• The Korean Journal of Physiology and Pharmacology
• /
• v.19 no.5
• /
• pp.461-465
• /
• 2015

Microglia, the resident macrophages in the central nervous system, can rapidly respond to pathological insults. Toll-like receptor 2 (TLR2) is a pattern recognition receptor that plays a fundamental role in pathogen recognition and activation of innate immunity. Although many previous studies have suggested that TLR2 contributes to microglial activation and subsequent pathogenesis following brain tissue injury, it is still unclear whether TLR2 has a role in microglia dynamics in the resting state or in immediate-early reaction to the injury in vivo. By using in vivo two-photon microscopy imaging and $Cx3cr1^{GFP/+}$ mouse line, we first monitored the motility of microglial processes (i.e. the rate of extension and retraction) in the somatosensory cortex of living TLR2-KO and WT mice; Microglial processes in TLR2-KO mice show the similar motility to that of WT mice. We further found that microglia rapidly extend their processes to the site of local tissue injury induced by a two-photon laser ablation and that such microglial response to the brain injury was similar between WT and TLR2-KO mice. These results indicate that there are no differences in the behavior of microglial processes between TLR2-KO mice and WT mice when microglia is in the resting state or encounters local injury. Thus, TLR2 might not be essential for immediate-early microglial response to brain tissue injury in vivo.

• Journal of Digital Contents Society
• /
• v.16 no.5
• /
• pp.671-680
• /
• 2015

The Joint Bayesian[1] method was published in 2012. Since then, it has been used for binary classification in almost all state-of-the-art face recognition methods. However, no improved methods have been published so far except 2D-JB[2]. In this paper we propose an improved version of the JB method that considers the features of both the given face image and its mirror image. In pattern classification, it is very likely to make a mistake when the value of the decision function is close to the decision boundary or the threshold. By making the value of the decision function far from the decision boundary, the proposed method reduces the errors. The experimental results show that the proposed method outperforms the JB and 2D-JB methods by more than 1% in the challenging LFW DB. Many state-of-the-art methods required tons of training data to improve 1% in the LFW DB, but the proposed method can make it in an easy way.

• Proceedings of the Korean Institute Of Construction Engineering and Management
• /
• 2007.11a
• /
• pp.347-352
• /
• 2007

Recently, automated construction machines have been developed for technically solving construction industry problems such as labor, productivity, quality and the profit decrease. In domestic construction industry, a research for developing an intelligent excavation robot has been performed. The primary objective of this research is to analysis state-of-the art technologies in order to recognize local ground shape in real-time and compute soil volume of earth moving. This research analyzed five elemental technologies for 3D modeling of local ground shape and selected an optimal technology among the five technologies through using AHP method. It is anticipated that the optimal technology selected for 3D modeling of local ground shape can be effectively used to develop the intelligent excavation robot.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.23 no.8
• /
• pp.1002-1009
• /
• 2012

This paper shows the research about radar target recognition using the measured radar signals from MSU(Michgan State University) bistatic radar system. In this research, we first did the bistatic measurements at $30^{\circ}$, $60^{\circ}$, $90^{\circ}$ using F-14, Mig-29, and F-22 scale models. Then, we extract the target feature vectors using time-frequency analysis methods such as STFT(Short Time Fourier Transform) and CWT(Continous Wavelet Transform) and perform the target classification test using MLP(Multi-layerd Perceptron) neural network. The results show that the target classification performance is too much dependent on the bistatic angles and the best performance is obtained at the $60^{\circ}$ bistatic angle.

• Journal of Korean society of Dental Hygiene
• /
• v.15 no.2
• /
• pp.205-216
• /
• 2015

Objectives: The purpose of the study is to investigate the psychological state of the patients according to skeletal class III malocclusion symptoms. Methods: The subjects were 200 skeletal class III malocclusion patients. The questionnaire consisted of general characteristics, clinical manifestation, and T score of Korean version of self-rated Symptom Checklist-90-Revision modified by Jae-hwan Kim. The data were analyzed using SAS version 9.2 and t-test, ANOVA, and ANCOVA were used. Clinical manifestation included subjective recognition and radiological analysis. The subjective recognition of the patients consisted of self-satisfaction of the appearance, phonation, mastication, and temporomandibular joint pain. T score consisted of somatization, obsessive-compulsive, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism. Results: The most serious factor in 9 scales was the severe TMJ pain by ANCOVA. Male patients had a higher T score in phobic anxiety, psyochoticism, somatization and depression than female patients. Those having low appearance satisfaction had the problem in interpersonal sensitivity. Obsessive-compulsive symptoms were conspicuous in phonation difficulty and temporomandibular pain. Conclusions: The patients with skeletal class III malocclusion have more satisfaction with appearance, pronunciation, and phonation than those with skeletal class III malocclusion and overjet. Proper dental treatment will improve the communication and quality of life.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.2
• /
• pp.71-77
• /
• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

