• Korean Journal of Forensic Psychology
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• v.12 no.2
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• pp.121-149
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• 2021

Statement Validity Analysis (SVA) is utilized in criminal investigations and the court to assess the credibility of given statements. During this procedure, the criteria for Criteria-Based Content Analysis (CBCA) are used to evaluate whether statements include the characteristics reflecting actual experiences about the event in question. Various studies had been conducted on the efficacy (classification rates) of CBCA criteria, yet the consistency of the findings was not investigated. In the current study, a meta-analysis was conducted with Korean CBCA studies reported from 2004 to 2020 (a total of fourteen studies). As a result, the total score of CBCA was found to successfully discriminate truth and fabrication. A significant positive (+) effect size was found with four criteria (3, 4, 10, and 12), all of which are classified as cognitive criteria. However, contrary to the underlying assumption for CBCA, criterion 18, classified as one of the motivational criteria, showed a significant negative (-) effect size. Meanwhile, moderator analyses were possible for eleven criteria (2~9, 12, 13, 15) and the results showed the significant effects of potential moderator variables such as the gender and status of the participants, study types and designs, number of raters, and publication status. The current results suggests that more careful attention is required to each criterion-especially the cognitive criteria-rather than the total CBCA score as well as the possible moderator effects in order to assess truthfulness of the statements. The implication, limitations, and suggestions for future studies were discussed.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.129-134
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• 1996

1차 년도 G-7 개발 과제로 수행된 자기 공명 진단 장치 (Magnetic Resonance Imaging System)의 개발 내용을 간략히 소개하였다. 성공적인 IT Compact 자기 공명 진단 장치의 완성을 위해 일차적으로 (1)RF (고주파), Gradient(경사 자계), Spectrometer 등의 Hard-ware 관련 MRI 핵심부분, (2) RF, Gradient, Spectrometer, Magnet 등의 각 Sub-system을 연결, 조합, 조정하여 하나의 체계적인 시스템으로 통합하고 운영하는 과정(System Integration), (3)사용자와 시스템을 연결하는 User Interface, Data Base Management, Real time 운영 SW 등과 (4)임상에 적용하여 구체적인 성능과 효용성을 확인하는 기술 등에 대하여 집중 연구하였다. 개발 방법은 (1)지난 16년간 국내에 축적 된 연구 개발 인력들을 최대한 활용하고 (2)연구 개발을 국제화 시켜 필요한 경우 부분별로 개발 인력을 해외에서 보완하고 (3)소수 정예 전문 인력 주의와 요소 기술 또는 중요 부품을 경쟁성 검토 후 필요 시 Out-sourcing 활용으로 최저의 비용으로 개발 기간을 최소화 하는 데 두었다. 개발된 1.0Tesla자기 공명 영상 장치는 미국 물리 학회에서 규격화한 Phantom및 임상 적용을 통하여 서울대 의대 연구 팀과 지속적으로 성능을 평가해 왔다. 개발된 시스템의 해상도는 $256{\times}256$ head 영상에서 1mm 이 하의 해상도를 가짐을 resolution phantom 을 통하여 확인할 수 있었고, $512{\times}512$ 영상에서 는 약 0.5 mm 의 물체를 분리 해냄으로써 외제 시스템들 보다 우수하게 평가 되었다. 차폐 경사코일의 Eddy current영향은2%이내로 촬영 시 영향은 거의 무시할 수 있었다. 또한, 개발된 영상 기법들, 즉 Multislice/Multi Echo, Oblique angle imaging, 64 Echo train을 갖는 고속 촬영 기술들이 자기 공명 장치에 장착되어 임상 적용에 문제가 없도록 하였다. 또한 20mT/m/Amp의 강력한 능동 차폐 경사 자계 코일(Active Shield Gradient Coil)을 기본 사양으로 하고, 수신단을 최대 6개로 확장토록 하여 2차년도의 초고속 촬영 기법(EPI) 및 Phased Array 코일 촬영이 가능토록 하였다. 1차 년도 개발 과제 수행 결과와 향후 개발 과제를 바탕으로 최종 목표인 국제 경쟁력이 있는 자기 공명 진단 장치 즉 기능과 영상의 질은 선진국 제품과 동일하거나 우수하되, 저가격을 구현한 상용화 제품이 완성되어, 첨단 의료기기로서 산업 구조 고도화에 기여하고 수입대체 뿐만 아니 라 수출을 통한 국익 창출과 국가의 기술을 통한 위상 제고에 기여되길 기대한다.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.230-241
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• 2021

