• Journal of Korea Multimedia Society
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• v.7 no.7
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• pp.877-885
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• 2004

In this paper, we propose an enhancement shot change detection method using the neural net and the robust feature selection out of multiple features. The previous shot change detection methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using robust features, which are supplementary each other, rather than using single feature. In this paper, we use the typical CART (classification and regression tree) of data mining method to select the robust features, and the backpropagation neural net to determine the threshold of the each selected features. And to evaluation the performance of the robust feature selection, we compare the proposed method to the PCA(principal component analysis) method of the typical feature selection. According to the experimental result. it was revealed that the performance of our method had better that than the PCA method.

• Information Systems Review
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• v.25 no.3
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• pp.139-162
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• 2023

With the emergence of new digital technologies into a supply chain, it is essential for companies to incorporate these technologies in managing their supply chains. However, various challenges have been identified in digital supply chain management, especially when it comes to its assessment. There are no universally agreed measurements for the performance of digital supply chain management within the research community so far. This paper explores an option of using user experience as one of possible measurements. Therefore, three different focus-group discussions were held and later analyzed with a qualitative content analysis. The subscription-based video on demand service, Netflix was used as an example in those discussions. Due to the fact that Netflix provides a digital product as a streamline service, user experience is critical for the company. Especially, user experience with a recommender system and related privacy issues have become significant for a company to retain existing customers and attract new customers in many fields. Since the recommender system and related privacy issues are parts of a digital supply chain, user experience can be one of appropriate measurements for digital supply chain management. This study opens a new perspective for research on performance measurements of digital supply chain management.

• Health Communication
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• v.12 no.1
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• pp.97-110
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• 2017

Purpose: This study is an overview of the experiences of nurses who have participated in a communication education program which was designed to develop proper change-of-shift dialogues. The goal of this program was to improve the communication competencies of outgoing and incoming nurses during handover and takeover of their shifts. Methods: The materials used in this study to analyze the experiences qualitatively were transcripts from narrative interviews with seven nurse participants. The education program consisted of two rounds of change-of-shift simulations by pairs of nurses, planning of a forthcoming change-of-shift, three lectures on ideal dialogue patterns, and time for video feedback. Afterwards the participants' experiences of the program were evaluated generally, highlighting the positive and the negative aspects, and how this educational experiences might affect their future change-of-shift activities. Results: High practicability, originality, professionalism, and effectiveness were some of the positive assessments made by the nurse participants. In addition, they pointed out that the sample video in which two professors performed an ideal handover and takeover and the paper kardex were both quite unrealistic. The location of the change-of-shift simulation was also unfamiliar so it needed to be supplemented. However, most of the nurses took for granted that such a communication education program is necessary and that it will provide a substantial help in their future job performance. In this regard they recommended the program to all related hospitals and nursing schools. Conclusion: The results of this study could be applied to other forms of communication education programs regardless of the specific area where communication takes place.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.1-15
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• 2024

This study aims to elucidate the characteristics of big tech platform companies' sports content business in an environment of rapid digital transformation. Specifically, this study examines the market structure of big tech platform companies with a focus on Amazon, revealing the role of sports content within this structure through an analysis of Amazon's sports marketing business and provides an outlook on the sports content business of big tech platform companies. Based on two-sided market platform business models, big tech platform companies incorporate sports content as a strategy to enhance the value of their platforms. Therefore, sports content is used as a tool to enhance the value of their platforms and to consolidate their monopoly position by maximizing profits by increasing the synergy of platform ecosystems such as infrastructure. Amazon acquires popular live sports broadcasting rights on a continental or national basis and supplies them to its platforms, which not only increases the number of new customers and purchasing effects, but also provides IT solution services to sports organizations and teams while planning and supplying various promotional contents, thus creates synergy across Amazon's platforms including its advertising business. Amazon also expands its business opportunities and increases its overall value by supplying live sports contents to Amazon Prime Video and Amazon Prime, providing technical services to various stakeholders through Amazon Web Services, and offering Amazon Marketing Cloud services for analyzing and predicting advertisers' advertising and marketing performance. This gives rise to a new paradigm in the sports marketing business in the digital era, stemming from the difference in market structure between big tech companies based on two-sided market platforms and legacy global companies based on one-sided markets. The core of this new model is a business through the development of various contents based on live sports streaming rights, and sports content marketing will become a major field of sports marketing along with traditional broadcasting rights and sponsorship. Big tech platform global companies such as Amazon, Apple, and Google have the potential to become new global sports marketing companies, and the current sports marketing and advertising companies, as well as teams and leagues, are facing both crises and opportunities.

