• Journal of KIISE:Computing Practices and Letters
• /
• v.16 no.1
• /
• pp.65-69
• /
• 2010

Moving Picture Expert Group(MPEG) is the organization foundedin 1998 to establish the standards for compressing and expressing the multimedia contents. The organization has established the technological standards such as MPEG-1, MPEG-2, MPEG-4 and MPEG-7. As the 3D video related standards, there is Multiview Profile which is included in the MPEG-2 video of 1996. However, as the MPEG-2 multiview profile is the standard for compressing the videos from two viewpoints on the object, it is not enough to meet the requirement of multiviewvideo technology. In addition, it does not have the technology on the viewpoint switching that it does not provide the services such as the user interaction. This paper proposes the structure in which the specific viewpoint can be described for video switching in addition to the current MPEG-4 system.

• Journal of Intelligence and Information Systems
• /
• v.18 no.2
• /
• pp.19-28
• /
• 2012

After the internet era, we are moving to the ubiquitous society. Nowadays the people are interested in the multimodal interaction technology, which enables audience to naturally interact with the computing environment at the exhibitions such as gallery, museum, and park. Also, there are other attempts to provide additional service based on the location information of the audience, or to improve and deploy interaction between subjects and audience by analyzing the using pattern of the people. In order to provide multimodal interaction service to the audience at the exhibition, it is important to distinguish the individuals and trace their location and route. For the location tracking on the outside, GPS is widely used nowadays. GPS is able to get the real time location of the subjects moving fast, so this is one of the important technologies in the field requiring location tracking service. However, as GPS uses the location tracking method using satellites, the service cannot be used on the inside, because it cannot catch the satellite signal. For this reason, the studies about inside location tracking are going on using very short range communication service such as ZigBee, UWB, RFID, as well as using mobile communication network and wireless lan service. However these technologies have shortcomings in that the audience needs to use additional sensor device and it becomes difficult and expensive as the density of the target area gets higher. In addition, the usual exhibition environment has many obstacles for the network, which makes the performance of the system to fall. Above all these things, the biggest problem is that the interaction method using the devices based on the old technologies cannot provide natural service to the users. Plus the system uses sensor recognition method, so multiple users should equip the devices. Therefore, there is the limitation in the number of the users that can use the system simultaneously. In order to make up for these shortcomings, in this study we suggest a technology that gets the exact location information of the users through the location mapping technology using Wi-Fi and 3d camera of the smartphones. We applied the signal amplitude of access point using wireless lan, to develop inside location tracking system with lower price. AP is cheaper than other devices used in other tracking techniques, and by installing the software to the user's mobile device it can be directly used as the tracking system device. We used the Microsoft Kinect sensor for the 3D Camera. Kinect is equippedwith the function discriminating the depth and human information inside the shooting area. Therefore it is appropriate to extract user's body, vector, and acceleration information with low price. We confirm the location of the audience using the cell ID obtained from the Wi-Fi signal. By using smartphones as the basic device for the location service, we solve the problems of additional tagging device and provide environment that multiple users can get the interaction service simultaneously. 3d cameras located at each cell areas get the exact location and status information of the users. The 3d cameras are connected to the Camera Client, calculate the mapping information aligned to each cells, get the exact information of the users, and get the status and pattern information of the audience. The location mapping technique of Camera Client decreases the error rate that occurs on the inside location service, increases accuracy of individual discrimination in the area through the individual discrimination based on body information, and establishes the foundation of the multimodal interaction technology at the exhibition. Calculated data and information enables the users to get the appropriate interaction service through the main server.

• Journal of the HCI Society of Korea
• /
• v.9 no.2
• /
• pp.61-68
• /
• 2014

Tabletop games have been applied to improve the ability of social collaboration based on the characteristics that more than two people simultaneously interact on the tabletop. Especially, the tabletop games can be used as an educational tool for children with autism when it is implemented by considering educational and psychological models for children's behavioral characteristics. However, the previous collaborative games were designed for only disabled children so that it is hard to reflect cognitive and humanistic effects in inclusive education, where disabled children and non-disabled children interact in a same spatiotemporal environment. In this paper, therefore, we design a collaborative game on a multi-touch tabletop to enable spontaneous communication between disabled children and non-disabled children. Through user study, we evaluate the improvement in terms of the positive interaction and the degree of attention by comparing with a conventional collaborative game(e.g., a board game). We found that negative interaction including disabled children's abnormal behavior decreased and positive interaction such as body gestures and verbal communications increased. In addition, the tabletop game supported high immersiveness to all children by deriving equal level of attention time including individual and joint attention. We anticipate that the proposed game design can be utilized to develop collaborative contents for people with differences on sociality and cognitive ability.

