• KIISE Transactions on Computing Practices
• /
• v.24 no.3
• /
• pp.145-150
• /
• 2018

Forwarding in opportunistic networks shows low performance because there may be no connecting paths between the source and the destination nodes due to the intermittent connectivity. Currently, social network analysis has been researched. Specifically, similarity is one of methods of social networks analysis. In this paper, we propose forwarding schemes based on representative similarities, and evaluate how much the forwarding performance increases. As a result, since the forwarding schemes are based on similarities, these schemes only forward messages to nodes with higher similarity as relay nodes, toward the destination node. These schemes have low network traffic and hop count while having stable transmission delay.

• KIEAE Journal
• /
• v.5 no.4
• /
• pp.25-32
• /
• 2005

In apartment complexes of Korea shared space becomes more and more important since it promotes social relationship among neighbors and also as a ecological point of view. After the Green Building system was introduced in the society, it attracted more attentive as an essential component for sustainable community. Now, it's expected the shared space plan or the community center plan will be a hot issue in the society. Therefore, we could see an aspect of the gradual change related to housing culture in Korea and make a prediction how to develop the shared space as researching domestic leading studies about the 'shared space'. The purpose of this study is to identify the trend of academic achievement as shared spaces. 14 books and 43 studies are searched and each of them are divided into according to the subject. The concept of the shared space was introduced in a holistic moment and the design plans were presented in books in the early 1990's, and total community center it was introduced. The studies are naturally divided into 4 parts as time passed that are characteristics of the block planning in the complex, the needs of the shared space, the actual condition of the using shared space, and the case studies of the shared space. The shared spaces under the structure of the community center are expected to be developed in a more elaborate way to cope with increasingly well-being needs.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.1
• /
• pp.368-391
• /
• 2018

Face recognition (FR) with a single sample per person (SSPP) is common in real-world face recognition applications. In this scenario, it is hard to predict intra-class variations of query samples by gallery samples due to the lack of sufficient training samples. Inspired by the fact that similar faces have similar intra-class variations, we propose a virtual sample generating algorithm called k nearest neighbors based virtual sample generating (kNNVSG) to enrich intra-class variation information for training samples. Furthermore, in order to use the intra-class variation information of the virtual samples generated by kNNVSG algorithm, we propose image set based multimanifold discriminant learning (ISMMDL) algorithm. For ISMMDL algorithm, it learns a projection matrix for each manifold modeled by the local patches of the images of each class, which aims to minimize the margins of intra-manifold and maximize the margins of inter-manifold simultaneously in low-dimensional feature space. Finally, by comprehensively using kNNVSG and ISMMDL algorithms, we propose k nearest neighbor virtual image set based multimanifold discriminant learning (kNNMMDL) approach for single sample face recognition (SSFR) tasks. Experimental results on AR, Multi-PIE and LFW face datasets demonstrate that our approach has promising abilities for SSFR with expression, illumination and disguise variations.

• Journal of Communications and Networks
• /
• v.17 no.4
• /
• pp.406-418
• /
• 2015

Cognitive radio networks (CRNs) have emerged as a promising solution to the problem of spectrum under utilization and artificial radio spectrum scarcity. The paradigm of dynamic spectrum access allows a secondary network comprising of secondary users (SUs) to coexist with a primary network comprising of licensed primary users (PUs) subject to the condition that SUs do not cause any interference to the primary network. Since it is necessary for SUs to avoid any interference to the primary network, PU activity precludes attempts of SUs to access the licensed spectrum and forces frequent channel switching for SUs. This dynamic nature of CRNs, coupled with the possibility that an SU may not share a common channel with all its neighbors, makes the task of multicast routing especially challenging. In this work, we have proposed a novel multipath on-demand multicast routing protocol for CRNs. The approach of multipath routing, although commonly used in unicast routing, has not been explored for multicasting earlier. Motivated by the fact that CRNs have highly dynamic conditions, whose parameters are often unknown, the multicast routing problem is modeled in the reinforcement learning based framework of learning automata. Simulation results demonstrate that the approach of multipath multicasting is feasible, with our proposed protocol showing a superior performance to a baseline state-of-the-art CRN multicasting protocol.

• Parasites, Hosts and Diseases
• /
• v.46 no.4
• /
• pp.269-271
• /
• 2008

A healthy 30-yr-old woman carrying an insect that had been caught in her living room visited the International Clinic at Severance Hospital, Seoul, in December 2007. The insect she brought was identified to be a nymph of a bedbug, Cimex lectularius, and her skin rashes looked typical bedbug's bites. Her apartment was investigated, and a dead body of a bedbug, cast skins, and hatched eggs were found in her rooms and neighbors' rooms in the same building. She was living in that apartment in Seoul for 9 months since she had moved from New Jersey, USA. We assume that the bedbugs were introduced from abroad, since there had been no report on bedbugs in Seoul for more than 2 decades at least. This is a report of a reemergence of the common bedbug, C. lectularius in Seoul, Korea.

