• Journal of the Korean Society of Radiology
• /
• v.83 no.2
• /
• pp.432-438
• /
• 2022

Colonic angiosarcoma is an extremely rare and aggressive malignant tumor with poor prognosis. We report a case of colonic epithelioid angiosarcoma with colonic obstruction and rapidly progressive hepatic metastasis in a 44-year-old female. Abdominal CT revealed a heterogeneously enhancing irregular mass in the ascending colon, causing proximal bowel distension. The patient underwent surgery, and histopathological examination revealed a poorly differentiated carcinoma. A follow-up liver dynamic MRI after 4 months revealed newly developed diffusely scattered numerous small nodules in both hepatic lobes with peripheral and nodular marked arterial hyperenhancement, raising the suspicion of hepatic angiosarcoma. A pathologic second opinion was obtained, and additional immunohistochemistry revealed colonic epithelioid angiosarcoma. The patient showed progressive hepatic metastasis on follow-up abdominal CT after 6 months and died 8 months after initial diagnosis. We describe an educational case of colonic angiosarcoma, a rare malignant tumor, with rapidly progressive hepatic metastasis that showed radiologic findings suggestive of angiosarcoma and enabled a re-diagnosis for proper treatment and prognosis prediction.

• Journal of Intelligence and Information Systems
• /
• v.21 no.1
• /
• pp.119-142
• /
• 2015

With the explosive growth in the volume of information, Internet users are experiencing considerable difficulties in obtaining necessary information online. Against this backdrop, ever-greater importance is being placed on a recommender system that provides information catered to user preferences and tastes in an attempt to address issues associated with information overload. To this end, a number of techniques have been proposed, including content-based filtering (CBF), demographic filtering (DF) and collaborative filtering (CF). Among them, CBF and DF require external information and thus cannot be applied to a variety of domains. CF, on the other hand, is widely used since it is relatively free from the domain constraint. The CF technique is broadly classified into memory-based CF, model-based CF and hybrid CF. Model-based CF addresses the drawbacks of CF by considering the Bayesian model, clustering model or dependency network model. This filtering technique not only improves the sparsity and scalability issues but also boosts predictive performance. However, it involves expensive model-building and results in a tradeoff between performance and scalability. Such tradeoff is attributed to reduced coverage, which is a type of sparsity issues. In addition, expensive model-building may lead to performance instability since changes in the domain environment cannot be immediately incorporated into the model due to high costs involved. Cumulative changes in the domain environment that have failed to be reflected eventually undermine system performance. This study incorporates the Markov model of transition probabilities and the concept of fuzzy clustering with CBCF to propose predictive clustering-based CF (PCCF) that solves the issues of reduced coverage and of unstable performance. The method improves performance instability by tracking the changes in user preferences and bridging the gap between the static model and dynamic users. Furthermore, the issue of reduced coverage also improves by expanding the coverage based on transition probabilities and clustering probabilities. The proposed method consists of four processes. First, user preferences are normalized in preference clustering. Second, changes in user preferences are detected from review score entries during preference transition detection. Third, user propensities are normalized using patterns of changes (propensities) in user preferences in propensity clustering. Lastly, the preference prediction model is developed to predict user preferences for items during preference prediction. The proposed method has been validated by testing the robustness of performance instability and scalability-performance tradeoff. The initial test compared and analyzed the performance of individual recommender systems each enabled by IBCF, CBCF, ICFEC and PCCF under an environment where data sparsity had been minimized. The following test adjusted the optimal number of clusters in CBCF, ICFEC and PCCF for a comparative analysis of subsequent changes in the system performance. The test results revealed that the suggested method produced insignificant improvement in performance in comparison with the existing techniques. In addition, it failed to achieve significant improvement in the standard deviation that indicates the degree of data fluctuation. Notwithstanding, it resulted in marked improvement over the existing techniques in terms of range that indicates the level of performance fluctuation. The level of performance fluctuation before and after the model generation improved by 51.31% in the initial test. Then in the following test, there has been 36.05% improvement in the level of performance fluctuation driven by the changes in the number of clusters. This signifies that the proposed method, despite the slight performance improvement, clearly offers better performance stability compared to the existing techniques. Further research on this study will be directed toward enhancing the recommendation performance that failed to demonstrate significant improvement over the existing techniques. The future research will consider the introduction of a high-dimensional parameter-free clustering algorithm or deep learning-based model in order to improve performance in recommendations.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
• /
• v.12 no.12
• /
• pp.1098-1125
• /
• 2000