• Journal of the HCI Society of Korea
• /
• v.13 no.2
• /
• pp.31-44
• /
• 2018

In the IoT environment, various things could be connected. Those connected things learn and operate themselves, by acquiring data. As human being, they have self-learning and self-operating systems. In the field of IoT study, therefore, the key issue is to design communication system connecting both of the two different types of subjects, human being(user) and the things. With the advent of the IoT environment, much research has been done in the field of UI design. It can be seen that research has been conducted to take complex factors into account through keywords such as multi-modality and interusability. However, the existing UI design method has limitations in structuring or testing interaction between things and users of IoT environment. Therefore, this paper suggests a new UI prototyping method. In this paper, the major analysis and studies are as follows: (1) defined what is the behavior process of the things (2) analyzed the existing IoT product (3) built a new framework driving personality types (4) extracted three representative personality models (5) applied the three models to the smart home service and tested UI prototyping. It is meaningful with that this study can confirm user experience (UX) about IoT service in a more comprehensive way. Moreover, the concept of the personality of things will be utilized as a tool for establishing the identity of artificial intelligence (AI) services in the future.

• Journal of Korea Technology Innovation Society
• /
• v.22 no.2
• /
• pp.220-241
• /
• 2019

In order to provide theoretical guidance to research in platform strategy, we build the conceptual framework based on the organizational ecology and analyze symbiotic/competitive relationship between platform entities. Platform owner and service provider (i.e. complementors) make symbiotic relationship, where platform owner provide service provider user-base and platform resources such as marketing tools and platform technology, and service provider provide platform owner services which users utilize. In addition to symbiotic relationships, platform owner has competitive relationship with other platform owners, and service provider builds competitive relationship with other service providers. In these relationships, the strategy of platform owner affects service provider and service provider builds a strategy for their own survival and success. This type of interaction makes competitive dynamics in platform. However, previous platform literature focuses on strategies to enhance network effect from the perspective of platform owner. Thus, there is little attention on interaction among the service providers. Using the framework based on community ecology of organizational ecology, we analyze interaction and strategy between platform owner and service provider in the viewpoint of platform openness strategy and platform pricing strategy. This research contributes to the literature of platform strategy by providing a theoretical framework based on organizational ecology to deeply understand the dynamics of platform.

• Journal of Intelligence and Information Systems
• /
• v.29 no.1
• /
• pp.249-263
• /
• 2023

Collaborative Filtering, a representative recommendation system methodology, consists of two approaches: neighbor methods and latent factor models. Among these, the latent factor model using matrix factorization decomposes the user-item interaction matrix into two lower-dimensional rectangular matrices, predicting the item's rating through the product of these matrices. Due to the factor vectors inferred from rating patterns capturing user and item characteristics, this method is superior in scalability, accuracy, and flexibility compared to neighbor-based methods. However, it has a fundamental drawback: the need to reflect the diversity of preferences of different individuals for items with no ratings. This limitation leads to repetitive and inaccurate recommendations. The Adaptive Deep Latent Factor Model (ADLFM) was developed to address this issue. This model adaptively learns the preferences for each item by using the item description, which provides a detailed summary and explanation of the item. ADLFM takes in item description as input, calculates latent vectors of the user and item, and presents a method that can reflect personal diversity using an attention score. However, due to the requirement of a dataset that includes item descriptions, the domain that can apply ADLFM is limited, resulting in generalization limitations. This study proposes a Generalized Adaptive Deep Latent Factor Recommendation Model, G-ADLFRM, to improve the limitations of ADLFM. Firstly, we use item ID, commonly used in recommendation systems, as input instead of the item description. Additionally, we apply improved deep learning model structures such as Self-Attention, Multi-head Attention, and Multi-Conv1D. We conducted experiments on various datasets with input and model structure changes. The results showed that when only the input was changed, MAE increased slightly compared to ADLFM due to accompanying information loss, resulting in decreased recommendation performance. However, the average learning speed per epoch significantly improved as the amount of information to be processed decreased. When both the input and the model structure were changed, the best-performing Multi-Conv1d structure showed similar performance to ADLFM, sufficiently counteracting the information loss caused by the input change. We conclude that G-ADLFRM is a new, lightweight, and generalizable model that maintains the performance of the existing ADLFM while enabling fast learning and inference.

