• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.5 s.311
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• pp.30-36
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• 2006

In this paper, a new type of written image segmentation based on relative comparison of region areas is proposed. The original image is composed of two distinctive regions; information and background. Compared with this binary original image, the observed one is the gray scale which is represented with complex regions with speckles and noise due to degradation or contamination. For applying threshold or statistical approach, there occurs the region-deformation problem in the process of binarization. At first step, the efficient iterated conditional mode (ICM) which takes the lozenge type block is used for regions formation into the binary image. Secondly the information region is estimated through selecting action and restored its primary state. Not only decision of the attachment to a region but also the calculation of the magnitude of its area are carried on at each current pixel iteratively. All region areas are sorted into a set and selected through the decision parameter which is obtained statistically. Our experiments show that these approaches are effective on ink-rubbed copy image (拓本 'Takbon') and efficient at shape restoration. Experiments on gray scale image show promising shape extraction results, comparing with the threshold-segmentation and conventional ICM method.

• Journal of the Korean Society for Library and Information Science
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• v.50 no.3
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• pp.171-191
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• 2016

The purpose of this study is to analyze the 'Framework for Information Literacy for Higher Education' filed by the ACRL (Association of College and Research Libraries) Board on February 2, 2015 and adopted on January 11, 2016. Six concepts central to information literacy in Framework and four main theories or models (i.e., threshold concepts, metaliteracy, Backward Design, and Liminal Space) underpinning the Framework were analyzed. The Framework provides conceptual or descriptive approach. In addition, the Framework is not designed to be implemented in a single information literacy session in a student's academic career. Instead, it is intended to be systematically integrated into the student's academic program at variety of levels. This study recommends curricular development and assessment methods supporting Framework as a further study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.1
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• pp.344-357
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• 2015

With the increase in a number of access technologies and data rates, a continuous connection among different networks is demand of the future wireless networks. In the last decade, user connectivity among different access networks remained a challenging job. Therefore, in this article, we proposed a user-centric and user-perspective based network selection mechanism for fast handover management in heterogeneous wireless networks. The proposed scheme selects the most appropriate network among available networks on the basis of resources i.e. cost, data rate, and link quality. Initially, we load the Media Independent Information Service (MIIS) with the information of cost and data rate provided by different network operators. Similarly, Mobile Node (MN) is also loaded with the user preferred cost and data rate for different applications. The MN obtains the information of cost and data rate from MIIS server upon a predefined threshold, and make a decision for handover according to its current cost and data rate. Furthermore, we employ an optimal threshold mechanism for initiation of the handover execution phase to minimize false handover indications. The proposed scheme is based on a survey for network selection and its implementation in C programming language to validate its performance and accuracy. The simulation result shows that the proposed scheme performs superior then the schemes present in the current literature.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.12 no.2
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• pp.229-237
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• 1992

Series system reliability analysis of non-reactive contaminant transport is performed in a two dimensional horizontal domain with two different limit state functions: (1) concentration threshold and (2) exposure time threshold. The transient source transport model is combined with the system reliability model to evaluate the probability that a specified maximum concentration at a node of interest would be exceeded or that a moderate concentration would exceed some exposure limit over a given period of time. The results give probabilities of exceedence greater than probability of each component and they tend to be dominanted by the component with larger probability. Transverse dispersivity turns out to be an important parameter in addition to hydraulic conductivity in a two-dimensional contaminant transport model with transient source. System sensitivity is found to reflect the corresponding sensitivity of both components, with the component with larger probability having a greater influence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.3
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• pp.575-583
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• 2013

In ad hoc networks, a distributed timing synchronization is studied using a firefly-inspired approach. We illuminate the exiting synchronization algorithm based on the theory of pulse-coupled oscillators so that the algorithm can be applied to multi-carrier systems through packet-based communications, where nodes communicate over an orthogonal frequency-division multiple access air interface. As our main result, we introduce a new sync-code detector, which optimally designs both the coupling function and the detection threshold when various network parameters such as the number of nodes in the network and network topology are given a priori. Computer simulations are performed to show the convergence to a synchronized state in realistic network environments.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.294-297
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• 2007

Steam and advection fogs are frequently observed in the Yellow Sea located between Korea and China during the periods of March-April and June-July respectively. This study uses the remote sensing (RS) data for monitoring sea fog. Meteorological data obtained from the Ieodo Ocean Research Station provided an informative synopsis for the occurrence of steam and advection fogs through a ground truth. The RS data used in this study was GOES-9, MTSAT-1R images and QuikSCAT wind data. A dual channel difference (DCD) approach using IR and near-IR channel of GOES-9 and MTSAT-1R satellites was applied to estimate the extension of the sea fog. For the days examined, it was found that not only the DCD but also the texture-related measurement and the weak wind condition are required to separate the sea fog from the low cloud. The QuikSCAT wind is used to provide a weak wind area less than threshold under stable condition of the surface wind around a fog event. The Laplacian computation for a measurement of the homogeneity was designed. A new combined method of DCD, QuikSCAT wind speed and Laplacian was applied in the twelve cases with GOES-9 and MTSAT-1R. The threshold values for DCD, QuikSCAT wind speed and Laplacian are -2.0 K, 8 m $s^{-1}$ and 0.1, respectively. The validation methods such as Heidke skill score, probability of detection, probability of false detection, true skill score and odds ratio show that the new combined method improves the detection of sea fog rather than DCD method.

