• Journal of Korean Neurosurgical Society
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• 제67권1호
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• pp.94-102
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• 2024

Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.

• Korean Journal of Ichthyology
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• 제36권2호
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• pp.139-155
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• 2024

Using the cytb gene region of the mitochondrial DNA of eight populations of Sarcocheilichthys nigripinnis morii and five populations of S. variegatus wakiyae, which belong to the genus Sarcocheilichthys from Korea, the genetic diversity and molecular phylogenetic relationships of each population were examined. As a result of the analysis, it was confirmed that the S. variegatus wakiyae population had higher genetic diversity than the S. nigripinnis morii population. In the phylogenetic tree of genus Sarcocheilichthys fish in Korea based on the cytb gene, the Yeongsan River (YSR) population of S. variegatus wakiyae forms a clade with the Tamjin River (TJR), Yeongsan River (YSR), and Seomjin River (SJR) population of S. nigripinnis morii, and genetic relationships that do not align with the current classification system were observed. Meanwhile, on the nuclear DNA phylogenetic tree, S. variegatus wakiyae and S. nigripinnis morii could be clearly distinguished, showing mitonuclear inconsistency where mitochondrial and nuclear DNA conflicted on the phylogenetic tree. The Seomjin River (SJR) population of S. nigripinnis morii was translocated to the Dongjin River (DJR) population, haplotype from which crossbreeding was presumed to have occurred was confirmed. Among the rivers flowing into the East Sea, the S. nigripinnis morii population is known to have been introduced and inhabit only the Hyeongsan River (HSR), and it is presumed to be a population formed by translocation from the Han River (HR) population, with a haplotype representing a unique genetic group also confirmed. The Han River (HR), Geum River (GR), and Mangyeong River (MGR) populations of S. nigripinnis morii formed a genetically identical population with S. czerskii and S. soldatovi distributed north of the Yalu River, and accordingly, a taxonomic reexamination was required through morphological and molecular phylogenetic studies by securing various specimens.

• The Journal of the Convergence on Culture Technology
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• 제10권3호
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• pp.173-180
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• 2024

We This study aimed to quantitatively analyze the theme of 'libertinage' and the associated issues of reason and emotion in 『Dangerous Liaisons』, a novel considered a masterpiece of libertine literature and an epistolary novel of the 18th century, using digital analysis tools. First, based on the frequency analysis of word usage using Voyant and LIWC 22, we confirmed that libertinage is manifested with keywords such as 'love' and 'time'. With Voyant's 'Contexts' feature, it was found that the letters sent by Valmont to Madame de Tourvel and those sent by Madame de Merteuil both have 'love' as the central theme. However, emotional vocabulary was higher in the former, whereas strategic vocabulary was more prevalent in the latter. Additionally, it was observed that the most frequently used word in the letters sent by Madame de Merteuil is 'time', with a higher frequency than 'love'. Thirdly, using LIWC 22, we measured the analytical thinking and emotional tone of the letters exchanged by the main characters, and analyzed how these values changed according to the chapters. Through these analyses, we confirmed that this novel, alongside Rousseau's "New Eloise," anticipates romanticism by embracing the theme of 'emotion,' which was rejected by 18th-century Enlightenment ideals.

• Land and Housing Review
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• 제15권3호
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• pp.177-188
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• 2024

This study aims to identify vulnerability factors through comprehensive safety diagnosis and to seek improvement measures for the safety and maintenance of facilities. In this study, the results of road tunnel inspections and diagnostics were converted into a database (DB). Using this data, we explored to identify vulnerable elements (NATM, ASSM) based on structural types and to develop efficient improvement measures. In this study, we analyzed 76 detailed safety diagnosis reports covering 45 different types of road tunnel facilities. In the detailed guidelines for comprehensive safety diagnosis, the database (DB) items for identifying vulnerable factors were selected by categorizing the basic information, such as the year of completion and damage items. In addition, AHP analysis was conducted separately through experts in related fields to analyze the correlation between damages. As a result, the primary vulnerability factors for NATM and ASSM were identified as cracks, leaks, insufficient lining thickness, and joint rear. ASSM was identified as relatively more susceptible to network cracks and material separation compared to NATM. In contrast, flaking and rebar exposure were interpreted as more significant vulnerabilities for NATM than for ASSM. In addition, the correlation between elements in NATM was found to be low, whereas in ASSM, the correlation between elements was high, indicating a more organic relationship.

