• Journal of Intelligence and Information Systems
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• v.29 no.4
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• pp.207-228
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• 2023

After COVID-19, organizations have widely adopted platforms such as zoom or developed their proprietary online real-time systems for remote work, with recent forays into incorporating the metaverse for meetings and publicity. While ongoing studies investigate the impact of avatar customization, expansive virtual environments, and past virtual experiences on participant satisfaction within virtual reality or metaverse settings, the utilization of the metaverse as a dedicated workspace is still an evolving area. There exists a notable gap in research concerning the factors influencing the performance of the metaverse as a workspace, particularly in non-immersive work-type metaverses. Unlike studies focusing on immersive virtual reality or metaverses emphasizing immersion and presence, the majority of contemporary work-oriented metaverses tend to be non-immersive. As such, understanding the factors that contribute to the success of these existing non-immersive metaverses becomes crucial. Hence, this paper aims to empirically analyze the factors impacting personal outcomes in the non-immersive metaverse workspace and derive implications from the results. To achieve this, the study adopts the Embodied Social Presence (ESP) model as a theoretical foundation, modifying and proposing a research model tailored to the non-immersive metaverse workspace. The findings validate that the impact of presence on task engagement and task involvement exhibits a moderating effect based on the metaverse platform used. Following interviews with participants engaged in non-immersive metaverse workplaces (specifically Gather Town and Ifland), a survey was conducted to gather comprehensive insights.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.697-705
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• 2009

An unsupervised (blind) method is proposed aiming at extracting rhythmic sources from commercial polyphonic music whose number of channels is limited to one. Commercial music signals are not usually provided with more than two channels while they often contain multiple instruments including singing voice. Therefore, instead of using conventional modeling of mixing environments or statistical characteristics, we should introduce other source-specific characteristics for separating or extracting sources in the under determined environments. In this paper, we concentrate on extracting rhythmic sources from the mixture with the other harmonic sources. An extension of nonnegative matrix factorization (NMF), which is called nonnegative matrix partial co-factorization (NMPCF), is used to analyze multiple relationships between spectral and temporal properties in the given input matrices. Moreover, temporal repeatability of the rhythmic sound sources is implicated as a common rhythmic property among segments of an input mixture signal. The proposed method shows acceptable, but not superior separation quality to referred prior knowledge-based drum source separation systems, but it has better applicability due to its blind manner in separation, for example, when there is no prior information or the target rhythmic source is irregular.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.819-825
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• 2024

The reason for recording dose data when using a diagnostic radiation source is to record and manage the dose to healthcare personnel and patients. The purpose of this study was to verify the difference in radiation dose when using diagnostic radiation generating devices and to inform users' awareness of dose reduction through measurement and analysis of dose in situations with and without shielding. The dose analysis of each equipment for two Korean C-arms and two German C-arms showed that the Korean FPD type C-arm had the highest dose value, followed by the German I.I type C-arm, German FPD type C-arm, Korean, and I.I type C-arm. The results of the dose analysis with and without shielding showed that the dose to the human phantom in a normal atmosphere increased by about 2 times due to scattered radiation, but the dose to the human phantom was reduced by about 5 times by wearing a shield (0.5mm/lead apron). More important than the management of radiation dose is the study of how to reduce exposure when using radiation, and since the radiation dose output from different equipment is different, it is necessary to provide dose information with and without shielding.

• Knowledge Management Research
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• v.25 no.1
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• pp.43-66
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• 2024

In an era where digital technology reshapes brand-consumer interactions, this study examines the influence of Nike's Run Club and Adidas' Runtastic apps on loyalty and advocacy. Analyzing 3,715 English reviews from January 2020 to October 2023 through text mining, and conducting a focused sentiment analysis on 155 'recommend' mentions, we explore the nuances of 'hot loyalty'. The findings reveal Nike as a 'companion' with an emphasis on emotional engagement, versus Runtastic's 'tool' focus on reliability. This underscores the varied consumer perceptions across similar platforms, highlighting the necessity for brands to integrate user preferences and address technical flaws to foster loyalty. Demonstrating how customized technology adaptations impact loyalty, this research offers crucial insights for digital brand strategy, suggesting a proactive approach in app development and management for brand loyalty enhancement

• Journal of Aerospace System Engineering
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• v.18 no.1
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• pp.11-20
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• 2024

