• Journal of the Korean housing association
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• v.26 no.2
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• pp.47-56
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• 2015

Traditional Hanok in modern society, depending on the improvement of economic and cultural level is evolving as a modern Hanok. An ideal of traditional Hanok and convenience of a modern housing does not match rather conflicting. This study deals the transformation of a new Hanok, which are build in Jeollanam-do province sponsored by local government from 2007. The subjects was selected 34 cases from Sunchon and Damyang which are build sponsored by Jeollanam-do local government from 2009 to 2011. The report is a design drawing of a Hanok, architectural survey of the Hanok research using questionnaires and interviews with the client or a resident, was confirmed by a visit to check and verify for each Hanok houses. Outside shape classification of Hanok were classified as straight, L type, and the interior space was analyzed by focusing on the living room, dining room, kitchen configuration consisting of housing space in public life. This study and the type of Hanok round out the framework from the perspective of residence' demands and realize new Hanok investigated and the evolution of the process is meaningful to find a Hanok.

• Journal of Labour Economics
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• v.38 no.3
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• pp.53-95
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• 2015

This paper first constructs an occupation code-skill match for the Korean labor market by following Autor-Dorn classification on the tasks framework. Over the last 34 years, middle-skill jobs have vanished enormously, while high-skill and low-skill jobs have both increased. Also, jobs have polarized more rapidly in recessions and changed uniquely by pushing old workers into middle and low-skilled jobs and the inter-sector reallocation of workers. Furthermore, jobless recoveries in the recent business cycle could have been alleviated considerably if job polarization had been mitigated.

• IEMEK Journal of Embedded Systems and Applications
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• v.8 no.2
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• pp.121-128
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• 2013

There have been various research efforts for pedestrian recognition in embedded imaging systems. However, many suffer from their heavy computational complexities. SVM classification method has been widely used for pedestrian recognition. The reduction of candidate region is crucial for low-complexity scheme. In this paper, We propose a real time HOG based pedestrian detection system on GPU which images are captured by a pair of cameras. To speed up humans on road detection, the proposed method reduces a number of detection windows with disparity-search and near-search algorithm and uses the GPU and the NVIDIA CUDA framework. This method can be achieved speedups of 20% or more compared to the recent GPU implementations. The effectiveness of our algorithm is demonstrated in terms of the processing time and the detection performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3806-3825
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• 2016

This paper brings out a neoteric frame of reference for visual semantic based 3d video search and retrieval applications. Newfangled 3D retrieval application spotlight on shape analysis like object matching, classification and retrieval not only sticking up entirely with video retrieval. In this ambit, we delve into 3D-CBVR (Content Based Video Retrieval) concept for the first time. For this purpose we intent to hitch on BOVW and Mapreduce in 3D framework. Here, we tried to coalesce shape, color and texture for feature extraction. For this purpose, we have used combination of geometric & topological features for shape and 3D co-occurrence matrix for color and texture. After thriving extraction of local descriptors, TB-PCT (Threshold Based- Predictive Clustering Tree) algorithm is used to generate visual codebook. Further, matching is performed using soft weighting scheme with L₂ distance function. As a final step, retrieved results are ranked according to the Index value and produce results .In order to handle prodigious amount of data and Efficacious retrieval, we have incorporated HDFS in our Intellection. Using 3D video dataset, we fiture the performance of our proposed system which can pan out that the proposed work gives meticulous result and also reduce the time intricacy.

• Journal of Electrical Engineering and Technology
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• v.11 no.6
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• pp.1857-1862
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• 2016

Human activity recognition using depth information is an emerging and challenging technology in computer vision due to its considerable attention by many practical applications such as smart home/office system, personal health care and 3D video games. This paper presents a novel framework of 3D human body detection, tracking and recognition from depth video sequences using spatiotemporal features and modified HMM. To detect human silhouette, raw depth data is examined to extract human silhouette by considering spatial continuity and constraints of human motion information. While, frame differentiation is used to track human movements. Features extraction mechanism consists of spatial depth shape features and temporal joints features are used to improve classification performance. Both of these features are fused together to recognize different activities using the modified hidden Markov model (M-HMM). The proposed approach is evaluated on two challenging depth video datasets. Moreover, our system has significant abilities to handle subject's body parts rotation and body parts missing which provide major contributions in human activity recognition.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.9
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• pp.47-52
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• 2020

