• Annals of Hepato-Biliary-Pancreatic Surgery
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• v.28 no.1
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• pp.70-79
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• 2024

Backgrounds/Aims: After pancreatoduodenectomy (PD), an early oral diet is recommended; however, the postoperative nutritional management of PD patients is known to be highly variable, with some centers still routinely providing parenteral nutrition (PN). Some patients who receive PN experience clinically significant complications, underscoring its judicious use. Using a large cohort, this study aimed to determine the proportion of PD patients who received postoperative nutritional support (NS), describe the nature of this support, and investigate whether receiving PN correlated with adverse perioperative outcomes. Methods: Data were extracted from the Recurrence After Whipple's study, a retrospective multicenter study of PD outcomes. Results: In total, 1,323 patients (89%) had data on their postoperative NS status available. Of these, 45% received postoperative NS, which was "enteral only," "parenteral only," and "enteral and parenteral" in 44%, 35%, and 21% of cases, respectively. Body mass index < 18.5 kg/m² (p = 0.03), absence of preoperative biliary stenting (p = 0.009), and serum albumin < 36 g/L (p = 0.009) all correlated with receiving postoperative NS. Among those who did not develop a serious postoperative complication, i.e., those who had a relatively uneventful recovery, 20% received PN. Conclusions: A considerable number of patients who had an uneventful recovery received PN. PN is not without risk, and should be reserved for those who are unable to take an oral diet. PD patients should undergo pre- and postoperative assessment by nutrition professionals to ensure they are managed appropriately, and to optimize perioperative outcomes.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.1-23
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• 2018

From the 21st century, various high-quality services have come up with the growth of the internet or 'Information and Communication Technologies'. Especially, the scale of E-commerce industry in which Amazon and E-bay are standing out is exploding in a large way. As E-commerce grows, Customers could get what they want to buy easily while comparing various products because more products have been registered at online shopping malls. However, a problem has arisen with the growth of E-commerce. As too many products have been registered, it has become difficult for customers to search what they really need in the flood of products. When customers search for desired products with a generalized keyword, too many products have come out as a result. On the contrary, few products have been searched if customers type in details of products because concrete product-attributes have been registered rarely. In this situation, recognizing texts in images automatically with a machine can be a solution. Because bulk of product details are written in catalogs as image format, most of product information are not searched with text inputs in the current text-based searching system. It means if information in images can be converted to text format, customers can search products with product-details, which make them shop more conveniently. There are various existing OCR(Optical Character Recognition) programs which can recognize texts in images. But existing OCR programs are hard to be applied to catalog because they have problems in recognizing texts in certain circumstances, like texts are not big enough or fonts are not consistent. Therefore, this research suggests the way to recognize keywords in catalog with the Deep Learning algorithm which is state of the art in image-recognition area from 2010s. Single Shot Multibox Detector(SSD), which is a credited model for object-detection performance, can be used with structures re-designed to take into account the difference of text from object. But there is an issue that SSD model needs a lot of labeled-train data to be trained, because of the characteristic of deep learning algorithms, that it should be trained by supervised-learning. To collect data, we can try labelling location and classification information to texts in catalog manually. But if data are collected manually, many problems would come up. Some keywords would be missed because human can make mistakes while labelling train data. And it becomes too time-consuming to collect train data considering the scale of data needed or costly if a lot of workers are hired to shorten the time. Furthermore, if some specific keywords are needed to be trained, searching images that have the words would be difficult, as well. To solve the data issue, this research developed a program which create train data automatically. This program can make images which have various keywords and pictures like catalog and save location-information of keywords at the same time. With this program, not only data can be collected efficiently, but also the performance of SSD model becomes better. The SSD model recorded 81.99% of recognition rate with 20,000 data created by the program. Moreover, this research had an efficiency test of SSD model according to data differences to analyze