• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.2
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• pp.89-97
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• 2013

The green IT technology is being introduced in diverse sectors, especially in the data center and green computer sectors. Rack-type PCs, which have been developed by improving the computer hardware, are effective for data centers and large businesses, but they are not usually introduced in small organizations such as small and medium businesses and schools because they require high initial costs. Power-saving PC software enables the inexpensive power control, but the installation of the power-saving software in all computers in the organization is not an easy task. Computer users in the organization are usually not cooperative as they do not think the power-saving cost is directly related to themselves. In this paper, a technique wherein the server has a restriction in providing the IP address to the computers that has no power-saving software is proposed, so that users will cooperate in the PC power-saving system to avoid inconvenience. In order to provide restricted IP address periodically, the server makes a request of power-saving software installation check for user's PC. Proposed technique is more effective ways to save computer energy, because it does not depend on specific systems or organizations.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.1
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• pp.1-8
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• 2018

Software testing is important to determine the reliability of the system, a task that requires a lot of effort and cost. Model-based testing has been proposed as a way to reduce these costs by automating test designs from models that regularly represent system requirements. For each path of model to generate an input value to perform a test, meta-heuristic technique is used to find the test data. In this paper, we propose an automatic test data generation method using a slicing method and a priority policy, and suppress unnecessary computation by excluding variables not related to target path. And then, experimental results show that the proposed method generates test data more effectively than conventional method.

• 전기의세계
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• v.28 no.8
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• pp.66-71
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• 1979

This paper describes electrical analysis of the information processing of the nervous system. A general-purpose electrical neuronal model for simulating the electrical activity in a single nerve cell and in small groups of nerve cell has constructed. This model consists of two basic electronic modules to represent respectively a "cell body" and an "axon (with synapses)", together with various related appurtenances. The primary advantages of this method are; holistic view, actual physical representation of various electrical activities in a single nerve cell, display of the activity of all nerve cells flexibility with respect to network parameters. Moreover, this model can effectively help push forward our general ability to explore and conceptualize the electrical activity of interconnected networks of nerve cell behaving in concert. Also, this electronic module technique is the best of various means for this task of realistic representation of aggregates of neurons.gregates of neurons.

• Electronics and Telecommunications Trends
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• v.35 no.3
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• pp.9-19
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• 2020

Recently, a technique for applying a deep learning language model pretrained from a large corpus to fine-tuning for each application task has been widely used as a language processing technology. The pretrained language model shows higher performance and satisfactory generalization performance than existing methods. This paper introduces the major research trends related to deep learning pretrained language models in the field of language processing. We describe in detail the motivations, models, learning methods, and results of the BERT language model that had significant influence on subsequent studies. Subsequently, we introduce the results of language model studies after BERT, focusing on SpanBERT, RoBERTa, ALBERT, BART, and ELECTRA. Finally, we introduce the KorBERT pretrained language model, which shows satisfactory performance in Korean language. In addition, we introduce techniques on how to apply the pretrained language model to Korean (agglutinative) language, which consists of a combination of content and functional morphemes, unlike English (refractive) language whose endings change depending on the application.

• Journal of Computing Science and Engineering
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• v.9 no.2
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• pp.73-82
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• 2015

Understanding how the topic evolves is an important and challenging task. A topic usually consists of multiple related events, and the accurate identification of event evolution relationship plays an important role in topic evolution analysis. Existing research has used the traditional vector space model to represent the event, which cannot be used to accurately compute the semantic similarity between events. This has led to poor performance in identifying event evolution relationship. This paper suggests constructing a semantic aspect-based vector space model to represent the event: First, use hierarchical Dirichlet process to mine the semantic aspects. Then, construct a semantic aspect-based vector space model according to these aspects. Finally, represent each event as a point and measure the semantic relatedness between events in the space. According to our evaluation experiments, the performance of our proposed technique is promising and significantly outperforms the baseline methods.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2014.11a
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• pp.100-101
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• 2014

The generation of 3D models for freeform buildings is an important task while continuous monitoring of the related spatial information at different time phases. Realistic models of freeform building have to provide high geometric accuracy and detail at an effective data size.(Al-kheder, S. 2008) The efficiency of this image-based technique has been increased considerably by the development of digital technologies. Furthermore, 3D data collection based on laser scanning has become an high quality 3D models for construction site. Therefore, in this research, we have an effort to review construction methods to make freeform envelope of building using 3D scanning technology.

