• 한국초등과학교육학회지:초등과학교육
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• 제39권4호
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• pp.494-505
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• 2020

In this study, we surveyed characteristics of the science related collaborative problem solving competency of pre-service elementary teachers, especially required in the digital age. The participants in online survey were 119 pre-service elementary teachers of National University of Education located in Gangwon province. The analyzed results of survey were as follows: First, pre-service teachers performed their task responsibly in collaborative problem solving context related to science. However, they lacked competencies in making rubrics for problem solving processes or outcomes, and setting up rules about team activities. Second, in using ICT technology, the competencies of utilizing tools such as app and software lacked compared with the competencies of searching data in online and using ppt. Third, there was no statistically significant difference among groups by their intensive major in university or selective subject in high school. Nevertheless, pre-service teachers majoring in natural science showed more persistence than those majoring in humanities in problem solving context. Finally, there was no significant gender difference except 'clear communication and accomplishment'. That is, female pre-service teachers performed more responsible in their task and showed more fluency in communication and presentation within their group than male counterparts. Based on these results, implications in the field of pre-service teacher education were discussed.

• 대한임상검사과학회지
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• 제41권3호
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• pp.140-144
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• 2009

Clinical laboratory testing plays a crucial role in the detection, diagnosis, and treatment of disease. Clinical laboratory scientists evaluate test results, develop and modify procedures, and establish and monitor programs, to ensure the accuracy of tests. It is clear that over the past decade the role of the clinical laboratory scientists has expanded and this process will be continued into the future. The purpose of this study is to clarify the factors influencing the job performance of clinical laboratory scientists and aim to provide the role and duties of clinical laboratory scientists. To examine the frequency of work context and the importance of task, the surveys were conducted on 168 clinical laboratory scientists. The questionnaire items were used 10 score by Likert scale. According to the results of this study, the important factor affecting the job performance was "Analyze laboratory findings to check the accuracy of the results", and the next factors were "Establish and monitor quality assurance programs", "Enter data from analyzer into computer", "Calibrate and maintain equipment". And the factors of "repeating same tasks" and "spend time making repetitive motions" were answered the highest. This study will provide strategies for improving work environment, developing education curriculum and method, and role of clinical laboratory scientists. We must continually upgrade our knowledge, and identify the new trends in technology and science and accept changes.

• 서비스연구
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• 제4권1호
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• pp.49-59
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• 2014

상황인식 기술은 유비쿼터스(스마트) 환경에서 지난 수년간 중요한 이슈로 떠오르고 있으며, 현재도 연구자들에 의해 많은 연구가 이루어 지고 있다. 상황인식 기술은 물리적인 환경으로부터 다양한 정보를 획득/가공하여 사용자에게 능동적인 서비스와 정보를 제공하는 컴퓨터 시스템이다. 상황인식 시스템은 각종 센서로부터 발생하는 낮은 수준의 상황정보를 높은 수준의 상황정보로 변환하여 사용자에게 원하는 서비스를 제공하는 환경을 만들어 준다. 본 논문에서는 물리적인 스마트 공간에 존재하는 각종 센서로부터 얻어진 하위단계(Low-level)의 Event-driven 센서정보를 온톨로지 기반 상황정보로 모델링 하여 상위단계(High-level) 상황정보로 변환하는 상황정보를 모델링하여 상황인식 시스템을 구현하였다. 또한 변환된 High-level 상황정보는 가상공간에서 ECA(Event, Condition, Action) 룰에 따라 사용자에게 언제 어디서나 사용자가 필요로 하는 능동적이고 지능적인 서비스를 제공하고, 스마트 홈 환경에서 사용자에게 다양한 가사 도우미 로봇 서비스의 구현 사례를 소개 하였다.