what feature of data exert influence upon the performance of recognizing texts in images. As a result, it is figured out that the number of labeled keywords, the addition of overlapped keyword label, the existence of keywords that is not labeled, the spaces among keywords and the differences of background images are related to the performance of SSD model. This test can lead performance improvement of SSD model or other text-recognizing machine based on deep learning algorithm with high-quality data. SSD model which is re-designed to recognize texts in images and the program developed for creating train data are expected to contribute to improvement of searching system in E-commerce. Suppliers can put less time to register keywords for products and customers can search products with product-details which is written on the catalog.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.5 no.1
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• pp.37-46
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• 2000

We investigated the temporal and spatial variations in heterotrophic dinoflagellates (hereafter HTD) and ciliates from June to September 1997 in the waters off Kohung, Korea where red tides dominated by harmful dinoflagellates had occurred from August to October since 1995. We took water samples five times from 5-7 depths at 3 stations in this study period. A total of 17 HTD species were present and of these species in the genus Protoperidinium were 11. The species number of tintinnids (hereafter TIN) present totalled 15 and several naked ciliate (hereafter NC) species were observed. The species numbers of HTD and TIN rapidly increased between August 1st and 21st and then reached to the maximum numbers of 13 and 10, respectively, on August 27 when red tides dominated by Gyrodinium impudicum were first observed in the study area. However the species numbers drastically decreased on September 22. The maximum densities of HTD, TIN, and NC were 45, 39, 57 cells $ml^{-1}$, respectively. ADAS, calculated by averaging the densities of a certain species in the all samples collected from all depths and stations at a sampling period, most increased between August 1st and 21st and then reached to the maximum density of f cells $ml^{-1}$ on August 27 for HTD, while did between August 21st and 27th and up to 7 cells $ml^{-1}$ for TIN. Unlike ADAS of HTD and TIN, that of NC did not change much with the maximum of 8 cells $ml^{-1}$ on August 27th. The pattern of the temperal variation in the species number and ADAS of HTD was similar to that of diatoms and the distributions of Protoperidinium spp. and diatoms had a strong positive correlation. This evidence suggests that HTD, in particular Protoperidinium spp. be a grazer on diatom. In general, the densities of HTD, TIN, and NC decreased with going to stations located in the outer bay. Therefore, the availability of suitable prey and distance from the coastal line might be responsible for the distribution of HTD, TIN, and NC. The results of the present study provide a basis for further experiments for the feeding by dominant HTD, TIN, and NC on dominant phytoplankton including red tide species and for understanding food webs in the planktonic community before, during, and after the red tide outbreak.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.33 no.5
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• pp.455-462
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• 2000

The objective of this study was to examine the physicochemical characteristics of coagulation reaction between loess and red tide organisms (RTO) and its feasibility, in developing a technology for the removal of RTO bloom in coastal sea. The physicochemical characteristics of loess were examined for a particle size distribution, surface characteristics by scanning electron microscope, zeta potential, and alkalinity and pH variations in sea water. Two kinds of RTO that were used in this study, Cylindrothen closterium and Skeietonema costatum, were sampled in Masan bay and were cultured in laboratory. Coagulation experiments were conducted using various concentrations of loess, RTO, and a jar tester. The supernatant and RTO culture solution were analyzed for pH, alkalinity, RTO cell number. A negative zeta potential of loess increased with increasing pH at $10^(-3)M$ NaCl solution and had -71.3 mV at pH 9.36. Loess had a positive zeta potential of +1,8 mV at pH 1.98, which resulted in a characteristic of material having an amphoteric surface charge. In NaCl and $CaCl_2$, solutions, loess had a decreasing negative zeta potential with increasing $Na^+\;and\;Ca^(+2)$ ion concentration and then didn't result in a charge reversal due to not occurring specific adsorption for $Na^+$ ion while resulted in a charge reversal due to occurring specific adsorption for $Ca^(+2)$ ion. In sea water, loess and RTO showed the similar zeta potential values of -112,1 and -9.2 mV, respectively and sea sand powder showed the highest zeta potential value of -25.7 mV in the clays. EDLs (electrical double-layers) of loess and RTO were extremely compressed due to high concentration of salts included in sea water, As a result, there didn't almost exist EDL repulsive force between loess and RTO approaching each other and then LVDW (London-yan der Waals) attractive force was always larger than EDL repulsive force to easily form a floe. Removal rates of RTO exponentially increased with increasing a loess concentration. The removal rates steeply increased until $800 mg/l$ of loess, and reached $100{\%}$ at 6,400 mg/l of loess. Removal rates of RTO exponentially increased with increasing a G-value. This indicated that mixing (i.e., collision among particles) was very important for a coagulation reaction. Loess showed the highest RTO removal rates in the clays.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.19 no.4
