• Convergence Security Journal
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• v.22 no.5
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• pp.135-143
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• 2022

The defense environment is rapidly changing, such as nuclear and missile threats of North Korea, changes in war patterns, and a decrease in military service resources due to low birth rate. In order to actively respond to these changes, the Korean military is promoting Defense Innovation 4.0 and is trying to foster an army armed with high technology such as artificial intelligence (AI), big data analysis, etc. In this regard, we analyze the effectiveness of the radar-based AI scientific guard system applied by high technology for guard operations using Analytic Hierarchy Process (AHP). We first select evaluation factors that can assess the effectiveness of the scientific guard system, and analyze its relative importance. Each evaluation factor was selected by deriving a significant concept from operating principle and how they work, and by consulting experts on the correlation between each factor and effectiveness of the scientific guard system. We examine the relative effects of the radar-based AI scientific guard system and existing scientific guard system based on the importance of the evaluation factors.

• Advances in nano research
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• v.15 no.4
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• pp.355-366
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• 2023

Biological corrosion, a crucial aspect of metal degradation, has received limited attention despite its significance. It involves the deterioration of metals due to corrosion processes influenced by living organisms, including bacteria. Soil represents a substantial threat to pipeline corrosion as it contains chemical and microbial factors that cause severe damage to water, oil, and gas transmission projects. To combat fouling and corrosion, corrosion inhibitors are commonly used; however, their production often involves expensive and hazardous chemicals. Consequently, researchers are exploring natural and eco-friendly alternatives, specifically nano-sized products, as potent corrosion inhibitors. This study aims to environmentally synthesize silver nanoparticles using an extract from Lagoecia cuminoides L and evaluate their effectiveness in preventing biological corrosion of buried pipes in soil. The optimal experimental conditions were determined as follows: a volume of 4 ml for the extract, a volume of 4 ml for silver nitrate (AgNO3), pH 9, a duration of 60 minutes, and a temperature of 60 degrees Celsius. Analysis using transmission electron microscopy confirmed the formation of nanoparticles with an average size of approximately 28 nm, while X-ray diffraction patterns exhibited suitable peak intensities. By employing the Scherer equation, the average particle size was estimated to be around 30 nm. Furthermore, antibacterial studies revealed the potent antibacterial activity of the synthesized silver nanoparticles against both aerobic and anaerobic bacteria. This property effectively mitigates the biological corrosion caused by bacteria in steel pipes buried in soil.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.185-192
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• 2024

The aviation has improved safety through technological innovation and strengthened flight safety through safety regulations and supervision by aviation authorities. As the industry's safety approach has evolved into a systematic approach to the aircraft system, airlines have established a safety management system. Technical defects or abnormal data in an aircraft can be warning signs that could lead to an accident, and the risk of an accident can be reduced by identifying and responding to these signs early. Therefore, management of abnormal warning signs is an essential element in promoting data-based decision-making and enhancing the operational efficiency and safety level of airlines. In this study, we present a model to statistically analyze quick access recorder (QAR) flight data in the preliminary analysis stage to analyze the patterns and causes of crab landing events that can lead to runway departures when landing an aircraft, and provide a precursor to a landing event. We aim to identify signs and causes and contribute to increasing the efficiency of safety management.

• Journal of Veterinary Science
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• v.25 no.5
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• pp.63.1-63.12
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• 2024

Importance: Glutamic acid decarboxylase 67 (GAD67) is a gamma-aminobutyric acid (GABA) synthesis enzyme associated with the function of other neurotransmitter receptors, such as the N-methyl-D-aspartate (NMDA) receptor and cannabinoid receptor 1. However, the role of GAD67 in the development of different abused drug-induced reward behaviors remains unknown. In order to elucidate the mechanisms of substance use disorder, it is crucial to study changes in biomarkers within the brain's reward circuit induced by drug use. Objective: The study was designed to examine the effects of the downregulation of GAD67 expression in the dorsal striatum on reward behavior development. Methods: We evaluated the effects of GAD67 knockdown on depression-like behavior and anxiety using the forced swim test and elevated plus maze test in a mouse model. We further determined the effects of GAD67 knockdown on ketamine- and JWH-018-induced conditioned place preference (CPP). Results: Knockdown of GAD67 in the dorsal striatum of mice increased depression-like behavior, but it decreased anxiety. Moreover, the CPP score on the NMDA receptor antagonist ketamine was increased by GAD67 knockdown, whereas the administration of JWH-018, a cannabinoid receptor agonist, did not affect the CPP score in the GAD67 knockdown mice group compared with the control group. Conclusions and Relevance: These results suggest that striatal GAD67 reduces GABAergic neuronal activity and may cause ketamine-induced NMDA receptor inhibition. Consequently, GAD67 downregulation induces vulnerability to the drug reward behavior of ketamine.

