• Journal of Korea Port Economic Association
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• v.38 no.3
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• pp.29-51
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• 2022

The International Maritime Organization (IMO) designated the Emission Control Area (ECA) in Northern Europe to reduce the NOx and SOx emissions from ships in the coastal areas. This study used Network slack-based measure (SBM) Data Envelopment Model (DEM) and Bootstrop Truncated Regression (BTR) model to analyze the ECA's impact on ferry companies' financial performances based on the financial data from eight ferry carriers in Northern Europe, the Mediterranean and North America from 2004 to 2017. To alleviate the problem of arbitrary variable selection in DEA, the variable selection criteria proposed by Dyson et al. (2001) were applied; the size of the company was considered through the Network SBM DEA model; and the company's profit-generating process was divided into stages to measure financial performance in more detail. In addition, the BTR model was applied to derive results that minimize the bias of the data. The study found that ECA regulations did not always negatively affect the shipping companies' financial performance. Rather, a steady increase in efficiency was observed for Northern European ferry companies which were subject to the strongest regulations. For North American ferry companies, government subsidies were found to have a significant impact on efficiency, and relatively small impact on efficiency due to the ECA and oil prices. For the Mediterranean ferry companies, efficiency values have decreased since the implementation of ECA regulation despite the lowest level of regulation in the region.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.17-25
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• 2023

In this paper, we propose a model that can perform human pose estimation through a MobileViT-based model with fewer parameters and faster estimation. The based model demonstrates lightweight performance through a structure that combines features of convolutional neural networks with features of Vision Transformer. Transformer, which is a major mechanism in this study, has become more influential as its based models perform better than convolutional neural network-based models in the field of computer vision. Similarly, in the field of human pose estimation, Vision Transformer-based ViTPose maintains the best performance in all human pose estimation benchmarks such as COCO, OCHuman, and MPII. However, because Vision Transformer has a heavy model structure with a large number of parameters and requires a relatively large amount of computation, it costs users a lot to train the model. Accordingly, the based model overcame the insufficient Inductive Bias calculation problem, which requires a large amount of computation by Vision Transformer, with Local Representation through a convolutional neural network structure. Finally, the proposed model obtained a mean average precision of 0.694 on the MS COCO benchmark with 3.28 GFLOPs and 9.72 million parameters, which are 1/5 and 1/9 the number compared to ViTPose, respectively.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.1-7
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• 2023

This paper proposes a small cell resource partitioning allocation method to solve interference to machine type communication devices (MTCD) and improve performance in 5G heterogeneous networks (HetNet) where macro base station (MBS) and many small cell base stations (SBS) are overlaid. In the 5G HetNet, since various types of MTCDs generate data traffic, the load on the MBS increases. Therefore, in order to reduce the MBS load, a cell range expansion (CRE) method is applied in which a bias value is added to the received signal strength from the SBS and MTCDs satisfying the condition is connected to the SBS. More MTCDs connecting to the SBS through the CRE will reduce the load on the MBS, but performance of MTCDs will degrade due to interference, so a method to solve this problem is needed. The proposed small cell resource partitioning allocation method allocates resources with less interference from the MBS to mitigate interference of MTCDs newly added in the SBS with CRE, and improve the overall MTCD performace using separating resources according to the performance of existing MTCDs in the SBS. Through simulation results, the proposed small cell resource partitioning allocation method shows performance improvement of 21% and 126% in MTCDs capacity connected to MBS and SBS respectively, compared to the existing resource allocation methods.

• Journal of Korean Home Economics Education Association
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• v.23 no.3
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• pp.91-119
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• 2011

The purpose of this study was to suggest the framework reflecting the interests of students in practical problems and social issues regarding perennial problems which correspond to the characteristics and goals of the 2007 revised curriculum. This study was carried into a literature review and 406 questionnaires, filled out by the 9th grade middle school students in Seoul and Gyeonggi province, were used for analysis. The main results of this study are summarized as follows: First, six perennial problems are ascertained, Next, the middle school students were most interested in 27 items of practical problems such as mapping out their career path, self-improvement and interpersonal relations. And finally, the middle school students' important social interests are adolescence issues, job preference bias, career choice, suicide and addiction to computer, appearance and money management behavior, house ownership and conspicious consumption, and lack of time to spend with family. This study suggested the framework which corresponds to the characteristics and goals of the 2007 revised curriculum.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• Korean Journal of Remote Sensing
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• v.31 no.6
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• pp.531-548
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• 2015

Atmospheric Motion Vector (AMV) from satellite images have shown Slow Speed Bias (SSB) in comparison with rawinsonde. The causes of SSB are originated from tracking, selection, and height assignment error, which is known to be the leading error. However, recent works have shown that height assignment error cannot be fully explained the cause of SSB. This paper attempts a new approach to examine the possibility of SSB reduction of COMS AMV by using a new target tracking algorithm. Tracking error can be caused by averaging of various wind patterns within a target and changing of cloud shape in searching process over time. To overcome this problem, Gaussian Mixture Model (GMM) has been adopted to extract the coldest cluster as target since the shape of such target is less subject to transformation. Then, an image filtering scheme is applied to weigh more on the selected coldest pixels than the other, which makes it easy to track the target. When AMV derived from our algorithm with sum of squared distance method and current COMS are compared with rawindsonde, our products show noticeable improvement over COMS products in mean wind speed by an increase of $2.7ms^{-1}$ and SSB reduction by 29%. However, the statistics regarding the bias show negative impact for mid/low level with our algorithm, and the number of vectors are reduced by 40% relative to COMS. Therefore, further study is required to improve accuracy for mid/low level winds and increase the number of AMV vectors.

