• Journal of Korean Library and Information Science Society
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• v.54 no.3
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• pp.295-320
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• 2023

Jeongseon-gun has the SaBuk Public Library, 17 small libraries, and the Jeongseon Educational Library. In 2023, with the completion of the Jeongseon County Public Library, there is a need to establish innovative library policy strategies that consider balanced development by region. The primary goal of this study was to set the direction for the future of Jeongseon County's public libraries and provide appropriate strategies. To achieve this, an examination of the local situation and characteristics of Jeongseon County was conducted, followed by an analysis of the operational status of the public libraries. Additionally, a satisfaction survey and demand analysis were conducted among the residents of Jeongseon County regarding the libraries, to analyze directions for library improvements. Ultimately, taking into account the local characteristics, library status, and residents' needs, an optimized strategy for the region was presented. As a result of the study, the operational goal to achieve the vision was set as "a life-friendly library that shares the healthy lives of residents of Jeongseon-gun," and emphasized its role as a companion close to daily life for the healthy lives of Jeongseon-gun residents. The four strategic tasks to promote the operational goals were expressed as "a library that grows with local residents," "a library that provides multicultural exchange," "a sustainable future-oriented library," and "a library that cooperates with the local community."

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.11
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• pp.1168-1172
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• 2011

Beam projector is popularly used for presentation. In order to pay attention to local area of the beam projector display, a laser pointer is used together with a pointing device(Mouse). Simple wireless presenter has limited functions of a pointing device such as "go to next slide" or "back to previous slide" in a specific application(Microsoft PowerPoint) through wireless channel; thus, there is inconvenience to do other tasks e.g., program execution, maximize/minimize window etc. provided by clicking mouse buttons. The main objective of this paper is to implement a multi-functional laser-pointer mouse that has the same functions of a computer mouse. In order to get position of laser spot in the projector display, an image processing to extract the laser spot in the camera image is required. In addition, we propose a transformation of the spot position into computer display coordinates to execute mouse functions on computer display.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.740-745
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• 2003

Motion tracking and object segmentation are the most fundamental and critical problems in vision tasks suck as motion analysis. An active contour model, snake, was developed as a useful segmenting and tracking tool for rigid or non-rigid objects. Snake is designed no the basis of snake energies. Segmenting and tracking can be executed successfully by energy minimization. In this research, two new paradigms for segmentation and tracking are suggested. First, because the conventional method uses only intensity information, it is difficult to separate an object from its complex background. Therefore, a new energy and design schemes should be proposed for the better segmentation of objects. Second, conventional snake can be applied in situations where the change between images is small. If a fast moving object exists in successive images, conventional snake will not operate well because the moving object may have large differences in its position or shape, between successive images. Snakes's nodes may also fall into the local minima in their motion to the new positions of the target object in the succeeding image. For robust tracking, the condensation algorithm was adopted to control the parameters of the proposed snake model called "adaptive color snake model(SCSM)". The effectiveness of the ACSM is verified by appropriate simulations and experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3762-3781
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• 2020

Infrared pedestrian target recognition is a vital problem of significant interest in computer vision. In this work, a novel infrared pedestrian target recognition method that uses heterogeneous features with multi-kernel transfer learning is proposed. Firstly, to exploit the characteristics of infrared pedestrian targets fully, a novel multi-scale monogenic filtering-based completed local binary pattern descriptor, referred to as MSMF-CLBP, is designed to extract the texture information, and then an improved histogram of oriented gradient-fisher vector descriptor, referred to as HOG-FV, is proposed to extract the shape information. Second, to enrich the semantic content of feature expression, these two heterogeneous features are integrated to get more complete representation for infrared pedestrian targets. Third, to overcome the defects, such as poor generalization, scarcity of tagged infrared samples, distributional and semantic deviations between the training and testing samples, of the state-of-the-art classifiers, an effective multi-kernel transfer learning classifier called MK-TrAdaBoost is designed. Experimental results show that the proposed method outperforms many state-of-the-art recognition approaches for infrared pedestrian targets.

• Clinical and Experimental Pediatrics
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• v.62 no.10
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• pp.395-399
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• 2019

Background: The esophagus is the most common part of gastrointestinal (GI) tract at the risk of stricture. Benign disorders are the leading causes of narrowing. Caustic ingestion is the most common cause of esophageal stricture in children, especially in developing countries. Clinical responses to the topical application of Mitomycin C in various medical procedures have been reported. Purpose: The study aimed to evaluate the methodology, efficacy, and side effects of Mitomycin C in the treatment of esophageal strictures. Methods: This study included 30 children with resistant esophageal strictures. Upper GI endoscopy was performed up to the area of stricture, esophageal dilatation was done, endoscopy was repeated, and Mitomycin C was applied topically under direct endoscopic vision. The effect of the procedure was followed over a period of 3-5 years. Results: The response to Mitomycin C was excellent (clinically and endoscopically) in 28 patients (93.3%) and good (endoscopically only) in 2 patients (6.7%). No side effects of topical Mitomycin C in children with esophageal strictures were reported in this study. Conclusion: Esophageal dilatation followed by local Mitomycin C application may be a useful strategy for treating resistant esophageal strictures.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1282-1290
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• 2017