In the recent era of NewSpace, unlike high-reliability satellites of the past, low-reliability satellites are being developed and mass-produced at a lower cost to launch constellations satellites. To achieve cost-effective cluster satellite development, satellite users and developers need to assess the feasibility of maintaining mission performance over the expected lifespan when cluster satellites are launched. Plans for replacements due to random failures should also be established to maintain performance. This study proposed a method for assessing system reliability and availability to maintain mission performance and establish replacement strategies for Earth observation constellation satellites. In this study, a constellation reliability and availability model considering mission performance required for a satellite constellation, situations of satellite backup, and additional ground backups was established. The reliability model was structured based on the concept of a k-out-of-n system and the availability model used a Markov chain model. Based on the proposed reliability model, the minimum number of satellites required to meet mission requirements was defined and satellites needed in orbit during the required mission period to satisfy mission reliability were calculated. This research also analyzed the number of spare satellites in orbit and on the ground required to meet the desired availability during required service period through availability analysis.

• Information Systems Review
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• v.19 no.3
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• pp.105-125
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• 2017

Although the relationship between social networking sites (SNS) use and performance has been widely studied, most of these studies have focused on comparing the SNS users' overall performance with that of non-SNS users instead of examining how using SNS midway of a task affects one's task performance. To address this research gap, an experiment was conducted to examine SNS use during a task and its influence on the performance of that task. In this experiment, the role of SNS in various situations was examined by reviewing the literature on break and performance as well as the types of breaks and tasks. Owing to its exploratory nature, this study used various types of data, such as electroencephalography interpretation data generated from a brain-computer interface, self-reported data, and data recorded by a computer. Those participants who used SNS showed an improved performance compared with those who took a short break while doing a simple task. Further analysis showed that the degree of SNS usage and engagement with SNS had positive effects on the participants' simple task performance, while social presence and reassurance of self-worth had negative and positive effects on the participants' complex task performance, respectively.

• Cartoon and Animation Studies
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• s.22
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• pp.81-97
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• 2011

The technology of 'Virtual Reality' has placed in advanced tools for human beings' joy and anger together with sorrow and pleasure in our generation. It has recently tried in a variety ways to use as an implication for treatment in the field of Cognitive Psychology. Especially, it widely approaches to human in terms of that a sense of reality in a virtual world through the five senses should reinterpret the meaning of cognition in the real world. Based on this paradigm shift, it allows for new treatment using the technology of virtual reality. A typical example is a field of Therapy in order to overcome panic disorder. It has advantages that in particular development of flexible interaction technologies in a virtual space can lead patients to experience psychological environments rather than physical one. the interaction technology provides environments in which users' five senses can be actively stimulated, it is very useful that information from the experiences in the virtual world allows people to learn through real experiences by renewing potential energies, advantages of Virtual Reality Therapy can be customized treatment by depending on symptoms in patients with panic disorder and are capable of differentiate application for the cure at each stage. It is to treat by leading patients to get accustomed to environments and situations in real world through care process with each symptom and stage. It is helpful that based on A Human-Sensibility Ergonomics, technologies like immersive virtual reality equipment, force-relative feedback and stereophonic sound, and like stimulating the sense of smell make people to induce experiences by stimulating human's five senses. There are many advantages of immersion in virtual world in that the phenomenon such as challenge, interaction, reality, illusion, and cooperation is expanded. As an application for therapy by growing such augmented reality, virtual space and sharing of data through the Internet and also inexpensive its availability have recently expanded the base. There are other benefits of Virtual Reality Therapy offering active interaction environments for cognitive experience which can provide appropriately adjusted environments for patients who are hard to overcome the real situation because of phobia. In addition to that it is safe and economical and patients' confidentiality is assured. Moreover, due to the principles of applying real-time navigation the Virtual Reality Therapy makes modification and supplementation easier and also it can reduce cybersickness because of the supply of Lenticular allowing people to see stereoscopy without eyeglasses, which makes sense of presence clearer. On top of that due to the development of interactive technologies, it is becoming close to sense of reality similar to real world by leading users to navigate by themselves and to operate objects in a virtual space. This paper will therefore examine, although it is of limited, characteristics of application of virtual reality technology based on A Human-Sensibility Ergonomics used for treatment for a disorder. this paper will analyse a range of its application and problems and it will suggest the future possibilities.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.64-80
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• 2018

