• Journal of Navigation and Port Research
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• v.32 no.6
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• pp.473-479
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• 2008

Recently the trade patterns of the entire economy are rapidly changing on development of IT. The field of port logistics is enforcing a competitiveness through preliminary offer of information and a batch process for improving the structure of logistics management which is apparently high cost and the low efficiency since 1990. But a previous EDI is insufficient in process ability. Bemuse it costs for the purchasing and maintenance of the expensive communication devices which is operated on the VAN environment. A web based EDI operating on an open network environment is needed to improve these problems and to handle transaction efficiently among many and unauthorized personals. Therefore, this study is willing to present a new web based model of the pull process which extracts the data when the receiver is needed to improve the push process which is transmitting data unilaterally.

• Journal of Digital Convergence
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• v.16 no.11
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• pp.17-27
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• 2018

In this paper, the research trends of port hinterland from 1990 to 2018 were analyzed periodically using the Social Network Analysis (SNA) method. The data were collected from major academic journals and totally 116 papers were identified for analysis. The results of the analysis showed that in the first period (1990-1999), keywords can be listed as "containerization", "transport infrastructure" and developed countries related keywords like "Italy", "Canada" and "Germany". The results of the second period (2000-2009) were originated from keywords such as "regionalization", "competitiveness", "Asian consolidation" and "technology". In the third period (2010-2018), the results were derived from keywords such as "intermodal transport", "dry port", "container" and container related keywords and "shipping" and shipping related keywords. We could see the studies of port hinterland are becoming more systematic and integrated. This study provides some important implications for both academic, and industrial viewpoints, and it is helpful to understand the research concentration.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.5
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• pp.2082-2102
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• 2018

In recent years, social network related applications such as WeChat, Facebook, Twitter and so on, have attracted hundreds of millions of people to share their experience, plan or organize, and attend social events with friends. In these operations, plenty of valuable information is accumulated, which makes an innovative approach to explore users' preference and overcome challenges in traditional recommender systems. Based on the study of the existing social network recommendation methods, we find there is an abundant information that can be incorporated into probability matrix factorization (PMF) model to handle challenges such as data sparsity in many recommender systems. Therefore, the research put forward a unified social network recommendation framework that combine tags, trust between users, ratings with PMF. The uniformed method is based on three existing recommendation models (SoRecUser, SoRecItem and SoRec), and the complexity analysis indicates that our approach has good effectiveness and can be applied to large-scale datasets. Furthermore, experimental results on publicly available Last.fm dataset show that our method outperforms the existing state-of-art social network recommendation approaches, measured by MAE and MRSE in different data sparse conditions.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.11
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• pp.243-251
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• 2021

The goal of this study is to examine the characteristics of Chinese visitors visiting Thailand, determine the rules, and give a reference for Thai tourism authorities and businesses when developing marketing strategies for the Chinese market. This paper constructs the tourism flow network and takes Bangkok as the major research target. The statistical characteristics of the network are studied using the SNA method, based on the trip notes of Thailand on www.mafengwo.cn, a prominent travel website in China as the data source. The results show that: Shanghai, Beijing, and Tianjin occupy important positions in the network; The flow direction of Chinese tourists to Thailand mainly tends to Bangkok, Chiang Mai, Pattaya, and Phuket Island; Grand Palace have strong tourism flow aggregation, diffusion, and control over other nodes in the whole network structure; Tom Yu Kuang has the greatest degree centrality in all Thai cuisine. The findings of the study can help relevant management departments create tourist policies and modify market strategies by developing the regular characteristics of China's tourism flow to Thailand in the theoretical field.

• ETRI Journal
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• v.40 no.4
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• pp.435-445
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• 2018

This paper proposes a human-like sign-language learning method that uses a deep-learning technique. Inspired by the fact that humans can learn sign language from just a set of pictures in a book, in the proposed method, the input data are pre-processed into an image. In addition, the network is partially pre-trained to imitate the preliminarily obtained knowledge of humans. The learning process is implemented with a well-known network, that is, a convolutional neural network. Twelve sign actions are learned in 10 situations, and can be recognized with an accuracy of 99% in scenarios with low-cost equipment and limited data. The results show that the system is highly practical, as well as accurate and robust.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.95-99
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• 2007

본 논문에서는 EPCglobal Network 상의 물류 정보 시스템인 EPC IS(Electronic Product Code Information Services)와 EPCIS Discovery System의 기능을 확장하여 사용자 정보를 유지할 수 있도록 한다. 본 논문에서 EPC IS에 저장된 정보는 공개(Public)정보와 비공개(Private)정보로 나뉘고, 물류 정보사용자에 따라 접근 가능한 정보가 다르다는 전제하에 물류 정보 사용자가 물류 정보 접근 시 사용자 정보를 유지하는 EPCIS Discovery System과 EPC IS의 연동을 통한 물류 정보 접근 제어가 이루어질 수 있도록 방법과 절차를 제안한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2013.06a
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• pp.81-82
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• 2013

Port of competition in the domestic market share of a particular port is gradually lowered. This is growing influence of external factors in accordance with changes in the market environment and the open economy. This liquidity factors have difficulties to explain. Using real-time data to identify network effects, means for establishing practical measures will have.

• ETRI Journal
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• v.45 no.2
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• pp.329-337
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• 2023

For safe last-mile autonomous robot delivery services in complex environments, rapid and accurate collision prediction and detection is vital. This study proposes a suitable neural network model that relies on multiple navigation sensors. A light detection and ranging technique is used to measure the relative distances to potential collision obstacles along the robot's path of motion, and an accelerometer is used to detect impacts. The proposed method tightly couples relative distance and acceleration time-series data in a complementary fashion to minimize errors. A long short-term memory, fully connected layer, and SoftMax function are integrated to train and classify the rapidly changing collision countermeasure state during robot motion. Simulation results show that the proposed method effectively performs collision prediction and detection for various obstacles.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.932-939
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• 2024

Program management presents unique challenges due to the complexity of interrelated projects and increased stakeholder engagement. While existing literature mainly focuses on project-level risk management, inter-project risks remain underexplored. This research addresses this gap by proposing a program risk analysis method that integrates project interdependence and stakeholder engagement. Leveraging social network analysis, the model enhances program risk management efficiency by identifying four types of inter-project risks and suggesting tailored response strategies. Through a case study of the Expo 2020 construction program, the effectiveness of the framework is demonstrated. This study enriches program and risk management literature, deepening our understanding of enhanced risk management in multi-project contexts.

• The Journal of Society for e-Business Studies
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• v.21 no.4
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• pp.55-67
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• 2016

Global courier companies have been devoting to get more customers and profits with different service because of the worse profits from price competition. So, the effort of improving satisfaction of customers through improving courier service qualities is more important than any other time. However, the previous way to measure courier service has limitation that costs lots of time and money from off-line survey. This limitation could be overcome with less effort and costs if utilizing on-line social big data analysis and it is so helpful to improve competitiveness of courier companies. Therefore, I have collected comments from domestic and international courier companies from big data on social network service, analyzed the satisfaction of customers by R and verified the result by comparing with American Customer Satisfaction Index (ACSI) and Korea National Customer Index (NCSI) in this research. I found out the result depicts clear correlation between SNS analysis and customer satisfaction. This study can be the foundation to predict customer satisfaction easily by utilizing real time SNS information.