• Annals of Surgical Treatment and Research
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• v.95 no.6
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• pp.324-332
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• 2018

Purpose: We present our experience involving the management of this disease, identifying prognostic factors affecting treatment outcomes. Methods: The patients treated for Fournier gangrene at our institution were retrospectively reviewed. Data collected included demographics, extent of soft tissue necrosis, predisposing factors, etiological factors, laboratory values, and treatment outcomes. The severity index and score were calculated. Multivariate regression analysis was used to determine the association between potential predictors and clinical outcomes. Results: A total of 41 patients (male:female = 33:8) were studied. The mean age was 54.4 years (range, 24-79 years). The most common predisposing factor was diabetes mellitus (n = 19, 46.3%). Sixteen patients (39.0%) were current smokers. Seven patients had chronic kidney disease. The most frequent etiology was urogenital lesion (41.5%). The mortality rate was 22.0% (n = 9). Multivariate regression analyses showed that extension of necrosis beyond perineal/inguinal area and pre-existing chronic kidney disease were significant and independent predictors of mortality. Extension of necrosis beyond perineal/inguinal area was a significant predictor of increased duration in the intensive care unit and hospital stay. In addition, pre-existing chronic kidney disease was a significant predictor of flap reconstruction in the wound. Conclusion: Fournier gangrene with extensive soft tissue necrosis and pre-existing chronic kidney disease was associated with poor prognosis and complexity of patient management. Early recognition of dissemination and premorbid renal function is essential to reduce mortality and establish a management plan for this disease.

• The Korean Journal of Archival Studies
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• no.14
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• pp.359-388
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• 2006

This article shows how the tradition of German historicism and positive historical science contributed to the establishment of German archival system, especially the principle of provenance and original order. The theory of historicism focused on the recognition and realization of the individuality of the history as a whole unit which is made up of the mutually and organically organized cultural entities. The theory of historicism as this kind of world view got its academic basis from the methodology of the positive historical science, namely the critical reviews on the archival sources which exist in mutually and organically organized record entities. In this context, the scholars of the historicism saw the establishment of the efficient archival systems as necessary. To some great degree, the emergence of the principle of the provenance and original order was its logical result. The author of this paper tried to highlight this point of view historically, on the basis of the activities of Ranke, Sybel and Lehmann around and in the Prussia Privy State Archives throughout the 19th century.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.293-298
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• 2021

In general, the guided weapon seeker and the guided control device process the target, search, recognition, and capture information to indicate the state of the guided missile, and play a role in controlling the operation and control of the guided weapon. The signals required for guided weapons are gaze change rate, visual signal, and end-stage fuselage orientation signal. In order to process the complex and difficult-to-process missile signals of recent missiles in real time, it is necessary to increase the data processing speed of the missiles. This study showed the processing speed after applying the stop and go and inverse enumeration algorithm among the parallel algorithm methods of PINQ and comparing the processing speed of the signal data required for the guided missile in real time using the guided missile inspection program. Based on the derived data processing results, we propose an effective method for processing missile data when applying a parallel processing algorithm by comparing the processing speed of the multi-core processing method and the single-core processing method, and the CPU core utilization rate.

• Journal of Korean Clinical Nursing Research
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• v.27 no.3
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• pp.233-244
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• 2021

Purpose: The purpose of this study was to investigate the actual utilization of clinical practice guidelines developed by Hospital Nurses Association. Methods: The subjects were 70 nurses who were in charge of guideline distributions in 70 advanced general hospital and general hospitals with 500 beds or more nationwide. Data were collected between June and August, 2020 by mail (return rate: 88.6%). Data were analyzed using descriptive statistics, t-test, and ANOVA with SPSS/WIN 24.0. Results: Among the clinical practice guidelines developed by Hospital Nurses Association, 72.9~90.1% were placed with book and electronic file in nursing department and 24.3~35.8% were placed with book and electronic file in each nursing unit at hospital. The average number of utilized clinical practice guidelines were 3.96±3.88, and average score of guideline utilization was score 2.85±0.79 which means 'use sometimes'. Conclusion: To improve the distribution and utilization of the clinical practice guidelines, it is necessary to enhance the recognition of values of evidence based nursing practice targeting head of nursing department and to stimulate the distribution and utilization of the clinical practice guidelines using diverse education programs for staff nurses.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.5
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• pp.668-674
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• 2022

Machine learning techniques using visual data have high usability in fields of industry and service such as scene recognition, fault detection, security and user analysis. Among these, user analysis through the videos from CCTV is one of the practical way of using vision data. Also, many studies about lightweight artificial neural network have been published to increase high usability for mobile and embedded environment so far. In this study, we propose the network combining the object detection and classification for mobile graphic processing unit. This network detects pedestrian and face, classifies age and gender from detected face. Proposed network is constructed based on MobileNet, YOLOv2 and skip connection. Both detection and classification models are trained individually and combined as 2-stage structure. Also, attention mechanism is used to improve detection and classification ability. Nvidia Jetson Nano is used to run and evaluate the proposed system.