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• pp.243-255
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• 2014

This study was investigated to estimate the relations between benthic environments and benthic polychaetous community from April 2012 to February 2013. Twenty four stations were selected sequentially with Seomjin River Estuary from the northern part of Gwangyang Bay. The study area could be divided into three characteristic zones based on salinity, water temperature, dissolved oxygen and pH such as Saline Water Zone (SWZ), Brackish Water Zone (BWZ), and Fresh Water Zone (FWZ). Salinity was above 30.0 psu in SWZ, drastically decreased toward inland in BWZ, and nearly zero psu in FWZ. SWZ showed its specific environmental characters like that water temperature fluctuated with little seasonal change and DO showed the lowest values among three zones, and pH maintained as consistent value without seasonal fluctuation. In FWZ, on the other hand, water temperature showed high seasonal fluctuation, DO showed the highest values among three zones, and pH fluctuated greatly. In sedimentary environment, mud, sand and sand/gravel were found as dominant sedimentary deposits in SWZ, BWZ and FWZ, respectively. Organic matter content and AVS in surface sediment were high in SWZ, while Chl-a content high in FWZ. This study area showed a marked environmental difference between FWZ and SWZ as follows: FWZ has coarse sediment and low salinity, low organic matter content, low AVS in FWZ but SWZ has fine sediment and high salinity, high organic matter content and AVS. Species number and mean density of benthic polychaete community was highest in Saline Water Zone (SWZ), drastically decreased in Brackish Water Zone (BWZ), and lowest in Fresh Water Zone (FWZ). Dominant polychates above 5.0% of individual numbers were 6 taxa. Lumbrineris longifolia, Prionospio cirrifera, Tharyx sp. occurred as main dominant species of all study periods, and Hediste sp., Praxillella affinis, Tylorrhynchus sp. dominantly occurred at some seasons. Inhabiting areas of dominant species were separated characteristically. Representative species in SWZ were Lumbrineris longifolia, Tharyx sp., Mediomastus sp.. Wide-appearing species between SWZ and BWZ were Prionospio cirrifera, Heteromastus filiformis, Aricidea sp.. Characteristic species in FWZ were Tylorrhynchus sp. and Hediste sp.. As the results of cluster analysis and nMDS based on the species composition of polychaetous community, unique station groups were established in SWZ and FWZ. Stations in BWZ were sub-divided into several groups with season. Pearson's correlation analysis and PCA between benthic environments and ecological characteristics of polychaetous community showed that salinity, sediment composition, organic content and dissolved oxygen played a role to determine the temporal and spatial distribution of the ecological characteristics as species number, mean density, abundance of main species, and ecological indices.

• The Korean Journal of Petroleum Geology
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• v.8 no.1_2 s.9
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• pp.1-43
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• 2000

A comparison study for understanding a stratigraphic response to tectonic evolution of sedimentary basins in the Yellow Sea and adjacent areas was carried out by using an integrated stratigraphic technology. As an interim result, we propose a stratigraphic framework that allows temporal and spatial correlation of the sedimentary successions in the basins. This stratigraphic framework will use as a new stratigraphic paradigm for hydrocarbon exploration in the Yellow Sea and adjacent areas. Integrated stratigraphic analysis in conjunction with sequence-keyed biostratigraphy allows us to define nine stratigraphic units in the basins: Cambro-Ordovician, Carboniferous-Triassic, early to middle Jurassic, late Jurassic-early Cretaceous, late Cretaceous, Paleocene-Eocene, Oligocene, early Miocene, and middle Miocene-Pliocene. They are tectono-stratigraphic units that provide time-sliced information on basin-forming tectonics, sedimentation, and basin-modifying tectonics of sedimentary basins in the Yellow Sea and adjacent area. In the Paleozoic, the South Yellow Sea basin was initiated as a marginal sag basin in the northern margin of the South China Block. Siliciclastic and carbonate sediments were deposited in the basin, showing cyclic fashions due to relative sea-level fluctuations. During the Devonian, however, the basin was once uplifted and deformed due to the Caledonian Orogeny, which resulted in an unconformity between the Cambro-Ordovician and the