This study has attempted to provide an important understanding about the information asymmetry in markets through empirical analysis on how the disclosure of low quality can increase demand even in the short run. More specifically, this study has extended the previous findings from the related literature by considering the effect of information search cost and providing empirical evidences about the effect of voluntary disclosure of low quality, using an experimental method with purchase scenarios. The results from our analysis show that reduced perceived risk have an important effect on sharing negative information, while the effect of information search cost is minimal. We also explain the circumstances whereby the information disclosure of a seller with low-quality product can enhance not only the seller's profitability but also customers' welfare by increasing the market demand and the demand for the seller claiming high quality.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.167-177
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• 2012

Recently, with the rapid development of information technology the field of e-book market is growing rapidly. The choice of an e-book device to improve user's comprehension is one of very important elements. The effectiveness evaluation between e-books and paper books has been studied previously, but there have not been progressed actively researches on the size of e-book devices based on user's comprehension. Considering these aspects, we in this paper selected e-book devices such as currently available PDA, netbook, and notebook, and then carried out the experiment about which device has the highest user's comprehension depending on the size of e-book devices. Understanding and memory about the content on the display were set as main factors in order to evaluate user's comprehension. We prepared in advance multiple examples of e-books and English words with similar difficulty, and evaluated user's comprehension through answering questions for each example after doing the experiment. 90 undergraduate students who use most widely e-books participated in the experiment, and the result was analyzed using SPSS statistical package. The experiment result showed that user's comprehension was higher in e-book device with middle size rather than the one with big size in display size.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.155-160
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• 2014

There are many image processing based algorithms and applications that fail when illumination change occurs. Therefore, the illumination change has to be detected then the illumination change occurred images need to be enhanced in order to keep the appropriate algorithm processing in a reality. In this paper, a new method for detecting illumination changes efficiently in a real time by using local region information and fuzzy logic is introduced. The effective way for detecting illumination changes in lighting area and the edge of the area was selected to analyze the mean and variance of the histogram of each area and to reflect the changing trends on previous frame's mean and variance for each area of the histogram. The ways are used as an input. The changes of mean and variance make different patterns w hen illumination change occurs. Fuzzy rules were defined based on the patterns of the input for detecting illumination changes. Proposed method was tested with different dataset through the evaluation metrics; in particular, the specificity, recall and precision showed high rates. An automatic parameter selection method was proposed for contrast limited adaptive histogram equalization method by using entropy of image through adaptive neural fuzzy inference system. The results showed that the contrast of images could be enhanced. The proposed algorithm is robust to detect global illumination change, and it is also computationally efficient in real applications.

• Progress in Medical Physics
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• v.21 no.4
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• pp.360-366
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• 2010

To generate on-board digital tomosynthesis (DTS) for three-dimensionalimage-guided radiation therapy (IGRT) as an alternative to conventional portal imaging or on-board cone-beam computed tomography (CBCT), two clinical cases (liver and bladder) were selected to illustrate the capabilities of on-board DTS for IGRT. DTS images were generated from subsets of CBCT projection data (45, 162 projections) using half-fan mode scanning with a Feldkamp-type reconstruction algorithm. Digital tomosynthesis slices appeared similar to coincident CBCT planes and yielded substantially more anatomic information. Improved bony and soft-tissue visibility in DTS images is likely to improve target localization compared with radiographic verification techniques and might allow for daily localization of a soft-tissue target. Digital tomosynthesis might allow targeting of the treatment volume on the basis of daily localization.

• 전기의세계
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• v.18 no.1
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• pp.33-37
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• 1969