• Journal of KIISE:Software and Applications
• /
• v.32 no.3
• /
• pp.192-201
• /
• 2005

For the past ten years, the goal of ubiquitous computing research has been the establishment of a new technology system with the aim 'Anytime, Anywhere, and Any form'. The needs for agent technology innovations such as ontology-based structure, ontology-based agent communication language, and multi-agents frameworks have been identified. This paper proposes a noble multi-agents architecture for ubiquitous systems. We suggest four major steps in the interaction between human and agents which enable ubiquitous agents to process by themselves to provide adaptive service to meet human's needs. First, we propose a semantic web technology to represent the association between information resources more explicitly Second, we construct a semantic ontology so that agents can recognize web contents.'Third, we propose a method to communicate between agents using OWL ontologies. Finally, we suggest a multi-agents structure based on the JADE of FIPA to analyze messages and get information. The semantic multi-agents framework proposed in this paper infers semantic situations using semantic web technology based on ontologies. A service provided is inferred differently according to user state because the multi-agents communicate by using OWL ontology language. Therefore, our system better infers context information than other without ontologies.

• Proceedings of the KSR Conference
• /
• 2011.10a
• /
• pp.428-435
• /
• 2011

In general, thickness of the sublayers under track is designed based on concept of vertical soil reaction value or vertical stiffness. However, this design method cannot take consideration into soil-track interaction under repetitive load, traffic condition and velocity of the train. Furthermore, the reinforced roadbed soils experience complex behavior that cannot be explained by conventional stress-strain relation expressed as soil reaction value k. The reinforced roadbed soils also can produce cumulative permanent deformation under repetitive load caused by train. Therefore new design method for the sublayers under track must be developed that can consider both elastic modulus and permanent deformation. In this study, a new design concept, a rule-of-thumb, is proposed as the form of design monograph that is developed using elastic multi-layer and finite element programs by analyzing stress and deformation in the sublayers with changing the thickness and elastic modulus of the sublayers and also using data obtained from repetitive triaxial test. This new design concept can be applied to design of the reinforced roadbed before developing full version of design methodology that can consider MGT, axial load and the material properties of the layers. The new design monograph allows the user to design the thickness of the reinforced roadbed based on permanent deformation, elastic modulus and MGT.

• Journal of the Korea Convergence Society
• /
• v.7 no.1
• /
• pp.25-30
• /
• 2016

Virtual reality items are increased take-all type of markets like Universal, such as the United States as a leader in the virtual reality technology. Multi-user have to get direct experiences with the whole body like visual, tactile, hearing, sense of movement, and it must be developed new forms of content platform to enjoy immerse deeply into the content. Visitors are not to enjoy the content passively but rather to enjoy the content actively. So it like that should develope content to maximize the immersion. It need the development of new forms of mixed 5D virtual reality Attraction content with all of factors like $360^{\circ}$ circle vision, stereoscopic images, interaction, simulator, and the environmental effect. We proposes how to make the color and brightness calibration technology for this purpose.

• Journal of the Korea Computer Graphics Society
• /
• v.7 no.1
• /
• pp.37-49
• /
• 2001

We propose an optimization of mutual information for multiresolution image registration to represent useful information as integrated form obtaining from complementary information of multi modality images. The method applies mutual information as cost function to measure the statistical dependency or information redundancy between the image intensities of corresponding pixels in both images, which is assumed to be maximal if the images are geometrically aligned. As experimental results we validate visual inspection for accuracy, changning initial condition and addictive noise for robustness. Since our method uses the native image rather than prior feature extraction, few user interaction is required to perform the registration. In addition it leads to robust density estimation and convergence as applying non-parametric density estimation and stochastic multiresolution optimization.