• Journal of Families and Better Life
• /
• v.31 no.3
• /
• pp.81-92
• /
• 2013

The purpose of this study is to identify difference in motivation of move to senior cohousing communities in Sweden during 10 years between the year of 2001 and 2010 by a longitudinal study. Questionnaire survey was used for the study. 313 data were collected from 12 senior cohousing communities, which were established by residents-initiated process. It includes 8 of Senior g${\aa}$rden cohousings in 2001 and 4 of +40 cohousings in 2010 nationwide in Sweden. The result indicates that there are significant differences in motivation of move to senior cohousing between 2001 and 2010. Comparing motivation of move to senior cohousing during 10 years, respondents of 2010 focus more on social merits than practical merits of cohousing as they move to cohousing communities. They stress more to the reasons as good contacts with neighbors, mutual supports, sharing common activities and getting rid of loneliness rather than burden of housing and garden management, and universal-designed house. The result of this study reveals motivation of move to senior cohousing has been changed during 10 years in Sweden.

• Journal of Information Processing Systems
• /
• v.13 no.4
• /
• pp.914-927
• /
• 2017

Weighted network link prediction is a challenge issue in complex network analysis. Unsupervised methods based on local structure are widely used to handle the predictive task. However, the results are still far from satisfied as major literatures neglect two important points: common neighbors produce different influence on potential links; weighted values associated with links in local structure are also different. In this paper, we adapt an effective link prediction model-local naive Bayes model into a weighted scenario to address this issue. Correspondingly, we propose a weighted local naive Bayes (WLNB) probabilistic link prediction framework. The main contribution here is that a weighted cluster coefficient has been incorporated, allowing our model to inference the weighted contribution in the predicting stage. In addition, WLNB can extensively be applied to several classic similarity metrics. We evaluate WLNB on different kinds of real-world weighted datasets. Experimental results show that our proposed approach performs better (by AUC and Prec) than several alternative methods for link prediction in weighted complex networks.

• The Bulletin of The Korean Astronomical Society
• /
• v.43 no.2
• /
• pp.35.1-35.1
• /
• 2018

Bars are commonly found in disk galaxies. However, how bars form is yet unclear. There are two common pictures for the bar formation mechanism. Bars form through a physical process inherent in galaxies, or through and external process like galaxy-galaxy interaction. In this paper, we present the observational evidence that bars can form from another channel, namely a cluster-cluster interaction. We examined 105 galaxy clusters at 0.015

• The Journal of Asian Finance, Economics and Business
• /
• v.8 no.8
• /
• pp.167-180
• /
• 2021

The "sharing economy" describes a type of business built on the sharing of resources - allowing customers to access goods when needed. While sharing goods has always been a common practice among friends, family, and neighbors, in recent years, the concept of sharing has moved from a community practice into a profitable business model. This study explores gaps between customers' actual usages and current policies on accommodation sharing by analyzing what needs to be done for the better establishment of sharing economy in society. The purpose of this study is to investigate perceptions of accommodation sharing by analyzing reviews and negative aspects that help resolve complaints and improve better services through policy establishment. This study investigates key attributes that influence business performance to improve citizens' decision-making for the usage of accommodation sharing. This study applies qualitative research by collecting demand- and supply-side reviews from selected registered accommodations using a random sampling procedure. This study finds that guests prefer entire house sharing with instrumental attributes related to properties. Entire house sharing of multiple dwellings shows business impacts in terms of high occupancy rate on the platform, while there are policy concerns with entire house sharing. The results provide policy and managerial implications by suggesting proper policies and considering relationships with citizens.

• Geomechanics and Engineering
• /
• v.29 no.3
• /
• pp.249-258
• /
• 2022

A disc cutter is an excavation tool on a tunnel boring machine (TBM) cutterhead; it crushes and cuts rock mass while the machine excavates using the cutterhead's rotational movement. Disc cutter wear occurs naturally. Thus, along with the management of downtime and excavation efficiency, abrasioned disc cutters need to be replaced at the proper time; otherwise, the construction period could be delayed and the cost could increase. The most common prediction models for TBM performance and for the disc cutter lifetime have been proposed by the Colorado School of Mines and Norwegian University of Science and Technology. However, design parameters of existing models do not well correspond to the field values when a TBM encounters complex and difficult ground conditions in the field. Thus, this study proposes a series of machine learning models to predict the disc cutter lifetime of a shield TBM using the excavation (machine) data during operation which is response to the rock mass. This study utilizes five different machine learning techniques: four types of classification models (i.e., K-Nearest Neighbors (KNN), Support Vector Machine, Decision Tree, and Staking Ensemble Model) and one artificial neural network (ANN) model. The KNN model was found to be the best model among the four classification models, affording the highest recall of 81%. The ANN model also predicted the wear rate of disc cutters reasonably well.