• Journal of Science and Technology Studies
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• v.18 no.3
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• pp.217-255
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• 2018

Bitcoin, which appeared in 2008, was merely a conceptual virtual currency, but it now enjoys the status as actual money. Bitcoin is an electronic money system that can be traded directly without a central trust institution. Thanks to the popularization of Bitcoin, blockchain technology has become a widespread concern. That technology is expanding not only the currency mechanism, but also a variety of other services. The possibility of a blockchain in relation to actual currency is ongoing. This paper investigates the technological characteristics and social construction of the blockchain by comparing the cases of Bitcoin, Namecoin, and MediBloc among blockchain applications. Namecoin emerged in 2013 is an attempt to replace the centralized Internet Domain Name System(DNS). There has been controversy over that current system for a long time, but replacing the already established system is not easy. Nevertheless, Namecoin has potential as an alternative. Meanwhile, MediBloc is an application that involves distributed management of medical data in South Korea. MediBloc claims that the key producers of medical data are patients themselves. This is to challenge to the question who is a knowledge producer of medical data. Through these three cases, it has discussed that blockchain technology does supports to form more democratic decision-making or simply provide a technical solution as automation. As a citizen, we can intervene in the realization of blockchains by presenting social agenda. This will be a method of the social construction of technology.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.748-755
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• 2006

In this paper, a trade-off design and fabrication of IPMC(Ionic Polymer Metal Composites) as an actuator for a flapping device have been described. Experiments for the internal solvent loss of IPMCs have been conducted for various combinations of cation and solvent in order to find out the best combination of cation and solvent for minimal solvent loss and higher actuation force. From the experiments, it was found that IPMCs with heavy water as their solvent could operate longer. Relations between length/thickness and tip force of IPMCs were also quantitatively identified for the actuator design from the tip force measurement of 200, 400, 640, and $800{\mu}m$ thick IPMCs. All IPMCs thicker than $200{\mu}m$ were processed by casting $Nafion^{TM}$ solution. The shorter and thicker IPMCs tended to generate higher actuation force but lower actuation displacement. To improve surface conductivity and to minimize solvent evaporation due to electrically heated electrodes, gold was sputtered on both surfaces of the cast IPMCs by the Physical Vapor Deposition(PVD) process. For amplification of a short IPMC's small actuation displacement to a large flapping motion, a rack-and-pinion type hinge was used in the flapping device. An insect wing was attached to the IPMC flapping mechanism for its flapping test. In this test, the wing flapping device using the $800{\mu}m$ thick IPMC. could create around $10^{\circ}{\sim}85^{\circ}$ flapping angles and $0.5{\sim}15Hz$ flapping frequencies by applying $3{\sim|}4V$.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1705-1711
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• 1991

On-line fault detection and diagnosis has an increasing interest in a chemical process industry, especially for a process control and automation. The chemical process needs an intelligent operation-aided workstation which can do such tasks as process monitoring, fault detection, fault diagnosis and action guidance in semiautomatic mode. These tasks can increase the performance of a process operation and give merits in economics, safety and reliability. Aiming these tasks, series of researches have been done in our lab. Main results from these researches are building appropriate knowledge representation models and a diagnosis mechanism for fault detection and diagnosis in a chemical process. The knowledge representation schemes developed in our previous research, the symptom tree model and the fault-consequence digraph, showed the effectiveness and the usefulness in a real-time application, of the process diagnosis, especially in large and complex plants. However in our previous approach, the diagnosis speed is its demerit in spite of its merits of high resolution, mainly due to using two knowledge models complementarily. In our current study, new knowledge representation scheme is developed which integrates the previous two knowledge models, the symptom tree and the fault-consequence digraph, into one. This new model is constructed using a material balance, energy balance, momentum balance and equipment constraints. Controller related constraints are included in this new model, which possesses merits of the two previous models. This new integrated model will be tested and verified by the real-time application in a BTX process or a crude unit process. The reliability and flexibility will be greatly enhanced compared to the previous model in spite of the low diagnosis speed. Nexpert Object for the expert system shell and SUN4 workstation for the hardware platform are used. TCP/IP for a communication protocol and interfacing to a dynamic simulator, SPEEDUP, for a dynamic data generation are being studied.