In Korea, citizens can only know general information about crime. Thus it is difficult to know how much they are exposed to crime. If the police can predict the crime risky area, it will be possible to cope with the crime efficiently even though insufficient police and enforcement resources. However, there is no prediction system in Korea and the related researches are very much poor. From these backgrounds, the final goal of this study is to develop an automated crime prediction system. However, for the first step, we build a big data set which consists of local real crime information and urban physical or non-physical data. Then, we developed a crime prediction model through machine learning method. Finally, we assumed several possible scenarios and calculated the probability of crime and visualized the results in a map so as to increase the people's understanding. Among the factors affecting the crime occurrence revealed in previous and case studies, data was processed in the form of a big data for machine learning: real crime information, weather information (temperature, rainfall, wind speed, humidity, sunshine, insolation, snowfall, cloud cover) and local information (average building coverage, average floor area ratio, average building height, number of buildings, average appraised land value, average area of residential building, average number of ground floor). Among the supervised machine learning algorithms, the decision tree model, the random forest model, and the SVM model, which are known to be powerful and accurate in various fields were utilized to construct crime prevention model. As a result, decision tree model with the lowest RMSE was selected as an optimal prediction model. Based on this model, several scenarios were set for theft and violence cases which are the most frequent in the case city J, and the probability of crime was estimated by $250{\times}250m$ grid. As a result, we could find that the high crime risky area is occurring in three patterns in case city J. The probability of crime was divided into three classes and visualized in map by $250{\times}250m$ grid. Finally, we could develop a crime prediction model using machine learning algorithm and visualized the crime risky areas in a map which can recalculate the model and visualize the result simultaneously as time and urban conditions change.

• Journal of Food Hygiene and Safety
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• v.25 no.4
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• pp.410-417
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• 2010

Various functional foods, marketing health and functional effects, have been distributed in the market. These products, being in forms of foods, tablets, and capsules, are likely to be mistaken as drugs. In addition, non-experts may sell these as foods, or use these for therapy. Efforts for creating health food regulations or building regulatory system for improving the current status of functional foods have been made, but these have not been communicated to consumers yet. As a result, problems of circulating functional foods for therapy or adding illegal medical to such products have persisted, which has become worse by internet media. The cause of this problem can be categorized into (1) product itself and (2) its use, but in either case, one possible cause is lack of communications with consumers. Potential problems that can be caused by functional foods include illegal substances, hazardous substances, allergic reactions, considerations when administered to patients, drug interactions, ingredients with purity or concentrations too low to be detected, products with metabolic activations, health risks from over- or under-dose of vitamin and minerals, and products with alkaloids. (Journal of Health Science, 56, Supplement (2010)). The reason why side effects related to functional foods have been increasing is that under-qualified functional food companies are exaggerating the functionality for marketing purposes. KFDA has been informing consumers, through its web pages, to address the above mentioned issues related to functional foods, but there still is room for improvement, to promote proper use of functional foods and avoid drug interactions. Specifically, to address these issues, institutionalizing to collect information on approved products and their side effects, settling reevaluation systems, and standardizing preclinical tests and clinical tests are becoming urgent. Also to provide crucial information, unified database systems, seamlessly aggregating heterogeneous data in different domains, with user interfaces enabling effective one-stop search, are crucial.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.742-757
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• 2001

Since database management systems(DBMSS) have limited lock resources, transactions requesting locks beyond the limit mutt be aborted. In the worst carte, if such transactions are aborted repeatedly, the DBMS can become paralyzed, i.e., transaction execute but cannot commit. Lock escalation is considered a solution to this problem. However, existing lock escalation methods do not provide a complete solution. In this paper, we prognose a new lock escalation method, adaptive lock escalation, that selves most of the problems. First, we propose a general model for lock escalation and present the concept of the unescalatable look, which is the major cause making the transactions to abort. Second, we propose the notions of semi lock escalation, lock blocking, and selective relief as the mechanisms to control the number of unescalatable locks. We then propose the adaptive lock escalation method using these notions. Adaptive lock escalation reduces needless aborts and guarantees that the DBMS is not paralyzed under excessive lock requests. It also allows graceful degradation of performance under those circumstances. Third, through extensive simulation, we show that adaptive lock escalation outperforms existing lock escalation methods. The results show that, compared to the existing methods, adaptive lock escalation reduces the number of aborts and the average response time, and increases the throughput to a great extent. Especially, it is shown that the number of concurrent transactions can be increased more than 16 ~256 fold. The contribution of this paper is significant in that it has formally analysed the role of lock escalation in lock resource management and identified the detailed underlying mechanisms. Existing lock escalation methods rely on users or system administrator to handle the problems of excessive lock requests. In contrast, adaptive lock escalation releases the users of this responsibility by providing graceful degradation and preventing system paralysis through automatic control of unescalatable locks Thus adaptive lock escalation can contribute to developing self-tuning: DBMSS that draw a lot of attention these days.