• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1195-1200
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• 2013

In this paper, we proposed an enhanced Max-Min neural network by auto-tuning of learning rate using fuzzy control method. For the reduction of training time required in the competition stage, the method was proposed that arbitrates dynamically the learning rate by applying the numbers of the accuracy and the inaccuracy to the input of the fuzzy control system. The experiments using real concrete crack images showed that the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.8
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• pp.1129-1135
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• 2013

A new vehicle detection algorithm based on the multiple optimal Adaboost classifiers with optimal feature selection is proposed. It consists of two major modules: 1) Theoretical DDISF(Distance Dependent Image Scaling Factor) based image scaling by site modeling of the installed cameras. and 2) optimal features selection by Haar-like feature analysis depending on the distance of the vehicles. The experimental results of the proposed algorithm shows improved recognition rate compare to the previous methods for vehicles and non-vehicles. The proposed algorithm shows about 96.43% detection rate and about 3.77% false alarm rate. These are 3.69% and 1.28% improvement compared to the standard Adaboost algorithmt.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.6
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• pp.67-75
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• 1998

Although the nCE(n-th order cross-entropy) error function resolves the incorrect saturation problem of conventional EBP(error back-propagation) algorithm, the performance of MLP's (multilayer perceptrons) trained using the nCE function depends heavily on the order of the nCE function. In this paper, we propose an adaptive learning rate to make the performance of MLP's insensitive to the order of the nCE error. Additionally, we propose a limited error signal of output node to prevent unstable learning due to the adaptive learning rate. The effectiveness of the proposed method is demonstrated in simulations of handwritten digit recognition and thyroid diagnosis tasks.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.8
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• pp.855-861
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• 2007

Haptic rendering is a process providing force feedback during interactions between a user and a virtual object. This paper presents a real-time haptic rendering technique for deformable objects based on visual information of intervention between a tool and a real object in a remote place. A user can feel the artificial reaction force through a haptic device in real-time when a slave system exerts manipulation tasks on a deformable object. The models of the deformable object and the manipulator are created from the captured image obtained with a CCD camera and the recognition of objects is achieved using image processing techniques. The force at a rate of 1 kHz for stable haptic interaction is deduced using extrapolation of forces at a low update rate. The rendering algorithm developed was tested and validated on a test platform consisting of a one-dimensional indentation device and an off-the shelf force feedback device. This software system can be used in a cellular manipulation system providing artificial force feedback to enhance a success rate of operations.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.17-22
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• 2017

In this paper, a password recognition system that can overcome a shoulder-surfing attack is developed. During the time period of password insertion, the developed system can prevent the attack and enhance the safety of the password. In order to raise the detection rate of the password image, the mopology technique is utilized. By adapting 4 times of the expansion and dilation, the niose from the binary image of the password is removed. Finally, the mobile phone application is also developed to recognize the one time password and the detection rate is measured. It is shown that the detection rate of 90% is achieved under the dark light condition.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2013.11a
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• pp.139-140
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• 2013

Ground source heat pump systems can achieve the energy saving of building and reduce CO₂ emission by utilizing stable ground temperature. However, they have many barriers such as high cost of installation, incompletion of design tool, lack of recognition as heating and cooling systems. In order to solve the problems, the building integrated geothermal system (BIGS) developed by several researches which use building foundation as a heat exchanger. In order to establish the optimum design tool of BIGS with the horizontal heat exchanger, the prediction method of ground heat exchange rate developed with numerical simulation model. In this study, the economic analysis for BIGS was conducted based on simulation results and the optimal design method was suggested. As a result, it was found that the case of 32 A, piping space 0.3 m, piping deep 0.5 m and flow rate 9.52 L/min was the best case as 50.1 W/m2 of heat exchange rate. In this case the initial cost was reduced to 115 million won.

• The KIPS Transactions:PartB
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• v.13B no.5 s.108
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• pp.561-568
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• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.241-250
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• 2012

Low birth rate is a persisting national challenge that causes a decrease in productive population and an increase in encumbrances by ever rising insurance premiums, eventually threatening the existence of the country. This study investigated the effectiveness of the current government's undergoing economic support of the child-birth promotion policy, "go-un-mam card", and suggested improvement plans about the problems derived on the basis of the perceptions of the card users. Multi-response analysis was used to find out the preference of the policy, and chi-square test was conducted to discover the user satisfaction rate and intent of re-parturition. Also, descriptive analysis was performed to identify the degree of the policy recognition. The results illustrated that a significant association exists between the satisfaction rate and the intention of re-parturition. In addition, pregnant women gained information about the policy from governmental agencies and medical institution as well as by word of mouth; then, applied to the policy. Also, the card users only took an advantage of discounts in the hospitals within the supported monetary amounts. Moreover, the card users expressed their dissatisfaction at the monetary amounts. For instance, the users were dissatisfied with the limit on the amount to be used in a day and requested upgrade on the monetary amounts. Based on the result, the government will improve and develop the go-un-mam card for the ultimate purpose of policy, increasing birth-rate.

• Journal of dental hygiene science
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• v.10 no.3
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• pp.141-146
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• 2010

The purpose of this study was to survey the knowledge of parents, to prepare basic data for the development of adjusted water fluoridation program. The survey with self-administrated questionnaire was carried out to n 1,418 parents of school-children in Kimje city and then analyzed obtained the results. The data were analysed using the chisquare test. Over all, 58.4 percent of parents has heard about adjusted water fluoridation. 50.1% respondents knew very well the object of water fluoridation program which is implemented to prevent dental caries. The recognition rate of water fluoridation were different according to respondent's education level(p=.000) and income(p=.019). The approval rate of water fluoridation were different according to respondent's education level age level and income(p<.001). The parents had the affirmative opinion for the adjusted water fluoridation was 4.5 times more than the negative opinion. Respondents approving and opposing for the implementation of water fluoridation were 82.3% and 17.7%, respectively. The recognition rate and approval rate of water fluoridation had the affirmative opinion for the adjusted water fluoridation was more than the negative opinion. Respondents approving and opposing for the implementation of water fluoridation were 85.5% and 14.2%, respectively. The parents of school children had affirmative opinion to the adjusted water fluoridation. So for implementation of the water fluoridation, it is required to reinforce education for inhabitants through delivery of right information and various publicity activities.