• Progress in Superconductivity and Cryogenics
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• v.21 no.1
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• pp.25-30
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• 2019

This paper presents a conceptual design approach of air-cored synchronous machine with high temperature superconductor (HTS) field winding. With a given configuration of a target machine, boundary conditions are set in the cylindrical coordinate system and analytic field calculation is performed by solving a governing equation. To set proper boundary conditions, current distributions of the field winding and the armature winding are expressed by the Fourier expansion. Based on analytic magnetic field calculation results, key machine parameters are calculated: 1) inductance, 2) critical current of field winding, 3) weight, 4) HTS conductor consumption, and 5) efficiency. To investigate all potential design options, 6 sweeping parameters are determined to characterize the geometry of the machine and the parameter calculation process is performed for each design options. Among design options satisfying constraints including >80 % critical current margin and >95 % efficiency, in this paper, a first-cut design was selected in terms of overall machine weight and HTS conductor consumption to obtain a lightweight and economical design. The goal is to design a 5-MW machine by referring to the same capacity machine that was previously constructed by another group. Our design output is compared with finite element method (FEM) simulation to validate our design approach.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.2
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• pp.87-96
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• 2019

Low power issue is one of the most critical problems in the Internet of Things (IoT), which are powered by battery. To solve this problem, various approaches have been presented so far. In this paper, we propose a method to reduce the power consumption by reducing the numbers of accesses into the flash memory consuming a large amount of power for on-chip software execution. Our approach is based on using cooperative logging structure to distribute the sampling overhead in single sensor node to adjacent nodes in case of rare-event applications. The proposed algorithm to identify event occurrence is newly introduced with negative feedback method by observing difference between past data and recent data coming from the sensor. When an event with need of flash access is determined, the proposed approach only allows access to write the sampled data in flash memory. The proposed event detection algorithm (EDA) result in 30% reduction of power consumption compared to the conventional flash write scheme for all cases of event. The sampled data from the sensor is first traced into the random access memory (RAM), and write access to the flash memory is delayed until the page buffer of the on-chip flash memory controller in the micro controller unit (MCU) is full of the numbers of the traced data, thereby reducing the frequency of accessing flash memory. This technique additionally reduces power consumption by 40% compared to flash-write all data. By sharing the sampling information via LoRa channel, the overhead in sampling data is distributed, to reduce the sampling load on each node, so that the 66% reduction of total power consumption is achieved in several IoT edge nodes by removing the sampling operation of duplicated data.

• Journal of Internet Computing and Services
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• v.18 no.6
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• pp.127-136
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• 2017

The strategy that using data collection from Netflix uses for its services is different from traditional human interaction and the communication, and it is represented by the systematic algorithm that rooted from intelligent information system based on the human interaction and communication. These characteristics allowed the study to reflect the influence of 'Asset specificity' which affects the continuous consumption of the media services of Netflix users through economic psychological analysis based on transactional cost economics. The result from the survey on actual Netflix users, three types of specificity (Space specificity, time specificity, relational specificity) reduced perceived searching cost whereas perceived instrumentality has increased, eventually reinforces the commitment to the service. This implies that the service characteristics of Netflix, trying to communicate with the individuals based on intelligent information system are distinct from the existing platform services and it gives the significance of work very effective for user's continuous consumption of the media services.

• Journal of Construction Engineering and Project Management
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• v.3 no.1
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• pp.14-21
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• 2013

To analyze building energy consumption, the building description for building energy performance analysis (BEPA) is required. The required data input for subject building is a basic step in the BEPA process. Since building information modeling (BIM) is applied in the construction industry, the required data for BEPA can be gathered from a single international standard file format like IFCXML. However, in most BEPA processes, since the required data cannot be fully used from the IFCXML file, a building description for BEPA must be created again. This paper proposes IFCXML-based automatic data input approach for BEA. After the required data for BEPA has been defined, automatic data input for BEPA is developed by a prototype system. To evaluate the proposed system, a common BIM file from the BuildingSMART website is applied as a sample model. This system can increase the efficiency and reliability of the BEPA process, since the data input is automatically and efficiently improved by directly using the IFCXML file..

• International conference on construction engineering and project management
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• 2013.01a
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• pp.173-180
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• 2013

To analyze building energy consumption, the building description for building energy performance analysis (BEPA) is required. The required data input for subject building is a basic step in the BEPA process. Since building information modeling (BIM) is applied in the construction industry, the required data for BEPA can be gathered from a single international standard file format like IFCXML. However, in most BEPA processes, since the required data cannot be fully used from the IFCXML file, a building description for BEPA must be created again. This paper proposes IFCXML-based automatic data input approach for BEA. After the required data for BEPA has been defined, automatic data input for BEPA is developed by a prototype system. To evaluate the proposed system, a common BIM file from the BuildingSMART website is applied as a sample model. This system can increase the efficiency and reliability of the BEPA process, since the data input is automatically and efficiently improved by directly using the IFCXML file.

• Korean System Dynamics Review
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• v.10 no.3
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• pp.105-124
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• 2009

The situation of the global food markets has been being rapidly restructured and entering on a new phase by new dynamic and driving forces. The factors such as economic growth and income increase, high energy price, globalization, urbanization, and global climate change are transforming patterns of food consumption, production, and markets. The prices and markets of world food and energy are getting increasingly linked each other. Food and fuel are the global dilemma issues associated with the risk of diverting farmland or of consuming cereals for biofuel production in detriment of the cereals supply to the global food markets. An estimated 100 million tons of grain per year are being redirected from food to fuel. Therefore, the objectives of this study are as follows: Firstly, the study examines situations of the world food and energy resources, analyzes the trends of prices of the crude oil and biofuel, and formulates the food-energy links mechanism. Secondly, the study builds a simulation model, based on system dynamics approach, for not only analyzing the global cereals market and energy market but also forecasting the global production, consumption, and stock of those markets by 2030 in the future. The model of this study consists of four sectors, i.e., world population dynamics sector, global food market dynamics sector, global energy market dynamics sector, scenario sector of world economic growth and oil price.

