• Journal of Communications and Networks
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• v.17 no.2
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• pp.100-109
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• 2015

Mobile phone carriers face challenges from three synergistic dimensions: Wireless, social, and mobile. Despite significant advances that have been made about social networks and human mobility, respectively, our knowledge about the interplay between two layers remains largely limited, partly due to the difficulty in obtaining large-scale datasets that could offer at the same time social and mobile information across a substantial population over an extended period of time. In this paper, we take advantage of a massive, longitudinal mobile phone dataset that consists of human mobility and social network information simultaneously, allowing us to explore the impact of human mobility patterns on the underlying social network. We find that human mobility plays an important role in shaping both local and global structural properties of social network. In contrast to the lack of scale in social networks and human movements, we discovered a characteristic distance in physical space between 10 and 20 km that impacts both local clustering and modular structure in social network. We also find a surprising distinction in trajectory overlap that segments social ties into two categories. Our results are of fundamental relevance to quantitative studies of human behavior, and could serve as the basis of anchoring potential theoretical models of human behavior and building and developing new applications using social and mobile technologies.

• Smart Structures and Systems
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• v.30 no.6
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Journal of the Korean Institute of Landscape Architecture
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• v.43 no.3
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• pp.101-113
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• 2015

The purpose of this study is increasing ventilation network usability for urban green space planning by enhancing its practicality and detail. A ventilation network feature extraction technique using roughness length($z_0$) was proposed. Continuously surfaced DZoMs generated from $z_0$(cadastral unit) using three interpolations(IDW, Spline, and Kriging) were compared to choose the most suitable interpolation method. Ventilation network features were extracted using the most suitable interpolation technique and studied with land cover and land surface temperature by spatial overlay comparison. Results show Kriging is most suitable for DZoM and feature extraction in comparison with IDW and Spline. Kriging based features are well fit to the land surface temperature(Landsat-7 ETM+) on summer and winter nights. Noteworthy is that the produced ventilation network appears to mitigate urban heat loads at night. The practical use of proposed ventilation network features are highly expected for urban green space planning, though strict validation and enhancement should follow. (1) $z_0$ enhancement, (2) additional ventilation network interpretation and editing, (3) linking disconnected ventilation network features, and (4) associated dataset enhancement with data integrity should technically preceded to enhance the applicability of a ventilation network for green space planning. The study domain will be expanded to the Seoul metropolitan area to apply the proposed ventilation network to green space planning practice.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.174-176
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• 2005

This treatise studies composing process that renew information mastered by interactive experience between environment and system via network among individuals. In the previous study map information regarding free space is learned by using of reinforced learning algorithm, which enable each individual to construct optimal action policy. Based on those action policy each individuals can obtain optimal path. Moreover decision process to distinguish best optimal path by comparing those in the network composed of each individuals is added. Also information about the finally chosen path is being updated. A self renewing method of each system information by sharing the each individual data via network is proposed Data enrichment by shilling the information of many maps not in the single map is tried Numerical simulation is conducted to confirm the propose concept. In order to prove its suitability experiment using micro-mouse by integrating and comparing the information between individuals is carried out in various types of map to reveal successful result.

• Journal of Information Processing Systems
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• v.19 no.4
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• pp.483-497
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• 2023

Depth estimation is one of the most complicated and difficult problems to deal with in the light field. In this paper, a compound attention convolutional neural network (CAttNet) is proposed to extract depth maps from light field images. To make more effective use of the sub-aperture images (SAIs) of light field and reduce the redundancy in SAIs, we use a compound attention mechanism to weigh the channel and space of the feature map after extracting the primary features, so it can more efficiently select the required view and the important area within the view. We modified various layers of feature extraction to make it more efficient and useful to extract features without adding parameters. By exploring the characteristics of light field, we increased the network depth and optimized the network structure to reduce the adverse impact of this change. CAttNet can efficiently utilize different SAIs correlations and features to generate a high-quality light field depth map. The experimental results show that CAttNet has advantages in both accuracy and time.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.12
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• pp.2370-2378
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• 2016

