• Journal of the Ergonomics Society of Korea
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• v.31 no.1
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• pp.49-61
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• 2012

Objective: The aim of this study is to offer a holism based Service Experience Analysis System(HSEAS) for service design. Background: Customer experience has been focused in a lot of service area. But it is difficult to understand the customer's needs and their experiences because it's so complex and uncertain. Thus it needs holistic approach that means it's difficult to explain general character merely through the understanding of small parts that composes an object and it must be analyzed within the overall context. Method: Accordingly, the thesis paper proposes the Service Experience Analysis System that satisfies the four following needs. (1) Need of solid Experience Framework in which the special quality of the service experience is considered, (2) need of support for the semantic cohesion between different kinds of data, (3) need of support for the management and search of vast data, and (4) need of building the knowledge base system for collaborative research. Results: HSEAS combines the short information in the customers' words and behaviors or situations and circumstances and provides a place of analysis where the context of the general experience can be read and allows concrete understanding of the actual state and factor of the problem as a Combined Data Analysis Tool. Conclusion: HSEAS becomes the center of information management, analysis and connection and it provides a free collaboration place where physical condition has no relations to as a knowledge base system based on network. Application: It is expected that length and width will be added to the analysis and assistance for effectively accumulating information will be provided in the area of diverse service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5039-5061
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• 2017

Cloud storage becomes a new trend that more and more users move their data to cloud storage servers (CSSs). To ensure the security of cloud storage, many cloud auditing schemes are proposed to check the integrity of users' cloud data. However, most of them are based on public key infrastructure, which leads to complex certificates management and verification. Besides, most existing auditing schemes are inefficient when user uploads a large amount of data or a third party auditor (TPA) performs auditing for multiple users' data on different CSSs. To overcome these problems, in this paper, we propose an efficient and secure auditing scheme based on identity-based cryptography. To relieve user's computation burden, we introduce a proxy, which is delegated to generate and upload homomorphic verifiable tags for user. We extend our auditing scheme to support auditing for dynamic data operations. We further extend it to support batch auditing in multiple users and multiple CSSs setting, which is practical and efficient in large scale cloud storage system. Extensive security analysis shows that our scheme is provably secure in random oracle model. Performance analysis demonstrates that our scheme is highly efficient, especially reducing the computation cost of proxy and TPA.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.2
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• pp.303-310
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• 2018

Bitcoin (BTC) is a cryptocurrency proposed by Satoshi Nakamoto in 2009. Bitcoin makes its transactions with no central authorities. This decentralization is accomplished with its mining, which is an operation that makes people compete to solve math puzzles to include new transactions into block, and eventually block chains (ledger) of bitcoin. Because miners need to solve a complex puzzles, they need a lot of computing resources. In return for miners' resources, bitcoin network gives newly minted bitcoins as a reward to miners when they succeed in mining. To prevent inflation, the reward is halved every 4 years. For example, in 2009 block reward was 50 BTC, but today, the block reward is 12.5 BTC. On the other hands, exchange rate for bitcoin and Korean Won (KRW) changed drastically from 924,000 KRW/BTC (January 12th, 2017) to 16,103,306 KRW/BTC (December 10th, 2017), which made mining more attractive. However, there are no rigorous researches on the profitability of bitcoin mining. In this paper, we evaluate the profitability of bitcoin mining.

• Journal of Korean Society of Steel Construction
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• v.16 no.4 s.71
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• pp.443-452
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• 2004

Recently, the Artificial Neural Network(ANN) which can organize complex non-linear problems by effectively applying the parallel computational model that is similar to the human brain, was adopted in the wide department of technology and resulted in many successful applications. In this study, a more appropriate formal method is suggested for the preliminary structural design stage controlled merely by the designer's experience and intuition. To do so, this study proposes a multi-level ANN according to the general progressive structural design procedure, using Back-Propagation Algorithm (BP) and Genetic Algorithm (GA) for the ANN learning. The preliminary structural design of cable-stayed bridges was applied to illustrate the applicability of the study formulated as stated above, and the results of two different learning methods were compared.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.185-192
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• 1995

