• The Journal of Korean Physical Therapy
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• v.14 no.3
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• pp.433-449
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• 2002

노인에 있어 낙상 (falls)의 결과는 신체 기능상의 상실을 가져 올 뿐 아니 라 종종 사망에 이르게 하는 원인이 되기도 하여 중대한 건강상의 문제로 다루어지고 있다. 정상적인 노화과정은 감각(sensory)과 운동 (motor)계의 감퇴 그리고 주의력의 쇠퇴와 연관되어 있는데, 노인들은 이러한 감각(sensory)과 운동(motor)계 (system)의 손상으로 여러 가지 자세(posture)와 보행 (walking)등을 수행하는데 어려움을 겪는다. 또한 노화와 관련된 변화들은 자세를 조절 (postural control) 하는데 있어서 주의력 (attention capacity)을 감소시킨다. 이러한 조건 하에서 노인들은 이중과업 (dual task)을 수행하는데 젊은 사랑들보다도 더 많은 어려움을 느끼며 이는 곧바로 낙상 (falls)의 가능성을 증가시키는 중요한 원인이 되고 있다. 이러한 점들을 고려할 때 낙상(falls)을 방지하기 위한 훈련 프로그램 (training program)은 단순한 신체운동(physical exercise) 보다는 자세조절 (postural control)시의 인지시스템 (cognitive system)이 포함된 중추 통합 기전(central integrative mechanisms)을 최적화 (optimize) 시킬 수 있는 방향으로 구성되어야 한다.

• Speech Sciences
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• v.8 no.4
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• pp.119-129
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• 2001

Language is one aspect of cognition, along with attention and concentration, learning and memory, visuospatial abilities, and executive function. The purpose of this study was to determine the effect of language intervention by cognitive approach on language expressive performance in a patient with conduction aphasia. This study used several tasks such as Attention and concentration task, visual memory tasks, memory tasks, categorization, divergent thinking, self-monitoring and evaluate thinking. The effects of treatment were evaluated by periodic probing of both trained and untrained familiar words in three tasks; picture naming, answering to questions and telling stories. The results showed improvements both in trained and untrained words. Therefore, we concluded that expressive language performance of this aphasic patient is amenable to this intervention, and that cognitive therapy approach can be useful.

• Journal of Information Processing Systems
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• v.9 no.4
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• pp.592-601
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• 2013

Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.22.3-22
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• 2001

An attention task, in which context information should be extracted from the first presented pattern, and the recognition answer of the second presented pattern should be generated using the context information, is employed in this paper. An Elman-type recurrent neural network is utilized to extract and keep the context information. A reinforcement signal that indicates whether the answer is correct or not, is only a signal that the system can obtain for the learning. Only by this learning, necessary context information became to be extracted and kept, and the system became to generate the correct answers. Furthermore, the function of an associative memory is observed in the feedback loop in the Elman-type neural network.

• IEMEK Journal of Embedded Systems and Applications
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• v.17 no.6
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• pp.319-327
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• 2022

Transformers are the most famous deep learning models that has achieved great success in natural language processing and also showed good performance on computer vision. In this survey, we categorized transformer-based models for computer vision, particularly object detection tasks and perform comprehensive comparative experiments to understand the characteristics of each model. Next, we evaluated the models subdivided into standard transformer, with key point attention, and adding attention with coordinates by performance comparison in terms of object detection accuracy and real-time performance. For performance comparison, we used two metrics: frame per second (FPS) and mean average precision (mAP). Finally, we confirmed the trends and relationships related to the detection and real-time performance of objects in several transformer models using various experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.7
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• pp.2407-2424
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• 2022

