• Title/Summary/Keyword: Distribution Information

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Detection of Freshwater Jellyfish (Craspedacusta sowerbii Lankester, 1880) by Biofilm eDNA in Miho River Watershed (미호강 수계 생물막의 환경유전자를 이용한 담수해파리 (Craspedacusta sowerbii Lankester, 1880) 유전자 탐색)

  • Keonhee Kim ;Hyeonjin Cho ;Jeong-Hui Kim;Yun-mo Yang;Hyunji Ju;Hyun-Gi Jeong
    • Korean Journal of Ecology and Environment
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    • v.56 no.3
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    • pp.250-258
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    • 2023
  • Freshwater jellyfish, a type of jellyfish exclusively found in freshwater, has a limited number of species but is found globally. However, their ecology and causes of occurrence are largely unknown. Therefore, understanding the distribution of polyps, which produce the larvae of freshwater jellyfish, can provide important data for comprehending their ecology. This study aims to explore the COI gene of freshwater jellyfish using environmental DNA from the microbial film in the Miho River system. Among the 12 survey points in the Miho River watershed, genetic material of freshwater jellyfish was detected in 8 points, mainly located upstream near reservoirs. These genetic materials were identified as genes of the well-known freshwater jellyfish species, Craspedacusta sowerbii. Notably, the C. sowerbii genes found in the Miho River watershed survey points were closely related to a species previously discovered in Italy. Consequently, utilizing environmental DNA to explore the genetic traces of freshwater jellyfish enables rapid screening of areas with a high likelihood of freshwater jellyfish occurrence. This approach is deemed to provide crucial information for understanding the distribution and ecology of freshwater jellyfish in Korea.

A novel method for determining dose distribution on panoramic reconstruction computed tomography images from radiotherapy computed tomography

  • Hiroyuki Okamoto;Madoka Sakuramachi;Wakako Yatsuoka;Takao Ueno;Kouji Katsura;Naoya Murakami;Satoshi Nakamura;Kotaro Iijima;Takahito Chiba;Hiroki Nakayama;Yasunori Shuto;Yuki Takano;Yuta Kobayashi;Hironori Kishida;Yuka Urago;Masato Nishitani;Shuka Nishina;Koushin Arai;Hiroshi Igaki
    • Imaging Science in Dentistry
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    • v.54 no.2
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    • pp.129-137
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    • 2024
  • Purpose: Patients with head and neck cancer (HNC) who undergo dental procedures during radiotherapy (RT) face an increased risk of developing osteoradionecrosis (ORN). Accordingly, new tools must be developed to extract critical information regarding the dose delivered to the teeth and mandible. This article proposes a novel approach for visualizing 3-dimensional planned dose distributions on panoramic reconstruction computed tomography (pCT) images. Materials and Methods: Four patients with HNC who underwent volumetric modulated arc therapy were included. One patient experienced ORN and required the extraction of teeth after RT. In the study approach, the dental arch curve (DAC) was defined using an open-source platform. Subsequently, pCT images and dose distributions were generated based on the new coordinate system. All teeth and mandibles were delineated on both the original CT and pCT images. To evaluate the consistency of dose metrics, the Mann-Whitney U test and Student t-test were employed. Results: A total of 61 teeth and 4 mandibles were evaluated. The correlation coefficient between the 2 methods was 0.999, and no statistically significant difference was observed (P>0.05). This method facilitated a straightforward and intuitive understanding of the delivered dose. In 1 patient, ORN corresponded to the region of the root and the gum receiving a high dosage (approximately 70 Gy). Conclusion: The proposed method particularly benefits dentists involved in the management of patients with HNC. It enables the visualization of a 3-dimensional dose distribution in the teeth and mandible on pCT, enhancing the understanding of the dose delivered during RT.

