• Journal of Korea Multimedia Society
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• v.11 no.7
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• pp.1007-1015
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• 2008

In order to provide real-time data from sensors and instruments at manufacturing processes on web, we proposed a communication service model based on XML(eXtensible Markup Language). HTML(Hyper Text Markup Language) is inadequate for describing real-time data from manufacturing plants while it is suitable for display of non-real-time multimedia data on web. For applying XML-based web service of process data in Intranet environment, real-time performance of communication services was evaluated to provide the system design criteria. XML schema for the data presentation was proposed and its communication performance was evaluated by simulation in terms of transmission delay due to increased message length and processing delay for transformation of raw data into defined format. For transformation of raw data into XML format, we proposed two structures: one is the scheme where transformation is done at an SCC(Supervisory Control Computer) after receiving real-time data from instruments. the other is the scheme where transformation is carried out at instruments before the data are transmitted to the SCC. Performances of two structures were evaluated on a testbed under various conditions such as six packet sizes and offered loads of 20%, 50% and 80%, respectively. Test results show that proposed schemes are applicable to the systems in Ethernet 100BaseT network if total message traffic is less than 7 Mbps.

• Clean Technology
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• v.28 no.1
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• pp.79-93
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• 2022

In this study, an electronics industrial wastewater activated sludge model (e-ASM) to be used as a Water Digital Twin was calibrated based on real high-tech electronics industrial wastewater treatment measurements from lab-scale and pilot-scale reactors, and examined for its treatment performance, effluent quality prediction, and optimal process selection. For specialized modeling of a high-tech electronics industrial wastewater treatment system, the kinetic parameters of the e-ASM were identified by a sensitivity analysis and calibrated by the multiple response surface method (MRS). The calibrated e-ASM showed a high compatibility of more than 90% with the experimental data from the lab-scale and pilot-scale processes. Four electronics industrial wastewater treatment processes-MLE, A2/O, 4-stage MLE-MBR, and Bardenpo-MBR-were implemented with the proposed Water Digital Twin to compare their removal efficiencies according to various electronics industrial wastewater characteristics. Bardenpo-MBR stably removed more than 90% of the chemical oxygen demand (COD) and showed the highest nitrogen removal efficiency. Furthermore, a high concentration of 1,800 mg L^-1 T MAH influent could be 98% removed when the HRT of the Bardenpho-MBR process was more than 3 days. Hence, it is expected that the e-ASM in this study can be used as a Water Digital Twin platform with high compatibility in a variety of situations, including plant optimization, Water AI, and the selection of best available technology (BAT) for a sustainable high-tech electronics industry.

• Asia pacific journal of information systems
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• v.22 no.1
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• pp.29-52
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• 2012