• Proceedings of the KIEE Conference
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• 1995.07c
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• pp.1085-1087
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• 1995

A large leakage current may be one of the critical issues for poly-silicon thin film transistors(poly-Si TFTs) for LCD applications. In order to reduce the leakage current of poly-Si TFTs, several offset gated structures have been reported. However, those devices, where the offset length in the source region is not same as that in the drain region, exhibit the asymmetric electrical performances such as the threshold voltage shift and the variation of the subthreshold slope. The different offset length is caused by the additional mask step for the conventional offset structures. Also the self-aligned implantation may not be applicable due to the mis-alignment problem. In this paper, we propose a new fabrication method for poly-Si TFTs with a self-aligned offset gated structure by employing a photo resistor reflow process. Compared with the conventional poly-Si TFTs, the device is consist of two gate electrodes, of which one is the entitled main gate where the gate bias is employed and the other is the entitled subgate which is separate from both sides of the main gate. The poly-Si channel layer below the offset oxide is protected from the injected ion impurities for the source/drain implantation and acts as an offset region of the proposed device. The key feature of our new device is the offset lesion due to the offset oxide. Our experimental results show that the offset region, due to the photo resistor reflow process, has been successfully obtained in order to fabricate the offset gated poly-Si TFTs. The advantages of the proposed device are that the offset length in the source region is the same as that in the drain region because of the self-aligned implantation and the proposed device does not require any additional mask process step.

• Imaging Science in Dentistry
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• v.50 no.2
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• pp.81-92
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• 2020

Intelligent systems(i.e., artificial intelligence), particularly deep learning, are machines able to mimic the cognitive functions of humans to perform tasks of problem-solving and learning. This field deals with computational models that can think and act intelligently, like the human brain, and construct algorithms that can learn from data to make predictions. Artificial intelligence is becoming important in radiology due to its ability to detect abnormalities in radiographic images that are unnoticed by the naked human eye. These systems have reduced radiologists' workload by rapidly recording and presenting data, and thereby monitoring the treatment response with a reduced risk of cognitive bias. Intelligent systems have an important role to play and could be used by dentists as an adjunct to other imaging modalities in making appropriate diagnoses and treatment plans. In the field of maxillofacial radiology, these systems have shown promise for the interpretation of complex images, accurate localization of landmarks, characterization of bone architecture, estimation of oral cancer risk, and the assessment of metastatic lymph nodes, periapical pathologies, and maxillary sinus pathologies. This review discusses the clinical applications and scope of intelligent systems such as machine learning, artificial intelligence, and deep learning programs in maxillofacial imaging.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.16 no.2
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• pp.153-159
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• 2005

Autistic disorder and other PDD are currently viewed as a largely genetically determined neurodevelopmental disorder, although its underlying biological causes remain to be established. In this review, we examine the available neurodevelopmental literature on autistic disorder and discuss the findings that have emerged. Typical neuropathological observations are rather consistent with respect to the limbic system (increased cell packing density and smaller neuronal size), the cerebellum (decreased number of Purkinje cells) and the cerebral cortex ($>50\%$ of the cases showed features of cortical dysgenesis). However, most of the reported studies had to contend with the problem of small sample sizes, the use of quantification techniques, not free of bias and assumptions, and high percentages of autistic subjects with comorbid mental retardation or epilepsy. Furthermore, data from the limbic system and on age-related changes lack replication by independent groups. It is anticipated that future neuropathological studies held great promise, especially as new techniques such as design-based stereology and gene expression are increasingly implemented and combined, larger samples are analysed, and younger subjects free of comorbidities are investigated.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.291.1-291.1
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• 2016

Graphene by one of the two-dimensional (2D) materials has been focused on electronic applications due to its ultrahigh carrier mobility, outstanding thermal conductivity and superior optical properties. Although graphene has many remarkable properties, graphene devices have low on/off current ratio due to its zero bandgap. Despite considerable efforts to open its bandgap, it's hard to obtain appropriate improvements. To solve this problem, heterojunction barristor was proposed based on graphene. Mostly, this heterojunction barristor is made by transition metal dichalcogenides (TMDs), such as molybdenum disulfide ($MoS_2$) and tungsten diselenide ($WSe_2$), which have extremely thickness scalability of TMDs. The heterojunction barristor has the advantage of controlling graphene's Fermi level by applying gate bias, resulting in barrier height modulation between graphene interface and semiconductor. However, charged impurities between graphene and $SiO_2$ cause unexpected p-type doping of graphene. The graphene's Fermi level modulation is expected to be reduced due to this p-doping effect. Charged impurities make carrier mobility in graphene reduced and modulation of graphene's Fermi level limited. In this paper, we investigated theoretically and experimentally a relevance between graphene's Fermi level and p-type doping. Theoretically, when Fermi level is placed at the Dirac point, larger graphene's Fermi level modulation was calculated between -20 V and +20 V of $V_{GS}$. On the contrary, graphene's Fermi level modulation was 0.11 eV when Fermi level is far away from the Dirac point in the same range. Then, we produced two types heterojunction barristors which made by p-type doped graphene and graphene treated 2.4% APTES, respectively. On/off current ratio (32-fold) of graphene treated 2.4% APTES was improved in comparison with p-type doped graphene.