A Study on the Application of Outlier Analysis for Fraud Detection: Focused on Transactions of Auction Exception Agricultural Products (부정 탐지를 위한 이상치 분석 활용방안 연구 : 농수산 상장예외품목 거래를 대상으로)

  • Kim, Dongsung;Kim, Kitae;Kim, Jongwoo;Park, Steve
    • Journal of Intelligence and Information Systems
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    • v.20 no.3
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    • pp.93-108
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    • 2014
  • To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

Transference of Trust from Retailers to Private Label Products and their Manufacturers (유통업체에 대한 신뢰가 Private Label 제품과 제조업체에 대한 신뢰로 전이되는 현상에 관한 연구)

  • Kim, Hyang-Mi;Kim, Jae-Wook;Lee, Jong-Ho
    • Journal of Distribution Research
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    • v.14 no.2
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    • pp.67-95
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    • 2009
  • The purpose of this study is to empirically examine the transference of trust process, an important factor to consumer's purchase decision-making. Even though several researchers have discussed the trust transference process, there is no research related to this concept. Specifically we have focused on the transference of trust from the retailer to low involvement private label (PL) products. PL products were chosen as transference of trust occurs under ambiguity due to lack of information about the product and their manufacturer. PL products provide relatively less information than national brand (NB) products. In addition, retailers have been rapidly expanding their PL product categories. To identify the theoretical and empirical limitations of prior studies, we discuss several theories explaining the transference of trust: 'Balance theory' and 'availability heuristic' in transference of cognitive trust; 'affective transference' and 'affect as information' in transference of affective trust. An empirical test was performed. A self completion questionnaire was developed and administered to a convenience sample of PL users. 206 usable questionnaire were received. The results show that the transference of trust plays a mediating role linking the retailer to the manufacturer and to the product. Although our model, which included the transference process of trust as a mediating effect, did not improve the competitive model, the coefficients of the respective paths were found to be better. This study confirms the transference of cognitive trust from the retailer to both the manufacturer and the product, but not for affective trust. We offer the explanation that PL products may tend to have affective trust resulting from brand familiarity but not to their PL manufacturers.

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The Effects of Sentiment and Readability on Useful Votes for Customer Reviews with Count Type Review Usefulness Index (온라인 리뷰의 감성과 독해 용이성이 리뷰 유용성에 미치는 영향: 가산형 리뷰 유용성 정보 활용)

  • Cruz, Ruth Angelie;Lee, Hong Joo
    • Journal of Intelligence and Information Systems
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    • v.22 no.1
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    • pp.43-61
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    • 2016
  • Customer reviews help potential customers make purchasing decisions. However, the prevalence of reviews on websites push the customer to sift through them and change the focus from a mere search to identifying which of the available reviews are valuable and useful for the purchasing decision at hand. To identify useful reviews, websites have developed different mechanisms to give customers options when evaluating existing reviews. Websites allow users to rate the usefulness of a customer review as helpful or not. Amazon.com uses a ratio-type helpfulness, while Yelp.com uses a count-type usefulness index. This usefulness index provides helpful reviews to future potential purchasers. This study investigated the effects of sentiment and readability on useful votes for customer reviews. Similar studies on the relationship between sentiment and readability have focused on the ratio-type usefulness index utilized by websites such as Amazon.com. In this study, Yelp.com's count-type usefulness index for restaurant reviews was used to investigate the relationship between sentiment/readability and usefulness votes. Yelp.com's online customer reviews for stores in the beverage and food categories were used for the analysis. In total, 170,294 reviews containing information on a store's reputation and popularity were used. The control variables were the review length, store reputation, and popularity; the independent variables were the sentiment and readability, while the dependent variable was the number of helpful votes. The review rating is the moderating variable for the review sentiment and readability. The length is the number of characters in a review. The popularity is the number of reviews for a store, and the reputation is the general average rating of all reviews for a store. The readability of a review was calculated with the Coleman-Liau index. The sentiment is a positivity score for the review as calculated by SentiWordNet. The review rating is a preference score selected from 1 to 5 (stars) by the review author. The dependent variable (i.e., usefulness votes) used in this study is a count variable. Therefore, the Poisson regression model, which is commonly used to account for the discrete and nonnegative nature of count data, was applied in the analyses. The increase in helpful votes was assumed to follow a Poisson distribution. Because the Poisson model assumes an equal mean and variance and the data were over-dispersed, a negative binomial distribution model that allows for over-dispersion of the count variable was used for the estimation. Zero-inflated negative binomial regression was used to model count variables with excessive zeros and over-dispersed count outcome variables. With this model, the excess zeros were assumed to be generated through a separate process from the count values and therefore should be modeled as independently as possible. The results showed that positive sentiment had a negative effect on gaining useful votes for positive reviews but no significant effect on negative reviews. Poor readability had a negative effect on gaining useful votes and was not moderated by the review star ratings. These findings yield considerable managerial implications. The results are helpful for online websites when analyzing their review guidelines and identifying useful reviews for their business. Based on this study, positive reviews are not necessarily helpful; therefore, restaurants should consider which type of positive review is helpful for their business. Second, this study is beneficial for businesses and website designers in creating review mechanisms to know which type of reviews to highlight on their websites and which type of reviews can be beneficial to the business. Moreover, this study highlights the review systems employed by websites to allow their customers to post rating reviews.