Consumers differ in the way they make a purchase. An audio mania would willingly make a bold, yet serious, decision to buy a top-of-the-line home theater system, while he is not interested in replacing his two-decade-old shabby car. On the contrary, an automobile enthusiast wouldn't mind spending forty thousand dollars to buy a new Jaguar convertible, yet cares little about his junky component system. It is product involvement that helps us explain such differences among individuals in the purchase style. Product involvement refers to the extent to which a product is perceived to be important to a consumer (Zaichkowsky, 2001). Product involvement is an important factor that strongly influences consumer's purchase decision-making process, and thus has been of prime interest to consumer behavior researchers. Furthermore, researchers found that involvement is closely related to perceived risk (Dholakia, 2001). While abundant research exists addressing how product involvement relates to overall perceived risk, little attention has been paid to the relationship between involvement and different types of perceived risk in an electronic commerce setting. Given that perceived risk can be a substantial barrier to the online purchase (Jarvenpaa, 2000), research addressing such an issue will offer useful implications on what specific types of perceived risk an online firm should focus on mitigating if it is to increase sales to a fullest potential. Meanwhile, past research has focused on such consumer responses as information search and dissemination as a consequence of involvement, neglecting other behavioral responses like online merchant selection. For one example, will a consumer seriously considering the purchase of a pricey Guzzi bag perceive a great degree of risk associated with online buying and therefore choose to buy it from a digital storefront rather than from an online marketplace to mitigate risk? Will a consumer require greater trust on the part of the online merchant when the perceived risk of online buying is rather high? We intend to find answers to these research questions through an empirical study. This paper explores the impact of enduring product involvement and perceived risks on required trust level, and further on online merchant choice. For the purpose of the research, five types or components of perceived risk are taken into consideration, including financial, performance, delivery, psychological, and social risks. A research model has been built around the constructs under consideration, and 12 hypotheses have been developed based on the research model to examine the relationships between enduring involvement and five components of perceived risk, between five components of perceived risk and required trust level, between enduring involvement and required trust level, and finally between required trust level and preference toward an e-tailer. To attain our research objectives, we conducted an empirical analysis consisting of two phases of data collection: a pilot test and main survey. The pilot test was conducted using 25 college students to ensure that the questionnaire items are clear and straightforward. Then the main survey was conducted using 295 college students at a major university for nine days between December 13, 2010 and December 21, 2010. The measures employed to test the model included eight constructs: (1) enduring involvement, (2) financial risk, (3) performance risk, (4) delivery risk, (5) psychological risk, (6) social risk, (7) required trust level, (8) preference toward an e-tailer. The statistical package, SPSS 17.0, was used to test the internal consistency among the items within the individual measures. Based on the Cronbach's ${\alpha}$ coefficients of the individual measure, the reliability of all the variables is supported. Meanwhile, the Amos 18.0 package was employed to perform a confirmatory factor analysis designed to assess the unidimensionality of the measures. The goodness of fit for the measurement model was satisfied. Unidimensionality was tested using convergent, discriminant, and nomological validity. The statistical evidences proved that the three types of validity were all satisfied. Now the structured equation modeling technique was used to analyze the individual paths along the relationships among the research constructs. The results indicated that enduring involvement has significant positive relationships with all the five components of perceived risk, while only performance risk is significantly related to trust level required by consumers for purchase. It can be inferred from the findings that product performance problems are mostly likely to occur when a merchant behaves in an opportunistic manner. Positive relationships were also found between involvement and required trust level and between required trust level and online merchant choice. Enduring involvement is concerned with the pleasure a consumer derives from a product class and/or with the desire for knowledge for the product class, and thus is likely to motivate the consumer to look for ways of mitigating perceived risk by requiring a higher level of trust on the part of the online merchant. Likewise, a consumer requiring a high level of trust on the merchant will choose a digital storefront rather than an e-marketplace, since a digital storefront is believed to be trustworthier than an e-marketplace, as it fulfills orders by itself rather than acting as an intermediary. The findings of the present research provide both academic and practical implications. The first academic implication is that enduring product involvement is a strong motivator of consumer responses, especially the selection of a merchant, in the context of electronic shopping. Secondly, academicians are advised to pay attention to the finding that an individual component or type of perceived risk can be used as an important research construct, since it would allow one to pinpoint the specific types of risk that are influenced by antecedents or that influence consequents. Meanwhile, our research provides implications useful for online merchants (both online storefronts and e-marketplaces). Merchants may develop strategies to attract consumers by managing perceived performance risk involved in purchase decisions, since it was found to have significant positive relationship with the level of trust required by a consumer on the part of the merchant. One way to manage performance risk would be to thoroughly examine the product before shipping to ensure that it has no deficiencies or flaws. Secondly, digital storefronts are advised to focus on symbolic goods (e.g., cars, cell phones, fashion outfits, and handbags) in which consumers are relatively more involved than others, whereas e- marketplaces should put their emphasis on non-symbolic goods (e.g., drinks, books, MP3 players, and bike accessories).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.19-38
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• 2017