• Journal of Korea Multimedia Society
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• v.15 no.9
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• pp.1165-1173
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• 2012

One of the most popular technologies in Web2.0 is tagging, and it widely applies to Web content as well as multimedia data such as image and video. Web users have expected that tags by themselves would be reused in information search and maximize the search efficiency, but wrong tag by irresponsible Web users really has brought forth a incorrect search results. In past papers, we have gathered various information resources and tags scattered in Web, mapped one tag onto other tags, and clustered these tags according to the corelation between them. A 3-tag based search algorithm which use the clustered tags of past papers, is proposed in this paper. For performance evaluation of the proposed algorithm, our algorithm is compared with image search result of Flickr, typical tag based site, and is evaluated in accuracy and recall factor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2270-2277
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• 2016

In modern society, creation and distribution of multimedia contents is being actively conducted. These multimedia information have come out the enormous amount daily, the amount of data is also large enough it can't be compared with past text information. Since it has been increased for a need of the method to efficiently store multimedia information and to easily search the information, various methods associated therewith have been actively studied. In particular, image search methods for finding what you want from the video database or multiple sequential images, have attracted attention as a new field of image processing. Image retrieval method to be implemented in this paper, utilizes the attribute of corner patches based on the corner points of the object, for providing a new method of efficient and robust image search. After detecting the edge of the object within the image, the straight lines using a Hough transformation is extracted. A corner patches is formed by defining the extracted intersection of the straight line as a corner point. After configuring the feature vectors with patches rearranged, the similarity between images in the database is measured. Finally, for an accurate comparison between the proposed algorithm and existing algorithms, the recall precision rate, which has been widely used in content-based image retrieval was used to measure the performance evaluation. For the image used in the experiment, it was confirmed that the image is detected more accurately in the proposed method than the conventional image retrieval methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.514-522
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• 2003

Contrary to the previous methods, in this paper, we propose an enhanced shot change detection method using multiple features and binary decision tree. The previous methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using multiple features, which are supplementary each other, rather than using single feature. In order to classify the shot changes, we use binary classification tree. According to this classification result, we extract important features among the multiple features and obtain threshold value for each feature. We also perform the cross-validation and droop-case to verify the performance of our method. From an experimental result, it was revealed that the EI of our method performed average of 2% better than that of the conventional shot change detection methods.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.536-541
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• 2007

In video coding standard H.264/AVC, motion estimation using multiple reference pictures improves compression efficiency but the efficiency depends upon image content not the number of reference pictures. So, the motion estimation includes a large amount of computation of no worth according to image. This paper proposes fast motion estimation algorithm that removes worthless computation in the motion estimation using multiple reference pictures. The proposed algorithm classifies a block into valid and invalid blocks for the multiple reference pictures and removes the workless computation by applying a single reference picture to the invalid block. To estimate the proposed algorithm's performance, image quality, bit rate, and motion estimation time are compared with ones of the conventional algorithm in the reference software JM 9.5. The simulation results show that the proposed algorithm can considerably save about 38.67% the averaged motion estimation time while keeping the image quality and the bit rate, whose are average values are -0.02dB and -0.77% respectively, as good as the conventional algorithm.

• Quality Improvement in Health Care
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• v.25 no.2
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• pp.2-15
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• 2019

Purpose: The purpose of this study is to provide basic data for the development of the most appropriate and effective educational materials for patients and their caregivers through the educational experiences of patient safety officer. Methods: This study is a qualitative analysis that involves using the focus group interview to understand the patient safety education experience of the patient safety officer. Results: The patient safety education experience of the patient safety officer is divided into four topics: (1) patient safety education content (2) patient safety education method (3) patient safety education status (4) activation and improvement of patient safety education. Additionally, the study incorporated twelve subtopics: (a) falls (b) speak up (c) patient safety campaign (d) patient safety rounding and a one on one training (e) education through medical staff (f) education using broadcast, video, post, among others (g) a lot of education in patient (h) patients not interested in patient safety education (i) patient safety education is less effective (j) human and medical expenses support (k) provision of standardized educational materials (l) patient safety culture for patient participation. Conclusions: This study indicate that education for patients and the caregivers should be inclusive and protective of stakeholders from the risks involved in patient safety events. The experience of patient safety officer is necessary for patient safety education for both patients and the caregivers since it is the source of basic data for the future development of patient safety education.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.85-110
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• 2018

A chatbot is an interactive assistant that utilizes many communication modes: voice, images, video, or text. It is an artificial intelligence-based application that responds to users' needs or solves problems during user-friendly conversation. However, the current version of the chatbot is focused on understanding and performing tasks requested by the user; its ability to generate personalized conversation suitable for relationship-building is limited. Recognizing the need to build a relationship and making suitable conversation is more important for social chatbots who require social skills similar to those of problem-solving chatbots like the intelligent personal assistant. The purpose of this study is to propose a text analysis method that evaluates relationships between chatbots and users based on content input by the user and adapted to the communication situation, enabling the chatbot to conduct suitable conversations. To evaluate the performance of this method, we examined learning and verified the results using actual SNS conversation records. The results of the analysis will aid in implementation of the social chatbot, as this method yields excellent results even when the private profile information of the user is excluded for privacy reasons.