• The Journal of Information Systems
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• v.26 no.4
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• pp.63-85
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• 2017

Purpose Recently, much attention in building smart factory has dramatically increased with an emergence of the Industry 4.0. As we noted a connectivity gap between main concerns of MIS and the automated manufacturing systems such as POP and MES, it is recommended that CPS (Cyber-Physical System) can be an important building block for the smart factory and enrich the depth of MIS knowledge. Therefore, first, this study attempted to identify the connectivity gap between the traditional field of MIS (ERP, SCM, CRM, etc.) and the automated manufacturing systems, and then recommended CPS as a technical bridge to fill the gap. Secondly, we studied concepts and research trend of CPS that is believed to be a virtual mechanism to manage manufacturing systems in an integrated manner. Finally, we suggested research and educational opportunities in MIS based on the CPS perspectives. Design/methodology/approach Since this paper introduced relatively new idea of CPS originally discussed in the field of engineering, traditional MIS research method such as survey and experiment may not fit well. Therefore this research collected technical cases through literature survey in engineering fields, video clips from Youtube, and field references from various ICT Exhibitions and Conventions. Then we analyzed and reorganized them to highlight the necessity of CPS and draw some insight to share with MIS academia. Findings This paper introduced CPS to bridge the connectivity gap between the traditional MIS and automated manufacturing system (smart factory), a concern far away from the MIS academia. Further, this paper suggested future research subjects of MIS such as developing software to share big production data and systems to support manufacturing decisions, and innovating MIS curricula including smart and intelligent manufacturing technology within the context of traditional enterprise systems.

• International Journal of Control, Automation, and Systems
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• v.1 no.2
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• pp.194-202
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• 2003

In this paper, we introduce a category of Multi-FNN (Fuzzy-Neural Networks) models, analyze the underlying architectures and propose a comprehensive identification framework. The proposed Multi-FNNs dwell on a concept of fuzzy rule-based FNNs based on HCM clustering and evolutionary fuzzy granulation, and exploit linear inference being treated as a generic inference mechanism. By this nature, this FNN model is geared toward capturing relationships between information granules known as fuzzy sets. The form of the information granules themselves (in particular their distribution and a type of membership function) becomes an important design feature of the FNN model contributing to its structural as well as parametric optimization. The identification environment uses clustering techniques (Hard C - Means, HCM) and exploits genetic optimization as a vehicle of global optimization. The global optimization is augmented by more refined gradient-based learning mechanisms such as standard back-propagation. The HCM algorithm, whose role is to carry out preprocessing of the process data for system modeling, is utilized to determine the structure of Multi-FNNs. The detailed parameters of the Multi-FNN (such as apexes of membership functions, learning rates and momentum coefficients) are adjusted using genetic algorithms. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between approximation and generalization (predictive) abilities of the model. To evaluate the performance of the proposed model, two numeric data sets are experimented with. One is the numerical data coming from a description of a certain nonlinear function and the other is NOx emission process data from a gas turbine power plant.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.119-128
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• 2004

With the growing traffic density and increasing comfort requirements, the automation of the drive train will gain importance in vehicles. The automatic clutch actuation relieves the drivers especially in urban driving and stop-and-go traffic conditions. This paper describes the dynamic modeling of a clutch actuator and clutch spring. The dynamic model of the clutch system is developed using MATLAB/Simulink, and evaluated by experimental data using a test rig. This performance simulator is useful to develop the clutch-by-wire (CBW) system for an automated manual transmission (AMT). The electro-mechanical type CBW system is also implemented as an automatic clutch for AMT. The prototype of CBW system is designed and implemented systematically, which is composed of an electric motor, worm gear and slider-crank mechanism. The test rig is developed to perform the basic function test of the automatic clutch, and the developed prototype is validated by the experimental data on the test rig.