• Journal of Service Research and Studies
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• v.13 no.2
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• pp.146-160
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• 2023

The spread of non-face-to-face services due to the COVID-19 pandemic has brought many changes in consumers' purchasing behavior and attracted much attention to new services. Could trying new services caused by this sudden environmental change alter consumers's choice patterns? This study proposes the research question of whether these new service experiences can change consumers' existing choice behavior, especially for risk-averse consumers who maintain their existing choice behavior or prefer safe alternatives. In this study, we examined whether trying out an unmanned payment services, one of innovative services that emerged after the pandemic crisis, can change the existing choice behavior of risk-averse consumers, i.e., make them more likely to prefer risky alternatives to safe alternatives. To accomplish these research goals, this research conducted one pilot survey and one study. The results of pilot survey showed that the stronger the prevention-focus tendency, the lower the self-efficacy to use the innovative service, with a negative relationship between them. Based on these findings, the study used an experimental method to examine the interaction effects between the use of innovation services and consumers' regulatory focus in a choice behavior and to explore the psychological mechanisms behind them. According to the results, it is found that prevention-focused consumers were more likely to choose risky alternatives and dissimilar extended brands following a trial of an unmanned payment service compared to not using that service. In contrast, promotion-focused consumers did not show different choice patterns regardless of following a trial of an innovative service. Furthermore, these results for prevention-focused consumers confirm the role of self-efficacy as a psychological mechanism. These findings shed light on the role of self-efficacy which has discussed in positive psychology into marketing area. Moreover, practical and academic implications are suggested by the finding that behavioral change occurs in risk-averse consumers, who are known to be hesitant to try new behaviors, indicating market expansion related to potential consumers for the use of the innovation services.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.1
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• pp.71-94
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• 2020

Korea's innovation cluster policy has been implemented since 2005 with the goal of balanced regional development. The purpose of this study is to investigate the factors affecting the sustainability of innovative cluster tenants by using Pangyo Techno Valley as an example. Pangyo Techno Valley was established under the leadership of the local government (Gyeonggi-do) rather than the central government and it is called "Silicon Valley of Korea" and "Asia Silicon Valley" and is becoming more representative. The growing number of companies in Pangyo Techno Valley decreased in 2017 compared to 2016. This is because Pangyo Techno Valley's business ecosystem will change from 2019. In this paper, quantitative and qualitative studies were conducted to investigate the influencing factors. Quantitative research was conducted based on the survey and qualitative research was applied through interviews. The quantitative research examined the factors affecting the sustainability of Pangyo Techno Valley, and the qualitative research examined the specific reasons and additional factors for the quantitative research results. The quantitative results showed that factors affecting sustainability in terms of changes in corporate internal conditions, human and physical infrastructure, cooperation and synergy, and occupancy patterns. The specific reason for the impact appeared in the qualitative research process. The support category of local governments did not show any significant factors in quantitative research. In addition, qualitative research suggested 'Good image of Pangyo Techno Valley' as the category that has the greatest impact on sustainability. It is shown that companies are passive and expect the role of local governments in activating cooperation network in Pangyo Techno Valley. In this paper, based on the results of the study, Pangyo Techno Valley is presented with a realistic plan based on real estate issues and an ideal plan with a long-term perspective.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.101-123
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• 2013

Recently due to the advancements of science and information technology, the socio-economic business areas are changing from the industrial economy to a knowledge economy. Furthermore, companies need to do creation of new value through continuous innovation, development of core competencies and technologies, and technological convergence. Therefore, the identification of major trends in technology research and the interdisciplinary knowledge-based prediction of integrated technologies and promising techniques are required for firms to gain and sustain competitive advantage and future growth engines. The aim of this paper is to understand the recent research trend in management of technology (MOT) and to foresee promising technologies with deep knowledge for both technology and business. Furthermore, this study intends to give a clear way to find new technical value for constant innovation and to capture core technology and technology convergence. Bibliometrics is a metrical analysis to understand literature's characteristics. Traditional bibliometrics has its limitation not to understand relationship between trend in technology management and technology itself, since it focuses on quantitative indices such as quotation frequency. To overcome this issue, the network focused bibliometrics has been used instead of traditional one. The network focused bibliometrics mainly uses "Co-citation" and "Co-word" analysis. In this study, a keywords network analysis, one of social network analysis, is performed to analyze recent research trend in MOT. For the analysis, we collected keywords from research papers published in international journals related MOT between 2002 and 2011, constructed a keyword network, and then conducted the keywords network analysis. Over the past 40 years, the studies in social network have attempted to understand the social interactions through the network structure represented by connection patterns. In other words, social network analysis has been used to explain the structures and behaviors of various social formations such as teams, organizations, and industries. In general, the social network analysis uses data as a form of matrix. In our context, the matrix depicts the relations between rows as papers and columns as keywords, where the relations are represented as binary. Even though there are no direct relations between papers who have been published, the relations between papers can be derived artificially as in the paper-keyword matrix, in which each cell has 1 for including or 0 for not including. For example, a keywords network can be configured in a way to connect the papers which have included one or more same keywords. After constructing a keywords network, we analyzed frequency of keywords, structural characteristics of keywords network, preferential attachment and growth of new keywords, component, and centrality. The results of this study are as follows. First, a paper has 4.574 keywords on the average. 90% of keywords were used three or less times for past 10 years and about 75% of keywords appeared only one time. Second, the keyword network in MOT is a small world network and a scale free network in which a small number of keywords have a tendency to become a monopoly. Third, the gap between the rich (with more edges) and the poor (with fewer edges) in the network is getting bigger as time goes on. Fourth, most of newly entering keywords become poor nodes within about 2~3 years. Finally, keywords with high degree centrality, betweenness centrality, and closeness centrality are "Innovation," "R&D," "Patent," "Forecast," "Technology transfer," "Technology," and "SME". The results of analysis will help researchers identify major trends in MOT research and then seek a new research topic. We hope that the result of the analysis will help researchers of MOT identify major trends in technology research, and utilize as useful reference information when they seek consilience with other fields of study and select a new research topic.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.73-97
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• 2007

