• Asian Journal for Public Opinion Research
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• v.5 no.1
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• pp.1-14
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• 2017

The Fukushima nuclear accident caused by an earthquake and a subsequent tsunami on March 11, 2011 has seriously impacted the environment surrounding the Fukushima Daiichi nuclear power plant. While all the residents near the plant were evacuated from the area deemed uninhabitable after the accident, residents of the neighboring area outside of the evacuation zone still seem to live in fear of invisible radiation. To understand Fukushima residents' thinking about the environmental risks that accompany a nuclear disaster, we utilize a poll of the residents of Fukushima conducted in 2013. Based on the survey data, we reveal factors that seem to strongly affect their knowledge and concerns about nuclear power plants. The results of the multivariate analysis show the importance of the following two factors: (1) confidence in mass media, and (2) trust in institutions in charge of administering the accident, especially the central government, the Nuclear and Industrial Safety Agency, and Tokyo Electric Power Company. We conclude that the more people trust mass media and particular institutions, the more likely it is that they are have an elevated sense of anxiety and fear of the presence of nuclear plants.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5936-5954
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• 2018

Eight out of the top ten the largest technology companies in the world are involved in some way with the coming mobile VR revolution since Facebook acquired Oculus. This trend has allowed the technology related with mobile VR to achieve remarkable growth in both academic and industry. Therefore, the importance of reproducing the acoustic expression for users to experience more realistic is increasing because auditory cues can enhance the perception of the complicated surrounding environment without the visual system in VR. This paper presents a audio downmixing system for auralization based on hardware, a stage of sound rendering pipelines that can reproduce realiy-like sound but requires high computation costs. The proposed system is verified through an FPGA platform with the special focus on hardware architectural designs for low power and real-time. The results show that the proposed system on an FPGA can downmix maximum 5 sources in real-time rate (52 FPS), with 382 mW low power consumptions. Furthermore, the generated 3D sound with the proposed system was verified with satisfactory results of sound quality via the user evaluation.

• International Journal of Contents
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• v.18 no.3
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• pp.11-20
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• 2022

Human Emotion Recognition is an exciting topic that has been attracting many researchers for a lengthy time. In recent years, there has been an increasing interest in exploiting contextual information on emotion recognition. Some previous explorations in psychology show that emotional perception is impacted by facial expressions, as well as contextual information from the scene, such as human activities, interactions, and body poses. Those explorations initialize a trend in computer vision in exploring the critical role of contexts, by considering them as modalities to infer predicted emotion along with facial expressions. However, the contextual information has not been fully exploited. The scene emotion created by the surrounding environment, can shape how people perceive emotion. Besides, additive fusion in multimodal training fashion is not practical, because the contributions of each modality are not equal to the final prediction. The purpose of this paper was to contribute to this growing area of research, by exploring the effectiveness of the emotional scene gist in the input image, to infer the emotional state of the primary target. The emotional scene gist includes emotion, emotional feelings, and actions or events that directly trigger emotional reactions in the input image. We also present an attention-based fusion network, to combine multimodal features based on their impacts on the target emotional state. We demonstrate the effectiveness of the method, through a significant improvement on the EMOTIC dataset.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.47-55
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• 2023

Recently, Sensor technologies are emerging to prevent traffic accidents and support safe driving in complex environments where human perception may be limited. The UWS is a technology that uses an ultrasonic sensor to detect objects at short distances. While it has the advantage of being simple to use, it also has the disadvantage of having a limited detection distance. The LDWS, on the other hand, is a technology that uses front image processing to detect lane departure and ensure the safety of the driving path. However, it may not be sufficient for determining the driving environment around the vehicle. To overcome these limitations, a system that utilizes FMCW radar is being used. The BSD radar system using FMCW continuously emits signals while driving, and the emitted signals bounce off nearby objects and return to the radar. The key technologies involved in designing the BSD radar system are tracking algorithms for detecting the surrounding situation of the vehicle. This paper presents a tracking algorithm for designing a BSD radar system, while explaining the principles of FMCW radar technology and signal types. Additionally, this paper presents the target tracking procedure and target filter to design an accurate tracking system and performance is verified through simulation.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.406-416
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• 2023

Alarm system performance is a critical aspect of safety. While existing research has extensively examined the influence of acoustic attributes on alarm performance, consonance's impact remains largely uncharted territory. This study bridges this research gap by investigating the effect of consonance on alarm systems. We extend our investigation to encompass not only the sound characteristics of the alarm but also the acoustic qualities of the surrounding environment, recognizing their potential impact on alarm efficacy. Prior studies consistently link consonance to annoyance levels, resulting in a negative user experience. Thus, we explore the relationship between consonance and alarm system performance, with a particular focus on modulating annoyance as an explanatory factor. Utilizing an oddball paradigm, we categorized standard and oddball sounds into consonant and dissonant types, creating four sound combinations. Participants were asked to respond to the irregularly presented oddball sounds while ignoring the constantly presented standard sounds. Our results reveal significant differences between groups, with the Standard Consonant/Oddball Dissonant (SC/OD) group displaying notably slower response times than the Standard Dissonant/Oddball Consonant (SD/OC) group. This reaction time variation aligns with differences in annoyance levels, as the SC/OD group reports higher annoyance, suggesting that reaction time discrepancies may be linked to increased arousal due to heightened annoyance.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.165-168
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• 2005

