• 보건의료산업학회지
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• 제8권3호
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• pp.207-218
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• 2014

This study was to compare the recognition of future career and nurse's characteristics according to nursing school system. This study was based on cross sectional descriptive method. The data were analyzed by $x^2$-test, t-test, and ANOVA using PASW WIN 18.0 program. The data represented that students who were doing associated degrees or bachelor degrees, showed the similar level recognition of future career and nurse's characteristics. However they showed differences in recognition of the career where they could create and new things(t=2.933, p=.004) and working part time(t=2.328, p=.021). In regards to recognition of nurse's characteristics bachelor degrees students had higher professional ethics($4.59{\pm}.44$). This study proposed that these research results could be used for improving methodology of nursing education.

• 디지털융복합연구
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• 제17권11호
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• pp.557-567
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• 2019

본 연구는 미래워크숍을 활용하여 진로직업상담가의 미래인식과 미래역량을 도출하고 미래적응력 향상에 대한 효과성을 검증하기 위하여 수행되었다. 이를 위해 진로직업상담가 25명을 대상으로 미래워크숍을 진행하였으며, 서면 작성된 자료와 미래워크숍에서 진행된 토론 내용을 통합하여 분석하였다. 분석을 위해 단어 빈도분석과 대응표본 T검증을 실시하였고, 합의를 통해 주제어 도출을 하였다. 연구결과, 첫째, 미래인식 키워드는 로봇, 인공지능, 여가, 교육, 편리, 장애인 등의 빈도가 높게 나타났다. 둘째, 미래노동현장에서는 첨단 기술로 인한 변화를 가장 많이 전망했다. 셋째, 진로직업상담 현장에서는 제4차 산업혁명 관련 전문 진로직업상담사와 로봇상담사가 등장할 것으로 전망했다. 넷째, 진로직업상담가의 미래역량으로 정보처리능력, 전문상담능력, 의사소통능력, 윤리의식이 도출되었다. 끝으로 미래워크숍 참여 이후 진로직업상담가의 미래적응력이 높아지는 것으로 확인되었다. 본 연구에서 도출된 미래역량은 진로직업상담가의 직무교육에도 활용될 수 있을 것으로 기대된다.

• 산업경영시스템학회지
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• 제46권1호
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• pp.55-67
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• 2023

Lightweight face recognition models, as one of the most popular and long-standing topics in the field of computer vision, has achieved vigorous development and has been widely used in many real-world applications due to fewer number of parameters, lower floating-point operations, and smaller model size. However, few surveys reviewed lightweight models and reimplemented these lightweight models by using the same calculating resource and training dataset. In this survey article, we present a comprehensive review about the recent research advances on the end-to-end efficient lightweight face recognition models and reimplement several of the most popular models. To start with, we introduce the overview of face recognition with lightweight models. Then, based on the construction of models, we categorize the lightweight models into: (1) artificially designing lightweight FR models, (2) pruned models to face recognition, (3) efficient automatic neural network architecture design based on neural architecture searching, (4) Knowledge distillation and (5) low-rank decomposition. As an example, we also introduce the SqueezeFaceNet and EfficientFaceNet by pruning SqueezeNet and EfficientNet. Additionally, we reimplement and present a detailed performance comparison of different lightweight models on the nine different test benchmarks. At last, the challenges and future works are provided. There are three main contributions in our survey: firstly, the categorized lightweight models can be conveniently identified so that we can explore new lightweight models for face recognition; secondly, the comprehensive performance comparisons are carried out so that ones can choose models when a state-of-the-art end-to-end face recognition system is deployed on mobile devices; thirdly, the challenges and future trends are stated to inspire our future works.

• 대한임베디드공학회논문지
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• 제6권4호
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• pp.201-207
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• 2011

This paper introduces a novel concept of 'Emotional Communication' for future smart phone. While traditional information based communication technologies focus on how to precisely transmit the content of message, emotional communication is intended to support and augment social relationship among people and to comfort the user to be happy. In this paper, we propose future communication services and core technologies which can estimate emotional desire of users and respond to the desire to be happy with connectedness and consolation from peoples. Firstly, we introduce emotion recognition techniques to estimate emotional desire of users. At second, the emotional responding services are categorized to four parts and the details are shown. Lastly we propose the process to implement emotional communication system and the main techniques to fulfill the system requirements for future smart-phone services.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2023년도 춘계학술발표대회
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• pp.748-750
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• 2023

Facial expression recognition technology's rapid growth and development have garnered significant attention in recent years. This technology holds immense potential for various applications, making it crucial to stay up-to-date with the latest trends and advancements. Simultaneously, it is essential to identify and address the challenges that impede the technology's progress. Motivated by these factors, this study aims to understand the latest trends, future directions, and challenges in facial expression recognition technology by utilizing text mining to analyze papers published between 2020 and 2023. Our research focuses on discerning which aspects of these papers provide valuable insights into the field's recent developments and issues. By doing so, we aim to present the information in an accessible and engaging manner for readers, enabling them to understand the current state and future potential of facial expression recognition technology. Ultimately, our study seeks to contribute to the ongoing dialogue and facilitate further advancements in this rapidly evolving field.