• Journal of the Ergonomics Society of Korea
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• v.24 no.1
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• pp.9-17
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• 2005

81.1% of traffic accidents is attributed to the drivers. In this regard, D/E model is a practical and effective method in terms of the cost and time in evaluating the road hazardousness. To examine the validity of the threshold values by the levels of demand We selected 10 subjects and collected their physiological signals while they were driving on Honam Highway (Jeonju ${\leftrighttarro}$ Hoideog section). Based on the collected data, the hazardous road condition was evaluated using the new threshold values of the effort level determined by cluster analysis. In applying the D/E model, a decision method based on the demand level was suggested, using a traffic accident prediction model. Additionally, the limit value of the effort level was determined using the drivers' physiological signal data collected at the highway. A comparison analysis of the two D/E models revealed no significant difference: The existing method and the clustering method determined 9 and 7 hazardous road zones, respectively, while actual traffic accidents were reported in 6 and 4 zones, respectively among the predicted road hazardous zones. However, the latter method suggested a more scientific and rational basis in determining the limit value of the Effort level. In conclusion, although D/E model has a great merit as a pioneering method to reflect human factors in evaluating the road hazardousness, it is believed that this method could be improved by a more dynamic method that considers the traffic conditions and the individual physiological signal of the drivers simultaneously in determining a better limit.

• Environmental and Resource Economics Review
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• v.28 no.4
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• pp.617-643
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• 2019

The Demilitarized Zone(DMZ) is a buffer zone set between the southern and northern limit lines established after the 1953 Armistice Agreement. It is an important natural environment conservation area where wild species of animals and plants live. On the other hand, the development pressure on the DMZ will increase when the inter-Korean economic cooperation is activated in the future. As a result, DMZ development should consider not only the economic cost-benefit aspects, but also how to assess and conserve the biodiversity of the DMZ, as well as the recovery costs and budget. This paper develope a sustainable DMZ management model under biodiversity uncertainly by using real option approach. The model is also designed to reflect the political risk and regional specificity of the DMZ. Through empirical analysis, I derive the biodiversity threshold (b^*) that can secure the DMZ investment economy under uncertainty. In addition, through the sensitivity analysis, I derive the factors influencing the biodiversity threshold, and suggest the policy implications for sustainable management of DMZ.

• Journal of the Korea Society of Computer and Information
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• v.24 no.2
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• pp.139-147
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• 2019

A false alarm, which is an incorrect report of an emergency, could trigger an unnecessary action. The predictive maintenance framework developed in our previous work has a feature whereby a machine alarm is triggered based on sensor data evaluation. The sensor data evaluator performs three essential evaluation steps. First, it evaluates each sensor data value based on its threshold (lower and upper bound) and labels the data value as "alarm" when the threshold is exceeded. Second, it calculates the duration of the occurrence of the alarm. Finally, in the third step, a domain expert is required to assess the results from the previous two steps and to determine, thereby, whether the alarm is true or false. There are drawbacks of the current evaluation method. It suffers from a high false-alarm ratio, and moreover, given the vast amount of sensor data to be assessed by the domain expert, the process of evaluation is prolonged and inefficient. In this paper, we propose a method for automatic false-alarm labeling that mimics how the domain expert determines false alarms. The domain expert determines false alarms by evaluating two critical factors, specifically the duration of alarm occurrence and identification of anomalies before or while the alarm occurs. In our proposed method, Hierarchical Temporal Memory (HTM) is utilized to detect anomalies. It is an unsupervised approach that is suitable to our main data characteristic, which is the lack of an example of the normal form of sensor data. The result shows that the technique is effective for automatic labeling of false alarms in sensor data.

• Journal of Animal Science and Technology
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• v.63 no.6
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• pp.1453-1463
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• 2021

Feeding is the most important behavior that represents the health and welfare of weanling pigs. The early detection of feed refusal is crucial for the control of disease in the initial stages and the detection of empty feeders for adding feed in a timely manner. This paper proposes a real-time technique for the detection and recognition of small pigs using a deep-leaning-based method. The proposed model focuses on detecting pigs on a feeder in a feeding position. Conventional methods detect pigs and then classify them into different behavior gestures. In contrast, in the proposed method, these two tasks are combined into a single process to detect only feeding behavior to increase the speed of detection. Considering the significant differences between pig behaviors at different sizes, adaptive adjustments are introduced into a you-only-look-once (YOLO) model, including an angle optimization strategy between the head and body for detecting a head in a feeder. According to experimental results, this method can detect the feeding behavior of pigs and screen non-feeding positions with 95.66%, 94.22%, and 96.56% average precision (AP) at an intersection over union (IoU) threshold of 0.5 for YOLOv3, YOLOv4, and an additional layer and with the proposed activation function, respectively. Drinking behavior was detected with 86.86%, 89.16%, and 86.41% AP at a 0.5 IoU threshold for YOLOv3, YOLOv4, and the proposed activation function, respectively. In terms of detection and classification, the results of our study demonstrate that the proposed method yields higher precision and recall compared to conventional methods.