• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.6
• /
• pp.229-234
• /
• 2014

As association between sensor networks that collect environmental information by using numberous sensor nodes and smartphones that are equipped with various sensors, many applications understanding users' context have been developed to interact users and their environments. Collected data should be stored with XML formatted metadata containing semantic information to share the collected data. In case of distance based clustering schemes, the efficiency of data collection decreases because metadata files are extended and changed as the purpose of each system developer. In this paper, we proposed a clustering scheme considering the structural similarity of metadata to reduce clustering construction time and improve the similarity of metadata among member nodes in a cluster.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2010.05a
• /
• pp.985-987
• /
• 2010

In this paper, we propose a maximum entropy-based emotion recognition model using individual average difference. In order to accurately recognize an user' s emotion, the proposed model utilizes the difference between the average of the given input physiological signals and the average of each emotion state' signals rather than only the input signal. For the purpose of alleviating data sparse -ness, the proposed model substitutes two simple symbols such as +(positive number)/-(negative number) for every average difference value, and calculates the average of physiological signals based on a second rather than the longer total emotion response time. With the aim of easily constructing the model, it utilizes a simple average difference calculation technique and a maximum entropy model, one of well-known machine learning techniques.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2019.10a
• /
• pp.781-784
• /
• 2019

최근 AI를 산업 서비스에 적용하기 위해 많은 회사들이 활발히 연구를 하고 있다. 아마존과 넷플릭스 같은 거대 기업들은 이미 빅데이터와 AI 머신러닝을 이용한 추천 시스템을 구현하였고 아마존은 매출의 35%가 추천에 의해 발생하고 넷플릭스 75%의 사용자가 추천을 통해 영화를 선택한다고 보고되었다. 이러한 두 기업의 높은 추천 효율성의 이유는 협업 필터링(Collaborative filtering)과 같은 다양한 추천 알고리즘과 방대한 상품 및 고객 행동(구매, 시청 등) 데이터 등이 존재하고 있기 때문이다. 기계학습에서 알고리즘 학습을 위한 데이터의 양이 많지 않을 경우 알고리즘의 성능을 보장할 수 없다는 것이 일반적인 의견이다. 방대한 데이터를 가진 기업에서 추천 알고리즘을 적극적으로 활용 및 연구하고 있는 것도 이러한 이유 때문이다. 반면, 오프라인 및 여행사 기반에서 온라인 기반으로 영역을 차츰 확대하고 있는 항공 서비스 고객 데이터의 경우, 산업의 특성상 많은 회원에 비해 고객 1명당 온라인에서 활동하는 이력이 많지 않은 것이 특징이다. 이는, 추천 알고리즘을 통한 서비스 제공에서 큰 제약사항으로 작용한다. 본 연구에서는, 이러한 희박한 고객 활동 데이터에서 최신성 기반의 추천 시스템을 통하여 제약사항을 극복하고 추천 효율을 높이는 방법을 제안한다. 고객의 최근 접속 이력 로그를 시간 기준으로 데이터 셋을 분할하여 추천 알고리즘에 반영하였을 때, 추천된 노선에 대한 고객의 반응을 추천 성능 지표인 CTR(Click-Through Rate)로 측정하여 성능을 확인해 보았다.

• The KIPS Transactions:PartA
• /
• v.11A no.5
• /
• pp.383-390
• /
• 2004

This paper propose a method that controls facial expression of 3D avatar by having the user select a sequence of facial expressions in the space of facial expressions. And we setup its system. The space of expression is created from about 2400 frames consist of motion captured data of facial expressions. To represent the state of each expression, we use the distance matrix that represents the distances between pairs of feature points on the face. The set of distance matrices is used as the space of expressions. But this space is not such a space where one state can go to another state via the straight trajectory between them. We derive trajectories between two states from the captured set of expressions in an approximate manner. First, two states are regarded adjacent if the distance between their distance matrices is below a given threshold. Any two states are considered to have a trajectory between them If there is a sequence of adjacent states between them. It is assumed . that one states goes to another state via the shortest trajectory between them. The shortest trajectories are found by dynamic programming. The space of facial expressions, as the set of distance matrices, is multidimensional. Facial expression of 3D avatar Is controled in real time as the user navigates the space. To help this process, we visualized the space of expressions in 2D space by using the multidimensional scaling(MDS). To see how effective this system is, we had users control facial expressions of 3D avatar by using the system. As a result of that, users estimate that system is very useful to control facial expression of 3D avatar in real-time.

• KIISE Transactions on Computing Practices
• /
• v.21 no.2
• /
• pp.101-108
• /
• 2015

This paper presents the implementation of a system that recommends empirical best routes based on classification of large trajectory data. As many location-based services are used, we expect the amount of location and trajectory data to become big data. Then, we believe we can extract the best empirical routes from the large trajectory repositories. Large trajectory data is clustered into similar route groups using Hadoop MapReduce framework. Clustered route groups are stored and managed by a DBMS, and thus it supports rapid response to the end-users' request. We aim to find the best routes based on collected real data, not the ideal shortest path on maps. We have implemented 1) an Android application that collects trajectories from users, 2) Apache Hadoop MapReduce program that can cluster large trajectory data, 3) a service application to query start-destination from a web server and to display the recommended routes on mobile phones. We validated our approach using real data we collected for five days and have compared the results with commercial navigation systems. Experimental results show that the empirical best route is better than routes recommended by commercial navigation systems.

