• Annual Conference of KIPS
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• 2023.11a
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• pp.644-647
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• 2023

건설은 경제 발전과 일자리 창출에 중요한 역할을 담당하고 있다. 그러나, 건설 산업은 타 산업에 비하여 고위험 산업으로, 매년 많은 사고와 재해가 발생하고 있다. 노동부 중대산업재해감독과에 따르면 2022 년 재해조사 대상 사망사고 발생 현황 발표 결과, 건설 사고 사망자는 341 명으로, 전체 산업재해 사망사고자의 53%를 차지하고 있다. 최근 사회 변화와 다양한 경기 변동, 물가 상승에 따라 건설 공사 비용 절감을 위한 안정성 결여, 시공 품질 관리의 어려움, 근로자 안전 의식 부족 등의 문제가 심화되고 있다. 이에 따라, 건설 현장의 근본적인 안전문화의 정착과 함께, 첨단 ICT 기술을 활용한 지능형 건설 안전관리 시스템의 구축이 필요한다. 그리고, 건설안전관리를 위한 스마트 건설 안전관리통합관제시스템(SCMS)의 기능과 적용 범위를 더욱 확대함으로써 건설 현장의 안전사고 예방을 개선할 수 있을 것으로 기대된다. 이를 위해 지속적인 다양한 연구와 데이터 수집과 분석 등 기술적인 연구와 함께 법과 제도에 대한 개선 논의가 필요하다.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.211-227
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• 2023

Personal service robots, a type of social robot that has emerged with the aging population and technological advancements, are undergoing a transformation centered around technologies that can extend independent living for older adults in their homes. For older adults to accept and use social robot innovations in their daily lives on a long-term basis, it is crucial to have a deeper understanding of user perspectives, contexts, and emotions. This research aims to comprehensively understand older adults by utilizing a mixed-method approach that integrates quantitative and qualitative data. Specifically, we employ the Van Kaam phenomenological methodology to group conversations into nine categories based on emotional cues and conversation participants as key variables, using voice conversation records between older adults and social robots. We then personalize the conversations based on frequency and weight, allowing for user segmentation. Additionally, we conduct profiling analysis using demographic data and health indicators obtained from pre-survey questionnaires. Furthermore, based on the analysis of conversations, we perform K-means cluster analysis to classify older adults into three groups and examine their respective characteristics. The proposed model in this study is expected to contribute to the growth of businesses related to understanding users and deriving insights by providing a methodology for segmenting older adult s, which is essential for the future provision of social robots with caregiving functions in everyday life.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.3
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• pp.29-41
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• 2013

This study set out to developing data exchange standard between roadside device and traffic information center fitted in a domestic environment by applying international standard ISO 15784. First, we defined message basic concept of 'Dialog' and essential elements should be defined to define the standard message for securing system compatibility by reference ISO 14817 and ISO 14827 Part 1. For defining standard message items exchanged between AVI and traffic information center, we formed Working Group under ITS Standards Technical Committee and analyzed data flow for ITS National Architecture, Standard messages of existing standards, and AVI operation messages actually operated on roadside now. So, we extracted 14 functionally needed messages and defined 28 standard messages adopting 'Dialog' concept. In case of the application protocol for data exchange standards, we defined basic requirements for securing interoperability and interchangeability considering domestic environment by analyzing reference standard of ISO 15784.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.05a
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• pp.265-272
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• 2002

