• 한국학교수학회논문집
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• 제22권3호
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• pp.241-256
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• 2019

본 연구는 '확률과 통계' 교과서에 제시된 과제의 맥락 유형과 과제를 수행할 때 요구되는 인지적 역량이 학생들에게 어떠한 학습기회를 제공하는지 살펴보았다. 이를 위해 2015 개정 수학과 교육과정에 따른 '확률과 통계' 검정교과서 전체 9권을 분석한 결과, 맥락 기반 과제(CF유형, RE유형)는 각 교과서마다 전체 과제 개수의 67.5%부터 78.0%로 나타났지만 실생활에 연관된 본질적인 과제(RE유형) 비율은 0.4%부터 2.0%로 나타나 교과서에 제시된 대부분의 맥락 기반 과제는 실생활 소재를 위장한 과제임을 알 수 있었다. 그리고 맥락 기반 과제의 인지적 역량은 각 교과서마다 재생산(Rp)범주에 속하는 과제 비율은 29.6%부터 50.0%로 다양하게 나타났고, 연결(Co)범주 과제 비율은 33.8%부터 54.3%, 반성(Rf)범주 과제 비율은 8.8%부터 20.0%로 나타나 과제수행 시 학생들이 반성적 인지 과정을 경험할 수 있는 학습기회는 다소 충분하지 않음을 알 수 있었다.

• 디지털융복합연구
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• 제12권11호
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• pp.265-272
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• 2014

본 논문에서는 다중센서를 사용한 솔라셀 장비의 상황인지 시스템을 설계하여 산업현장에서 발생할 수 있는 다양한 산업재해를 예방하고 대처하기 위한 시스템을 제안한다. 솔라셀 장비의 주변 및 주요 위치에 다중 센서를 설치하고, 이러한 장치로부터 주변상황과 솔라셀 장비에 대한 데이터를 획득하여 로컬메모리에 저장 후 서버에 전송한다. 저장된 데이터는 상황인지 알고리즘에 의하여 상황을 인지하고 인지된 결과에 따라 판단한다. 관리자는 상황인지 알고리즘을 통해 판단 된 결과에 따라 실시간으로 생산현장과 장비들에 대한 상태를 모니터링 할 수 있는 환경을 갖게 된다. 오늘날 유비쿼터스 환경에 놓인 산업현장의 상황인지 시스템은 실시간 점검을 통해 산업재해에 대처하기 위한 적절한 정보를 제공하는 서비스가 될 것이다.

• 한국초등과학교육학회지:초등과학교육
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• 제33권2호
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• pp.217-230
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• 2014

This study explores the features of sociocultural context of experiment classes taught by a science subject teacher. Two experiment classes on electric circuit for fifth graders were observed and video recorded. The data was also collected through student interviews and teacher interviews. Using the cultural historical activity theory, we extracted the six sociocultural factors and analyzed their interactions. This study could identify that four features of the sociocultural context of the cases. First, the rules of science classes were not decided by the teacher, but formed and modified through the negotiation between the teacher and students or between the students. Second, elementary students played a game, i.e. 'Countdown game', during their electricity experiments, which had both positive and negative influences on science learning. Third, the science teacher feels a limit on life guidance because of the position as a subject teacher in an elementary school. Lastly, although the science teacher had enough time to prepare science classes, there was no guarantee of the improvement of teaching quality. Based on the results of this study, educational implications are discussed in terms of teaching science experiments and of the science subject teacher system.

• 한국초등과학교육학회지:초등과학교육
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• 제37권1호
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• pp.39-53
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• 2018

The purpose of this study was to investigate the conceptual structure of subjects related to matter having pre-service elementary school teachers by applying semantic network analysis (SNA). The analyzed concepts in the subjects of matter were 6 words such as 'atom', 'molecule', 'ion', 'electron', 'matter' and 'particle'. The results of SNA of the concepts are as follows : 1. In the semantic network of 'atom', words having a high betweenness centrality were linked with the words based on both the scientific context and the everyday context. 2. The network of 'molecule' was analyzed to be more organized than the network of the 'atom'. 3. In the network of 'ion', the group of words of the scientific context was distinguished from the group of words of the everyday context. 4. The network of 'electron' was analyzed to be more oriented on electricity and magnetism in the field of physics. 5. In the network of 'matter', the words related to compounds were linked with knowledge of history of science. 6. The network of 'particle' was not structured with words based on particulate nature of matter.

• 한국음향학회지
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• 제32권2호
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• pp.174-180
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• 2013

본 논문은 HMM 기반의 TTS 시스템을 위하여 상호유사도 비율을 이용한 결정트리 기반의 문맥 군집화 알고리즘을 제안한다. 기존의 알고리즘들은 유사한 통계적 특성을 가지는 문맥종속 HMM을 하나로 묶고 있다. 그러나 기존의 알고리즘들은 결정트리의 나누어진 노드간의 통계적 유사도를 고려하지 않음으로 인하여 최종 노드 사이의 통계적인 차이를 보장하지 못한다. 제안한 알고리즘은 분리된 노드들 간의 통계적 유사도를 최소화하여 모델 파라미터의 신뢰도를 향상시킨다. 실험 결과를 통해 제안한 알고리즘이 기존의 알고리즘들에 비해 우수한 성능을 나타낸다는 것을 확인할 수 있다.