R&D into future technologies should be conducted in conjunction with technological innovation strategies that are linked to corporate survival within a framework of information and knowledge-based competitiveness. As such, future technology strategies should be ensured through open R&D organizations. The development of future technologies should not be conducted simply on the basis of future forecasts, but should take into account customer needs in advance and reflect them in the development of the future technologies or services. This research aims to select as segmentation variables the customers' attitude towards accepting future telecommunication technologies and their value orientation in their everyday life, as these factors wilt have the greatest effect on the demand for future telecommunication services and thus segment the future telecom service market. Likewise, such research seeks to segment the market from the stage of technology R&D activities and employ the results to formulate technology development strategies. Based on the customer attitude towards accepting new technologies, two groups were induced, and a hierarchical customer segmentation model was provided to conduct secondary segmentation of the two groups on the basis of their respective customer value orientation. A survey was conducted in June 2006 on 800 consumers aged 15 to 69, residing in Seoul and five other major South Korean cities, through one-on-one interviews. The samples were divided into two sub-groups according to their level of acceptance of new technology; a sub-group demonstrating a high level of technology acceptance (39.4%) and another sub-group with a comparatively lower level of technology acceptance (60.6%). These two sub-groups were further divided each into 5 smaller sub-groups (10 total smaller sub-groups) through two rounds of segmentation. The ten sub-groups were then analyzed in their detailed characteristics, including general demographic characteristics, usage patterns in existing telecom services such as mobile service, broadband internet and wireless internet and the status of ownership of a computing or information device and the desire or intention to purchase one. Through these steps, we were able to statistically prove that each of these 10 sub-groups responded to telecom services as independent markets. We found that each segmented group responds as an independent individual market. Through correspondence analysis, the target segmentation groups were positioned in such a way as to facilitate the entry of future telecommunication services into the market, as well as their diffusion and transferability.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.7-17
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• 2009

The precise analysis of exercise data for designing an effective rehabilitation system is very important as a feedback for planing the next exercising step. Many subjective and reliable research outcomes that were obtained by analysis and evaluation for the human motor ability by various methods of biomechanical experiments have been introduced. Most of them include quantitative analysis based on basic statistical methods, which are not practical enough for application to real clinical problems. In this situation, data mining technology can be a promising approach for clinical decision support system by discovering meaningful hidden rules and patterns from large volume of data obtained from the problem domain. In this research, in order to find relational rules between posture training type and muscle activation pattern, we investigated an application of the WAR(Weishted Association Rule) to the biomechanical data obtained mainly for evaluation of postural control ability. The discovered rules can be used as a quantitative prior knowledge for expert's decision making for rehabilitation plan. The discovered rules can be used as a more qualitative and useful priori knowledge for the rehabilitation and clinical expert's decision-making, and as a index for planning an optimal rehabilitation exercise model for a patient.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.225-229
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• 2012

Background: Males have a higher prevalence of hepatocellular carcinoma (HCC) than females in general, but the reasons for the sex disparity are still obscure. DNA copy number alteration (CNA) is a major feature of solid tumors including HCC, but whether CNA plays a role in sex-related differences in HCC development has never been evaluated. Methods: High-resolution array comparative genomic hybridization (CGH) was used to examine 17 female and 46 male HCC patients with chronic hepatitis B virus (HBV) infection in Shanghai, China. Two-tailed Fisher's exact or ${\chi}^2$ tests was used to compare CNAs between females and males. Results: The overall frequencies and patterns of CNAs in female and male cases were similar. However, female HCC tumors presented more copy number gains compared to those in males on 1q21.3-q22 (76.5% vs. 37.0%, P = 0.009), 11q11 (35.3% vs. 0.0%, P = 0.0002) and 19q13.31-q13.32 (23.5% vs. 0.0%, P = 0.004), and loss on 16p11.2 (35.3% vs. 6.5%, P = 0.009). Relative to females, male cases had greater copy number loss on 11q11 (63.0% vs. 17.6%, P = 0.002). Further analyses showed that 11q11 gain correlated with 19q13.31-q13.32 gain (P = 0.042), 11q11 loss (P = 0.011) and 16p11.2 loss (P = 0.033), while 1q21.3-q22 gain correlated with 19q13.31-q13.32 gain (P = 0.046). Conclusions: These findings suggest that CNAs may play a role in sex-related differences in HBVassociated HCC development.