• Title/Summary/Keyword: User Reviews

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The Evolution of Innovation Policy and Innovation Theory (기술혁신정책의 진화와 기술혁신이론)

  • Song Wi-Chin
    • Journal of Science and Technology Studies
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    • v.2 no.1 s.3
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    • pp.39-61
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    • 2002
  • This study reviews the emergence of new innovation policy paradigm in advanced countries and their impacts on the development of innovation theories in 1980s and 1990s. It shows that the characteristics of new policy paradigm are the emphasis on the user-orientedness and the socio-economic aspects of innovation and the preference of capability enhancement of innovators over resource subsidy This new perspectives of innovation policies had effects on the emergence and development of 'the innovation system theory' which is based on the key concepts such as interactive teaming, innovating capability and national systems of innovation. In spite of the development of the innovation system theory, it has some problems to be solved for the innovation policy design because 'the social' is still peripheral factors in the constitution on the innovation system theory. This study makes some suggestions to incorporate the social dimension of innovation into the innovation system theory.

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Web-based Personal Dose Management System for Data Recording on Dosimeter Usage: A Case of Tanzania Atomic Energy Commission

  • Mseke, Angela;Ngatunga, John Ben;Sam, Anael;Nyambo, Devotha G.
    • International Journal of Computer Science & Network Security
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    • v.22 no.2
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    • pp.15-22
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    • 2022
  • Modern technology drives the world, increasing performance while reducing labor and time expenses. Tanzania Atomic Energy Commission (TAEC) tracks employee's levels of exposure to radiation sources using dosimeters. According to legal compliance, workers wear dosimeters for three months and one month at the workplace. However, TAEC has problems in tracking, issuing and returning dosimeters because the existing tracking is done manually. The study intended to develop a Personal Dose Management System (PDMS) that processes and manages the data collected by dosimeters for easy and accurate records. During the requirements elicitation process, the study looked at the existing system. PDMS' requirement gathering included document reviews, user interviews, and focused group discussions. Development and testing of the system were implemented by applying the evolutionary prototyping technique. The system provides a login interface for system administrators, radiation officers, and Occupational Exposed Workers. The PDMS grants TAEC Staff access to monitor individual exposed workers, prints individual and institutional reports and manages workers' information. The system reminds the users when to return dosimeters to TAEC, generate reports, and facilitates dispatching and receiving dosimeters effectively. PDMS increases efficiency and effectiveness while minimizing workload, paperwork, and inaccurate records. Therefore, based on the results obtained from the system, it is recommended to use the system to improve dosimeter data management at the institution.

Priority Analysis for Consumers' Purchasing Factors of Seafood Online Using AHP Method (온라인 플랫폼을 활용한 수산식품 구매요인 우선순위 분석: AHP 기법을 활용하여)

  • Jeong, Hyun-Ki;Kee, Hae-Kyung;Park, Se-Hyun
    • Asia-Pacific Journal of Business
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    • v.13 no.3
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    • pp.449-461
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    • 2022
  • Purpose - The purpose of this study to explore factors consumers prioritize when purchasing seafood online. The originality of the study lies on adopting AHP-based approach in analyzing prioritized purchasing factors of seafood online. Design/methodology/approach - A survey was conducted targeting Korean consumers who have purchased seafood online. AHP method was applied to rank factors consumers prioritize before making decision. Findings - First, product's factor ranked first among other high level factors including delivery service, seller, online platform. Second, sanitation, taste, country of origin ranked first, second, third respectively, within product's factors. Third, safe delivery, timeliness, information accuracy ranked first, second, third respectively, within delivery factors. Fourth, consumer reviews, consumer response ability, promotion ranked first, second, third within seller factors. Fifth, Personal information management system, credibility, user-friendliness ranked first, second, third, within online platform factors. Research implications or Originality - To activate seafood online market, it is crucial to assure consumers that the seafood is well managed in a sanitary way from the production site to table. Existing government programs such as seafood traceability system, HACCP, and cold-chain infrastructure needs improvement. Due to highly perishable characteristic of seafood, delivery factors matter when purchasing online. Online platforms needs to continue to improve delivery service. Seafood products are mostly not branded and without objective information about their properties. Creating quality classification and seafood brands are likely to help consumers chose seafood online.