• 전기학회논문지
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• 제65권12호
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• pp.2218-2224
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• 2016

Opportunistic routing is designed for an environment where there is no stable end-to-end routing path between source node and destination node, and messages are forwarded via intermittent contacts between nodes and routed using a store-carry-forward mechanism. In this paper, we consider PRoPHET(Probabilistic Routing Protocol using History of Encounters and Transitivity) protocol as a base opportunistic routing protocol and propose an efficient context-aware opportunistic routing protocol by using the context information of delivery predictability and node type, e.g., pedestrian, car, and tram. In the proposed protocol, the node types of sending node and receiving node are checked. Then, if either sending node or receiving node is tram, messages are forwarded by comparing the delivery predictability of receiving node with predefined delivery predictability thresholds depending on the combination of sending node and receiving node types. Otherwise, messages are forwarded if the delivery predictability of receiving node is higher than that of sending node, as defined in PRoPHET protocol. Finally, we analyze the performance of the proposed protocol from the aspect of delivery ratio, overhead ratio, and delivery latency. Simulation results show that the proposed protocol has better delivery ratio, overhead ratio, and delivery latency than PRoPHET protocol in most of the considered simulation environments.

• 대한인간공학회지
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• 제26권2호
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• pp.61-66
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• 2007

The networked home is connected to the external world using a high speed network. The devices inside the house are connected using a wired and wireless network. Acquiring the user data is an essential step for designing the user interface in user centered design. In networked home, the numbers of use cases are exponentially increased because connected use cases are considered. Because the user data for networked home are too complicated, they are acquired and analyzed by a structured methodology. We surveyed 40 people to acquire the context data home and analyzed by 5W1H (Who, Where, What, When, Why, How). We established a framework for the user data using tasks, user, time, space, objects and environment. The data for home context was structured by our framework. This framework makes simple the home context and is helpful for user interface design in home network.

• ETRI Journal
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• 제42권2호
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• pp.230-238
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• 2020

Human-object interaction (HOI) detection is a popular computer vision task that detects interactions between humans and objects. This task can be useful in many applications that require a deeper understanding of semantic scenes. Current HOI detection networks typically consist of a feature extractor followed by detection layers comprising small filters (eg, 1 × 1 or 3 × 3). Although small filters can capture local spatial features with a few parameters, they fail to capture larger context information relevant for recognizing interactions between humans and distant objects owing to their small receptive regions. Hence, we herein propose a three-stream HOI detection network that employs a context convolution module (CCM) in each stream branch. The CCM can capture larger contexts from input feature maps by adopting combinations of large separable convolution layers and residual-based convolution layers without increasing the number of parameters by using fewer large separable filters. We evaluate our HOI detection method using two benchmark datasets, V-COCO and HICO-DET, and demonstrate its state-of-the-art performance.

• 가족자원경영과 정책
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• 제20권2호
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• pp.165-184
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• 2016

This study was conducted to identify factors which predict and discriminate women' reemployment. 288 married women whose careers had been interrupted for more than 1 year and 287 married women who re-entered into the labor market within 5 years were surveyed. Collected data were analyzed by logistic regression analysis. In the personal factor(reemployment need), proximal context factors(career barriers, family support and expectation for reemployment) and background context factors(SES, family life cycle), background context factors were revealed not to predict significantly women's reemployment. Secondly, in the case of proximal context factors, it was found that 'expectation of family members for reemployment' and 'sharing family care' had strong effects on reemployment. And compared with interrupted women, reemployed women were less likely to perceive career barriers. Specifically, they showed lower expectation to their job and status which they would achieve, less perceived gender/age discrimination in labor market, and had more confidence that they could find a job. Finally, with regard to the personal factor (reemployment need), the lower women had self-actualization need, the higher economic need, and the higher social need, it was highly likely to classify into reemployed women. We discussed the way to improve reemployment of career interrupted women based on above mentioned findings.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권2호
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• pp.383-403
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• 2021

With the development of mobile edge computing (MEC), some late-model application technologies, such as self-driving, augmented reality (AR) and traffic perception, emerge as the times require. Nevertheless, the high-latency and low-reliability of the traditional cloud computing solutions are difficult to meet the requirement of growing smart cars (SCs) with computing-intensive applications. Hence, this paper studies an efficient offloading decision and resource allocation scheme in collaborative vehicular edge computing networks with multiple SCs and multiple MEC servers to reduce latency. To solve this problem with effect, we propose a context-aware offloading strategy based on differential evolution algorithm (DE) by considering vehicle mobility, roadside units (RSUs) coverage, vehicle priority. On this basis, an autoregressive integrated moving average (ARIMA) model is employed to predict idle computing resources according to the base station traffic in different periods. Simulation results demonstrate that the practical performance of the context-aware vehicular task offloading (CAVTO) optimization scheme could reduce the system delay significantly.