A review on the papers published in the Korean Journal of Air-Conditioning and Refrigerating Engineering in 1998 and 1999 has been done. Focus has been put on current status of research in the aspect of heating, cooling, ventilation, sanitation and building environment. The conclusions are as follows. 1) A review of the recent studies on fluid flow, turbomachinery and pipe-network shows that many experimental investigations are conducted in applications of impingement jets. Researches on turbulent flows, pipe flows, pipe-networks are focused on analyses of practical systems and prediction of system performance. The results of noise reduction in the turbomachinery are also reported. 2) A review of the recent studies on heat transfer analysis and heat exchanger shows that there were many papers on the channel flow with the application to the design of heat exchanger in the heat transfer analysis. Various experimental and numerical papers on heat exchanger were also published, however, there were few papers available for the analysis of whole system including heat exchanger. 3) A review of the recent studies on heat pump system have focused on the multi-type system and the heat pump cycle to utilize treated sewage as the heat source. The defrosting and the frosting behaviors in the fin-tube heat exchanger is experimentally examined by several authors. Several papers on the ice storage cooling system are presented to show the dynamic simulation program and optimal operation conditions. The study on the micro heat pipes for the cooling of high power electronic components is carried out to examine the characteristics of heat and mass transfer processed. In addition to these, new type of separate thermosyphon is studied experimentally. 4) The recent studies on refrigeration/air conditioning system have focused on the system performance and efficiency for new alternative refrigerants. New systems operating with natural refrigerants are drawing lots of attention. In addition to these, evaporation and condensation heat transfer characteristics of traditional and new refrigerants are investigated for plain tubes and also for microfin tubes. Capillary tubes and orifice are main topics of research as expansion devices and studies on thermophysical properties of new refrigerants and refrigerant/oil mixtures are widely carried out. 5) A review of the recent studies on absorption cooling system shows that numerous experimental and analytical studies on the improvement of absorber performance have been presented. Dynamic analysis of compressor have been performed to understand its vibration characteristics. However research works on tow-phase flow and heat transfer, which could be encountered in the refrigeration system and various phase-change heat exchanger, were seemed to be insufficient. 6) A review of recent studies on duct system shows that the methods for circuit analysis, and flow balancing have been presented. Researches on ventilation are focused on the measurement of ventilation efficiency, and variation of ventilation efficiency with ventilation methods by numerous experimental and numerical studies. Furthermore, many studies have been conducted in real building in order to estimate indoor thermal environments. Many research works to get some information for cooling tower design have been performed but are insufficient. 7) A review on the recent studies on architectural thermal environment and building mechanical systems design shows that thermal comfort analysis is sitting environment, thermal performance analysis of Korean traditional building structures., and evaluation of building environmental load have been performed. However research works to improve the performance of mechanical system design and construction technology were seemed to be insufficient.

• Journal of Intelligence and Information Systems
• /
• v.29 no.2
• /
• pp.101-114
• /
• 2023

In the wartime, aircraft carrying out a mission to strike the enemy deep in the depth are exposed to the risk of being shoot down. As a key combat force in mordern warfare, it takes a lot of time, effot and national budget to train military flight personnel who operate high-tech weapon systems. Therefore, this study studied the path problem of predicting the route of emergency escape from enemy territory to the target point to avoid obstacles, and through this, the possibility of safe recovery of emergency escape military flight personnel was increased. based problem, transforming the problem into a TSP, VRP, and Dijkstra algorithm, and approaching it with an optimization technique. However, if this problem is approached in a network problem, it is difficult to reflect the dynamic factors and uncertainties of the battlefield environment that military flight personnel in distress will face. So, MDP suitable for modeling dynamic environments was applied and studied. In addition, GIS was used to obtain topographic information data, and in the process of designing the reward structure of MDP, topographic information was reflected in more detail so that the model could be more realistic than previous studies. In this study, value iteration algorithms and deterministic methods were used to derive a path that allows the military flight personnel in distress to move to the shortest distance while making the most of the topographical advantages. In addition, it was intended to add the reality of the model by adding actual topographic information and obstacles that the military flight personnel in distress can meet in the process of escape and escape. Through this, it was possible to predict through which route the military flight personnel would escape and escape in the actual situation. The model presented in this study can be applied to various operational situations through redesign of the reward structure. In actual situations, decision support based on scientific techniques that reflect various factors in predicting the escape route of the military flight personnel in distress and conducting combat search and rescue operations will be possible.

