• Title/Summary/Keyword: Human Similarity

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AI-Based Project Similarity Evaluation Model Using Project Scope Statements

  • Ko, Taewoo;Jeong, H. David;Lee, JeeHee
    • International conference on construction engineering and project management
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    • 2022.06a
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    • pp.284-291
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    • 2022
  • Historical data from comparable projects can serve as benchmarking data for an ongoing project's planning during the project scoping phase. As project owners typically store substantial amounts of data generated throughout project life cycles in digitized databases, they can capture appropriate data to support various project planning activities by accessing digital databases. One of the most important work tasks in this process is identifying one or more past projects comparable to a new project. The uniqueness and complexity of construction projects along with unorganized data, impede the reliable identification of comparable past projects. A project scope document provides the preliminary overview of a project in terms of the extent of the project and project requirements. However, narratives and free-formatted descriptions of project scopes are a significant and time-consuming barrier if a human needs to review them and determine similar projects. This study proposes an Artificial Intelligence-driven model for analyzing project scope descriptions and evaluating project similarity using natural language processing (NLP) techniques. The proposed algorithm can intelligently a) extract major work activities from unstructured descriptions held in a database and b) quantify similarities by considering the semantic features of texts representing work activities. The proposed model enhances historical comparable project identification by systematically analyzing project scopes.

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The Effect of Virtual Human Lecturer's Human Likeness on Educational Content Satisfaction: Focused on the Theory of Experiential Economy (가상 휴먼 강사의 인간 유사도가 교육 콘텐츠 만족감에 미치는 영향: 체험경제이론을 중심으로)

  • Gong, Li;Bae, Sujin;Kwon, Ohbyung
    • The Journal of the Korea Contents Association
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    • v.22 no.7
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    • pp.524-539
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    • 2022
  • With the advent of generative artificial intelligence technology, it became possible to create a virtual human, and produce a lecture video only with textual information. It is expected that the virtual human will enhance the efficient production of educational contents and the student's entertainment experience and satisfaction. However, there have been still few studies that have demonstrated the process of how virtual human technology reaches students' satisfaction. Therefore, the purpose of this study is to empirically examine whether the human likeness, which is the main characteristic of a virtual human based on Uncanny Valley theory, affects human experience and satisfaction. In particular, human likeness of the Uncanny Valley theory was subdivided into human likeness in the visual and verbal dimensions, and the process of reaching satisfaction was understood based on the experience economy model. In particular, human similarity in Uncanny Valley theory was classified as similarity in the visual and language levels, and the process of reaching satisfaction based on the experiential economic model was analyzed with a partial least squares structure model equation (PLS-SEM). The survey was conducted online for a panel of office workers at a specialized research institution in China. The results indicate that both the visual and verbal human likeness had a positive effect on experience economy factors (education, entertainment, esthetic, escape), and then these experiential factors had a significant effect on satisfaction. The results also provide some suggestions to consider when designing educational contents by virtual human.

Implementation of Korean Sentence Similarity using Sent2Vec Sentence Embedding (Sent2Vec 문장 임베딩을 통한 한국어 유사 문장 판별 구현)

  • Park, Sang-Kil;Shin, MyeongCheol
    • Annual Conference on Human and Language Technology
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    • 2018.10a
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    • pp.541-545
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    • 2018
  • 본 논문에서는 Sent2Vec을 이용한 문장 임베딩으로 구현한 유사 문장 판별 시스템을 제안한다. 또한 한국어 특성에 맞게 모델을 개선하여 성능을 향상시키는 방법을 소개한다. 고성능 라이브러리 구현과 제품화 가능한 수준의 완성도 높은 구현을 보였으며, 자체 구축한 평가셋으로 한국어 특성을 반영한 모델에 대한 P@1 평가 결과 Word2Vec CBOW에 비해 9.25%, Sent2Vec에 비해 1.93% 더 높은 성능을 보였다.

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Synthesis and in Vitro Stability Evaluations of 5-(2'-(N-(1-methyl-3'-carbamylphenyl)-n-propyl))aminoethyl)-8-hydroxy-4-methylcarbostyril Derivatives (5-(2'-(N-(1-메틸-3-(3'-카바밀페닐)-n-프로필))아미노에틸)-8-히드록시-4- 메틸카보스티릴 유도체의 합성 및 안정성 연구)

  • 윤성화;박규순
    • YAKHAK HOEJI
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    • v.39 no.5
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    • pp.506-510
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    • 1995
  • The 5-(2'-(N-(1-methyl-3'-carbamylphenyl)-n-propyl))aminoethyl)-8- hydroxy-4-methyl-carbostyril derivatives which have isoelectronic and isosteric structural similarity with dobutamine without having the Catechol-O-Methyltransferase (COMT) vulnerable m-hydroxy group were synthesized via 7 synthetic steps, and their stabilities in phosphate buffer solution(pH=7.4), human blood. 80% human plasma and 20% rat liver homogenate were determined in vitro condition.

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Zero-shot Lexical Semantics based on Perplexity of Pretrained Language Models (사전학습 언어모델의 Perplexity에 기반한 Zero-shot 어휘 의미 모델)

  • Choi, Heyong-Jun;Na, Seung-Hoon
    • Annual Conference on Human and Language Technology
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    • 2021.10a
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    • pp.473-475
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    • 2021
  • 유의어 추천을 구현하기 위해서는 각 단어 사이의 유사도를 계산하는 것이 필수적이다. 하지만, 기존의 단어간 유사도를 계산하는 여러 방법들은 데이터셋에 등장하지 않은 단어에 대해 유사도를 계산 할 수 없다. 이 논문에서는 이를 해결하기 위해 언어모델의 PPL을 활용하여 단어간 유사도를 계산하였고, 이를 통해 유의어를 추천했을 때 MRR 41.31%의 성능을 확인했다.

