• 한국정보과학회논문지:소프트웨어및응용
• /
• 제33권2호
• /
• pp.201-219
• /
• 2006

높은 소프트웨어의 품질은 유지하면서, 최소한의 비용으로 소프트웨어를 개발하기 위해서는 소프트웨어 개발 프로젝트의 상황에 알맞은 프로세스를 적용하는 것이 중요하다. 일반적으로 상용 프로세스나 조직의 표준 프로세스를 프로젝트팀에 적용하고 있으나, 대부분의 경우, 경험부족이나 인력부족 등의 이유로 일반적인 프로세스를 어떤 가감도 없이 그대로 적용함으로써 오히려 소프트웨어 개발에 있어서 오버헤드를 초래하고 있다. 프로세스 테일러링 작업을 수행하는 경우에도, 대부분의 테일러링 작업은 몇몇 프로세스 엔지니어의 경험에 의존하는 실정이다. 이런 경우, 테일러링 결과로서의 프로세스는 얻을 수 있으나 타당한 근거를 제시하기 힘들고, 많은 시간을 요한다. 따라서 본 논문에서는 인공신경망 기반의 학습이론을 프로세스 테일러링에 적용함으로써 테일러링 작업 중에서도 많은 시간을 필요로 하는 프로세스 필터링 작업을 자동화하는 방안을 소개하고 있다. 뿐만 아니라 필터링된 프로세스를 재구성하여 그 결과 얻어지는 프로젝트 상황에 적합하게 테일러링된 프로세스를 실제 프로젝트에 적용한 후 얻을 수 있는 피드백 자료를 학습의 자료로 다시 사용함으로써, 인공신경망의 정확도를 높여나가는 방법까지를 제시하고 있다. 본 논문에서는 이렇게 제시한 소프트웨어 개발 프로세스의 테일러링 방법의 실효성을 충분한 샘플자료를 바탕으로 한 실질적인 적용례를 통해 입증하고 있다.

• 한국생활과학회지
• /
• 제21권5호
• /
• pp.837-848
• /
• 2012

This study evaluated the types of daily routines that occurred in child care centers based on four general categorizations: time spent on indoor free choice activities, outdoor activities, group activities and special activities. In addition, resulting child care teacher behaviors were examined based on daily routine types. A total 23 classes' activity times and teacher behaviors were observed. The collected data were analyzed using descriptive statistics, hierarchical cluster, and Mann-Whitney U. Results indicated that there were 2 principle daily routine, 'indoor/outdoor activity time oriented' and 'group activity time oriented'. Analysis showed that teachers who belonged to the 'indoor/outdoor activity time oriented' type showed more positive affect, positive guidance, neural guidance, and less non-involved behavior. Results suggest the importance of time spent on free choice activities in the context of daily routine for quality childcare.

• 대한의생명과학회지
• /
• 제13권4호
• /
• pp.273-278
• /
• 2007

Stem cells have been the subject of increasing scientific interest because of their utility in numerous biomedical applications. Stem cells are capable of renewing themselves; that is, they can be continuously cultured in an undifferentiated state, giving rise to more specialized cells of the human body. Therefore, stem cells are an important new tools for developing unique, in vitro model systems to test drugs and chemicals and a potential to predict or anticipate toxicity in humans. In the present study, in vitro cultured F3 immortalized human neural stem cell line and in vivo adult Sprague Dawley rats was used to evaluate the cytotoxicity of anticancer drug paclitaxel. In vitro apoptotic activity of paclitaxel was evaluated in F3 cell line by a MTT assay and DAPI test. The cell death was induced with the treatment of 20 nM paclitaxel and chromatin degradation was detected by DAPI staining, which was analyzed by fluorescent microscope. In vivo studies, we also observed nestin immunoreactivity on subventricular zone, which is stem cell rich region in the adult brain of the SD rat. Immunofluorescent staining result shows that pixel intensities of nestin were decreased in a dose dependent manner. These results suggest that paclitaxel is able to induce cytotoxic activity both in F3 neural stem cell line and neural stem cell in SD rat brain.

• The Korean Journal of Physiology
• /
• 제27권1호
• /
• pp.79-91
• /
• 1993

The present study was carried out to determine the effects of cocaine (0.25, 1.0, 10.0 mg/kg, i.p.) on the interactions between spontaneously active neurons within ensembles of simultaneously recorded neurons in the primary somatosensory cortex (Sl, n= 20) and the ventroposterolateral (VPL, n= 16) thalamic nucleus of awake rats. Spike triggered cross correlation histograms were constructed between pairs of simultaneously recorded neurons. Among 101 neuronal pairs analyzed, 22.7% showed correlations indicative of various functional connections among the cortical cells, two corticothalamic interactions and one thalamocortical excitatory interaction. There were also 15 cofiring activities among SI cortical cells. These functional connectivities appeared to be modulated (weakened, abolished, or strengthened) during the 5 to 30 min following cocaine injection. The effects of saline were tested as a control, but it did not appear to alter the functional connectivities. In general, cocaine-induced changes of the functional interactions were mainly due to the concomitant alterations of the uncorrelated background discharges. These results suggest that the biphasic effects of cocaine on the spontaneously established neural networks among the SI cortical and the VPL thalamic cells of conscious rat were mainly indirect. However, various changes of the functional interactions by different doses of cocaine appeared to be a possible neural network mechanism for the cocaine induced modulation of afferent somatosensory transmission.