• Journal of the Korean Society of Safety
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• v.17 no.4
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• pp.173-177
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• 2002

THERP (Technique for Human Error Rate Prediction) methodology has been widely used for probabilistic safety assessments. The NUREG report involving this methodology is also called the HRA handbook. The THERP assumes that all actions involved in implementing a task are considered as components. In this paper human error rates associated with maintenance are evaluated by the THERP methodology. A gas governor system is used as an example which is also a risky system like nuclear power plants. It is also demonstrated that this approach is flexible in that it can be applied to any operator actions related to test and maintenance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1255-1258
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• 2022

Recently, immersive VR/AR contents have actively increased, and various services related to VR/AR allow users to experience remote places. For example, if failure situations occur frequently in factory of the remote site, mixed reality (MR) with a synthetic virtual human expert in reconstructed remote location can help immediate maintenance task with interaction between the operator and the virtual expert. In this paper, we present a technique for synthesizing the virtual human after capturing a 360-degree panorama of a remote environment, and analyze the effects to apply a method of guiding virtual human by interaction types. According to this paper, it was shown that co-presence level significantly increased when verbal, facial expression, and non-verbal animation of the virtual human was all expressed.

• Journal of Construction Engineering and Project Management
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• v.8 no.1
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• pp.10-21
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• 2018

Many construction projects involve a plethora of safety-related problems that can cause loss of productivity, diminished revenue, time overruns, and legal challenges. Incorporating data collection and analytics methods can help overcome the root causes of many such problems. However, in a dynamic construction workplace collecting data from a large number of resources is not a trivial task and can be costly, while many contractors lack the motivation to incorporate technology in their activities. In this research, an Android-based mobile application, Preemptive Construction Site Safety (PCS2) is developed and tested for real-time location tracking, trajectory prediction, and prevention of potential collisions between workers and site hazards. PCS2 uses ubiquitous mobile technology (smartphones) for positional data collection, and a robust trajectory prediction technique that couples hidden Markov model (HMM) with risk-taking behavior modeling. The effectiveness of PCS2 is evaluated in field experiments where impending collisions are predicted and safety alerts are generated with enough lead time for the user. With further improvement in interface design and underlying mathematical models, PCS2 will have practical benefits in large scale multi-agent construction worksites by significantly reducing the likelihood of proximity-related accidents between workers and equipment.

• Therapeutic Science for Rehabilitation
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• v.9 no.2
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• pp.7-25
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• 2020

Objective : The purpose of this study was to analyze the effects of dual-task training on stroke patients. Methods : We searched the databases such as NDSL, RISS, PubMed, CoChrane and EMBASE for publications in the past decade. Finally, 10 papers were selected. Qualitative assessment was performed according to the traditional single-layer evidence model, and meta-analysis was performed using the Comprehensive Meta Analysis 3.0 program. Results : The quality level of each of the 10 selected papers all correspond to I and II in the traditional single-layer evidence model. The motor tasks that constitute dual-task training comprised walking or balancing tasks in 7 articles and the motor tasks related to upper extremity were selected in 3 studies. The effect sizes for ADL function and Cognitive function were 0.65 and 0.64 (medium size effect) respectively. Moreover, the effect sizes of Lower extremity and Upper extremity motor function were 0.34 and 0.22 (small size effect) respectively. The effect size of ADL function and Cognitive function were statistically significant p<0.05). Conclusion : This study confirmed that dual-ask training can be a useful intervention technique for recovering a stroke patient's ability to perform daily activities and cognitive functions. This could be used as a helpful data when selecting appropriate intervention for stroke patients in the clinical setting.