• 한국인터넷방송통신학회논문지
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• 제18권6호
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• pp.133-137
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• 2018

아두이노는 소형 마이컴으로 다양한 산업에 사용되고 있으며 특히, 오픈소스 하드웨어 IoT 디바이스로 널리 사용되고 있다. 아두이노의 멀티태스킹 방식은 크게 수퍼루프 타이밍과 RTOS 쓰레드 방식으로 나뉘며 수퍼루프 타이밍 방식은 구현이 단순하고 이해하기 쉽다는 장점이 있지만 하나의 작업이 길어지면 다음 작업의 실행에 영향을 줄 수 있다는 단점을 가진다. 또 RTOS 쓰레드 방식은 다른 작업시간에 영향을 받지 않고 실행할 수 있다는 장점을 갖지만 소형 마이컴인 아두이노는 쓰레드의 개수가 늘어나면 쓰레드의 컨텍스트 스위칭타임으로 수퍼루프 타이밍 방식에는 없는 부가 시간이 발생하는 단점이 있다. 본 논문은 이와 같은 서로 다른 특징들을 분석하기 위하여 아두이노 우노 R3와 FreeRTOS를 사용하였으며 실험을 위한 태스크는 빌트인 LED 포트에 8000번의 디지털 신호를 보내도록 작성하였다. 같은 크기의 태스크를 두 방식으로 실행하면 수퍼루프 방식이 FreeRTOS 멀티태스킹 보다 3ms 빠른 실행을 보인다. 여러 개의 태스크를 동시에 실행하면 수퍼루프 방식의 태스크는 순차 실행으로 첫 태스크와 마지막 태스크의 실행시간 차가 크게 나타나며 FreeRTOS 방식은 모두 중첩되어 동시에 실행 가능하지만 30ms 정도의 컨텍스트 스위칭타임의 실행 시간지연이 발생한다.

• 감성과학
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• 제16권3호
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• pp.305-310
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• 2013

This user-centered research aims to empirically evaluate color temperature (K) and illuminance (lx) of residential bathroom lightings to determine the most optimal lighting conditions for productive task performance as well as for satisfying users' emotional needs. Using 3 LED lighting fixtures, 4 types of lighting contexts were investigated; main lighting, task lighting, shower lighting, and bath lighting. Two lightings were installed parallel to the vertical edges of the main bathroom mirror to be used as main and task lighting, while another fixture was installed above the bathtub to be used for shower and bathing. For each lighting context, subjects (N＝54) were instructed to perform a few tasks during which time the users were exposed to different lighting conditions with color temperature ranging from 2700 K ~ 6500 K and illuminance ranging from 100 lx ~ 700 lx. Upon completing the given tasks, subjects were asked to evaluate the lighting conditions and their applicability for performing the given tasks. Based on the user evaluations, the most optimal lighting conditions for the different lighting scenarios are as follow: 1) 3500 K ~ 4300 K and 150 lx for main lighting, 2) 3500 K ~ 4300 K and 500 lx ~ 700 lx for task lighting, and 3) 2700 K ~ 3500 K and 100 lx ~ 150 lx for shower/bath lighting. These results can be used to adjust the lighting standards suggested by KS, as well as be utilized by both engineers and designers in designing new types of user-centered bathroom lightings.

• 한국IT서비스학회지
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• 제16권3호
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• pp.103-111
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• 2017

The real time scheduling is a key research area in high performance computing and has been a source of challenging problems. A periodic task is an infinite sequence of task instance where each job of a task comes in a regular period. The RMS (Rate Monotonic Scheduling) algorithm has the advantage of a strong theoretical foundation and holds out the promise of reducing the need for exhaustive testing of the scheduling. Many real-time systems built in the past based their scheduling on the Cyclic Executive Model because it produces predictable schedules which facilitate exhaustive testing. In this work we propose hybrid scheduling method which combines features of both of these scheduling algorithms. The original rate monotonic scheduling algorithm didn't consider the uniform sampling tasks in the real time systems. We have enumerated some issues when the RMS is applied to our hybrid scheduling method. We found the scheduling bound for the hard real-time systems which include the uniform sampling tasks. The suggested hybrid scheduling algorithm turns out to have some advantages from the point of view of the real time system designer, and is particularly useful in the context of large critical systems. Our algorithm can be useful for real time system designer who must guarantee the hard real time tasks.