한전은 1968년 11월 3일 오전 10시 04분을 기하여 154KV 전계통의 직접접지방식 전환을 단행하였다. 종전의 P.C(소고선륜) 중성점접지방식을 직접접지방식으로 전환한것으로서 전력사상 특기 할 만한 근대화사업이며 다년간을 두고 추진해온 중요과제였다. 전력계통의 확대와 복잡화는 선진국가에서도 실시하고 있는 직접접지방식의 채택을 불가변하게 하였고 또한 1차 AID송배전차관도 이의 채택을 조건부로 승인되었던 것으로서 1968년 이후에 건설되는 송변전기기는 직접접지계에서만 운전할 수 있는 절연Level 650KV급이 도입되어 부산화력발전소 3호기가 준공되는 1968년 10월말까지는 직접접지전환이 반드시 이루어져야 하는 실정에 놓여 있었다. 그런데 직접접지방식의 단점인 인접통신선에 미치는 유도장해를 해결하는 문제가 다년간을 두고 진지하게 검토되어 왔으나 해결이 늦어지고 있었다. 사유는 154KV 계통에 인근된 통신선이라면 체신부, 내무부, 교통부, 국방부등 여러기관의 것이 있는데, 유도장해보안방법과 유도보상비문제에 대하여 전력측(상공부, 한전)과 통신측(상기의 체신부등)의 견해차가 해소되지 않기 때문이었다. 그것이 1968년 5월에 와서 전력.통신쌍방이 범국가적입장에서 제반애로를 무릅쓰고 최소한의 투자로 가능한 범위내의 보안책으로서 우선 Arrester 보안방식을 채택하기로 합의되어 경제장관회의를 거쳐 시공하기에 이른것이다. 이 란을 빌려 이 사업의 필요성과 경위및 통신선유도장해방지를 위한 보안방식내용을 간단히 소개함으로써 앞으로 이 분야의 항구적인 유도대책연구에 다소나마 참고가 된다면 다행으로 생각하겠다.면서 예측강우의 질이 저하되기 시작하였으나 QPM을 합성함으로써 생산한 BQPF는 보다 신뢰성있고 양호한 결과를 얻을 수 있었다. 이러한 결과들은 향후 정량적 분포형강우 예측을 이용한 실시간 홍수유출 예측시 댐운영자는 리드타임(홍수선행시간)을 충분히 확보함으로서 안정적이고 예측 가능한 홍수조절을 하는데 도움을 줄 수 있을 것으로 기대된다. 이와 같이 다양한 단기저수지 유입량의 예측정보 제공으로 다목적댐 저수지 운영모형의 효용성을 제고하여 향후 실제 저수지 유입량 예측에 이용함으로써 저수지 단기운영효율 개선에 기여할 수 있을 것으로 사료된다.다. 이것은 여름철 강수량이 증가하고, 호우발생빈도, 특히 8월의 강수일수가 증가하고 있다는 것과 밀접한 관련이 있다. 여름과 가을에 우리나라에 영향을 미치는 태풍의 수는 뚜렷한 추세를 보이지 않으나, 2002년 루사, 2003년 매미로 인하여 각각 6조원, 4조원 이상의 막대한 피해가 발생하였다. 태풍에 의한 피해액은 GDP 대비 약 0.9%(태풍 루사)로 최근 경제상장률과 비교해 보면, 상당한 비율을 차지한다. 우리나라에 영향을 미치는 태풍은 연근해의 해수면 온도가 높아지면 세기가 강해질 가능성이 높다. 폭설과 한파일수도 평년대비 최근 10년 감소하였고 일최저기온이 영하 $10^{\circ}C$ 이하인 날도 연간 발생일수가 감소하였다. 최근 10년간 우리나라 기후의 변화특성은 기온상승과 더불어 서리종료일이 앞당겨지고 열대야가 증가하고 폭설, 한파, 겨울철 일최저기온 영하 10도 이하인 날의 감소 등이 나타나고, 여름철 재해의 원인인 호우일수는 증가하는 추세이다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.28 no.2
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• pp.57-78
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• 2017

SNS is a useful tool to quickly deliver information in an emergency given their speed and expandability. Especially, SNS in the event of a disaster or an accident can offer on-site, accurate and detailed updates about essential information such as the safety of victims and the development of the situation, served as a valuable complement to the conventional media. This study aims to perform a comparative analysis on how social media are currently used by emergency management authorities in South Korea and other countries. Based on the results, this study proposed more effective ways to exploit SNS and improve efficiency of disaster management. To accomplish the goals, this study collected tweet information from various sources including the FEMA of the U. S., the FDMA and the Central Disaster Council of Japan, and the MPSS of Korea. The collected tweet information was analyzed by feedback, time series, and information types. The feedback analysis aims to quantify the number of monthly user feedback in order to assess user satisfaction about the tweet information. The time series analysis identifies the number of tweet information, feedback index and keywords by country for certain duration, examining why certain messages showed high feedback indices and what kind of contents should be offered by the authorities. Finally, the analysis of information type reviews the type of information contained in the tweet information that drew users' attention to identify the information type in which the authorities should deliver information to users. Based on these analyses, this study proposed improvement methods to use Tweeter in MPSS.

• Journal of the Korea Society of Computer and Information
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• v.29 no.5
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• pp.21-29
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• 2024

Reducing the radiation dose during CT scanning can lower the risk of radiation exposure, but not only does the image resolution significantly deteriorate, but the effectiveness of diagnosis is reduced due to the generation of noise. Therefore, noise removal from CT images is a very important and essential processing process in the image restoration. Until now, there are limitations in removing only the noise by separating the noise and the original signal in the image area. In this paper, we aim to effectively remove noise from CT images using the wavelet transform-based GAN model, that is, the WT-GAN model in the frequency domain. The GAN model used here generates images with noise removed through a U-Net structured generator and a PatchGAN structured discriminator. To evaluate the performance of the WT-GAN model proposed in this paper, experiments were conducted on CT images damaged by various noises, namely Gaussian noise, Poisson noise, and speckle noise. As a result of the performance experiment, the WT-GAN model is better than the traditional filter, that is, the BM3D filter, as well as the existing deep learning models, such as DnCNN, CDAE model, and U-Net GAN model, in qualitative and quantitative measures, that is, PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity Index Measure) showed excellent results.