• Korean Journal of Agricultural and Forest Meteorology
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• v.13 no.2
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• pp.79-86
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• 2011

Cold-air drainage and pooling occur in most mountain valleys at night. Local climates with cold-air pooling could affect phenology and distribution of crop plants. A high resolution infrared imaging radiometer was used to visualize the cold-air drainage and thermal belt formation over a small mountainous watershed (ca. $10{\times}5{\times}1$ km for the maximum length${\times}$width${\times}$depth). Thermal images on $640{\times}480$ pixels were scanned across the Akyang valley (south of Mt. Jiri National Park) by the radiometer installed at a local peak ('Hyongjebong', 1,117 m a.s.l.) at dawn of 17 May 2011, when the synoptic condition was favorable for the surface cooling and cold-air drainage. Major findings are: (1) Cold-air drainage and accumulation was clearly identified by the lowest brightness temperature mainly at the valley bottom. (2) So-called 'thermal belt' with higher brightness temperature was found partway up the valley sidewalls and showed up to $5^{\circ}C$ departure from the valley bottom temperature. (3) Digital thermography showed feasibility for validation of the high definition geospatial temperature models currently in use for the plot-specific agrometeorological service.

• Journal of Navigation and Port Research
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• v.36 no.1
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• pp.69-74
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• 2012

Recent global supply chain, improving the efficiency of container shipping process is very important. In the overseas shipping of goods, the voyage of super containership is common to overcome amount of increasing cargo. Thus, container terminal managers make an experiment on the double cycle and dual cycle operation, which ship loading and unloading were carried out simultaneously, for maximizing the productivity of quay side. Yard Tractors(YTs) pooling methods also are introduced for increasing the efficiency of assignment of YTs. In this paper, we analyzed the efficiency of dual cycling through comparing existing pooling methods with the modified method for the dual cycling. We developed a simulation model using simulation analysis software, Arena. The result of experiment shown that the more dual cycling don't always increase the gross crane rate(GCR), which means productivity of quay cranes(QCs) per hour.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.275-279
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• 2013

Objectives: A number of studies have shown that chronic hepatitis B virus infection is implicated in susceptibility to pancreatic cancer. However, the results are still controversial. This meta-analysis aimed to quantitatively assess the relationship between chronic hepatitis B virus infection and incidence of pancreatic cancer of cohort and case-control studies. Methods: A literature search was performed for entries from 1990 to 2012 using PUBMED and EMBASE. Studies were included if they reported odds ratios (ORs) and corresponding 95% CIs of pancreatic cancer with respect to the infection of hepatitis B virus. Results: Eight studies met the inclusion criteria, which included five case-control studies and three cohort studies. Compared with individuals who have not infection of hepatitis B virus, the pooled OR of pancreatic cancer was 1.403 (95%CI: 1.139-1.729, P=0.001) for patients with hepatitis B virus infection. Sub-group analysis by study design showed that the summary OR was 1.43 (95%CI: 1.06-1.94, P=0.021) when pooling case-control studies and 1.31 (95%CI: 1.00-1.72, P=0.05) when pooling cohort studies. Conclusion: Findings from this meta-analysis suggest that chronic hepatitis B virus infection may increase the risk of pancreatic cancer. This relationship needs to be confirmed by further follow-up studies.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.10-17
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• 2017

We propose classification algorithms for human and dog movement. The proposed algorithms use micro-Doppler signals obtained from humans and dogs moving in four different directions. A two-stage classifier based on a support vector machine (SVM) is proposed, which uses a radial-based function (RBF) kernel and $16^{th}$-order linear predictive code (LPC) coefficients as feature vectors. With the proposed algorithms, we obtain the best classification results when a first-level SVM classifies the type of movement, and then, a second-level SVM classifies the moving object. We obtain the correct classification probability 95.54% of the time, on average. Next, to deal with the difficult classification problem of human and dog running, we propose a two-layer convolutional neural network (CNN). The proposed CNN is composed of six ($6{\times}6$) convolution filters at the first and second layers, with ($5{\times}5$) max pooling for the first layer and ($2{\times}2$) max pooling for the second layer. The proposed CNN-based classifier adopts an auto regressive spectrogram as the feature image obtained from the $16^{th}$-order LPC vectors for a specific time duration. The proposed CNN exhibits 100% classification accuracy and outperforms the SVM-based classifier. These results show that the proposed classifiers can be used for human and dog classification systems and also for classification problems using data obtained from an ultra-wideband (UWB) sensor.

• Journal of the Korea Computer Graphics Society
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• v.23 no.3
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• pp.95-103
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• 2017

Horizon correction is a crucial stage for image composition enhancement. In this paper, we propose a deep learning based method for estimating the slanted angle of a photograph and correcting it. To estimate and correct the horizon direction, existing methods use hand-crafted low-level features such as lines, planes, and gradient distributions. However, these methods may not work well on the images that contain no lines or planes. To tackle this limitation and robustly estimate the slanted angle, we propose a convolutional neural network (CNN) based method to estimate the slanted angle by learning more generic features using a huge dataset. In addition, we utilize multiple adaptive spatial pooling layers to extract multi-scale image features for better performance. In the experimental results, we show our CNN-based approach robustly and accurately estimates the slanted angle of an image regardless of the image content, even if the image contains no lines or planes at all.