Carboniferous-Triassic units. The second orogenic event, Indosinian Orogeny, occurred in the late Permian-late Triassic, when the North China block began to collide with the South China block. Collision of the North and South China blocks produced the Qinling-Dabie-Sulu-Imjin foldbelts and led to the uplift and deformation of the Paleozoic strata. Subsequent rapid subsidence of the foreland parallel to the foldbelts formed the Bohai and the West Korean Bay basins where infilled with the early to middle Jurassic molasse sediments. Also Piggyback basins locally developed along the thrust. The later intensive Yanshanian (first) Orogeny modified these foreland and Piggyback basins in the late Jurassic. The South Yellow Sea basin, however, was likely to be a continental interior sag basin during the early to middle Jurassic. The early to middle Jurassic unit in the South Yellow Sea basin is characterized by fluvial to lacustrine sandstone and shale with a thick basal quartz conglomerate that contains well-sorted and well-rounded gravels. Meanwhile, the Tan-Lu fault system underwent a sinistrai strike-slip wrench movement in the late Triassic and continued into the Jurassic and Cretaceous until the early Tertiary. In the late Jurassic, development of second- or third-order wrench faults along the Tan-Lu fault system probably initiated a series of small-scale strike-slip extensional basins. Continued sinistral movement of the Tan-Lu fault until the late Eocene caused a megashear in the South Yellow Sea basin, forming a large-scale pull-apart basin. However, the Bohai basin was uplifted and severely modified during this period. h pronounced Yanshanian Orogeny (second and third) was marked by the unconformity between the early Cretaceous and late Eocene in the Bohai basin. In the late Eocene, the Indian Plate began to collide with the Eurasian Plate, forming a megasuture zone. This orogenic event, namely the Himalayan Orogeny, was probably responsible for the change of motion of the Tan-Lu fault system from left-lateral to right-lateral. The right-lateral strike-slip movement of the Tan-Lu fault caused the tectonic inversion of the South Yellow Sea basin and the pull-apart opening of the Bohai basin. Thus, the Oligocene was the main period of sedimentation in the Bohai basin as well as severe tectonic modification of the South Yellow Sea basin. After the Oligocene, the Yellow Sea and Bohai basins have maintained thermal subsidence up to the present with short periods of marine transgressions extending into the land part of the present basins.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of Distribution Research
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• v.15 no.3
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• pp.71-110
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• 2010

1. Introduction Today Internet is recognized as an important way for the transaction of products and services. According to the data surveyed by the National Statistical Office, the on-line transaction in 2007 for a year, 15.7656 trillion, shows a 17.1%(2.3060 trillion won) increase over last year, of these, the amount of B2C has been increased 12.0%(10.2258 trillion won). Like this, because the entry barrier of on-line market of Korea is low, many retailers could easily enter into the market. So the bigger its scale is, but on the other hand, the tougher its competition is. Particularly due to the Internet and innovation of IT, the existing market has been changed into the perfect competitive market(Srinivasan, Rolph & Kishore, 2002). In the early years of on-line business, they think that the main reason for success is a moderate price, they are awakened to its importance of on-line service quality with tough competition. If it's not sure whether customers can be provided with what they want, they can use the Web sites, perhaps they can trust their products that had been already bought or not, they have a doubt its viability(Parasuraman, Zeithaml & Malhotra, 2005). Customers can directly reserve and issue their air tickets irrespective of place and time at the Web sites of travel agencies or airlines, but its empirical studies about these Web sites for reserving and issuing air tickets are insufficient. Therefore this study goes on for following specific objects. First object is to measure service quality and service recovery of Web sites for reserving and issuing air tickets. Second is to look into whether above on-line service quality and on-line service recovery have an impact on overall service quality. Third is to seek for the relation with overall service quality and customer satisfaction, then this customer satisfaction and loyalty intention. 