Antecedents of Trust and Effects on Committment in B2B e-Marketplace (B2B 마켓플레이스에서 신뢰의 선행요인과 몰입에 미치는 영향)

  • Oh, Sang-Hyun;Kim, Sang-Hyeon
    • Journal of Distribution Research
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    • v.13 no.1
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    • pp.1-33
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    • 2008
  • As the interest in the business-to-business(B2B) electronic commerce is increasing, many companies are participating in the B2B e-Marketplaces. The e-Marketplace is defined as the virtual market that many players take part in to transact. The e-Marketplace has an influenced on the manner in which organizational buyers and sellers interact. As a result, it is important to develop an understanding of the behaviors of firms that use these electronic marketplaces. The purpose of this study is to develop a comprehensive model for trust and commitment of B2B e-Marketplace and empirically to examine their structural relationships. Drawing from trust and commitment theory in the interorganizational relationship and B2B electronic commerce context, this study identifies network externality, interactivity, justice, quality of information sharing, institutional assurance as the determinants of trust and commitment of e-Marketplace. The proposed model hypothesized that (1) trust is a function of network externality, interactivity, justice, quality of information sharing, institutional assurance, (2) attitudinal and behavioral commitment is a function of trust, (3) behavioral commitment is a function of attitudinal commitment. The proposed model is tested using organizational-level survey data from 187 buying organizations that conduct business in MRO e-Marketplaces. The data were tested by reliability test, correlation analysis, exploratory factor analysis, confirmatory factor analysis and covariance structure analysis. The results indicate that (1) trust is influenced by network externality, interactivity, justice, institutional assurance, (2) attitudinal commitment and behavioral commitment is influenced by trust (3) behavioral commitment is influenced by attitudinal commitment. Also, the empirical results confirmed that trust play a strong, central role in determinging e-Marketplace commitment. The key theoretical contribution of this research is that it begins to extend interorganizational information system literature in areas such as B2B Internet e-Marketplace. Managerially, this study contributes tn the understanding of the role of B2B e-Markeplace providers in Internet situation. And Limitations of this study and guidelines for future researches are also discussed.

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The Gains To Bidding Firms' Stock Returns From Merger (기업합병의 성과에 영향을 주는 요인에 대한 실증적 연구)

