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중국인 관광객의 한국 관광목적지에 대한 인지와 경험의 차이 연구 - 빅데이터 기반 텍스트 분석
Wang, Dayu,Zhang, Xuantao,Zhang, Bingchao 한국공공사회학회 2021 공공사회연구 Vol.11 No.3
본 연구는 기계 프로그래밍과 인공지능의 조합이라는 혁신적인 방법을 사용하여 한국 관광목적지에 대한 중국 관광객의 인지와 평가를 탐구하였다. 텍스트 마이닝 기술을 기반으로 14,000개 이상의 중국인 관광객들의 한국 관광리뷰에 대한 심층적 분석을 진행했으며, 리뷰 분류와 카테고리 추출을 통해 빅데이터에 기반한 중국인들의 한국관광 리뷰 인지요소를 추출 및 요약하였다. 동시에 선형관계 행렬(Colinear relation matrix)과 시맨틱 클러스터링 기술(Semantic clustering technology) 방법을 이용하여 중국인 관광객의 인식차이를 분석하고, 방한 중국인 관광객의 인지차이 이미지를 생성하여, 방한 중국인 관광객의 인지차이와 규칙을 정확하게 제시 하였다. 연구에 따르면 (1) 방한 중국인 관광객이 인지하는 주요 요소에는 주로 경험적 요소, 관광지 자원 요소, 관리 서비스 요소 및 구조적 기능 요소가 있다. (2) 방한 중국인 관광객의 한국에 대한 인지는 상당한 차이를 지니며 주로 경험 감정 요소, 관광지의 자원적 요소 및 구조적 기능적 요소에 반영된다. (3) 관광객 심리회계이론(Mental accounting Theory)은 방한 중국인 관광객의 인지 차이의 특성과 법칙을 해석하는 데 적합하다. 본 연구는 빅 데이터의 맥락에서 관광인지 연구를 위한 새로운 접근방식을 제공하여 수많은 관광객 리뷰를 관광지 마케팅을 위한 새로운 데이터소스로 변환 시켰다. 또한 기존 관광인지 이론을 보완 및 교차 검증하고 온라인 관광 리뷰에 감정도감(情感图像)분석을 성공적으로 적용하여 관광지 관리에 시사점을 줄 수 있는 것으로 기대한다. This paper innovatively applies a combination of machine programming and manual rooting to explore Chinese tourists’ perception and evaluation of destinations in South Korean. Based on text mining technology, we conducted an in-depth analysis of more than 34,000 online reviews of South Korea written by Chinese tourists on domestic online social media and for travel agencies. Through review layering and category extraction, the perception factors of Chinese tourists to South Korea rooted in big data were refined and summarized. Meanwhile, the co-occurrence analysis and semantic clustering technology are used to deeply describe the perception differences of Chinese tourists, generate portraits of the perception differences of Chinese tourists to South Korea, and accurately reveal the perception differences and laws of Chinese tourists to South Korea. The study found that: (1) The key factors that Chinese tourists perceive in South Korea are mainly destination resources, experience emotion, management service, and structure characteristics; (2) There are significant differences in perceptions of Chinese tourists to South Korea, which are mainly reflected in experience emotion factors, destination resources factors and management service factors. (3) The theory of tourist mental accounts is suitable for interpreting the characteristics and preferences of perceived experience differences between Chinese tourists to South Korea. This exploratory research provides new ideas for tourism perception research in the context of big data, and converts a large number of tourist online reviews into alternative new data sources for tourism destination marketing. Complement and cross-validate existing tourism perception theories, and successfully apply emotional image analysis to tourist online reviews, providing a valuable reference for tourism destination management practices.
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Xuan Ruoyue,Dai Qingfeng,He Can,Zhang Dayu,Pan Chengyuan 한국응용곤충학회 2021 Journal of Asia-Pacific Entomology Vol.24 No.1
Pseudocapritermes Kemner is a termite group that constructs subterranean gallery systems in topsoil. This genus is distributed in the Oriental region and contains 18 species. Dependence on the morphological measurements of soldiers makes the taxonomy of Pseudocapritermes difficult. In this study, we compared morphological characters of soldiers and adults of P. largus and P. sowerbyi. In addition, three fulllength mitochondrial genes (COI, COII, and 16S rRNA) were sequenced from a total of eight P. largus and P. sowerbyi colonies. Morphological comparison of soldiers showed that P. largus is larger than P. sowerbyi, but there was overlap in some measurements. In adults, the morphological characters of P. largus were congruent with those of P. sowerbyi. Sequence alignments of COI, COII, and 16S rRNA revealed a high pairwise genetic identity (ranging from 99.64 to 100%) between the two species, which suggested that P. largus and P. sowerbyi are the same species. Molecular phylogenetic analysis based on COII revealed that Pseudocapritermes belongs to the Termes group having soldiers with asymmetrical snapping mandibles and is more closely related to Sinocapritermes than to other Termes group genera distributed in China. Morphological similarity and genetic identity indicate that P. largus is a junior synonym of P. sowerbyi.
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Xigui Wang,Yongmei Wang,Yixiang Liu,Xinbo Zhang,Dayu Zheng 대한기계학회 2018 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.32 No.7
The minimum of tooth surface flash temperature and vibration acceleration RMS design is proposed and analyzed. The tooth contact analysis (TCA) and the load tooth contact analysis (LTCA) method and multi-objective optimization are also detailed. Satisfying design variables in multiple physical quantities leads to the minimum of multi-objective optimization. Considering the tooth surface loading conditions are uniform or not, the optimal modification of the tooth surface for improving gear comprehensive characteristics under various load bearing conditions is improved. The tooth surface flash temperature and vibration acceleration root mean square (RMS) values in different transmission modes of marine ship power rear gears drive system are derived. This research considers the multi-objective optimization modifications of tooth surface, and its main purpose is to propose an approach to help design tooth corrections to simultaneously optimize several objective physical quantities.
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Ensemble learning-based hierarchical retrieval of similar cases for site planning
Wang Pengyue,Guo Maozu,Han Yunsong,Zhao Lingling,Zhou Xiaoping,Zhang Dayu 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.6
Site planning not only involves the arrangement of a large number of elements but also considers the complexity of urban systems; hence, the design process involves large workloads and is time consuming. Retrieving similar existing cases helps architects optimize or accelerate the design process. This paper proposes a computational approach that provides valuable references by retrieving similar cases. Three types of attributes are extracted to represent a given parcel: land-use attributes, geometric attributes (area, orientation, etc.), and environmental attributes (greening rate, surrounding facilities, etc.). The complete hierarchical retrieval process is divided into three phases. The first phase selects cases whose land-use attributes are consistent with the target parcel. Then, the similarity distances between the given target parcel and the selected cases are calculated using geometric attributes. The eXtreme Gradient Boosting (XGBoost) classifier is adopted to determine which case is similar to the target parcel. Finally, similarity scores of the retrieved cases are calculated based on the environmental attributes to provide more options during the actual design. In total, 1189 cases with different land-use types in Beijing were collected for the case base. The comparative experimental results confirmed that the proposed ensemble learning-based hierarchical retrieval of similar cases approach improves the accuracy of retrieval results. Furthermore, we use a real-world target parcel to demonstrate the superiority and flexibility of the retrieval process.
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