기존의 인터넷 웹사이트에서는 사용자의 만족을 극대화시키기 위하여 사용자별로 개인화 된 서비스를 제공하는 협력적 필터링 방식을 적용하고 있다 협력적 여과 기술은 비슷한 선호도를 가지는 사용자들과의 상관관계를 기반으로 취향에 맞는 아이템을 예측하여 특정 사용자에게 추천하여준다. 그러나 협력적 필터링은 추천을 받기 위해서 특정 수 이상의 아이템에 대한 평가를 요구하며, 또한 전체 사용자에 대해 단지 비슷한 선호도를 가지는 일부 사용자 정보에 의지하여 추천함으로써 나머지 사용자 정보를 무시하는 경향이 있다. 그러나 나머지 사용자 정보에도 추천을 위한 유용한 정보가 숨겨져 있다. 우리는 이러한 숨겨진 유용한 추천 정보를 발견하기 위하여 본 논문에서는 협력적 여과 방식과 함께 데이터 마이닝(Data Mining)에서 사용되는 연관 규칙(Association Rule)을 추천에 사용한다. 연관 규칙은 한 항목 그룹과 다른 항목 그룹 사이에 존재하는 연관성을 규칙(Rule)의 형태로 표현한 것이다. 이와 같이 생성된 연관 규칙은 개인 구매도 분석, 상품의 교차 매매(Cross-Marketing), 카탈로그 디자인, 염가 매출품(Loss Leader)분석, 상품 진열, 구매 성향에 따른 고객 분류 다양하게 사용되고 있다. 그러나 이런 연관 규칙은 추천 시스템에서 잘 응용되지 못하고 있는 실정이다. 본 논문에서 우리는 연관 규칙을 추천 시스템에 적용해, 항목 그룹 사이에 연관성을 유도함으로써 추천에 효율적으로 사용할 수 있음을 보였다. 즉 전체 사용자의 히스토리(History) 정보를 기반으로 아이템 사이의 연관 규칙을 유도하고 협력적 여과 방식과 함께 보조적으로 연관 규칙을 추천을 위해 사용함으로써 추천 시스템에 효율성을 높였다. 구축, 각종 전자문서 생성, 전자 결제, 온라인 보험 가입, 해운 선용품 판매 및 관련 정보 제공 등 해운 거래를 위한 종합적인 서비스가 제공되어야 한다. 이를 위해, 본문에서는 e-Marketplace의 효율적인 연계 방안에 대해 해운 관련 업종별로 제시하고 있다. 리스트 제공형, 중개형, 협력형, 보완형, 정보 연계형 등이 있는데, 이는 해운 분야에서 사이버 해운 거래가 가지는 문제점들을 보완하고 업종간 협업체제를 이루어 원활한 거래를 유도할 것이다. 그리하여 우리나라가 동북아 지역뿐만 아니라 세계적인 해운 국가 및 물류 ·정보 중심지로 성장할 수 있는 여건을 구축하는데 기여할 것이다. 나타내었다.약 1주일간의 포르말린 고정이 끝난 소장 및 대장을 부위별, 별 종양개수 및 분포를 자동영상분석기(Kontron Co. Ltd., Germany)로 분석하였다. 체의 변화, 장기무게, 사료소비량 및 마리당 종양의 개수에 대한 통계학적 유의성 검증을 위하여 Duncan's t-test로 통계처리 하였고, 종양 발생빈도에 대하여는 Likelihood ration Chi-square test로 유의성을 검증하였다. C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스에 AIN-76A 정제사료만을 투여한 대조군의 대장선종의 발생률은 84%(Group 3; 21/25례)로써 I3C 100ppm 및 300ppm을 투여한 경우에 있어서는 각군 모두 60%(Group 1; 12/20 례, Group 2; 15/25 례)로 감소하는 경향을 나타내었다. 대장선종의 마리당 발생개수에 있어서는 C57BL/6J-Apc$^{min/+}$계 수컷 이형접합체 형질전환 마우스에 AIN-76A 정제사료

• Phonetics and Speech Sciences
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• v.16 no.3
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• pp.79-86
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• 2024

Transformer models have shown remarkable performance in extracting meaningful information from sequential input data such as text and images, and are gaining attention as end-to-end models for speech recognition. This study compared the performances of the Transformer speech recognition model and its enhanced versions, the Conformer and E-Branchformer, when applied to Korean speech recognition. Using Korean speech data from AIHub, we prepared a training set of approximately 7,500 hours and evaluated the models using the ESPnet toolkit. Additionally, we compared syllables and subwords as recognition units and analyzed the performance differences with changes in the number of tokens using Byte Pair Encoding. The results showed that the E-Branchformer achieved the best performance in Korean speech recognition and Conformer outperformed Transformer but degraded in performance for long utterances owing to cross-attention alignment errors. We aimed to determine the optimal settings by analyzing the performance changes with subword token adjustments. This study comprehensively evaluated model accuracy and processing speed to maximize the efficiency of Korean speech recognition. This is expected to contribute to the training of large-scale Korean speech recognition models and improve Conformer recognition errors. Future research should include additional experiments with diverse Korean speech datasets and enhance the recognition performance through structural improvements in the Conformer.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.504-510
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• 2009