  • Kim, Yong-Kap
    • Management & Information Systems Review
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    • v.23
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    • pp.41-74
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    • 2007
  • In Korea, corporate merger activities were activated since 1980, and nowadays(particuarly since 1986) the changes in domestic and international economic circumstances have made corporate managers have strong interests in merger. Korea and America have different business environments and it is easily conceivable that there exists many differences in motives, methods, and effects of mergers between the two countries. According to recent studies on takeover bids in America, takeover bids have information effects, tax implications, and co-insurance effects, and the form of payment(cash versus securities), the relative size of target and bidder, the leverage effect, Tobin's q, number of bidders(single versus multiple bidder), the time period (before 1968, 1968-1980, 1981 and later), and the target firm reaction (hostile versus friendly) are important determinants of the magnitude of takeover gains and their distribution between targets and bidders at the announcement of takeover bids. This study examines the theory of takeover bids, the status quo and problems of merger in Korea, and then investigates how the announcement of merger are reflected in common stock returns of bidding firms, finally explores empirically the factors influencing abnormal returns of bidding firms' stock price. The hypotheses of this study are as follows ; Shareholders of bidding firms benefit from mergers. And common stock returns of bidding firms at the announcement of takeover bids, shows significant differences according to the condition of the ratio of target size relative to bidding firm, whether the target being a member of the conglomerate to which bidding firm belongs, whether the target being a listed company, the time period(before 1986, 1986, and later), the number of bidding firm's stock in exchange for a stock of the target, whether the merger being a horizontal and vertical merger or a conglomerate merger, and the ratios of debt to equity capital of target and bidding firm. The data analyzed in this study were drawn from public announcements of proposals to acquire a target firm by means of merger. The sample contains all bidding firms which were listed in the stock market and also engaged in successful mergers in the period 1980 through 1992 for which there are daily stock returns. A merger bid was considered successful if it resulted in a completed merger and the target firm disappeared as a separate entity. The final sample contains 113 acquiring firms. The research hypotheses examined in this study are tested by applying an event-type methodology similar to that described in Dodd and Warner. The ordinary-least-squares coefficients of the market-model regression were estimated over the period t=-135 to t=-16 relative to the date of the proposal's initial announcement, t=0. Daily abnormal common stock returns were calculated for each firm i over the interval t=-15 to t=+15. A daily average abnormal return(AR) for each day t was computed. Average cumulative abnormal returns($CART_{T_1,T_2}$) were also derived by summing the $AR_t's$ over various intervals. The expected values of $AR_t$ and $CART_{T_1,T_2}$ are zero in the absence of abnormal performance. The test statistics of $AR_t$ and $CAR_{T_1,T_2}$ are based on the average standardized abnormal return($ASAR_t$) and the average standardized cumulative abnormal return ($ASCAR_{T_1,T_2}$), respectively. Assuming that the individual abnormal returns are normal and independent across t and across securities, the statistics $Z_t$ and $Z_{T_1,T_2}$ which follow a unit-normal distribution(Dodd and Warner), are used to test the hypotheses that the average standardized abnormal returns and the average cumulative standardized abnormal returns equal zero.

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Knowledge Management Strategy of a Franchise Business : The Case of a Paris Baguette Bakery (프랜차이즈 기업의 지식경영 전략 : 파리바게뜨 사례를 중심으로)

  • Cho, Joon-Sang;Kim, Bo-Yong
    • Journal of Distribution Science
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    • v.10 no.6
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    • pp.39-53
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    • 2012
  • It is widely known that knowledge management plays a facilitating role that contributes to upgrading organizational performance. Knowledge management systems (KMS), especially, support the knowledge management process including the sharing, creating, and using of knowledge within a company, and maximize the value of knowledge resources within an organization. Despite this widely held belief, there are few studies that describe how companies actually develop, share, and practice their knowledge. Companies in the domestic small franchise sector, which are in the early stages in terms of knowledge management, need to improve their KMS to manage their franchisees effectively. From this perspective, this study uses a qualitative approach to explore the actual process of knowledge management implementation. This article presents a case study of PB (Paris Baguette) company, which is the first to build a KMS in the franchise industry. The study was able to confirm the following facts through the analysis of target companies. First, the chief executive's support is a critical success factor and this support can increase the participation of organization members. Second, it is important to build a process and culture that actively creates and leverages information in knowledge management activities. The organizational learning culture should be one where the creation, learning, and sharing of new knowledge is developed continuously. Third, a horizontal network organization is needed in order to make relationships within the organization more close-knit. Fourth, in order to connect the diverse processes such as knowledge acquisition, storage, and utilization of knowledge management activities, information technology (IT) capabilities are essential. Indeed, IT can be a powerful tool for improving the quality of work and maximizing the spread and use of knowledge. However, during the construction of an intranet based KMS, research is required to ensure that the most efficient system is implemented. Finally, proper evaluation and compensation are important success factors. In order to develop knowledge workers, an appropriate program of promotion and compensation should be established. Also, building members' confidence in the benefits of knowledge management should be an ongoing activity. The company developed its original KMS to achieve a flexible and proactive organization, and a new KMS to improve organizational and personal capabilities. The PB case shows that there are differences between participants perceptions and actual performance in managing knowledge; that knowledge management is not a matter of formality but a paradigm that assures the sharing of knowledge; and that IT boosts communication skills, thus creating a mutual relationship to enhance the flow of knowledge and information between people. Knowledge management for building organizational capabilities can be successful when considering its focus and ways to increase its acceptance. This study suggests guidelines for major factors that corporate executives of domestic franchises should consider to improve knowledge management and the higher operating activities that can be used.