• International Journal of Advanced Culture Technology
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• 제5권1호
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• pp.83-89
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• 2017

In this paper, we propose an extended method of one-hot Long Short-Term Memory (LSTM) and evaluate the performance on spam filtering task. Most of traditional methods proposed for spam filtering task use word occurrences to represent spam or non-spam messages and all syntactic and semantic information are ignored. Major issue appears when both spam and non-spam messages share many common words and noise words. Therefore, it becomes challenging to the system to filter correct labels between spam and non-spam. Unlike previous studies on information filtering task, instead of using only word occurrence and word context as in probabilistic models, we apply a neural network-based approach to train the system filter for a better performance. In addition to one-hot representation, using term weight with attention mechanism allows classifier to focus on potential words which most likely appear in spam and non-spam collection. As a result, we obtained some improvement over the performances of the previous methods. We find out using region embedding and pooling features on the top of LSTM along with attention mechanism allows system to explore a better document representation for filtering task in general.

• 말소리와 음성과학
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• 제2권4호
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• pp.109-118
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• 2010

Using a speeded classification task (Garner, 1978), we investigated the perceptual interaction of distinctive features in Korean consonants. The main questions of this study were whether listeners can perceptually identify the component features that make up complex consonant sounds, whether these features are processed independently or dependently and whether there is a systematic hierarchy in their dependency. Participants were asked to classify syllables based on their difference in distinctive features in the task. Reaction times for this task were also gathered. For example, participants classified spoken syllables /ta/ and /pa/ as one category and /$t^ha$/ and /$p^ha$/ as another in terms of aspiration condition. In terms of articulation, participants classified /ta/ and /$t^ha$/ as one category and /pa/ and /$p^ha$/ as another. We assumed that the difference between their RTs represents their interdependency. We compared the laryngeal features and place features (Experiment 1), resonance features and place features (Experiment 2), and manner features and laryngeal features (Experiment 3). The results showed that distinctive features were not perceived in a completely independent way, but they had an asymmetric and hierarchical interdependency. The laryngeal features were found to be more independent compared to place and manner features. We discuss these results in the context of perceptual basis in phonology.

• Journal of Information Processing Systems
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• 제17권5호
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• pp.905-917
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• 2021

In recent years, edge computing technology consists of several Internet of Things (IoT) devices with embedded sensors that have improved significantly for monitoring, detection, and management in an environment where big data is commercialized. The main focus of edge computing is data optimization or task offloading due to data and task-intensive application development. However, existing offloading approaches do not consider correlations and associations between data and tasks involving edge computing. The extent of collaborative offloading segmented without considering the interaction between data and task can lead to data loss and delays when moving from edge to edge. This article proposes a range segmentation of dynamic offloading (RSDO) algorithm that isolates the offload range and collaborative edge node around the edge node function to address the offloading issue.The RSDO algorithm groups highly correlated data and tasks according to the cause of the overload and dynamically distributes offloading ranges according to the state of cooperating nodes. The segmentation improves the overall performance of edge nodes, balances edge computing, and solves data loss and average latency.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제10권8호
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• pp.319-330
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• 2021

최근 오픈 도메인 자연어 질문 응답 분야에서는 다중 작업, 다중 홉 질문 응답에 관한 연구들이 활발히 진행되어 오고 있다. 본 논문에서는 이러한 다중 작업, 다중 홉 질문들에 효과적으로 응답하기 위해, 계층적 그래프 기반의 새로운 심층 신경망 모델을 제안한다. 제안 모델에서는 계층적 그래프와 그래프 신경망을 이용해 여러 문단들로부터 서로 다른 수준의 맥락 정보를 얻어낸 후, 이들을 활용하여 답변 유형, 뒷받침 문장들과 답변 영역 등을 동시에 예측해낸다. 본 논문에서는 오픈 도메인 자연어 질문 응답 데이터 집합인 HotpotQA를 이용한 실험들을 통해, 제안 모델의 높은 성능과 긍정적 효과를 입증한다.