2. Theoretical Background 2.1 On-line Service Quality Barnes & Vidgen(2000; 2001a; 2001b; 2002) had invented the tool to measure Web sites' quality four times(called WebQual). The WebQual 1.0, Step one invented a measuring item for information quality based on QFD, and this had been verified by students of UK business school. The Web Qual 2.0, Step two invented for interaction quality, and had been judged by customers of on-line bookshop. The WebQual 3.0, Step three invented by consolidating the WebQual 1.0 for information quality and the WebQual2.0 for interactionquality. It includes 3-quality-dimension, information quality, interaction quality, site design, and had been assessed and confirmed by auction sites(e-bay, Amazon, QXL). Furtheron, through the former empirical studies, the authors changed sites quality into usability by judging that usability is a concept how customers interact with or perceive Web sites and It is used widely for accessing Web sites. By this process, WebQual 4.0 was invented, and is consist of 3-quality-dimension; information quality, interaction quality, usability, 22 items. However, because WebQual 4.0 is focusing on technical part, it's usable at the Website's design part, on the other hand, it's not usable at the Web site's pleasant experience part. Parasuraman, Zeithaml & Malhorta(2002; 2005) had invented the measure for measuring on-line service quality in 2002 and 2005. The study in 2002 divided on-line service quality into 5 dimensions. But these were not well-organized, so there needed to be studied again totally. So Parasuraman, Zeithaml & Malhorta(2005) re-worked out the study about on-line service quality measure base on 2002's study and invented E-S-QUAL. After they invented preliminary measure for on-line service quality, they made up a question for customers who had purchased at amazon.com and walmart.com and reassessed this measure. And they perfected an invention of E-S-QUAL consists of 4 dimensions, 22 items of efficiency, system availability, fulfillment, privacy. Efficiency measures assess to sites and usability and others, system availability measures accurate technical function of sites and others, fulfillment measures promptness of delivering products and sufficient goods and others and privacy measures the degree of protection of data about their customers and so on. 2.2 Service Recovery Service industries tend to minimize the losses by coping with service failure promptly. This responses of service providers to service failure mean service recovery(Kelly & Davis, 1994). Bitner(1990) went on his study from customers' view about service providers' behavior for customers to recognize their satisfaction/dissatisfaction at service point. According to them, to manage service failure successfully, exact recognition of service problem, an apology, sufficient description about service failure and some tangible compensation are important. Parasuraman, Zeithaml & Malhorta(2005) approached the service recovery from how to measure, rather than how to manage, and moved to on-line market not to off-line, then invented E-RecS-QUAL which is a measuring tool about on-line service recovery. 2.3 Customer Satisfaction The definition of customer satisfaction can be divided into two points of view. First, they approached customer satisfaction from outcome of comsumer. Howard & Sheth(1969) defined satisfaction as 'a cognitive condition feeling being rewarded properly or improperly for their sacrifice.' and Westbrook & Reilly(1983) also defined customer satisfaction/dissatisfaction as 'a psychological reaction to the behavior pattern of shopping and purchasing, the display condition of retail store, outcome of purchased goods and service as well as whole market.' Second, they approached customer satisfaction from process. Engel & Blackwell(1982) defined satisfaction as 'an assessment of a consistency in chosen alternative proposal and their belief they had with them.' Tse & Wilton(1988) defined customer satisfaction as 'a customers' reaction to discordance between advance expectation and ex post facto outcome.' That is, this point of view that customer satisfaction is process is the important factor that comparing and assessing process what they expect and outcome of consumer. Unlike outcome-oriented approach, process-oriented approach has many advantages. As process-oriented approach deals with customers' whole expenditure experience, it checks up main process by measuring one by one each factor which is essential role at each step. And this approach enables us to check perceptual/psychological process formed customer satisfaction. Because of these advantages, now many studies are adopting this process-oriented approach(Yi, 1995). 2.4 Loyalty Intention Loyalty has been studied by dividing into behavioral approaches, attitudinal approaches and complex approaches(Dekimpe et al., 1997). In the early years of study, they defined loyalty focusing on behavioral concept, behavioral approaches regard customer loyalty as "a tendency to purchase periodically within a certain period of time at specific retail store." But the loyalty of behavioral approaches focuses on only outcome of customer behavior, so there are someone to point the limits that customers' decision-making situation or process were neglected(Enis & Paul, 1970; Raj, 1982; Lee, 2002). So the attitudinal approaches were suggested. The attitudinal approaches consider loyalty contains all the cognitive, emotional, voluntary factors(Oliver, 1997), define the customer loyalty as "friendly behaviors for specific retail stores." However these attitudinal approaches can explain that how the customer loyalty form and change, but cannot say positively whether it is moved to real purchasing in the future or not. This is a kind of shortcoming(Oh, 1995). 3. Research Design 3.1 Research Model Based on the objects of this study, the research model derived is