Collaborative filtering (CF) algorithm has been popularly used for implementing recommender systems. Until now, there have been many prior studies to improve the accuracy of CF. Among them, some recent studies adopt 'hybrid recommendation approach', which enhances the performance of conventional CF by using additional information. In this research, we propose a new hybrid recommender system which fuses CF and the results from the social network analysis on trust and distrust relationship networks among users to enhance prediction accuracy. The proposed algorithm of our study is based on memory-based CF. But, when calculating the similarity between users in CF, our proposed algorithm considers not only the correlation of the users' numeric rating patterns, but also the users' in-degree centrality values derived from trust and distrust relationship networks. In specific, it is designed to amplify the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the trust relationship network. Also, it attenuates the similarity between a target user and his or her neighbor when the neighbor has higher in-degree centrality in the distrust relationship network. Our proposed algorithm considers four (4) types of user relationships - direct trust, indirect trust, direct distrust, and indirect distrust - in total. And, it uses four adjusting coefficients, which adjusts the level of amplification / attenuation for in-degree centrality values derived from direct / indirect trust and distrust relationship networks. To determine optimal adjusting coefficients, genetic algorithms (GA) has been adopted. Under this background, we named our proposed algorithm as SNACF-GA (Social Network Analysis - based CF using GA). To validate the performance of the SNACF-GA, we used a real-world data set which is called 'Extended Epinions dataset' provided by 'trustlet.org'. It is the data set contains user responses (rating scores and reviews) after purchasing specific items (e.g. car, movie, music, book) as well as trust / distrust relationship information indicating whom to trust or distrust between users. The experimental system was basically developed using Microsoft Visual Basic for Applications (VBA), but we also used UCINET 6 for calculating the in-degree centrality of trust / distrust relationship networks. In addition, we used Palisade Software's Evolver, which is a commercial software implements genetic algorithm. To examine the effectiveness of our proposed system more precisely, we adopted two comparison models. The first comparison model is conventional CF. It only uses users' explicit numeric ratings when calculating the similarities between users. That is, it does not consider trust / distrust relationship between users at all. The second comparison model is SNACF (Social Network Analysis - based CF). SNACF differs from the proposed algorithm SNACF-GA in that it considers only direct trust / distrust relationships. It also does not use GA optimization. The performances of the proposed algorithm and comparison models were evaluated by using average MAE (mean absolute error). Experimental result showed that the optimal adjusting coefficients for direct trust, indirect trust, direct distrust, indirect distrust were 0, 1.4287, 1.5, 0.4615 each. This implies that distrust relationships between users are more important than trust ones in recommender systems. From the perspective of recommendation accuracy, SNACF-GA (Avg. MAE = 0.111943), the proposed algorithm which reflects both direct and indirect trust / distrust relationships information, was found to greatly outperform a conventional CF (Avg. MAE = 0.112638). Also, the algorithm showed better recommendation accuracy than the SNACF (Avg. MAE = 0.112209). To confirm whether these differences are statistically significant or not, we applied paired samples t-test. The results from the paired samples t-test presented that the difference between SNACF-GA and conventional CF was statistical significant at the 1% significance level, and the difference between SNACF-GA and SNACF was statistical significant at the 5%. Our study found that the trust/distrust relationship can be important information for improving performance of recommendation algorithms. Especially, distrust relationship information was found to have a greater impact on the performance improvement of CF. This implies that we need to have more attention on distrust (negative) relationships rather than trust (positive) ones when tracking and managing social relationships between users.

• The Journal of Society for e-Business Studies
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• v.23 no.2
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• pp.1-20
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• 2018

Car Sharing Service is provided with sharing the vehicleas you can use it anywhere and anytime. The paper verified the factors impact between providing infrastructure characteristics such as scarcity, system quality and service quality and user evaluation factors based on DeLone & McLean IS Success Model. User evaluation factors have an influence on net benefit. D&M IS model mainly proved inner organization impact. The research collected experienced car sharing service, we analyzed the 224 respondents. The result of the hypothesis follows. The scarcity of time is negatively related to perceived social support and app trust. Provisional coupon is positively related to perceived social support and app trust. But, scarcity of quantity is not related to user evaluation factors. Most of the system qualities are related to app trust, however, privacy concern isn't related to app trust. the paper's demographic characteristic is lack of experience frequency. User evaluation factors that are perceived social support and app trust are positively related to user satisfaction and WoM intention. User satisfaction is individual impact and WoM intention is organization impact. Two factors are the net benefit in car sharing service. The area of sharing economy should more study about correlation among experimental various factors. Thus, the paper has different significant from antecedent research. because of trying to experimental analysis.

• The Journal of Information Systems
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• v.26 no.4
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• pp.379-400
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• 2017

Purpose The purpose of this study is to investigate the effects of ICT on multilevel marketing organizations (MLMs) whose members are both salespeople and consumers. This study explores the effects of the latest ICT convergence on the direct selling, which is the oldest sales method, and suggests the direction for the development of network marketing. Therefore, we will propose the changes in direct sales brought by ICT and predict the future direction of network marketing in preparation for the 4th Industrial Revolution era. Design/methodology/approach Exploratory case study was the methodology selected for this paper. The case study enables the use of multiple methods for data collection and analysis. This study applies qualitative case-study methodology on Amway Korea, which is the top seller of MLM organizations, to better understand the impact of ICT. This study conducted an in-depth interview with four different levels of MLM members (e.g. membership, ruby, emerald, diamond) which are based on the qualification system of MLM organizations and observed their behaviors. Findings This study revealed that the ICT impact on network marketing organizations(MLMs) could be summarized as follows : new membership growth, easier communication with customers, increase in work efficiency, increase in organizational trust, change in educational environment, and increase in the use of social media. Based on the interview, we propose the changes of network marketing organizations in the fourth industrial revolution era and the future strategy of Amway Korea as follows: (1) retention of royal ABOs, (2) harmony with SMEs, (3) utilization of Big Data, (4) creation of IoT business model, and (5) construction of successful O2O business platform.

