed. The foreground objects are individually extracted from the final ROI windows. In the experiments, the effectiveness of the proposed method is demonstrated using several IR images, in which human subjects are captured at a long distance. The average probability of error is shown to be lower than that obtained from other conventional methods such as Gonzalez, Otsu, k-means, and EM methods.

• Computers and Concrete
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• v.14 no.6
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• pp.727-743
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• 2014

The management of existing concrete bridges has become a major social concern in many developed countries due to the large number of bridges exhibiting signs of significant deterioration. This problem has increased the demand for effective maintenance and renewal planning. In order to implement an appropriate management procedure for a structure, a wide array of corrective strategies must be evaluated with respect to not only the condition state of each defect but also safety, economy and sustainability. This paper describes a new performance evaluation system for existing concrete bridges. The system evaluates performance based on load carrying capability and durability from the results of a visual inspection and specification data, and describes the necessity of maintenance. It categorizes all girders and slabs as either unsafe, severe deterioration, moderate deterioration, mild deterioration, or safe. The technique employs an expert system with an appropriate knowledge base in the evaluation. A characteristic feature of the system is the use of neural networks to evaluate the performance and facilitate refinement of the knowledge base. The neural network proposed in the present study has the capability to prevent an inference process and knowledge base from becoming a black box. It is very important that the system is capable of detailing how the performance is calculated since the road network represents a huge investment. The effectiveness of the neural network and machine learning method is verified by comparing diagnostic results by bridge experts.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.4
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• pp.238-246
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• 2011

This paper proposes a new semantic representation and its associated similarity measure. The representation expresses textual context observed in a context of a certain term as a network where nodes are terms and edges are the number of cooccurrences between connected terms. To compare terms represented in networks, a graph kernel is adopted as a similarity measure. The proposed representation has two notable merits compared with previous semantic representations. First, it can process polysemous words in a better way than a vector representation. A network of a polysemous term is regarded as a combination of sub-networks that represent senses and the appropriate sub-network is identified by context before compared by the kernel. Second, the representation permits not only words but also senses or contexts to be represented directly from corresponding set of terms. The validity of the representation and its similarity measure is evaluated with two tasks: synonym test and unsupervised word sense disambiguation. The method performed well and could compete with the state-of-the-art unsupervised methods.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.1 s.178
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• pp.64-71
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• 2006

Ultraprecision machining and MEMS technology have been taken more and more important position in machining of microparts. Micro endmilling is one of the prominent technology that has wide spectrum of application field ranging from macro parts to micro products. Also, the method of micro-grooving using micro endmill is used widely owing to many merit, but has problems of precision and quality of products due to tool wear and tool fracture. This investigation deals with state monitoring using acoustic emission(AE) signal in the micro-grooving. Characteristic evaluation of AE raw signal, AE hit and frequency analysis for condition monitoring is presented. Also, the feature extraction of AE signal directly related to machining process is executed. Then, the distinctive micro endmill state according to the each tool condition is classified by the fuzzy C-means algorithm.

• Asian Journal of Atmospheric Environment
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• v.12 no.3
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• pp.215-231
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• 2018

In order to understand the variation of air quality and the concentration of atmospheric particulates in Chengdu Second Ring Road renovation project, this paper starts to investigate the surrounding residents' opinions on the influenced environment and their daily lives via questionnaires. Then the study numerically simulates the change rule of atmospheric particulates in terms of time and space by using the Gaussian dispersion-deposition model and the compartment model. The optimized scientific scheme is selected by the improved fuzzy analytical hierarchy process(FAHP) to help decision making for the future urban reconstructions. Finally, the reduced emissions of atmospheric particulates are measured when the improvement scheme is provided. According to the study, it can be concluded that the concentration of atmospheric particulates increases rapidly in central Chengdu city during the renovation project, which results in worsening air quality in Chengdu during March 2012 to March 2013. Taking related measures on energy saving and emission reduction can effectively reduce the concentration of atmospheric particulates and promote economic, environmental and social coordination.

• Proceedings of the Korean System Dynamics Society
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• 1999.08a
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• pp.105-132
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• 1999

If a system such as a port has a large boundary and complexity, and the system's substance is considered as a black box, forecast accuracy will be very low. Furthermore various components in a port exert significant influence on each other. To copy with these problem the form of structure models were introduced by using SD method. The Competitive Ports Model had several sub-systems consisting of each Unit Port models, and each Unit Port model was made by quantitative, qualitative factors and their feedback loops. The fact that all components of one port have influence on the components of the other ports should be taken into account to construct Competitive Port Models. However, with the current approach that is impossible, and in this paper, therefore, models were simplified by HFP adapted to integrate level variables of unit port models. Although many studies on modelling of port competitive situation have been conducted, both theoretical frame and methodology are still very weak. In this study, a new algorithm called ESD(Extensional System Dynamics) for the evaluation of port competition was presented, and applied to simulate port systems in northeast Asia.

• Proceedings of the KOSOMBE Conference
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• v.1990 no.05
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• pp.33-37
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• 1990

In this paper, a new method for lung area segmentation in chest radiographs has been presented. The movivation of this study is to include fuzzy informations about the relation between the image date structure and the area to be segmented in the segmentation process efficiently. The proposed method approached the segmentation problem in the perspective of pattern classification, using trainable pattern classifier, multi-layer perceptron. Having been trained with 10 samples, this method gives acceptable segmentation results, and also demonstrated the desirable property of giving better results as the training continues with more training samples.