• Journal of the Korean Association of Geographic Information Studies
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• 제27권3호
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• pp.99-114
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• 2024

Recently, the concept of neighborhood unit plan has been receiving attention due to expectations of balanced development and sustainable development through resolving regional gaps and reflecting regional characteristics. Accessibility to essential living facilities that can support daily life is considered an important factor in neighborhood unit plan. Therefore, this study analyzed accessibility from facilities based on the living facilities and access range set in the neighborhood unit plan, and analyzed spatial accessibility inequality in connection with the neighborhood unit plan and spatial clustering. As a result of analyzing accessibility in Busan Metropolitan City, various accessibility ranges were found depending on the facility. In addition, as a result of analyzing in connection with spatial clustering, regional inequality was found, such as hotspot areas in Gangdong, old downtown, Dongrae, and Haeundae, and coldspot areas in Gangseo and Gijang, and spatial inequality was found in which hotspots and coldspots exist simultaneously within the same neighborhood unit. Considering these spatial characteristics, detailed planning and policy establishment are necessary for facilities lacking in small-size neighborhood units, and the results of the analysis are expected to be meaningful in realizing the urban policy of balanced development that has been recently promoted.

• Resources Recycling
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• 제33권4호
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• pp.3-14
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• 2024

The preheating and calcination processes in cement manufacturing, which are crucial for producing the cement intermediate product clinker, require a substantial quantity of fossil fuels to generate high-temperature thermal energy. However, owing to the ever-increasing severity of environmental pollution, considerable efforts are being made to reduce carbon emissions from fossil fuels in the cement industry. Several preliminary studies have focused on increasing the usage of alternative fuels like refuse-derived fuel (RDF). Alternative fuels offer several advantages, such as reduced carbon emissions, mitigated generation of nitrogen oxides, and incineration in preheaters and kilns instead of landfilling. However, owing to the diverse compositions of alternative fuels, estimating their calorific value is challenging. This makes it difficult to regulate the preheater stability, thereby limiting the usage of alternative fuels. Therefore, in this study, a model based on deep neural networks is developed to accurately predict the preheater temperature and propose optimal fuel input quantities using explainable artificial intelligence. Utilizing the proposed model in actual preheating process sites resulted in a 5% reduction in fossil fuel usage, 5%p increase in the substitution rate with alternative fuels, and 35% reduction in preheater temperature fluctuations.

• Journal of Life Science
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• 제34권10호
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• pp.744-754
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• 2024

Cancer cells exhibit a unique metabolic process for uncontrolled cell division, providing bioenergy and intermediates, which are significantly different from normal cells. Here an aerobic glycolysis converts most of the pyruvate produced from glucose into lactate and inefficiently produced ATP. Cancer cells counter their lack of energy through glutamine metabolism, together with glucose. Glutamine is the most abundant amino acid in the blood and is used for the synthesis of amino acids, nucleotides, and lipids, as well as bioenergy through glutaminolysis. Cancer cells rely on glutamine rather than normal cells, showing more than half of the tricarboxylic acid cycle metabolites derived from glutamine, called glutamine addiction. Oncogenes c-Myc also regulates the expression of various genes involved in glutamine metabolism and promotes the absorption of glutamine. Whether glutaminase (GLS) causes or inhibits tumors is controversial. However, GLS1 is a promising treatment target due to its higher carcinogenic incidence, whereas GLS2 is known to act as a tumor suppressor. The 4th-generation metabolic anti-cancer therapy, which has been actively investigated since the mid-2010s, is based on a complex and sophisticated network of cancer metabolites. These drugs directly regulate the energy metabolism of cancer cells to maximize anti-cancer effects without side effects. GLS is a crucial enzyme for cancer metabolism and tumor progression that catalyzes the first stage in the process of glutaminolysis. The development of anti-cancer drugs targeting GLS enzymes has emerged as a promising strategy.