• 대한인간공학회지
• /
• 제35권4호
• /
• pp.225-235
• /
• 2016

Objective: The aim of this study is to model all levels of situation awareness (SA), which would be able to predict situation awareness quantitatively. Background: When measuring situation awareness, directly measuring SA methods such as SAGAT and SART have been utilized. Several approaches (cognitive modeling approaches) were introduced to model SA but level 3 SA was not completed. For real-life situation, however, it is necessary to detect the problematic level of SA rather than overall SA. Therefore, we proposed a new model of all levels of SA in this study. Method: In order to model all levels of SA, this study chose factors in ACT-R architecture through literature review. ATC (Air Traffic Control)-related simulation task was video-taped to analyze human behaviors in order to model all levels of SA including level 3. Results: As a result, regression analyses show that cognitive activities (neural activations) represented for all levels of SA were highly correlated with SAGAT. Conclusion: In conclusion, neural activations in ACT-R could be proved to be effective to model all levels of SA. Application: Our SA model could be used to predict all levels of SA quantitatively without directly measuring the SA of operators.

• 한국멀티미디어학회논문지
• /
• 제20권8호
• /
• pp.1291-1298
• /
• 2017

Optical coherence tomography (OCT) is the most common medical imaging device with the ability to image the retina in eyes at micrometer resolution and to visualize the pathological indicators of many retinal diseases such as Age-Related Macular Degeneration (AMD) and diabetic retinopathy. Accordingly, there have been research activities to analyze and process OCT images to identify those indicators and make medical decisions based on the findings. In this paper, we use a deep convolutional neural network for analysis of OCT volume data to distinguish AMD from normal patients. We propose a novel approach where images in each OCT volume are grouped together into sub-volumes and the network is trained by those sub-volumes instead of individual images. We conducted an experiment using public data set to evaluate the performance of the proposed approach. The experiment confirmed performance improvement of our approach over the traditional image-by-image training approach.

• 대한수학교육학회지:수학교육학연구
• /
• 제20권1호
• /
• pp.21-43
• /
• 2010

본고에서는 인식론의 여러 분야인 선천주의(nativism), 경험주의(empiricism), 구성주의(constructivism) 등이 신경생물학적으로 어떻게 대응되어 나타나는가를 고찰하고, 그들 주장의 장단점을 살펴본다. 두 번째로 위의 이론들을 통해 수학교육의 기본이 되는 수인지(numerical/mathematical cognitipn) 분야를 소개하고 현재 연구 동향과 수학교육에의 적용을 모색한다. 이어서 fMRI 등의 뇌영상 촬영기법 등을 통해 현재까지 알려진 기초 대수적 활동과 관련된 두뇌 영역을 확정해보고자 한다.

• Journal of Multimedia Information System
• /
• 제3권3호
• /
• pp.91-96
• /
• 2016

Network security is an interesting area in Information Technology. It has an important role for the manager monitor and control operating of the network. There are many techniques to help us prevent anomaly or malicious activities such as firewall configuration etc. Intrusion Detection System (IDS) is one of effective method help us reduce the cost to build. The more attacks occur, the more necessary intrusion detection needs. IDS is a software or hardware systems, even though is a combination of them. Its major role is detecting malicious activity. In recently, there are many researchers proposed techniques or algorithms to build a tool in this field. In this paper, we improve the performance of IDS. We explore and analyze the impact of activation functions applying to recurrent neural network model. We use to KDD cup dataset for our experiment. By our experimental results, we verify that our new tool of IDS is really significant in this field.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제11권12호
• /
• pp.5878-5904
• /
• 2017

This paper proposes a novel intelligent wheelchair vehicle system that enables upper limb exercises, lower limb standing exercises and rehabilitation training in a daily life. The proposed system, which can be used to prevent at least the degeneration of body movements and further atrophy of musculoskeletal system functions, considers the characteristics and mobility of the old and the disabled. Its main purpose is to help the old and the disabled perform their daily activities as much as they can, minimizing the extent of secondary disabilities. In other words, the system will provide the old and the disabled with regular and quantitative rehabilitation exercises and diagnosis using the wheelchair-based upper/lower limb rehabilitation vehicle system and then verify their effectiveness. The system comprises an electric wheelchair, a biometric module to identify individual characteristics, and an upper/lower limb rehabilitation vehicle. In this paper the design and configuration of the developed vehicle is described, and its operation method is presented. Moreover, to verify the tracking performance of the proposed system, dangerous situations according to biosignal changes occurring during the rehabilitation exercise of a non-disabled examinee are analyzed and the performance of the upper/lower limb rehabilitation exercise function depending on muscle strength is evaluated through a neural network algorithm.

• 전기전자학회논문지
• /
• 제24권2호
• /
• pp.523-528
• /
• 2020

스마트 모바일 장치의 확산은 인간의 일상 행동 분석을 보다 일반적이고 간단하게 만들었다. 행동 분석은 이미 본인 인증, 감시, 건강 관리 등 많은 분야에서 사용 중이고 그 유용성이 증명되었다. 본 논문에서는 스마트폰의 가속도 센서 신호를 사용하여 효율적이고 정확하게 행동 인식을 수행하는 합성곱 신경망(모델 A)과 순환 신경망까지 적용한(모델 B) 심층 신경망 모델을 제시한다. 모델 A는 batch normalization과 같은 단순한 기법만 적용해도 이전의 결과보다 더 작은 모델로 더 높은 성능을 달성할 수 있다는 것을 보인다. 모델 B는 시계열 데이터 모델링에 주로 사용되는 LSTM 레이어를 추가하여 예측 정확도를 더욱 높일 수 있음을 보인다. 이 모델은 29명의 피실험자를 대상으로 수집한 벤치마크 데이트 세트에서 종합 예측 정확도 97.16%(모델 A), 99.50%(모델 B)를 달성했다.