• Journal of Practical Engineering Education
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• v.14 no.2
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• pp.413-423
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• 2022

The purpose of this study is to analyze the role of the job competency assessor who assess achievement of job performance ability based on NCS (educational training, qualifications, field experience, etc.) through competency assessment. For this purpose, job analysis including development and verification of the job model and selection of core task are conducted. As a result, main duties of the job competency assessor are to understand the NCS based assessment principle, establish an assessment plan, design and develop assessment tools, assess competence, provide feedback and re-assessment, record and manage assessment result, verify the internal assessment result, establish the RPL (recognition of prior learning) plan, implement the RPL and verify the RPL assessment result, and 48 task are derived. In addition, a total of 21 core tasks are derived based on the threshold value multiplied by the importance and difficulty of the task for each duty. Based on this, implications for job analysis of the job competency assessor are presented.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.395-401
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• 2023

Sound Event Detection (SED) aims to identify not only sound category but also time interval for target sounds in an audio waveform. It is a critical technique in field of acoustic surveillance system and monitoring system. Recently, various models have introduced through Detection and Classification of Acoustic Scenes and Events (DCASE) Task 4. This paper explored how to design optimal parameters of DenseNet based model, which has led to outstanding performance in other recognition system. In experiment, DenseRNN as an SED model consists of DensNet-BC and bi-directional Gated Recurrent Units (GRU). This model is trained with Mean teacher model. With an event-based f-score, evaluation is performed depending on parameters, related to model architecture as well as model training, under the assessment protocol of DCASE task4. Experimental result shows that the performance goes up and has been saturated to near the best. Also, DenseRNN would be trained more effectively without dropout technique.

• Smart Media Journal
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• v.11 no.11
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• pp.25-31
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• 2022

Deep learning-based image processing is essential for autonomous vehicles. To process road images in real-time in a System-on-Chip (SoC) environment, we need to execute deep learning models on a NPU (Neural Procesing Units) specialized for deep learning operations. In this study, we imported seven open-source image processing deep learning models, that were developed on GPU servers, to Texas Instrument Deep Learning (TIDL) NPU environment. We confirmed that the models imported in this study operate normally in the SoC virtual environment through performance evaluation and visualization. This paper introduces the problems that occurred during the migration process due to the limitations of NPU environment and how to solve them, and thereby, presents a reference case worth referring to for developers and researchers who want to port deep learning models to SoC environments.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.51-77
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• 2023

This study analyzed the respective teaching and learning-related services offered by the Centers for Teaching and Learning and the academic libraries to find the proper roles of libraries regarding this type of service. We interviewed librarians to collect the data. The content analysis of the qualitative interview data enabled us to identify the librarians' perceptions of teaching and learning support, service provision method, strengthening relationships with other academic units, recognition of libraries' roles within the universities, and generating more investment for the libraries. Finally, the analysis led to six suggestions for libraries' teaching and learning support functions, such as advertising the availability of specific academic discipline or unit-oriented library services, strengthening librarian's capabilities as educators, bolstering digital information literacy of the faculty members and students, injecting libraries' views into the development and maintaining fundamental knowledge-related programs, emphasizing the notion of human-centered libraries, and finding new ways to utilize library space.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.659-663
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• 2023

이 논문은 한국어 음성인식 성능을 개선하고자 기존 음성인식 과정을 자모단위 음성인식 모델과 신경망 기반 자모 병합 모델 총 두 단계로 구성하였다. 한국어는 조합어 특성상 음성 인식에 필요한 음절 단위가 약 2900자에 이른다. 이는 학습 데이터셋에 자주 등장하지 않는 음절에 대해서 음성인식 성능을 저하시키고, 학습 비용을 높이는 단점이 있다. 이를 개선하고자 음절 단위의 인식이 아닌 51가지 자모 단위(ㄱ-ㅎ, ㅏ-ㅞ)의 음성인식을 수행한 후 자모 단위 인식 결과를 음절단위의 한글로 병합하는 과정을 수행할 수 있다[1]. 자모단위 인식결과는 초성, 중성, 종성을 고려하면 규칙 기반의 병합이 가능하다. 하지만 음성인식 결과에 잘못인식된 자모가 포함되어 있다면 최종 병합 결과에 오류를 생성하고 만다. 이를 해결하고자 신경망 기반의 자모 병합 모델을 제시한다. 자모 병합 모델은 분리되어 있는 자모단위의 입력을 완성된 한글 문장으로 변환하는 작업을 수행하고, 이 과정에서 음성인식 결과로 잘못인식된 자모에 대해서도 올바른 한글 문장으로 변환하는 오류 수정이 가능하다. 본 연구는 한국어 음성인식 말뭉치 KsponSpeech를 활용하여 실험을 진행하였고, 음성인식 모델로 Wav2Vec2.0 모델을 활용하였다. 기존 규칙 기반의 자모 병합 방법에 비해 제시하는 자모 병합 모델이 상대적 음절단위오류율(Character Error Rate, CER) 17.2% 와 단어단위오류율(Word Error Rate, WER) 13.1% 향상을 확인할 수 있었다.