Korean Sentiment Model Interpretation using LIME Algorithm (LIME 알고리즘을 이용한 한국어 감성 분류 모델 해석)

  • Nam, Chung-Hyeon;Jang, Kyung-Sik
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.12
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    • pp.1784-1789
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    • 2021
  • Korean sentiment classification task is used in real-world services such as chatbots and analysis of user's purchase reviews. And due to the development of deep learning technology, neural network models with high performance are being applied. However, the neural network model is not easy to interpret what the input sentences are predicting due to which words, and recently, model interpretation methods for interpreting these neural network models have been popularly proposed. In this paper, we used the LIME algorithm among the model interpretation methods to interpret which of the words in the input sentences of the models learned with the korean sentiment classification dataset. As a result, the interpretation of the Bi-LSTM model with 85.24% performance included 25,283 words, but 84.20% of the transformer model with relatively low performance showed that the transformer model was more reliable than the Bi-LSTM model because it contains 26,447 words.

Enhancing Recommender Systems by Fusing Diverse Information Sources through Data Transformation and Feature Selection

  • Thi-Linh Ho;Anh-Cuong Le;Dinh-Hong Vu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.5
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    • pp.1413-1432
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    • 2023
  • Recommender systems aim to recommend items to users by taking into account their probable interests. This study focuses on creating a model that utilizes multiple sources of information about users and items by employing a multimodality approach. The study addresses the task of how to gather information from different sources (modalities) and transform them into a uniform format, resulting in a multi-modal feature description for users and items. This work also aims to transform and represent the features extracted from different modalities so that the information is in a compatible format for integration and contains important, useful information for the prediction model. To achieve this goal, we propose a novel multi-modal recommendation model, which involves extracting latent features of users and items from a utility matrix using matrix factorization techniques. Various transformation techniques are utilized to extract features from other sources of information such as user reviews, item descriptions, and item categories. We also proposed the use of Principal Component Analysis (PCA) and Feature Selection techniques to reduce the data dimension and extract important features as well as remove noisy features to increase the accuracy of the model. We conducted several different experimental models based on different subsets of modalities on the MovieLens and Amazon sub-category datasets. According to the experimental results, the proposed model significantly enhances the accuracy of recommendations when compared to SVD, which is acknowledged as one of the most effective models for recommender systems. Specifically, the proposed model reduces the RMSE by a range of 4.8% to 21.43% and increases the Precision by a range of 2.07% to 26.49% for the Amazon datasets. Similarly, for the MovieLens dataset, the proposed model reduces the RMSE by 45.61% and increases the Precision by 14.06%. Additionally, the experimental results on both datasets demonstrate that combining information from multiple modalities in the proposed model leads to superior outcomes compared to relying on a single type of information.

The Critical Success Factors Influencing the Use of Mobile Learning and its Perceived Impacts in Students' Education: A Systematic Literature Review

  • Abdulaziz Alanazi;Nur Fazidah Binti Elias;Hazura Binti Mohamed;Noraidah Sahari
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.18 no.3
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    • pp.610-632
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    • 2024
  • Mobile Learning (M-learning) adoption and success in supporting students' learning engagement mainly depend on many factors. Therefore, this study systematically reviews the literature, synthesizes and analyzes the predictors of M-learning adoption, and uses success for students' learning engagement. Literature from 2016 to 2023 in various databases is covered in this study. Based on the review's findings, the factors that influence students' learning engagement when it comes to M-learning usage and adoption, can be divided into technical, pedagogical, and social factors. More specifically, technical factors include mobile devices availability and quality, connectivity to the internet, and user-friendly interfaces, pedagogical factors include effective instructional design, teaching methods, and assessment strategies, and social factors include motivation of students, social interaction and perceived enjoyment - all these factors have a significant impact on the M-learning adoption and use success. The findings of the review also indicated that M-learning has a key role in enhancing the learning engagement of students through different ways, like increasing their motivation, attention, and participation in their process of learning, paving the way for interaction and building relationships opportunities with peers and instructors, which in turn, can lead to strengthening the learning environment. The implications of these findings extend beyond immediate educational contexts, offering vital insights for future educational technology strategies and policy decisions, particularly in addressing global educational challenges and embracing technological advancements in learning.

