• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2002년도 추계학술대회 논문집
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• pp.595-598
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• 2002

Laser scanners are getting used more and more in reverse engineering and inspection. For CNC-driven laser scanners, it is important to automate the scanning operations to improve the accuracy of capture point data and to reduce scanning time in industry. However, there are few research works on laser scan planning system. In addition, it is difficult to directly analyze multi-patched freeform models. In this paper, we propose an STL (Stereolithography) mesh based laser scan planning system for complex freeform surfaces. The scan planning system consists of three steps and it is assumed that the CAD model of the part exists. Firstly, the surface model is approximated into STL meshes. From the mesh model, normal vector of each node point is estimated. Second, scan directions and regions are determined through the region growing method. Also, scan paths are generated by calculating the minimum-bounding rectangle of points that can be scanned in each scan direction. Finally, the generated scan directions and paths are validated by checking optical constraints and the collision between the laser probe and the part to be scanned.

• 경영과학
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• 제10권1호
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• pp.81-105
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• 1993

The objective of the paper is to develop models for determining the aggregate budget size in long-range R&D planning of KT(Korea Telecom.) and for allocating it by strategically adopted technologies for KT's TOP(Telecommunication-Oriented Paradise) Strategy. In the model of R&D budget size determination, the linear regression analysis is applied. In allocating the R&D expenditure, criteria weighting and technological importance ranking are determined by means of the Analytic Hierarchy Process(AHP) as a decision aid, along with hierarchical representation and pairwse comparisons. R&D budget analysis provides to basic data for the mid-and long-range R&D planning. The model then needs to be adjusted as the TOP project plan becomes specific. Resource allocation model for R&D based on AHP can be used to identify the importance of the technologies for TOP according to short-, mid-, and long-term perspectives without further modification. It is expected that the R&D budget analysis model works as the basis for planning R&D investment strategies and that the resource allocation model for R&D contributes to the effective use of the limited resource.

• 산경연구논집
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• 제6권1호
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• pp.17-26
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• 2015

Purpose - Ethical management connects corporate management outcomes and emphasizes organizational cooperation. It also links human resource management, auditing, and financial management to increase employee job satisfaction. A survey of American enterprises showed that employees with high ethical consciousness had greater job satisfaction and lower turnover. Research design, data, and methodology - Hypotheses and models based on previous studies were used to investigate the effects of ethical management on employee job satisfaction and turnover intentions. To examine hypotheses empirically, a questionnaire survey based on previous studies was administered to service business workers in Seoul. Results - The study investigated the effects of ethical management practices in relation to factors such as top management's willingness to put them into practice, their appropriateness and implementation within operations, and their influence on job satisfaction, and also examined the effects of job satisfaction on turnover intentions. Conclusions - Ethical management greatly influences job satisfaction and turnover intentions, providing organizational members with alternatives regarding ethical considerations, and to place a strong emphasis on management willingness and enterprise regulations and policies.

• The Journal of Asian Finance, Economics and Business
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• 제7권10호
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• pp.359-368
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• 2020

This research seeks to explain factors and relationship models of entrepreneurs capable of building service innovations in Andaman coast with the ultimate aim to ignite sufficient development of regional tourism, increase working potentials, and provide a guideline for tour operations. Initially, document examination and discussions with five experts were conducted to build in-depth interview questions. 19 entrepreneurs were interviewed to examine factors involved and we consulted later with the five experts and six successful entrepreneurs in the regions, as well as with the representatives of the Association of Thai Tour Operators and Tourism Authority of Thailand (TAT) of Phuket, Krabi, and Trang. The results were analyzed according to the theory of resource-based and innovative entrepreneurs. The factors obtained were generated from systematic causes: Nature of Entrepreneurships and Organizational capabilities, the mediator variables of Service Innovation Capability; and Organizational Performance (non-finance). Moreover, the external factors needing to be adjusted regarding the environmental changes were described. The tour operators are suggested to build networking to increase tourism potential with sustainability by providing the entrepreneurs opportunities to be involved in tourism development, accessing the knowledge, technology and innovations resulting in sustainable tourism, quality livelihood, and sustainable ecological management of communities.

• Industrial Engineering and Management Systems
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• 제8권1호
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• pp.37-46
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• 2009

Patient safety has become a growing concern in health care. The U.S. Institute of Medicine (IOM) report "To Err Is Human: Building a Safer Health System" in 1999 included estimations that medical error is the eighth leading cause of death in the United States and results in up to 100,000 deaths annually. However, many adverse events and errors occur in surgical practice. Within all kinds of surgical adverse events, wrong-side/wrong-site, wrong-procedure, and wrong-patient adverse events are the most devastating, unacceptable, and often result in litigation. Much literature claims that systems must be put in place to render it essentially impossible or at least extremely difficult for human error to cause harm to patients. Hence, this research aims to develop a prototype system based on active RFID that detects and prevents errors in the OR. To fully comprehend the operating room (OR) process, multiple rounds of on site discussions were conducted. IDEF0 models were subsequently constructed for identifying the opportunity of improvement and performing before-after analysis. Based on the analysis, the architecture of the proposed RFID-based OR system was developed. An on-site survey conducted subsequently for better understanding the hardware requirement will then be illustrated. Finally, an RFID-enhanced system based on both the proposed architecture and test results was developed for gaining better control and improving the safety level of the surgical operations.