Recently, personalized-adaptive services became the center of interest in the world. However the services about music are not widely diffused out. That is because the analyzing of music information is more difficult than analyzing of text information. In this paper, we propose a music recommendation system which provides personalized services. The system keeps a user's listening list and analyzes it to select pieces of music similar to the user's preference. For analysis, the system extracts properties from the sound wave of music and the time when the user listens to music. Based on the properties, a piece of music is mapped into a point in the property space and the time is converted into the weight of the point. At this time, if we select and analyze the group which is selected by user frequently, we can understand user's taste. However, it is not easy to predict how many groups are formed. To solve this problem, we apply the K-means clustering algorithm to the weighted points. We modified the K-means algorithm so that the number of clusters is dynamically changed. This manner limits a diameter so that we can apply this algorithm effectively when we know the range of data. By this algorithm we can find the center of each group and recommend the similar music with the group. We also consider the time when music is released. When recommending, the system selects pieces of music which is close to and released contemporarily with the user's preference. We perform experiments with one hundred pieces of music. The result shows that our proposed algorithm is effective.

• The Journal of the Korea Contents Association
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• v.5 no.3
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• pp.29-35
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• 2005

The task for chromosome analysis and diagnosis by experienced cytogenetists are being concerned as repetitive, time consuming job and expensive. For that reason, intelligent agent based on chromosome knowledge base using web has been developed to be able to analyze chromosomes and obtain necessary advises from the knowledge base instead of human experts. That is to say, the knowledge base of IF THEN production rule was implemented to a knowledge domain with normal and abnormal chromosomes, and then the inference results by the knowledge base could enter the inference data into the database. Experimental data were composed of normal chromosomes of 2,736 cases and abnormal chromosomes of 259 cases that have been obtained from GTG-banding metaphase peripheral blood and amniotic fluid samples. The completed intelligent agent for the chromosome knowledge base provides variously morphological information by analysis of normal or abnormal chromosomes also has the advantage of being able to consult with the user on the chromosome analysis and diagnosis.

• Smart Media Journal
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• v.4 no.4
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• pp.80-85
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• 2015

As the number of applications using the internet the rapidly increasing incidence of cyber attacks made on the internet has been increasing. In the equipment of L3 DDoS attack detection equipment in the world and incomplete detection of application layer based intelligent. Next-generation networks domestic product in high-performance wired and wireless network threat response techniques to meet the diverse requirements of the security solution is to close one performance is insufficient compared to the situation in terms of functionality foreign products, malicious code detection and signature generation research primarily related to has progressed malware detection and analysis of the research center operating in Window OS. In this paper, we describe the current status survey and analysis of the latest variety of new attack techniques and analytical skills with the latest cyber-attack analysis prejudice the security situation.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.313-319
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• 2015

As the number of applications using the internet the rapidly increasing incidence of cyber attacks made on the internet has been increasing. In the equipment of L3 DDoS attack detection equipment in the world and incomplete detection of application layer based intelligent. Next-generation networks domestic product in high-performance wired and wireless network threat response techniques to meet the diverse requirements of the security solution is to close one performance is insufficient compared to the situation in terms of functionality foreign products, malicious code detection and signature generation research primarily related to has progressed malware detection and analysis of the research center operating in Window OS. In this paper, we describe the current status survey and analysis of the latest variety of new attack techniques and analytical skills with the latest cyber-attack analysis prejudice the security situation.

• Knowledge Management Research
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• v.23 no.3
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• pp.129-152
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• 2022

As a key infrastructure for digital transformation, the spread of data, network, artificial intelligence (D.N.A.) fields and the emergence of promising industries are laying the groundwork for active digital innovation throughout the economy. In this study, by applying the text mining methodology, major topics were derived by using the abstract, publication year, and research field of the study corresponding to the SCIE, SSCI, and A&HCI indexes of the WoS database as input variables. First, main keywords were identified through TF and TF-IDF analysis based on word appearance frequency, and then topic modeling was performed using g-DMR. With the advantage of the topic model that can utilize various types of variables as meta information, it was possible to properly explore the meaning beyond simply deriving a topic. According to the analysis results, topics such as business intelligence, manufacturing production systems, service value creation, telemedicine, and digital education were identified as major research topics in digital transformation. To summarize the results of topic modeling, 1) research on business intelligence has been actively conducted in all areas after COVID-19, and 2) issues such as intelligent manufacturing solutions and metaverses have emerged in the manufacturing field. It has been confirmed that the topic of production systems is receiving attention once again. Finally, 3) Although the topic itself can be viewed separately in terms of technology and service, it was found that it is undesirable to interpret it separately because a number of studies comprehensively deal with various services applied by combining the relevant technologies.