Since the mitigation of fear of crime significantly enhances the consumptions in a city, studies focusing on urban safety analysis have received much attention as means of revitalizing the local economy. In addition, with the development of computer vision and machine learning technologies, efficient and automated analysis methods have been developed. Previous studies have used global features to predict the safety of cities, yet this method has limited ability in accurately predicting abstract information such as safety assessments. Therefore we used a Convolutional Context Neural Network (CCNN) that considered "context" as a decision criterion to accurately predict safety of cities. CCNN model is constructed by combining a stacked auto encoder with a fully connected network to find the context and use it in the CNN model to predict the score. We analyzed the RMSE and correlation of SVR, Alexnet, and Sharing models to compare with the performance of CCNN model. Our results indicate that our model has much better RMSE and Pearson/Spearman correlation coefficient.

• International Journal of Quality Innovation
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• v.9 no.2
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• pp.11-30
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• 2008

The purpose of this study is to develop BSC model of social enterprise. Performance analysis tool of BSC have been brought over from the business world, designed and created from the perspectives of profit-based businesses. The BSC is a strategic performance measurement and management tool designed for the private sector acting as a communication/information and learning system, to measure 'where we are now' and 'where to aim for next'. It prescribes a plan for translating 'vision' and 'strategy' into concrete action across four perspectives at different stages, depending on the business. These perspectives are 'financial', 'customer', 'internal processes' and 'learning and growth', each of which is connected by cause-and-effect relationships that reflect the firm's strategy. Social aims of social enterprise are to accomplish desired outcomes which are to employ vulnerable people and to provide social services. The measurement factors of financial perspective are stable funding, efficiency of budgeting, stakeholders' financial supports, and trade profit. The measurement factors of customer perspective are government, social service users, employees, local communities, sup plier, social activity company, and partnership with external organizations. The measurement factors of internal process perspective are organizational culture, organizational structure/management, internal/external communication, quality of products and services, information sharing. The measurement factors of learning and growth perspective are training and development, management participation, knowledge sharing, leadership of CEO and manager, and learning culture.

• Journal of Institute of Control, Robotics and Systems
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• v.2 no.1
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• pp.26-34
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• 1996

One of the challenging tasks in visual inspection using CCD camera is to identify surface defects in an image with complex textured backgeound. In microscopic view, the surface of real objects shows regular or random textured patterns. In this paper, we present a visual inspection algorithm to extract abnormal surface defects in an image with textured background. The algorithm uses the space and frequency information at the same time by introducing the Dominant Frequency Map(DFM) which can describe the frequency characteristics of every small local region of an input image. We demonstrate the feasibility and effectiveness of the method through a series of real experiments for a 14" TV CRT mold. The method successfully identifies a variety of infinitesimal defects, whose size is larger than $50\mu\textrm{m}$, of the mold. The experimental results show that the DFM based method is less sensitive to the environmental changes, such as illumination and defocusing, than conventional vision techniques.ques.

• Journal of Korea Multimedia Society
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• v.19 no.12
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• pp.1909-1918
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• 2016

This paper presents a unified framework for joint Convolutional Neural Network (CNN) based vehicle detection by leveraging multi-spectral image pairs. With the observation that under challenging environments such as night vision and limited light source, vehicle detection in a single color image can be more tractable by using additional far-infrared (FIR) image, we design joint CNN architecture for both RGB and FIR image pairs. We assume that a score map from joint CNN applied to overall image can be considered as confidence of vehicle existence. To deal with various scale ratios of vehicle candidates, multi-scale images are first generated scaling an image according to possible scale ratio of vehicles. The vehicle candidates are then detected on local maximal on each score maps. The generation of overlapped candidates is prevented with non-maximal suppression on multi-scale score maps. The experimental results show that our framework have superior performance than conventional methods with a joint framework of multi-spectral image pairs reducing false positive generated by conventional vehicle detection framework using only single color image.

• Journal of KIISE:Software and Applications
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• v.31 no.11
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• pp.1534-1542
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• 2004

A novel vision-based scheme of extracting real-time traffic information parameters is presented. The method is based on a region classification followed by a spatio-temporal image analysis. The detection region images for each traffic lane are classified into one of the three categories: the road, the vehicle, and the shadow, using statistical and structural features. Misclassification in a frame is corrected by using temporally correlated features of vehicles in the spatio-temporal image. Since only local images of detection regions are processed, the real-time operation of more than 30 frames per second is realized without using dedicated parallel processors, while ensuring detection performance robust to the variation of weather conditions, shadows, and traffic load.