• Industrial Engineering and Management Systems
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• 제11권1호
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• pp.54-69
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• 2012

Chan and Qi (SCM 8/3 (2003) 209) developed an innovative measurement method that aggregates performance measures in a supply chain into an overall performance index. The method is useful and makes a significant contribution to supply chain management. Nevertheless, it can be cumbersome in computation due to its highly complex algorithmic fuzzy model. In aggregating the performance information, weights used by Chan and Qi-which aim to address the imprecision of human judgments-are incompatible with weights in additive models. Furthermore, the default assumption of linearity of its scoring procedure could lead to an inaccurate assessment of the overall performance. This paper addresses these limitations by developing an alternative measurement that takes care of the above. This research integrates three different approaches to multiple criteria decision analysis (MCDA)-the multiattribute value theory (MAVT), the swing weighting method and the eigenvector procedure-to develop a comprehensive assessment of supply chain performance. One case study is presented to demonstrate the measurement of the proposed method. The performance model used in the case study relies on the Supply Chain Operations Reference (SCOR) model level 1. With this measurement method, supply chain managers can easily benchmark the performance of the whole system, and then analyze the effectiveness and efficiency of the supply chain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.4120-4132
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• 2017

In this research, we implement a deformable object simulation system using OpenGL's shader language, GLSL4.3. Deformable object simulation is implemented by using volumetric mass-spring system suitable for real-time simulation among the methods of deformable object simulation. The compute shader in GLSL 4.3 which helps to access the GPU resources, is used to parallelize the operations of existing deformable object simulation systems. The proposed system is implemented using a compute shader for parallel processing and it includes a bounding box-based collision detection solution. In general, the collision detection is one of severe computing bottlenecks in simulation of multiple deformable objects. In order to validate an efficiency of the system, we performed the experiments using the 3D volumetric objects. We compared the performance of multiple deformable object simulations between CPU and GPU to analyze the effectiveness of parallel processing using GLSL. Moreover, we measured the computation time of bounding box-based collision detection to show that collision detection can be processed in real-time. The experiments using 3D volumetric models with 10K faces showed the GPU-based parallel simulation improves performance by 98% over the CPU-based simulation, and the overall steps including collision detection and rendering could be processed in real-time frame rate of 218.11 FPS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권5호
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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.

• 디지털산업정보학회논문지
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• 제17권4호
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• pp.53-62
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• 2021

Deep learning models such as convolutional neural networks and recurrent neual networks process a huge amounts of data, so they require a lot of storage and consume a lot of time and power due to memory access. Recently, research is being conducted to reduce memory usage and access by compressing data using the feature that many of deep learning data are highly sparse and localized. In this paper, we propose a compression-decompression method of storing only the non-zero data and the location information of the non-zero data excluding zero data. In order to make the location information of non-zero data, the matrix data is divided into sections uniformly. And whether there is non-zero data in the corresponding section is indicated. In this case, section division is not executed only once, but repeatedly executed, and location information is stored in each step. Therefore, it can be properly compressed according to the ratio and distribution of zero data. In addition, we propose a hardware structure that enables compression and decompression without complex operations. It was designed and verified with Verilog, and it was confirmed that it can be used in hardware deep learning accelerators.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.540-557
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• 2021

Privacy vulnerability of social networks is one of the major concerns for social science research and business analysis. Most existing studies which mainly focus on un-weighted network graph, have designed various privacy models similar to k-anonymity to prevent data disclosure of vertex attributes or relationships, but they may be suffered from serious problems of huge information loss and significant modification of key properties of the network structure. Furthermore, there still lacks further considerations of privacy protection for important sensitive edges in weighted social networks. To address this problem, this paper proposes a privacy preserving method to protect sensitive weighted edges. Firstly, the sensitive edges are differentiated from weighted edges according to the edge betweenness centrality, which evaluates the importance of entities in social network. Then, the perturbation operations are used to preserve the privacy of weighted social network by adding some pseudo-edges or modifying specific edge weights, so that the bottleneck problem of information flow can be well resolved in key area of the social network. Experimental results show that the proposed method can not only effectively preserve the sensitive edges with lower computation cost, but also maintain the stability of the network structures. Further, the capability of defending against malicious attacks to important sensitive edges has been greatly improved.