• The Research Journal of the Costume Culture
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• v.29 no.4
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• pp.538-553
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• 2021

As interest in the sustainable fashion industry continues to increase along with climate issues, it is necessary to identify research trends in sustainable fashion and seek new development directions. Therefore, this study aims to analyze research trends on sustainable fashion. For this purpose, related papers were collected from the KCI (Korean Citation Index) and Scopus, and 340 articles were used for the study. The collected data went through data transformation, data preprocessing, topic modeling analysis, core topic derivation, and visualization through a Python algorithm. A total of eight topics were obtained from the comprehensive analysis: consumer clothing consumption behavior and environment, upcycle product development, product types by environmental approach, ESG business activities, materials and material development, process-based approach, lifestyle and consumer experience, and brand strategy. Topics were related to consumption, production, and education of sustainable fashion, respectively. KCI analysis results and Scopus analysis results derived eight topics but showed differences from the comprehensive analysis results. This study provides primary data for exploring various themes of sustainable fashion. It is significant in that the data were analyzed based on probability using a research method that excluded the subjective value of the researcher. It is recommended that follow-up studies be conducted to examine social trends.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.2
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• pp.107-114
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• 2024

Mobile ad hoc networks represent self-configuring networks of mobile devices that communicate without relying on a fixed infrastructure. However, traditional routing protocols in such networks encounter challenges in selecting efficient and reliable routes due to dynamic nature of these networks caused by unpredictable mobility of nodes. This often results in a failure to meet the low-delay and low-energy consumption requirements crucial for such networks. In order to overcome such challenges, our paper introduces a novel multi-objective and adaptive routing scheme based on the Q-learning reinforcement learning algorithm. The proposed routing scheme dynamically adjusts itself based on measured network states, such as traffic congestion and mobility. The proposed approach utilizes Q-learning to select routes in a decentralized manner, considering factors like energy consumption, load balancing, and the selection of stable links. We present a formulation of the multi-objective optimization problem and discuss adaptive adjustments of the Q-learning parameters to handle the dynamic nature of the network. To speed up the learning process, our scheme incorporates informative shaped rewards, providing additional guidance to the learning agents for better solutions. Implemented on the widely-used AODV routing protocol, our proposed approaches demonstrate better performance in terms of energy efficiency and improved message delivery delay, even in highly dynamic network environments, when compared to the traditional AODV. These findings show the potential of leveraging reinforcement learning for efficient routing in ad hoc networks, making the way for future advancements in the field of mobile ad hoc networking.

• The Journal of Industrial Distribution & Business
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• v.12 no.6
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• pp.75-88
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• 2021

Purpose: This research aimed at exploring the functions of consumers' perceiving approach and avoidance roles and their feeling anger and disgust in the effect of the two types of self-discrepancy at social identity such as the ideal self-discrepancy and the ought self-discrepancy on within-self domain versus across-self domain consumption. Research design, data, and methodology - This study divided the self-discrepancy group into the ideal self-discrepancy and the ought self-discrepancy group as experimental groups for empirical study. Self-discrepancy type between-subjects design was used to develop two types of questionnaire according to the type of experimental groups. The platform, 'questionnaire stars' of 'WeChat' in China was used to collect 103 data from the ideal self-discrepancy group and 102 from the ought self-discrepancy group for empirical study. T-test and the structural equation model in Amos 21 were used to verify hypotheses developed through theoretical review. Results - First, ideal self-discrepancy positively affected the role-approaching goal and anger. Second, ought self-discrepancy positively affected the role-avoiding goal and disgust. Third, the role-approaching goal and anger positively influenced on the within- versus across- domain consumption. Fourth, the disgust negatively influenced on the within- versus across- domain consumption, however the role-avoiding goal did not influence on the consumption. Fifth, there was the mediation roles of anger (disgust) in the effects of ideal (ought) self-discrepancy on the consumption. Conclusions - When consumers feel anger at the ideal self- discrepancy induced by in-group, it is necessary for the marketers to promote their product brand used by the in-group. They should develop and advertise the messages priming the ideal self-discrepancy and the anger to increase the intent to purchase or use their product brand when the in-group members have used the brand by relating the brand to their social identity concerned with the ideal self-discrepancy. However, marketers should help consumers feel disgust by developing and advertising the messages expressing the ought self-discrepancy to lead the consumers to the place of purchasing or using their product brand when the members have used the brand based on keeping the consistence between the brand and other social identity not related to the ought self-discrepancy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.4
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• pp.1692-1711
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• 2016

Energy is a scarce resource in wireless sensor networks (WSNs). A variety of clustering protocols for WSNs, such as the zone-based stable election protocol-enhanced (ZSEP-E), have been developed for energy optimization. The ZSEP-E is a heterogeneous zone-based clustering protocol that focuses on unbalanced energy consumption with parallel formation of clusters in zones and election of cluster heads (CHs). Most ZSEP-E research has assumed probabilistic election of CHs in the zones by considering the maximum residual energy of nodes. However, studies of the diverse CH election parameters are lacking. We investigated the performance of the ZSEP-E in such scenarios using a fuzzy logic approach based on three descriptors, i.e., energy, density, and the distance from the node to the base station. We proposed an efficient ZSEP-E scheme to adapt and elect CHs in zones using fuzzy variables and evaluated its performance for different energy levels in the zones.