A common control model used to implement computer integrated manufacturing(CIM) is based on the hierarchical decomposition of the shop floor activities, in which supervisory controllers are responsible for all the interactions among subordinates. Although the hierarchical control philosophy provides for easy understanding of complex systems, an emerging manufacturing paradigm, agile manufacturing, requires a new control structure necessary to accommodate the rapid development of a shop floor controller. This is what is called CSCW(computer supported cooperative work)-based control or component-based heterarchical control. As computing resources and communication network on the shop floor become increasingly intelligent and powerful, the new control architecture is about to come true in a modern CIM system. In this paper, CSCW-based control is adopted and investigated, in which a controller for a unit of device performs 3 main functions - planning, scheduling and execution. In this paper, attention is paid to a planning function and all the detailed planning activities for CSCW-based shop floor control are identified. Interactions with other functions are also addressed. Generally speaking, planning determines tasks to be scheduled in the future. In other words, planning analyzes process plans and transforms process plans into detailed plans adequate for shop floor control. Planning is also responsible for updating the process plan and identifying/resolving replanning activities whether they come from scheduling or execution.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.9
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• pp.906-910
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• 2008

As the mobile environment becomes widely used, there is a growth on the concern about recognizing and sharing user context. Sharing context makes the interaction between human more plentiful as well as helps to keep a good social relationship. Recently, it has been applied to some messengers or mobile applications with sharing simple contexts, but it is still required to recognize and share more complex and diverse contexts. In this paper, we propose a context-aware messenger that collects various sensory information, recognizes representative user contexts such as emotion, stress, and activity by using dynamic Bayesian networks, and visualizes them. It includes a modular model that is effective to recognize various contexts and displays them in the form of icons. We have verified the proposed method with the scenario evaluation and usability test.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1016-1022
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• 2010

Far-talking recognition and distributed speech recognition networking techniques are essential to control various and complex home services conveniently with voices. It is possible to control devices everywhere at home by using only voices. In this paper, we have developed the server-client DSP module for distributed speech recognition network system and proposed a new decision rule to decide intelligently whether to accept the recognition results or not by the transferred confidence rate. Simulation results show that the proposed decision rule delivers better performances than the conventional decision by majority rule or decision by first-arrival. Also, we have proposed the new interrupt-polling technique to remedy the defect of existing delay technique which always has to wait several clients' results for a few seconds. The proposed technique queries all client's status after first-arrival and decides whether to wait or not. It can remove unnecessary delay-time without any performance degradation.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.9
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• pp.901-908
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• 2013

The introduction of industrial intelligent robot using vision sensor has been interested in automated factory. 2D and 3D vision sensors have used to recognize object and to estimate object pose, which is for packaging parts onto a complete whole. But it is not trivial task due to illumination and various types of objects. Object image has distorted due to illumination that has caused low reliability in recognition. In this paper, recognition method of complex shape object has been proposed. An accurate object region has detected from combined binary image, which has achieved using DoG filter and local adaptive binarization. The object has recognized using neural network, which is trained with sub-divided object class according to object type and rotation angle. Predefined shape model of object and maximal slope have used to estimate the pose of object. The performance has evaluated on ETRI database and recognition rate of 96% has obtained.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2938-2956
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• 2020

Objective image quality assessment (IQA) models have been developed by effective features to imitate the characteristics of human visual system (HVS). Actually, HVS is extremely sensitive to color degradation and complex texture changes. In this paper, we firstly reveal that many existing full reference image quality assessment (FR-IQA) methods can hardly measure the image quality with contrast and masking texture changes. To solve this problem, considering texture masking effect, we proposed a novel FR-IQA method, called Texture and Color Quality Index (TCQI). The proposed method considers both in the masking effect texture and color visual perceptual threshold, which adopts three kinds of features to reflect masking texture, color difference and structural information. Furthermore, random forest (RF) is used to address the drawbacks of existing pooling technologies. Compared with other traditional learning-based tools (support vector regression and neural network), RF can achieve the better prediction performance. Experiments conducted on five large-scale databases demonstrate that our approach is highly consistent with subjective perception, outperforms twelve the state-of-the-art IQA models in terms of prediction accuracy and keeps a moderate computational complexity. The cross database validation also validates our approach achieves the ability to maintain high robustness.

• Journal of KIISE
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• v.43 no.4
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• pp.460-469
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• 2016

Internet of Things (IoT) is an environment where various devices are connected to each other via a wired/wireless network and where the devices gather, process, exchange, and share information. Some of the most important types of IoT devices are mobile IoT devices such as smartphones. These devices provide various high-performance services to users but cannot be supplied with power all the time; therefore, power management appropriate to a given IoT environment is necessary. Power management of mobile IoT devices involves complex relationships between various entities such as application processors (APs), HW modules inside/outside AP, Operating System (OS), platforms, and applications; a method is therefore needed to systematically analyze and manage these relationships. In addition, variabilities related to power management such as various policies, operational environments, and algorithms need to be analyzed and applied to power management development. In this paper, engineering principles and a method based on them are presented in order to address these challenges and support systematic development of IoT device power management. Power management of connected helmet systems was used to validate the feasibility of the proposed method.