With the 4th industrial revolution, condition monitoring using machine learning techniques has become popular among researchers. An overload due to complex operations causes several irregularities in MOSFETs. This study investigated the acquired voltage to analyze the overcurrent effects on MOSFETs using a failure mode effect analysis (FMEA). The results indicated that the voltage pattern changes greatly when the current is beyond the threshold value. Several features were extracted from the collected voltage signals that indicate the health state of a switched-mode power supply (SMPS). Then, the data were reduced to a smaller sample space by using a principal component analysis (PCA). A robust machine learning algorithm, the support vector machine (SVM), was used to classify different health states of an SMPS, and the classification results are presented for different parameters. An SVM approach assisted by a PCA algorithm provides a strong fault diagnosis framework for an SMPS.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.201-220
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• 2020

Trackers, especially long-term (LT) trackers, now have a more complex structure and more intensive computation for nowadays' endless pursuit of high accuracy and robustness. However, computing efficiency of LT trackers cannot meet the real-time requirement in various real application scenarios. Considering heterogeneous CPU-GPU platforms have been more popular than ever, it is a challenge to exploit the computing capacity of heterogeneous platform to improve the efficiency of LT trackers for real-time requirement. This paper focuses on TLD, which is the first LT tracking framework, and proposes an efficient parallel implementation based on OpenCL. In this paper, we firstly make an analysis of the TLD tracker and then optimize the computing intensive kernels, including Fern Feature Extraction, Fern Classification, NCC Calculation, Overlaps Calculation, Positive and Negative Samples Extraction. Experimental results demonstrate that our efficient parallel TLD tracker outperforms the original TLD, achieving the 3.92 speedup on CPU and GPU. Moreover, the parallel TLD tracker can run 52.9 frames per second and meet the real-time requirement.

• Journal of Korean Institute of Industrial Engineers
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• v.25 no.1
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• pp.87-99
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• 1999

A shop floor control system(SFCS) performs the production activities required to fill orders. In order to effectively control these activities, the autonomous agent-based heterarchical shop floor control architecture is adopted where a supervisor does not exist. In this paper, we define functional perspective of the heterarchical shop floor control using planning, scheduling, and execution modules. In particular, we focus on an execution module that can coordinate the planning and scheduling modules and a general execution module that easily can be modified to execute the other equipment. The execution module can be defined informally as a module that downloads and performs a set of scheduled tasks. The execution module is also responsible for identifying and resolving various errors whether they come from hardware or software. The purpose of this research is to identify all the execution activities and solving techniques under the assumptions of the heterarchical control architecture. And we model the execution module in object-oriented modelling technique for generalization. The execution module modeled in object-oriented concept can be adopted to the other execution module easily. This paper also proposes a classification scheme for execution activities of the heterarchical control architecture. Petri-nets are used as a unified framework for modeling and controlling execution activities. For solving the nonexistence of a supervisor, a negotiation-based solution technique is utilized.

• Korean Journal of Cognitive Science
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• v.11 no.1
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• pp.9-24
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• 2000

This paper analyzes the distribution and classification of unrealized arguments of a predicate often called zero pronouns. in spoken Korean. Based on the transcript of a one-hour-Iong dialogue. recorded from public radio stations. I present the statistical data on argument ellipsis in Korean with respect to the frequency of zero ronouns as well as the nature of their antecedents. I go further to review some of the previous efforts to identify the discourse- theoretic functions of zero-pronouns in the framework of Centering Theory. and propose that the zero-pronouns in spoken Korean be divided into center-insensitive vs. center-sensitive classes. I also point out a couple of language-particular idiosyncrasies found in Korean, such as morpho-syntactic elements and encyclopaedic knowledge. that interact with center management in on-going discourse and often lead to difficulties in applying the centering rules and constraints to Korean.

• Journal of Korean Library and Information Science Society
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• v.37 no.3
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• pp.193-208
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• 2006

The customer satisfaction. which is close with the loyalty, rate of disconnection and re-purchase and the new customer creation is important in point of the enterprise performance measurement system. There have been a number of studies that applied different models in other to assess the customer satisfaction of public and non-public area. But the general evaluation models which are existing can't consider the discrimination characteristic of different types of products or services. And these models didn't reflect the quality of the Internet environment of the public library service which appears newly. This study delved into literature of library service and customer satisfaction evaluation and suggest the classification system of public library service and the evaluation model of customer satisfaction for public library.