• Journal of the Korean Chemical Society
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• v.63 no.2
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• pp.73-77
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• 2019

We compared methodologies based on the density functional theory (DFT), e.g., time-dependent DFT (TD-DFT), TD-DFT within Tamm-Dancoff approximation (TDA-DFT), and spin-unrestricted DFT (UDFT), that are usually employed to optimize the geometries of ${\pi}$-conjugated molecules in their lowest lying triplet excited ($T_1$) state. As a model system for ${\pi}$-conjugated molecules, we employed 1,2,3,4,5-pentacyano-6-phenyl-benzene. In conjunction with 6-31G(d) basis sets, we made use of gap-tuned range-separated ${\omega}B97X$ functional which is often employed recently in the calculations of molecular excited states. Near the equilibrium geometries, we found that the important difference between the geometries derived at UDFT level and those at TD-DFT or TDA-DFT methods: more stable ground-state energies but higher triplet excitation energies for UDFT derived geometries. In the studies, we discuss such differences in more detail.

• Korean Journal of Radiology
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• v.24 no.7
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• pp.647-659
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• 2023

Objective: The study was conducted to investigate the effect of correct occlusion of the left atrial appendage (LAA) on intracardiac blood flow and thrombus formation in patients with atrial fibrillation (AF) using four-dimensional (4D) flow magnetic resonance imaging (MRI) and three-dimensional (3D)-printed phantoms. Materials and Methods: Three life-sized 3D-printed left atrium (LA) phantoms, including a pre-occlusion (i.e., before the occlusion procedure) model and correctly and incorrectly occluded post-procedural models, were constructed based on cardiac computed tomography images from an 86-year-old male with long-standing persistent AF. A custom-made closed-loop flow circuit was set up, and pulsatile simulated pulmonary venous flow was delivered by a pump. 4D flow MRI was performed using a 3T scanner, and the images were analyzed using MATLAB-based software (R2020b; Mathworks). Flow metrics associated with blood stasis and thrombogenicity, such as the volume of stasis defined by the velocity threshold ($\left|\vec{V}\right|$ < 3 cm/s), surface-and-time-averaged wall shear stress (WSS), and endothelial cell activation potential (ECAP), were analyzed and compared among the three LA phantom models. Results: Different spatial distributions, orientations, and magnitudes of LA flow were directly visualized within the three LA phantoms using 4D flow MRI. The time-averaged volume and its ratio to the corresponding entire volume of LA flow stasis were consistently reduced in the correctly occluded model (70.82 mL and 39.0%, respectively), followed by the incorrectly occluded (73.17 mL and 39.0%, respectively) and pre-occlusion (79.11 mL and 39.7%, respectively) models. The surfaceand-time-averaged WSS and ECAP were also lowest in the correctly occluded model (0.048 Pa and 4.004 Pa^-1, respectively), followed by the incorrectly occluded (0.059 Pa and 4.792 Pa^-1, respectively) and pre-occlusion (0.072 Pa and 5.861 Pa^-1, respectively) models. Conclusion: These findings suggest that a correctly occluded LAA leads to the greatest reduction in LA flow stasis and thrombogenicity, presenting a tentative procedural goal to maximize clinical benefits in patients with AF.

• Journal of Society of Preventive Korean Medicine
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• v.4 no.1
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• pp.32-50
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• 2000

On the process of research in the plan on oriental medical participation in the industrial health sponsored by BK21 project, we carried out the oriental medical health examination program for workers during former half-year We reached the conclusion as follows, 1. The oriental medical health examination program is contents and formalities that should be determined by present industrial health system, based on the oriental medical system and scholastic character, and included probability of the western and oriental medical cooperation. 2. The oriental medical health examination program can promote capability of individual health management and productive power of workers, and it is capable to manage on the self-conscious symptoms and macroschophically approach to their environment 3. The oriental medical health examination program that we have developed, is flow as questionare, understanding of working environment, information of result and later management. It is composed of three fields as follow , first, use of pulse diagnostic apparatus, understanding of the health promotion life style, and diagnosis of the oriental medical doctor, second, analysis of constitution, third, photographing for understanding of the musculoskeletal disorders, questionare for musculoskeletal self-conscious symptoms, and diagnosis of oriental medical doctor. 4. The oriental medical health examination program that we have developed, progressive from the view point of health, makes the oriental medical doctor's roll more important. It is the first trial at the western and oriental medical cooperation and characterized by excellence about musouloskeletal disorders. But it need to be improved in aspects of time and specialist on the health examination, diagnostic apparatus, control of examinant and later management. So we think that it needs research on the employment of health examination specialist, establishment of later management system, development of significantly diagnosable standard and assessable form on the health examination, and contents of health examination on the western and oriental medical cooperation.