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Models for evaluating and predicting the user satisfaction of product designs (제품다자인의 감성만족도 평가 및 예측모델 개발)

  • Han, Seong-Ho
    • Journal of the Ergonomics Society of Korea
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    • v.20 no.1
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    • pp.87-113
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    • 2001
  • This study introduces the concept of image/impression of a product design, human interface elements, and the relationships between them. It is assumed that the human interface can be decomposed into detailed design elements, called human interface elements. This study attempts to build functional relationships between the image/impression of a product and human interface elements. Two different human factors experiments were conducted to demonstrate the effectiveness of the approach suggested in this study. A total of 35 audio/visual consumer electronics products (e.g., CD players, VCRs) were shown on a display screen and the subjects were instructed to evaluate them in terms of eight image/impression dimensions. One experiment was conducted using Korean subjects while the other using American subjects. The functional relationships were modeled by using the multiple linear regression technique. Similarity and difference between the Korean and the American subjects were analyzed. The approach suggested in this study is expected to help designers and developers identify important design variables to enhance the subjective satisfaction of a product design.

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Identification and Phylogenetic Analysis of Long Terminal Repeat Elements of the Human Endogenous Retrovirus K Family (HERV-K) from a Human Brain cDNA Library

  • Kim, Heui-Soo;Lee, Young-Choon
    • Animal cells and systems
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    • v.5 no.2
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    • pp.133-137
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    • 2001
  • Long terminal repeats (LTRs) of the human endogenous retrovirus K family (HERV-K) have been found to be coexpressed with sequences of genes closely located nearby. We examined transcribed HERV-K LTR elements in human brain tissue. Using cDNA synthesized from mRNA of the human brain, we performed PCR amplification and identified ten HERV-K LTR elements. These LTR elements showed a high degree of sequence similarity (92.4-99.7%) with the human-specific LTR elements. A phylogenetic tree obtained by the neighbor-joining method revealed that HERV-K LTR elements could be divided into two groups through evolutionary divergence. Some HERV-K LTR elements (HKL-B7, HKL-B8, HKL-B10) belonging to the group II from human brain cDNA were closely related to the human-specific HERV-K LTR elements. Our data suggest that HERV-K LTR element are active in the human brain; they could conceivably play a pathogenic role in human diseases such as psychosis.

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Similarity Model Analysis and Implementation for Enzyme Reaction Prediction (효소 반응 예측을 위한 유사도 모델 분석 및 구현)

  • Oh, Joo-Seong;Na, Do-Kyun;Park, Chun-Goo;Ceong, Hyi-Thaek
    • The Journal of the Korea institute of electronic communication sciences
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    • v.13 no.3
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    • pp.579-586
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    • 2018
  • With the beginning of the new era of bigdata, information extraction or prediction are an important research area. Here, we present the acquisition of semi-automatically curated large-scale biological database and the prediction of enzyme reaction annotation for analyzing the pharmacological activities of drugs. Because the xenobiotic metabolism of pharmaceutical drugs by cellular enzymes is an important aspect of pharmacology and medicine. In this study, we apply and analyze similarity models to predict bimolecular reactions between human enzymes and their corresponding substrates. Thirteen models select to reflect the characteristics of each cluster in the similarity model. These models compare based on sensitivity and AUC. Among the evaluation models, the Simpson coefficient model showed the best performance in predicting the reactivity between the enzymes. The whole similarity model implement as a web service. The proposed model can respond dynamically to the addition of reaction information, which will contribute to the shortening of new drug development time and cost reduction.

The Effects of the Attributes of Korean Celebrity Advertising Models on Chinese Consumer's Intention to Purchase Korean Fashion Brands (한국 연예인 광고모델 속성이 중국 소비자 한국 패션브랜드 구매도에 미치는 영향)

  • Kwon, Yoo-Jin;Hong, Byung-Sook;Seo, Si-Won;Cho, Mi-Ae
    • Journal of the Korean Society of Clothing and Textiles
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    • v.33 no.3
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    • pp.477-488
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    • 2009
  • As the Korean cultural contents, such as drama, films, music, gained popularity in China, Korean fashion brands used Korean celebrities as their models to as a sales promotion strategy for Chinese consumers. With the point of view that the advertising model as a human capital as well, the purpose of this study is to investigate the factors of attributes of Korean celebrity advertising model, and to analyze effects on fashion brand recognition, preference, trust and purchase intention. With convenience sampling, the research surveyed Shanghai consumers in their 20's to early 30's who had purchased Korean fashion items. The 291 responses were analyzed by frequency analysis, reliability test, factor analysis, multiple regression analysis, The results are as follows. Frist, Korean celebrity advertising model attribute factors were divided into similarity, familiarity, popularity, attractiveness and trust. Second, the brand recognition was affected by similarity, familiarity and popularity factors, and the brand preference was affected by similarity, familiarity, popularity and attractiveness factors. Third, the trust of Korean fashion brands was affected by similarity, familiarity, attractiveness, trust, brand recognition and brand preference. Lastly, the intention to purchase Korean Fashion brand was affected by similarity, familiarity, attractiveness, brand recognition, brand preference and brand trust.