• The Korean Journal of Air & Space Law and Policy
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• 제25권2호
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• pp.139-162
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• 2010

In terms of the international air transport, the open skies policy implies freedom in the sky or opening the sky. In the normative respect, the open skies policy is a kind of open-door policy which gives various forms of traffic right to other countries, but on the other hand it is a policy of free competition in the international air transport. Since the Airline Deregulation Act of 1978, the United States has signed an open skies agreement with many countries, starting with the Netherlands, so that competitive large airlines can compete in the international air transport market where there exist a lot of business opportunities. South Korea now has an open skies agreement with more than 20 countries. The frequent flyer program (FFP) is part of a broad-based marketing alliance which has been used as an airfare strategy since the U.S. government's airline deregulation. The membership-based program is an incentive plan that provides mileage points to customers for using airline services and rewards customer loyalty in tangible forms based on their accumulated points. In its early stages, the frequent flyer program was focused on marketing efforts to attract customers, but now in the environment of intense competition among airlines, the program is used as an important strategic marketing tool for enhancing business performance. Therefore, airline companies agree that they need to identify customer needs in order to secure loyal customers more effectively. The outcomes from an airline's frequent flyer program can have a variety of effects on international competition. First, the airline can obtain a more dominant position in the air flight market by expanding its air route networks. Second, the availability of flight products for customers can be improved with an increase in flight frequency. Third, the airline can preferentially expand into new markets and thus gain advantages over its competitors. However, there are few empirical studies on the airline frequent flyer program. Accordingly, this study aims to explore the effects of the program on international competition, after reviewing the types of strategic alliance between airlines. Making strategic airline alliances is a worldwide trend resulting from the open skies policy. South Korea also needs to be making open skies agreements more realistic to promote the growth and competition of domestic airlines. The present study is about the performance of the airline frequent flyer program and international competition under the open skies policy. With a sample of five global alliance groups (Star, Oneworld, Wings, Qualiflyer and Skyteam), the study was attempted as an empirical study of the effects that the resource structures and levels of information technology held by airlines in each group have on the type of alliance, and one-way analysis of variance and regression analysis were used to test hypotheses. The findings of this study suggest that both large airline companies and small/medium-size airlines in an alliance group with global networks and organizations are able to achieve high performance and secure international competitiveness. Airline passengers earn mileage points by using non-flight services through an alliance network with hotels, car-rental services, duty-free shops, travel agents and more and show high interests in and preferences for related service benefits. Therefore, Korean airline companies should develop more aggressive marketing programs based on multilateral alliances with other services including hotels, as well as with other airlines.

• Journal of Intelligence and Information Systems
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• 제21권2호
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• pp.93-112
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• 2015

Depending on the change in consumer's consumption pattern, existing retail shop has evolved in hypermarket or convenience store offering grocery and daily products mostly. Therefore, it is important to maintain the inventory levels and proper product configuration for effectively utilize the limited space in the retail store and increasing sales. Accordingly, this study proposed proper product configuration and inventory level strategy based on RFM(Recency, Frequency, Monetary) model and SOM(self-organizing map) for manage the retail shop effectively. RFM model is analytic model to analyze customer behaviors based on the past customer's buying activities. And it can differentiates important customers from large data by three variables. R represents recency, which refers to the last purchase of commodities. The latest consuming customer has bigger R. F represents frequency, which refers to the number of transactions in a particular period and M represents monetary, which refers to consumption money amount in a particular period. Thus, RFM method has been known to be a very effective model for customer segmentation. In this study, using a normalized value of the RFM variables, SOM cluster analysis was performed. SOM is regarded as one of the most distinguished artificial neural network models in the unsupervised learning tool space. It is a popular tool for clustering and visualization of high dimensional data in such a way that similar items are grouped spatially close to one another. In particular, it has been successfully applied in various technical fields for finding patterns. In our research, the procedure tries to find sales patterns by analyzing product sales records with Recency, Frequency and Monetary values. And to suggest a business strategy, we conduct the decision tree based on SOM results. To validate the proposed procedure in this study, we adopted the M-mart data collected between 2014.01.01~2014.12.31. Each product get the value of R, F, M, and they are clustered by 9 using SOM. And we also performed three tests using the weekday data, weekend data, whole data in order to analyze the sales pattern change. In order to propose the strategy of each cluster, we examine the criteria of product clustering. The clusters through the SOM can be explained by the characteristics of these clusters of decision trees. As a result, we can suggest the inventory management strategy of each 9 clusters through the suggested procedures of the study. The highest of all three value(R, F, M) cluster's products need to have high level of the inventory as well as to be disposed in a place where it can be increasing customer's path. In contrast, the lowest of all three value(R, F, M) cluster's products need to have low level of inventory as well as to be disposed in a place where visibility is low. The highest R value cluster's products is usually new releases products, and need to be placed on the front of the store. And, manager should decrease inventory levels gradually in the highest F value cluster's products purchased in the past. Because, we assume that cluster has lower R value and the M value than the average value of good. And it can be deduced that product are sold poorly in recent days and total sales also will be lower than the frequency. The procedure presented in this study is expected to contribute to raising the profitability of the retail store. The paper is organized as follows. The second chapter briefly reviews the literature related to this study. The third chapter suggests procedures for research proposals, and the fourth chapter applied suggested procedure using the actual product sales data. Finally, the fifth chapter described the conclusion of the study and further research.