The objects, which can be personal digital assistants, electronic rings, doors or even clothes, offer embedded chips with computation facilities and are generally called artifacts. I later realized that this was not so the real problem is actually authentication. Recent results indicate scalability problems for flat ad hoc networks. Sensor network achieves function that handle surrounding information perception through sensor and sensed information to network that is consisted of sensor nodes of large number. Research about new access control techniques and height administration techniques need authentication information persons' certification assurance level classification in sensor network environment which become necessary different view base with authentication information at node for application of AAA technology in USN environment that must do authentication process using information that is collected from various sensor mountings. So, get base authentication information in sensor type and present weight grant model by security strength about authentication information through information who draw. In this paper collected information of sensor nodes model who give weight drawing security reinforcement as authentication information by purpose present be going to. and Must be able to can grasp special quality of each sensor appliances in various side and use this and decide authentication assurance level for value estimation as authentication information elements. Therefore, do to define item that can evaluate Authentication information elements thus and give simple authentication assurance level value accordingly because applying weight. Present model who give authentication assurance level value and weight for quotation according to security strength.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.2
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• pp.186-190
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• 2015

Intelligent vehicle plans motion and navigate itself based on the surrounding environment perception. Hence, the precise environment recognition is an essential part of self-driving vehicle. There exist many vulnerable road users (e.g. vehicle, pedestrians) on vehicular driving environment, the vehicle must percept all the dynamic obstacles accurately for safety. In this paper, we propose an multiple vehicle tracking algorithm using microwave radar. Our proposed system includes various special features. First, exceptional radar measurement model for vehicle, concentrated on the corner, is described by mixture density network (MDN), and applied to particle filter weighting. Also, to conquer the curse of dimensionality of particle filter and estimate the time-varying number of multi-target states, reversible jump markov chain monte carlo (RJMCMC) is used to sampling step of the proposed algorithm. The robustness of the proposed algorithm is demonstrated through several computer simulations.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.993-997
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• 2009

Designs in the modernism era were produced for the purpose of standardization of items and devices centered on efficiency and functions, and the will of design consumers in the industrial era, when consumption exceeded production, was limited to the objects of consumption. But, after the post-modernism era, design consumers have started to entail acts of exclusive possession such as participation in the design idolization, partipation, tuning, control and parody as design consumers in the digital environment do not passively accept what is given to them anymore, and aggressively intervene in the process of design production and management. It is expected that designs will change from the system in which only professionals can produce and manage its production to that of cooperating with consumers to produce designs, and various forms of consumers' exclusive possession will change all sort of design environments including production methods surrounding design products and distribution. Therefore, this study seeks to induce efficient design production by understanding changes of consumers' cultural environment resisting standardization and structuralization with smoothy perception between producers and consumers through classification of consumers' appropriation into de-construction, re-signification and self-identification.

• Journal of the Korean School Mathematics Society
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• v.11 no.3
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• pp.377-397
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• 2008

In today's secondary school mathematics curriculum, assessment is to be focused on evaluating the student's mathematical thinking rather than finding the correct solution to the problem. A descriptive evaluation method is therefore introduced to the school districts and suggested as an alternative assessment method in K-12 school mathematics. Descriptive evaluation method is widely available for use in schools, but there are barriers to using it since the teachers are forced to use the method by the school districts. In this research, we surveyed 120 secondary school mathematics teachers in Seoul and the surrounding metropolitan area to understand the status and the perception about using descriptive evaluation. The goal of the study was to find and understand the direct implications of using the new assessment method in secondary mathematics classes. The study showed that most of the mathematics teachers used the descriptive assessment method during their regular exam periods which is given twice per semester. Most of the open-ended problems used for descriptive evaluation were medium or high level math questions which were graded by the teachers at least 3 times to ensure objective evaluation. The teachers stated that objectivity in grading, administrative situation, and development of descriptive problems were the difficult barriers in descriptive evaluation. The teachers in the survey also commented that teachers' administrative responsibility should be reduced and that school environment in general should be improved for the new assessment method to become successful. Finally, the study showed that development of more descriptive problems with specific grading guidelines need to be developed for each grade level.

• Asia pacific journal of information systems
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• v.24 no.4
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.