• Journal of Biosystems Engineering
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• v.42 no.1
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• pp.23-43
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• 2017

Purpose: As application-specific wireless sensor networks are gaining popularity, this paper discusses the development and field performance of the GHAN, a greenhouse area network system to monitor, control, and access greenhouse microenvironments. GHAN, which is an upgraded system, has many new functions. It is an intelligent wireless sensor and actuator network (WSAN) system for next-generation greenhouses, which enhances the state of the art of greenhouse automation systems and helps growers by providing them valuable information not available otherwise. Apart from providing online spatial and temporal monitoring of the greenhouse microclimate, GHAN has a modified vapor pressure deficit (VPD) fuzzy controller with an adaptive-selective mechanism that provides better control of the greenhouse crop VPD with energy optimization. Using the latest soil-matrix potential sensors, the GHAN system also ascertains when, where, and how much to irrigate and spatially manages the irrigation schedule within the greenhouse grids. Further, given the need to understand the microclimate control dynamics of a greenhouse during the crop season or a specific time, a statistical assessment tool to estimate the degree of optimality and spatial variability is proposed and implemented. Methods: Apart from the development work, the system was field-tested in a commercial greenhouse situated in the region of Punjab, India, under different outside weather conditions for a long period of time. Conclusions: Day results of the greenhouse microclimate control dynamics were recorded and analyzed, and they proved the successful operation of the system in keeping the greenhouse climate optimal and uniform most of the time, with high control performance.

• Journal of Internet Computing and Services
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• v.9 no.6
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• pp.49-62
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• 2008

AV (Atomic Vulnerability) is a conceptual definition representing a vulnerability in a systematic way, AVs are defined with respect to its type, location, and result. It is important information for meaning based vulnerability analysis method. Therefore the existing vulnerability can be expressed using multiple AVs, CVE (common vulnerability exposures) which is the most well-known vulnerability information describes the vulnerability exploiting mechanism using natural language. Therefore, for the AV-based analysis, it is necessary to search specific keyword from CVE's description and classify it using keyword and determination method. This paper introduces software design and implementation result, which can be used for atomic vulnerability analysis. The contribution of this work is in design and implementation of software which converts informal vulnerability description into formal AV based vulnerability definition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5459-5473
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• 2017

Recently, a tracking algorithm called the spatial-temporal context model has been proposed to locate a target by using the contextual information around the target. This model has achieved excellent results when the target undergoes slight occlusion and appearance changes. However, the target location in the current frame is based on the location in the previous frame, which will lead to failure in the presence of fast motion because of the lack of a prediction mechanism. In addition, the spatial context model is updated frame by frame, which will undoubtedly result in drift once the target is occluded continuously. This paper proposes two improvements to solve the above two problems: First, four possible positions of the target in the current frame are predicted based on the displacement between the previous two frames, and then, we calculate four confidence maps at these four positions; the target position is located at the position that corresponds to the maximum value. Second, we propose a target reliability criterion and design an adaptive threshold to regulate the updating speed of the model. Specifically, we stop updating the model when the reliability is lower than the threshold. Experimental results show that the proposed algorithm achieves better tracking results than traditional STC and other algorithms.

• Journal of Power Electronics
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• v.16 no.6
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• pp.2119-2128
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• 2016

Due to detection and control errors, some high-frequency harmonics with voltage-source characteristics cause circulating currents in modular inverters. Moreover, the circulating currents are usually affected by the output filters (OF) of each module due to their filter and resonance properties. The interaction among the circulating currents in the modules increase the power loss and reduce system stability and control precision. Therefore, this paper reports the results of a study on the SPWM high-frequency harmonics circulating currents for a double-module VSI. In the paper, an analysis of the circulating-current circuits is briefly described. Next, a mathematic model of the single-module output voltage based on the carrier frequency of SPWM is built. On this basis, through mathematic modeling of high-frequency harmonic circulating currents, the formation mechanism and distribution characteristics of circular currents and their influences are studied in detail. Finally, the influences of the OF on the circulating currents are studied by mainly taking an LC-type filter as an example. A theoretical analysis and experimental results demonstrate some important characteristics. First, the carrier phase shifting of the SPWM for each module is the major cause of the SPWM harmonic circulating currents, and the circulating currents are in an odd distribution around n-times the carrier frequency $n{\omega}_s$, where n = 1, 2, 3, ${\ldots}$. Second, the harmonic circular currents do not flow into the parallel system. Third, the OF can effectively suppress the non-circulating part of the high-frequency harmonic currents but is ineffective for the circulation part, and actually reduces system stability.