Recently, Transformer has made great progress in video retrieval tasks due to its high representation capability. For the structure of a Transformer, the cascaded self-attention modules are capable of capturing long-distance feature dependencies. However, the local feature details are likely to have deteriorated. In addition, increasing the depth of the structure is likely to produce learning bias in the learned features. In this paper, an improved Transformer structure named TransDCS (Transformer with Dynamic Convolution and Shortcut) is proposed. A Multi-head Conv-Self-Attention module is introduced to model the local dependencies and improve the efficiency of local features extraction. Meanwhile, the augmented shortcuts module based on a dual identity matrix is applied to enhance the conduction of input features, and mitigate the learning bias. The proposed model is tested on MSRVTT, LSMDC and Activity-Net benchmarks, and it surpasses all previous solutions for the video-text retrieval task. For example, on the LSMDC benchmark, a gain of about 2.3% MdR and 6.1% MnR is obtained over recently proposed multimodal-based methods.

• Journal of Ecology and Environment
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• v.45 no.4
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• pp.293-304
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• 2021

Despite the consumption of bee brood in several parts of the world, particularly in the tropical areas, the practice has received comparatively little attention. We have reviewed all the available information on the nutrient composition and functional properties of different developmental stages of honey bee workers belonging to different species and subspecies. Noticing the competent nutrient composition of, in particular, honey bee brood, pupae, and prepupae, we suggest that they could be a potential source of human nutrition as well as animal feed. Moreover, drone brood is an ideal candidate for use as a food or as food ingredient. However, to analyze the functional properties of different honey bee species remains a task for further analysis.

• Korean Journal of Cognitive Science
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• v.27 no.1
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• pp.1-25
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• 2016

The present study investigated the effect size of attention and consciousness on change detection. We confirmed the effect size of consciousness by comparing the condition which combined attention and consciousness and the condition of attention without consciousness. Then, we confirmed the effect size of attention by comparing the condition of attention without consciousness and the control condition which excluded attention and consciousness. For this purpose, change detection task and continuous flash suppression (CFS) were used. CFS renders a highly visible image invisible. In CFS, one eye is presented with a static stimulus, while the other eye is presented with a series of rapidly changing stimuli, such as mondrian patterns. The result is that the static stimulus becomes suppressed from conscious awareness by the stimuli presented in the other eye. We used a customized device with smartphone and google cardboard instead of stereoscope to trigger CFS. In Experiment 1-1, we reenacted some study to validate our experimental setup. Our experimental setup produced the duration of stimulus suppression that were similar to those of preceding research. In Experiment 1-2, we reenacted a study for attention without consciousness using an customized device. The results showed that attention without consciousness more strongly work as a cue. We think that it is reasonable to use CFS treatment employing smartphone and google cardboard for a follow-up study. In Experiment 2, when performing the change detection task, we measured the effect size of consciousness and attention by manipulating the consciousness level of cue. We used the method in which everything but the variable of interest kept being fixed. That way, the difference this independent variable makes to the action of the entire system can be isolated. We found that there was significant difference of correct response rate on change detection performance among different consciousness level of cue. In this study, we investigated that not only the role of attention and consciousness were different also we were able to estimated the effect size.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.351-357
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• 1994

At least two projects for English-to-Korean translation have been already in action for the last few years, but so far no attention has been paid to the problem of resolving pronominal reference and a default pronoun translation has been considered instead. In this paper we argue that pronous cannot be handled trivially in an English-to-Korean translation and one cannot bypass the task of resolving anaphoric reference if aiming at good and natural translation. In addition, we propose lexical transfer rules for English-to-Korean anaphor translation and outline an anaphora resolution model for an English-to-Korean MT system in operation.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.17 no.30
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• pp.199-208
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• 1994

The needs for manufacturing decisions to be made in a strategic context has been recognized for many years. A manufacturing strategy is made up of many decisions and each of these needs to be considered in the strategic context. Currently in many industrial componies, starategic developments are predominantly based on corporate marketing decisions. Therefore, the attention of manufacturing managers focused primarily upon the day-to-day part of their task. This study suggests a connection scheme between corporate and manufacturing strategy. The essencial role of manufacturing manager is to make compony competitive.