• Journal of Internet Computing and Services
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• 제15권3호
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• pp.45-52
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• 2014

The Ubiquitous-City (U-City) is a smart or intelligent city to satisfy human beings' desire to enjoy IT services with any device, anytime, anywhere. It is a future city model based on Internet of everything or things (IoE or IoT). It includes a lot of video cameras which are networked together. The networked video cameras support a lot of U-City services as one of the main input data together with sensors. They generate huge amount of video information, real big data for the U-City all the time. It is usually required that the U-City manipulates the big data in real-time. And it is not easy at all. Also, many times, it is required that the accumulated video data are analyzed to detect an event or find a figure among them. It requires a lot of computational power and usually takes a lot of time. Currently we can find researches which try to reduce the processing time of the big video data. Cloud computing can be a good solution to address this matter. There are many cloud computing methodologies which can be used to address the matter. MapReduce is an interesting and attractive methodology for it. It has many advantages and is getting popularity in many areas. Video cameras evolve day by day so that the resolution improves sharply. It leads to the exponential growth of the produced data by the networked video cameras. We are coping with real big data when we have to deal with video image data which are produced by the good quality video cameras. A video surveillance system was not useful until we find the cloud computing. But it is now being widely spread in U-Cities since we find some useful methodologies. Video data are unstructured data thus it is not easy to find a good research result of analyzing the data with MapReduce. This paper presents an analyzing system for the video surveillance system, which is a cloud-computing based video data management system. It is easy to deploy, flexible and reliable. It consists of the video manager, the video monitors, the storage for the video images, the storage client and streaming IN component. The "video monitor" for the video images consists of "video translater" and "protocol manager". The "storage" contains MapReduce analyzer. All components were designed according to the functional requirement of video surveillance system. The "streaming IN" component receives the video data from the networked video cameras and delivers them to the "storage client". It also manages the bottleneck of the network to smooth the data stream. The "storage client" receives the video data from the "streaming IN" component and stores them to the storage. It also helps other components to access the storage. The "video monitor" component transfers the video data by smoothly streaming and manages the protocol. The "video translator" sub-component enables users to manage the resolution, the codec and the frame rate of the video image. The "protocol" sub-component manages the Real Time Streaming Protocol (RTSP) and Real Time Messaging Protocol (RTMP). We use Hadoop Distributed File System(HDFS) for the storage of cloud computing. Hadoop stores the data in HDFS and provides the platform that can process data with simple MapReduce programming model. We suggest our own methodology to analyze the video images using MapReduce in this paper. That is, the workflow of video analysis is presented and detailed explanation is given in this paper. The performance evaluation was experiment and we found that our proposed system worked well. The performance evaluation results are presented in this paper with analysis. With our cluster system, we used compressed $1920{\times}1080(FHD)$ resolution video data, H.264 codec and HDFS as video storage. We measured the processing time according to the number of frame per mapper. Tracing the optimal splitting size of input data and the processing time according to the number of node, we found the linearity of the system performance.