• Journal of Bio-Environment Control
• /
• v.32 no.4
• /
• pp.501-512
• /
• 2023

This study aimed to assess and determine the optimal model for predicting the full bloom date of 'Fuji' apples across South Korea. We evaluated the performance of four distinct models: the Development Rate Model (DVR)1, DVR2, the Chill Days (CD) model, and a sequentially integrated approach that combined the Dynamic model (DM) and the Growing Degree Hours (GDH) model. The full bloom dates and air temperatures were collected over a three-year period from six orchards located in the major apple production regions of South Korea: Pocheon, Hwaseong, Geochang, Cheongsong, Gunwi, and Chungju. Among these models, the one that combined DM for calculating chilling accumulation and the GDH model for estimating heat accumulation in sequence demonstrated the most accurate predictive performance, in contrast to the CD model that exhibited the lowest predictive precision. Furthermore, the DVR1 model exhibited an underestimation error at orchard located in Hwaseong. It projected a faster progression of the full bloom dates than the actual observations. This area is characterized by minimal diurnal temperature ranges, where the daily minimum temperature is high and the daily maximum temperature is relatively low. Therefore, to achieve a comprehensive prediction of the blooming date of 'Fuji' apples across South Korea, it is recommended to integrate a DM model for calculating the necessary chilling accumulation to break dormancy with a GDH model for estimating the requisite heat accumulation for flowering after dormancy release. This results in a combined DM+GDH model recognized as the most effective approach. However, further data collection and evaluation from different regions are needed to further refine its accuracy and applicability.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.57-71
• /
• 2013

Over a billion people in the world generate new news minute by minute. People forecasts some news but most news are from unexpected events such as natural disasters, accidents, crimes. People spend much time to watch a huge amount of news delivered from many media because they want to understand what is happening now, to predict what might happen in the near future, and to share and discuss on the news. People make better daily decisions through watching and obtaining useful information from news they saw. However, it is difficult that people choose news suitable to them and obtain useful information from the news because there are so many news media such as portal sites, broadcasters, and most news articles consist of gossipy news and breaking news. User interest changes over time and many people have no interest in outdated news. From this fact, applying users' recent interest to personalized news service is also required in news service. It means that personalized news service should dynamically manage user profiles. In this paper, a content-based news recommendation system is proposed to provide the personalized news service. For a personalized service, user's personal information is requisitely required. Social network service is used to extract user information for personalization service. The proposed system constructs dynamic user profile based on recent user information of Facebook, which is one of social network services. User information contains personal information, recent articles, and Facebook Page information. Facebook Pages are used for businesses, organizations and brands to share their contents and connect with people. Facebook users can add Facebook Page to specify their interest in the Page. The proposed system uses this Page information to create user profile, and to match user preferences to news topics. However, some Pages are not directly matched to news topic because Page deals with individual objects and do not provide topic information suitable to news. Freebase, which is a large collaborative database of well-known people, places, things, is used to match Page to news topic by using hierarchy information of its objects. By using recent Page information and articles of Facebook users, the proposed systems can own dynamic user profile. The generated user profile is used to measure user preferences on news. To generate news profile, news category predefined by news media is used and keywords of news articles are extracted after analysis of news contents including title, category, and scripts. TF-IDF technique, which reflects how important a word is to a document in a corpus, is used to identify keywords of each news article. For user profile and news profile, same format is used to efficiently measure similarity between user preferences and news. The proposed system calculates all similarity values between user profiles and news profiles. Existing methods of similarity calculation in vector space model do not cover synonym, hypernym and hyponym because they only handle given words in vector space model. The proposed system applies WordNet to similarity calculation to overcome the limitation. Top-N news articles, which have high similarity value for a target user, are recommended to the user. To evaluate the proposed news recommendation system, user profiles are generated using Facebook account with participants consent, and we implement a Web crawler to extract news information from PBS, which is non-profit public broadcasting television network in the United States, and construct news profiles. We compare the performance of the proposed method with that of benchmark algorithms. One is a traditional method based on TF-IDF. Another is 6Sub-Vectors method that divides the points to get keywords into six parts. Experimental results demonstrate that the proposed system provide useful news to users by applying user's social network information and WordNet functions, in terms of prediction error of recommended news.

• Journal of Technology Innovation
• /
• v.14 no.1
• /
• pp.31-66
• /
• 2006

The country with a relative abundance of human capital conducts relatively more R&D in the steady state than its partner. This country acquires the know-how to produce a relatively wider range of innovative goods. High technology comprises a large share of the national economy in the human-capital rich country and real output growth is faster. This prediction would seem to accord weakly with empirical observation of Korean economy.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.16 no.4
• /
• pp.396-402
• /
• 2014