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One Boundary Diffusion Model Analysis on Distributions of Eye Fixation Durations in Reading; Eye Movement Tracking Study (우리글 읽기에서 나타난 성인과 청소년의 고정시간 분포분석과 단일경계 확산모형 제안)

  • Choo, Hyeree;Koh, Sungryong
    • Korean Journal of Cognitive Science
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    • v.32 no.1
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    • pp.1-53
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    • 2021
  • The aim of this study was to analyze word frequency effects on eye fixation duration in Korean reading with a one-boundary diffusion model and to show how these phenomena differ between adults (20-28yrs) and adolescents (13-14yrs). We predicted that the drift rate parameter in the boundary diffusion model would reflect the information processing of the fovea during silent reading. Through an eye movement tracking experiment while controlling word properties such as the word frequency and the age of acquisition, Experiment 1 and Experiment 2 show that the information processing pertaining to words to be placed in the fovea is connected to the drift rate of the one-boundary diffusion model parameters. In Experiment 1,in the adult group, the mean difference in the fixation time in the response proportion between the presence of high-frequency condition and low-frequency condition in the adult group was higher in quantile 0.9 than it was in the 0.1 quantile, but in the adolescent group, the mean difference in the fixation time in the response proportion between the two conditions was not significantly in the 0.9 quartile.In Experiment 2, the mean difference in the fixation time in the response proportion between early-acquired condition and late-acquired condition in both groups was also higher in the quantile 0.9 than in the 0.1 quantile. The distribution of the two conditions in the both groups was positively skewed, and the difference showed the same pattern found in the results of Ratcliff(Ratcliff & McKoon, 2008). Based on the experimental results, we propose one-boundary diffusion model as a tool to explain word property effects and individual differences in reading. In particular, we suggest that the drift rate parameter in the boundary diffusion model reflects the information processing of the fovea during reading. In addition, the results show that one-boundary diffusion model can be used to predict the aforementioned phenomena in reading.

Modeling and mapping fuel moisture content using equilibrium moisture content computed from weather data of the automatic mountain meteorology observation system (AMOS) (산악기상자료와 목재평형함수율에 기반한 산림연료습도 추정식 개발)

  • Lee, HoonTaek;WON, Myoung-Soo;YOON, Suk-Hee;JANG, Keun-Chang
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.3
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    • pp.21-36
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    • 2019
  • Dead fuel moisture content is a key variable in fire danger rating as it affects fire ignition and behavior. This study evaluates simple regression models estimating the moisture content of standardized 10-h fuel stick (10-h FMC) at three sites with different characteristics(urban and outside/inside the forest). Equilibrium moisture content (EMC) was used as an independent variable, and in-situ measured 10-h FMC was used as a dependent variable and validation data. 10-h FMC spatial distribution maps were created for dates with the most frequent fire occurrence during 2013-2018. Also, 10-h FMC values of the dates were analyzed to investigate under which 10-h FMC condition forest fire is likely to occur. As the results, fitted equations could explain considerable part of the variance in 10-h FMC (62~78%). Compared to the validation data, the models performed well with R2 ranged from 0.53 to 0.68, root mean squared error (RMSE) ranged from 2.52% to 3.43%, and bias ranged from -0.41% to 1.10%. When the 10-h FMC model fitted for one site was applied to the other sites, $R^2$ was maintained as the same while RMSE and bias increased up to 5.13% and 3.68%, respectively. The major deficiency of the 10-h FMC model was that it poorly caught the difference in the drying process after rainfall between 10-h FMC and EMC. From the analysis of 10-h FMC during the dates fire occurred, more than 70% of the fires occurred under a 10-h FMC condition of less than 10.5%. Overall, the present study suggested a simple model estimating 10-h FMC with acceptable performance. Applying the 10-h FMC model to the automatic mountain weather observation system was successfully tested to produce a national-scale 10-h FMC spatial distribution map. This data will be fundamental information for forest fire research, and will support the policy maker.