• Journal of Preventive Medicine and Public Health
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• v.50 no.2
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• pp.91-99
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• 2017

Objectives: As in many low-income and middle-income countries, out-of-pocket (OOP) payments by patients or their families are a key healthcare financing mechanism in Bangladesh that leads to economic burdens for households. The objective of this study was to identify whether and to what extent socioeconomic, demographic, and behavioral factors of the population had an impact on OOP expenditures in Bangladesh. Methods: A total of 12 400 patients who had paid to receive any type of healthcare services within the previous 30 days were analyzed from the Bangladesh Household Income and Expenditure Survey data, 2010. We employed regression analysis for identify factors influencing OOP health expenditures using the ordinary least square method. Results: The mean total OOP healthcare expenditures was US dollar (USD) 27.66; while, the cost of medicines (USD 16.98) was the highest cost driver (61% of total OOP healthcare expenditure). In addition, this study identified age, sex, marital status, place of residence, and family wealth as significant factors associated with higher OOP healthcare expenditures. In contrary, unemployment and not receiving financial social benefits were inversely associated with OOP expenditures. Conclusions: The findings of this study can help decision-makers by clarifying the determinants of OOP, discussing the mechanisms driving these determinants, and there by underscoring the need to develop policy options for building stronger financial protection mechanisms. The government should consider devoting more resources to providing free or subsidized care. In parallel with government action, the development of other prudential and sustainable risk-pooling mechanisms may help attract enthusiastic subscribers to community-based health insurance schemes.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.6
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• pp.567-572
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• 2019

In this paper, we propose an algorithm to perform convolution, pooling, and ReLU operations in CNN using binary image and binary kernel. It decomposes 256 gray-scale images into 8 bit planes and uses a binary kernel consisting of -1 and 1. The convolution operation of binary image and binary kernel is performed by addition and subtraction. Logically, it is a binary operation algorithm using the XNOR and comparator. ReLU and pooling operations are performed by using XNOR and OR logic operations, respectively. Through the experiments to verify the usefulness of the proposed algorithm, We confirm that the CNN operation can be performed by converting it to binary logic operation. It is an algorithm that can implement deep running even in a system with weak computing power. It can be applied to a variety of embedded systems such as smart phones, intelligent CCTV, IoT system, and autonomous car.

• Journal of Navigation and Port Research
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• v.33 no.8
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• pp.555-562
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• 2009

At container terminals, a major measurement of productivity can be work-efficiency in quay-side. At the apron, containers are loaded onto the ship and unloaded to apron by Q/C(Quay Crane). For improving the productivity of quay crane, the more efficient Y/T(Yard Tractor) operation method is necessary in container terminals. Between quay-side and yard area, current transferring methods is single-cycling which doesn't start loading unless it finishes unloading. Dual-cycling is a technique that can be used to improve the productivity of quay-side and utility of yard tractor by ship loading and unloading simultaneously. Using the dual-cycling at terminals only necessitates an operational change without purchasing extra equipment. Exactly, Y/T operation method has to be changed the dedicate system to pooling system. This paper presents an efficient ship loading and unloading plan in container terminals, which use the dual-cycling. We propose genetic and tabu search algorithm for this problem.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.9
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• pp.2056-2063
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• 2012

In a port terminal, containers are stored and transshipped by yard tractors and crane vehicles. For operation efficiency of the terminal, location information of these vehicles is an essential factor. However, most of port terminals try to estimate location of these assets using indirect methods such as event tracking of shipping or unshipping containers. Because these kinds of events are rarely occurred, location of the event includes seriously locating error compared to a real location of vehicle. In this paper, we propose a real-time asset tracking system to obtain accurate and reliable location of terminal assets. The proposed system overcomes a location estimation error caused by container stacks which interrupt wireless communication. In order to mitigate uncertainty and increase accuracy of location estimation, we designed hardwares and multi-step locating system to resolve additional preblems. We implemented system components, and installed these at a port environment for evaluation. The result shows superiority of the system that the accuracy is approximately 5.87 meters (CEP).

• Management & Information Systems Review
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• v.33 no.4
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• pp.63-75
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• 2014

The paper investigates empirically the determinants of standardization activity at the industry level, focusing on market structure. The enactments or amendments of collective standards is used as the proxy variable for standardization activity. The independent variables, in addition to market structure, are technological opportunity, factor intensity, export ratio, and industry characteristics(assembly). We estimated the logistic regression model(so-called Logit), using the pooling data for 9 Korean industries, including foods, textiles, chemicals, nonmetallic minerals, metals, electronics and electrics, machinery, automobiles, and shipbuilding, over 2006-2009. The empirical finding shows that market structure has no any effects on the enactments or amendments of collective standards in Korea. This might infer that oligopolistic firms devote themselves to de facto standards determined by market rather than de jure standards such as collective standards and Korean Standards(KS). Besides market structure variable, whereas technological opportunity and assembly characteristics are likely to relate positively with the enactments or amendments of collective standards, capital intensity and export ratio have no any relationship with industrial standardization, respectively.