• SUVANNABHUMI
• /
• v.6 no.2
• /
• pp.3-18
• /
• 2014

With natural resources-terrestrial or coastal-fastly diminishing, governments are now resorting to biodiversity conservation, fast-tracking the introduction of new legislations, as well as the amendment of existing ones, and laying out programs that interpret existing practices and research agendas. This paper examines how biodiversity conservation-in addition to eco-tourism-has become an important symbol of the modernizing state of Sabah, Malaysia. It further examines the effects of biodiversity conservation on state and community management of natural resources, with particular reference to the management of natural resources by the indigenous peoples of Sabah. Citing case studies and focusing on a forest community at Kiau Nuluh, in the district of Kota Belud, Sabah, this paper evaluates strategies used by indigenous groups to maintain access and control over the management of natural resources-and by implication to livelihoods-via ecotourism, making creative alliances with non-government organisations as well as forging cooperation with government agencies which act as custodians of these resources. For a majority of indigenous groups however, the practice of biodiversity conservation has meant reduced and controlled access to natural resources, considering the fundamental issue of the lack of security of tenure to the land claimed under customary rights. New initiatives at recognizing Indigenous and Community Conserved Areas (ICCAs) by international conservation groups provide a means for tenure recognition, for a price, of course. The recognition of ICCAs also faces obstacles arising from developmentalist ideology which upholds that forests are valuable only when converted to other land use, and not left to stand for their intrinsic value.

• 21st centry Political Science Review
• /
• v.28 no.2
• /
• pp.189-209
• /
• 2018

This study is about Taiwanese Official Development Assistance. This study explains the history, the institution, the policies and several major determinants which affect distribution of Taiwanese ODA. Taiwanese ODA shows several features. State survival, recognition from the international society and competition with China have been main goals of Taiwanese ODA. In addition, the Taiwanese government has tried to promote economic interests in both trade and investment by giving ODAs and by linking them with foreign economic policies. Taiwanese ODA policy has gradually changed from political conerns to more acceptance of international ODA norms and institutions. Especially in the period of MDGs and SDGs, the Taiwanese government has tried to comply with existing and newly developing international ODA norms. This study shows on 'exceptional' case of non OECD-DAC member country's ODA policies. In the future, more studies which compare similarities and differences of OECD DAC members' and non-members' ODA policies will be needed. Based upon more studies, we may find general goals and policies pursued by donor countries.

• International Journal of Computer Science & Network Security
• /
• v.21 no.8
• /
• pp.267-275
• /
• 2021

Smart application is developed in this paper by using an android-based platform to automatically determine the human emergency state (Lifesaver) by using different technology sensors of the mobile. In practice, this Lifesaver has many applications, and it can be easily combined with other applications as well to determine the emergency of humans. For example, if an old human falls due to some medical reasons, then this application is automatically determining the human state and then calls a person from this emergency contact list. Moreover, if the car accidentally crashes due to an accident, then the Lifesaver application is also helping to call a person who is on the emergency contact list to save human life. Therefore, the main objective of this project is to develop an application that can save human life. As a result, the proposed Lifesaver application is utilized to assist the person to get immediate attention in case of absence of help in four different situations. To develop the Lifesaver system, the GPS is also integrated to get the exact location of a human in case of emergency. Moreover, the emergency list of friends and authorities is also maintained to develop this application. To test and evaluate the Lifesaver system, the 50 different human data are collected with different age groups in the range of (40-70) and the performance of the Lifesaver application is also evaluated and compared with other state-of-the-art applications. On average, the Lifesaver system is achieved 95.5% detection accuracy and the value of 91.5 based on emergency index metric, which is outperformed compared to other applications in this domain.

• Journal of the Institute of Convergence Signal Processing
• /
• v.2 no.3
• /
• pp.16-23
• /
• 2001

In this paper, we propose the pseudo n-gram language models for speech recognition with middle size vocabulary compared to large vocabulary speech recognition using the statistical n-gram language models. The proposed method is that it is very simple method, which has the standard structure of ARPA and set the word probability arbitrary. The first, the 1-gram sets the word occurrence probability 1 (log likelihood is 0.0). The second, the 2-gram also sets the word occurrence probability 1, which can only connect the word start symbol and WORD, WORD and the word end symbol . Finally, the 3-gram also sets the ward occurrence probability 1, which can only connect the word start symbol , WORD and the word end symbol . To verify the effectiveness of the proposed method, the word recognition experiments are carried out. The preliminary experimental results (off-line) show that the word accuracy has average 97.7% for 452 words uttered by 3 male speakers. The on-line word recognition results show that the word accuracy has average 92.5% for 20 words uttered by 20 male speakers about stock name of 1,500 words. Through experiments, we have verified the effectiveness of the pseudo n-gram language modes for speech recognition.