Social Network Service(SNS) users are increasing globally. Within that trend, 'SNS attacking' victims are increasing in social network service space like KakaoStory, facebook, or Instargram as people damage others' personality or reputation. In this paper is to investigate and analyze awareness of negative behavior attributed to disinhibition effect with undergraduates who are the group of people using social network service the most diversely in smart environment and devise preventive measures to reduce social network service attacking victims and attackers. In social network service space, undergraduates are hardly aware of other people's personality, defamation, or invasion of privacy, and the level of guilt they feel towards social network service attacking is seriously low. To solve this problem, this study suggests preventive measures so that they can be equipped with awareness and regulations right for this social network service age and can prevent negative behavior resulted from disinhibition effect.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.4
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• pp.59-67
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• 2015

There are several methods for building optimal eco-villages in a narrow territory. To derive a new optimal eco-village factors by combining environmental factors from ubiquitous sensor network and topography factors, this study attempted to investigate ecological spaces of specific human settlements, to compare those with the spatial analytical results on natural real settlements, and to draw a construction plan for an optimal ecological village. This study presented a new milestone for building eco-villages in the large or small village units of the entire country in the fact that we can find a living space to make natural healing possible by integrating ecological factors and wellbeing spatial configuration using more healthy natural space. Also, this study proposed a practical method to do so.

• Journal of Korea Multimedia Society
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• v.21 no.5
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• pp.626-637
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• 2018

Human exchanges information not only through words, but also through body gesture or hand gesture. And they can be used to build effective interfaces in mobile, virtual reality, and augmented reality. The past 2D gesture recognition research had information loss caused by projecting 3D information in 2D. Since the recognition of the gesture in 3D is higher than 2D space in terms of recognition range, the complexity of gesture recognition increases. In this paper, we proposed a real-time gesture recognition deep learning model and application in 3D space using deep learning technique. First, in order to recognize the gesture in the 3D space, the data collection is performed using the unity game engine to construct and acquire data. Second, input vector normalization for learning 3D gesture recognition model is processed based on deep learning. Thirdly, the SELU(Scaled Exponential Linear Unit) function is applied to the neural network's active function for faster learning and better recognition performance. The proposed system is expected to be applicable to various fields such as rehabilitation cares, game applications, and virtual reality.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.1
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• pp.121-133
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• 2015

IoT utilized network vitalization between objects are being rapidly established within current IT communication environment. Therefore the worth of smart mirrors is rising for it is a tool to allow online network between objects to be possible in human communication environment. For effective IoT generation's communication, this research intends to evaluate the smart mirror's value for practical uses based on the users' experiences. For the UX evaluation according to the locations where it will be used, Peter Morville's Honeycomb model and Jocob Nielsen's usage evaluation principles were referred to analyze effectiveness of 4 factors, utilization convenience, communication effectiveness, mass interest and space adequateness on households, public places and work places. Hence, we have were led to an objective result through statistical analysis method based on survey. As a result, we have confirmed the smart mirror's positive influence on the users' effective communication in all places. Especially in households, utilization convenience and space adequateness appeared to be high that confirmed sufficient users' need for the home-automation services. In public places, the communication effectiveness and space adequateness ranked high to confirm that the smart mirror utilization is adequate to provide location information. Also, in work places, the mass adequateness was high that we were able to confirm that supply of work place-specific service contents would bring meaningful results to the users. The smart mirrors are the adequate method to provide effective communication in IoT generation with high possibilities in further development.

• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.105-112
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• 2015

Product Lifecycle Management (PLM) ranges from design concepts of products to disposal. In this paper, we focus on the production planning phase in PLM, which is related to process planning and production scheduling and so on. In this study, key decisions for the creation of production plans are defined as production-planning attributes. Production-planning attributes correlate complexly in production-planning problems. Traditionally, the production-planning problem splits sub-problems based on experiences, because of the complexity. In addition, the orders in which to solve each sub-problem are determined by priorities between sub-problems. However, such approaches make solution space over-restricted and make it difficult to find a better solution. We have proposed a representation of combinations of alternatives in production-planning attributes by using Zero-Suppressed Binary Decision Diagrams. The ZDD represents only feasible combinations of alternatives that satisfy constraints in the production planning. Moreover, we have developed a solution search method that solves production-planning problems with ZDDs. In this paper, we propose an approach for managing solution candidates by ZDDs' network for addressing larger production-planning problems. The network can be created by linkages of ZDDs that express constraints in individual sub-problems and between sub-problems. The benefit of this approach is that it represents solution space, satisfying whole constraints in the production planning. This case study shows that the validity of the proposed approach.