The spring season in Korea features a dynamic landscape with a variety of flowers such as magnolias, azaleas, forsythias, cherry blossoms and royal azaleas flowering sequentially one after another. However, the narrowing of south-north differences in flowering dates and those among the flower species was observed in 2014, taking a toll on economic and shared communal values of seasonal landscape. This study was carried out to determine whether the 2014 incidence is an outlier or a mega trend in spring phenology. Data on flowering dates of forsythias and cherry blossoms, two typical spring flower species, as observed for the recent 60 years in 6 weather stations of Korea Meteorological Administration (KMA) indicate that the difference spanning the flowering date of forsythias, the flower blooming earlier in spring, and that of cherry blossoms that flower later than forsythias was 30 days at the longest and 14 days on an average in the climatological normal year for the period 1951-1980, comparing with the period 1981-2010 when the difference narrowed to 21 days at the longest and 11 days on an average. The year 2014 in particular saw the gap further narrowing down to 7 days, making it possible to see forsythias and cherry blossoms blooming at the same time in the same location. 'Cherry blossom front' took 20 days in traveling from Busan, the earliest flowering station, to Incheon, the latest flowering station, in the case of the 1951-1980 normal year, while 16 days for the 1981-2010 and 6 days for 2014 were observed. The delay in flowering date of forsythias for each time period was 20, 17, and 12 days, respectively. It is presumed that the recent climate change pattern in the Korean Peninsula as indicated by rapid temperature hikes in late spring contrastive to slow temperature rise in early spring immediately after dormancy release brought forward the flowering date of cherry blossoms which comes later than forsythias which flowers early in spring. Thermal time based heating requirements for flowering of 2 species were estimated by analyzing the 60 year data at the 6 locations and used to predict flowering date in 2014. The root mean square error for the prediction was within 2 days from the observed flowering dates in both species at all 6 locations, showing a feasibility of thermal time as a prognostic tool.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.17 no.2
• /
• pp.108-125
• /
• 2015

The agro-climatic index is one of the ways to assess the climate resources of particular agricultural areas on the prospect of agricultural production; it can be a key indicator of agricultural productivity by providing the basic information required for the implementation of different and various farming techniques and practicalities to estimate the growth and yield of crops from the climate resources such as air temperature, solar radiation, and precipitation. However, the agro-climate index can always be changed since the index is not the absolute. Recently, many studies which consider uncertainty of future climate change have been actively conducted using multi-model ensemble (MME) approach by developing and improving dynamic and statistical downscaling of Global Climate Model (GCM) output. In this study, the agro-climatic index of Korean Peninsula, such as growing degree day based on $5^{\circ}C$, plant period based on $5^{\circ}C$, crop period based on $10^{\circ}C$, and frost free day were calculated for assessment of the spatio-temporal variations and uncertainties of the indices according to climate change; the downscaled historical (1976-2005) and near future (2011-2040) RCP climate sceneries of AR5 were applied to the calculation of the index. The result showed four agro-climatic indices calculated by nine individual GCMs as well as MME agreed with agro-climatic indices which were calculated by the observed data. It was confirmed that MME, as well as each individual GCM emulated well on past climate in the four major Rivers of South Korea (Han, Nakdong, Geum, and Seumjin and Yeoungsan). However, spatial downscaling still needs further improvement since the agro-climatic indices of some individual GCMs showed different variations with the observed indices at the change of spatial distribution of the four Rivers. The four agro-climatic indices of the Korean Peninsula were expected to increase in nine individual GCMs and MME in future climate scenarios. The differences and uncertainties of the agro-climatic indices have not been reduced on the unlimited coupling of multi-model ensembles. Further research is still required although the differences started to improve when combining of three or four individual GCMs in the study. The agro-climatic indices which were derived and evaluated in the study will be the baseline for the assessment of agro-climatic abnormal indices and agro-productivity indices of the next research work.

• The Journal of Engineering Geology
• /
• v.22 no.3
• /
• pp.343-351
• /
• 2012

This study proposes a modified equation to calculate the factor of safety for an infinite slope considering the saturation depth ratio as a new variable calculated from rainfall infiltration into unsaturated soil. For the proposed equation, this study introduces the concepts of the saturation depth ratio and subsurface flow depth. Analysis of the factor of safety for an infinite slope is conducted by the sequential calculation of the effective upslope contributing area, subsurface flow depth, and the saturation depth ratio based on quasi-dynamic wetness index theory. The calculation process makes it possible to understand changes in the factor of safety and the infiltration behavior of individual rainfall events. This study analyzes stability changes in an infinite slope, considering the saturation depth ratio of soil, based on the proposed equation and the results of soil column tests performed by Park et al. (2011 a). The analysis results show that changes in the factor of safety are dependent on the saturation depth ratio, which reflects the rainfall infiltration into unsaturated weathered gneiss soil. Under continuous rainfall with intensities of 20 and 50 mm/h, the time taken for the factor of safety to decrease to less than 1.3 was 2.86-5.38 hours and 1.34-2.92 hours, respectively; in the case of repeated rainfall events, the time taken was between 3.27 and 5.61 hours. The results demonstrate that it is possible to understand changes in the factor of safety for an infinite slope dependent on the saturation depth ratio.