• 지역과문화
• /
• v.7 no.1
• /
• pp.99-126
• /
• 2020

This study aimed to investigate the effects of multicultural complexes on activating local culture. Prior studies that discuss activating local culture through multicultural complexes focus on literature reviews or quantitative research methods, which do not incorporate the detailed and practical opinions of the users of the location. Therefore, this study collected detailed information through in-depth interviews with users, and investigated the future development methods of multicultural complexes based on the obtained information. It focused on the Asia Culture Center (ACC) in Gwangju, which is considered a prime example of a multicultural complex, and conducted in-depth interviews with citizens who have lived in Gwangju for at least five years as well as visited the ACC to investigate the research question from a detailed perspective. The results revealed that although the citizens of Gwangju have a positive perception of the functions of ACC as a cultural space representing the city that activates the local culture, they perceive it as partially insufficient to be considered a multicultural complex. Major findings included the following: the contents of the ACC do not have a mass appeal, its inflexible hours of operation inconvenience visitors, and the contents available for visitors lack in quantity and quality. Therefore, in order for the ACC to appeal as a successful multicultural complex, it is necessary to cooperate with the members of the community to investigate their needs with respect to the contents and location, and prepare strategic plans to satisfy those needs.

• Journal of the Korea Computer Graphics Society
• /
• v.30 no.1
• /
• pp.1-10
• /
• 2024

In immersive virtual environments including mixed reality (MR) and virtual reality (VR), avatars or agents, which are virtual humans, are being studied and applied in various ways as factors that increase users' social presence. Recently, studies are being conducted to apply generative AI as an agent to improve user learning effects or suggest a collaborative environment in an immersive virtual environment. This study proposes a novel method for interface application of a virtual assistant agent (VAA) using OpenAI's ChatGPT in an immersive virtual environment including VR and MR. The proposed method consists of an information agent that responds to user queries and a control agent that controls virtual objects and environments according to user needs. We set up a development environment that integrates the Unity 3D engine, OpenAI, and packages and development tools for user participation in MR and VR. Additionally, we set up a workflow that leads from voice input to the creation of a question query to an answer query, or a control request query to a control script. Based on this, MR and VR experience environments were produced, and experiments to confirm the performance of VAA were divided into response time of information agent and accuracy of control agent. It was confirmed that the interface application of the proposed VAA can increase efficiency in simple and repetitive tasks along with user-friendly features. We present a novel direction for the interface application of an immersive virtual environment through the proposed VAA and clarify the discovered problems and limitations so far.

• Journal of the Korea Society for Simulation
• /
• v.25 no.2
• /
• pp.41-49
• /
• 2016

Counter Fire Operations can be characterized as having a system of systems that key features include situational awareness, command and control systems and highly responsive strike achieved by precision weapons. Current modeling methodology cannot provide an appropriate methodology for a system of systems and utilizes modeling and simulation tools to implement analytic options which can be time consuming and expensive. We explain developing methodology and tools for the effectiveness analysis of the counter fire operations under Network Centric Warfare Environment and suggest how to support a efficient decision making with the methodology and tools. Theater Counter Fire Operations tools consist of Enemy block, ISR block, C2 block and Shooter block. For the convenience of using by domain expert or non simulation expert, it is composed of the environments that each parameter and algorithm easily can be altered by user.

• Science of Emotion and Sensibility
• /
• v.21 no.2
• /
• pp.3-14
• /
• 2018

For satisfying consumer needs, commercial facilities require a variety of sale-related space expressions and eye-catching product arrangements; space composition can also be a direct marketing strategy. The human eye is the sensory organ that acquires the largest amount of information, and an analysis of visual information helps in understanding visual relations between . However, the existing studies are mostly focused on analysis of still frames in experimental images, and there is a lack of studies analyzing gaze information based on mobile images of commercial spaces. Therefore, this study analyzed emotional responses through gaze information of space users in reality using a video of a movement route through a commercial facility. The analysis targeted straight sections of the moving route; based on the data acquired, sectional characteristics of five gaze intensity ranges were examined. As a result, section A, the starting point of the route, had a low gaze intensity, while section B had the highest gaze intensity. This indicates that, starting in section B, the subjects explored the space in a stable way and needed time to adapt to the experimental video. In relation to space characteristics of the gaze-concentrated area, display formats of the right stores in 4 of 6 sections received greater attention. The gaze of consumers was mostly focused on props, and big gaze information was revealed in showcase display formats of the stores. In conclusion, this analysis method can provide highly useful direct design data about merchandise display and merchandise component arrangement based on consumer visual preference.

• The KIPS Transactions:PartA
• /
• v.18A no.6
• /
• pp.255-264
• /
• 2011

A sensor network is a special network that makes physical data sensed by sensor nodes and manages the data. The sensor network is a technology that can apply to many parts of field. It is very important to transmit the data to a user at real-time. The core of the sensor network is a sensor node and small operating system that works in the node. TinyOS developed by UC Berkeley is a sensor network operating system that used many parts of field. It is event-driven and component-based operating system. Basically, it uses non-preemptive scheduler. If an urgent task needs to be executed right away while another task is running, the urgent one must wait until another one is finished. Because of that property, it is hard to guarantee real-time requirement in TinyOS. According to recent study, Priority Level Scheduler, which can let one task preempt another task, was proposed in order to have fast response in TinyOS. It has restrictively 5 priorities, so a higher priority task can preempt a lower priority task. Therefore, this paper suggests Preemptive EDF(Earliest Deadline First) Scheduler that guarantees a real-time requirement and reduces average respond time of user tasks in TinyOS.