• Journal of Information Processing Systems
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• 제17권6호
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• pp.1138-1156
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• 2021

Emotional semantics are the highest level of semantics that can be extracted from an image. Constructing a system that can automatically recognize the emotional semantics from images will be significant for marketing, smart healthcare, and deep human-computer interaction. To understand the direction of image emotion recognition as well as the general research methods, we summarize the current development trends and shed light on potential future research. The primary contributions of this paper are as follows. We investigate the color, texture, shape and contour features used for emotional semantics extraction. We establish two models that map images into emotional space and introduce in detail the various processes in the image emotional semantic recognition framework. We also discuss important datasets and useful applications in the field such as garment image and image retrieval. We conclude with a brief discussion about future research trends.

• 한국도서관정보학회지
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• 제25권
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• pp.19-50
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• 1996

The purpose of this paper is to study on ownership and access in future library. For this purpose, this is criticized about recognition regarding future library of Library and Information Science researchers in Korea. And, this is reviewed the present stages of collection development and a role of future books, future libraries and future librarians in Korea. The result of this study is known unrealistic reality analysis and forecast surrounding future library discourse and at the same time that following Western model is not fit for future library in Korea. This study is proposed resolving of problems to access based on physical collection in future library.

• 한국콘텐츠학회논문지
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• 제20권7호
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• pp.86-96
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• 2020

본 연구는 이미지 인식기술 서비스의 산업 적용 사례를 기반으로 인공지능이 이미지 인식기술에 어떠한 역할을 하고 있는지 살펴보았다. 이미지 인식 기술을 사용하여 위성사진을 인공지능으로 분석해 특정 국가의 원유 저장탱크의 산출 내역을 밝혀내거나, 사용자가 촬영하거나 다운로드한 이미지와 유사한 이미지나 제품을 검색해주기도 하며, 과일의 산출량을 정렬한다거나 식물의 질병을 탐지해 낼 수도 있다. 딥러닝과 신경망 알고리즘을 기반으로 사람의 나이, 성별, 기분까지도 인식할 수 있어 이미지 인식 기술이 다양한 산업에서 적용되고 있음을 확인하였다. 본 연구에서는 국내 및 해외의 이미지 인식 기술의 활용 사례를 살펴보는 것 뿐 아니라, 어떠한 형태로 산업에 적용되고 있는지 확인을 할 수 있다. 또한, 본 연구를 통하여 여러 산업에서 이미지 인식기술을 구현하고 적용하여 발전시킨 여러 성공 사례들을 중심으로 향후 연구의 방향성을 제시했으며, 향후 국내 이미지 인식 기술이 나아가야 할 방향을 고찰해 볼 수 있다.

• 한국도서관정보학회지
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• 제25권
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• pp.1-18
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• 1996

The purpose of this paper is to study on ownership and access in future library. For this purpose, this is criticized about recognition regarding future library of Library and Information Science researchers in Korea. And this is reviewed the present stages of collection development and a role of future books, future libraries and future librarians in Korea. The result of this study is known unrealistic reality analysis and forecast surrounding future library discourse and at the same time that following Western model is not fit for future library in Korea. This study is proposed resolving of problems to access based on physical collection in future library.

• ETRI Journal
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• 제26권3호
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• pp.273-276
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• 2004

We propose a novel feature processing technique which can provide a cepstral liftering effect in the log-spectral domain. Cepstral liftering aims at the equalization of variance of cepstral coefficients for the distance-based speech recognizer, and as a result, provides the robustness for additive noise and speaker variability. However, in the popular hidden Markov model based framework, cepstral liftering has no effect in recognition performance. We derive a filtering method in log-spectral domain corresponding to the cepstral liftering. The proposed method performs a high-pass filtering based on the decorrelation of filter-bank energies. We show that in noisy speech recognition, the proposed method reduces the error rate by 52.7% to conventional feature.