Review on Artificial Intelligence Education for K-12 Students and Teachers (K-12 학생 및 교사를 위한 인공지능 교육에 대한 고찰)

  • Kim, Soohwan;Kim, Seonghun;Lee, Minjeong;Kim, Hyeoncheol
    • The Journal of Korean Association of Computer Education
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    • v.23 no.4
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    • pp.1-11
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    • 2020
  • The purpose of this study is to propose the direction of AI education in K-12 education through investigating and analyzing aspects of the purpose, content, and methods of AI education as the curriculum and teacher training factors. We collected and analyzed 9 papers as the primary literature and 11 domestic and foreign policy reports as the secondary literature. The collected literatures were analyzed by applying a descriptive reviews, and the implications were derived by analyzing the curriculum components and TPACK elements for multi-dimensional analysis. As a result of this study, AI education targets were divided into three steps: AI users, utilizer, and developers. In K-12 education, the user and utilizer stages are appropriate, and artificial intelligence literacy must be included for user education. Based on the current computing thinking ability and coding ability for utilizer education, the implication was derived that it is necessary to target the ability to create creative output by applying the functions of artificial intelligence. In addition to the pedagogical knowledge and the ability to use the platform, The teacher training is necessary because teachers need content knowledge such as problem-solving, reasoning, learning, perception, and some applied mathematics, cognitive / psychological / ethical of AI.

A Study on Application of Dynamic Design Elements for Designing Ambient Media (엠비언트 미디어의 디자인을 위한 동적인 디자인 요소의 활용에 관한 연구)

  • Park, Jin-Yung;Park, Sun-Young;Nam, Tek-Jin
    • 한국HCI학회:학술대회논문집
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    • 2008.02b
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    • pp.233-238
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    • 2008
  • Ambient Media (or ambient displays, Wisneski et al 1998) is one of newly emergent dynamic design objects, representing information through subtle changes of everyday objects and environments. Unlike the existing GUI-based media focusing on the situation that a user is concentrating the media, ambient media enable a user to be peripherally aware of the information without his/her concentration. In order to design ambient media, it is necessary to interpret the basic elements of dynamic changes in physical space and the proper method to apply them for peripherally representing information in ambient media. The aim of this study is to investigate dynamic design elements and the method to apply them for ambient media design in physical space. We explored and refined the type of the dynamic design elements, analyzing dynamic qualities of ambient media cases as well as various time based design fields. As a result, 4 dynamic elements - tempo, connectivity, intensity and rhythm- were proposed. By literature reviews related to peripheral awareness in psychology or ambient media, we analyzed the characteristics of dynamic design elements. Based on that, we developed a new ambient media, 'Cyber Pung-Kyung', and applied dynamic elements for designing the prototype system. The research outcome is expected to contribute designing ambient media which can represent information peripherally or centrally as needed. Understanding the dynamic design elements is helpful for designing various time based design outcomes as well.

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A Study on a Recombination Method for the Bottom-up Construction of Spatial Information Products (재조합을 위한 Bottom-up 공간정보제품 제작 방법)

  • Choi, Jae-Yeon;Kim, Eun-Hyung
    • Journal of Cadastre & Land InformatiX
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    • v.47 no.2
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    • pp.185-199
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    • 2017
  • This study is on a recombination method for the construction of spatial information products which demands are unpredictably various. The present production method of digital maps is not flexible enough for their reusability because it is not object-oriented but top-down. Each spatial object needs to have particular attributes to be recombined. The demand changes the production method through the reclassification of data and changing the properties. In a user perspective, the bottom-up method can produce on-demand spatial information products including existing digital maps. The method is derived from case studies and theoretical reviews and compared with the existing production method. In the method spatial information products are reclassified by their geometry objects such as point, line, and polygon, with basic attributes, and other related domain attributes. The geometry objects and domain attributes are connected by adding new attributes for their later relationship and management, which make the recombination possible. To prove its usability of the method it is tested for current and future user demands including the national base map, thematic maps and the future spatial information products.

A Study on the Visual Representation of TREC Text Documents in the Construction of Digital Library (디지털도서관 구축과정에서 TREC 텍스트 문서의 시각적 표현에 관한 연구)

  • Jeong, Ki-Tai;Park, Il-Jong
    • Journal of the Korean Society for information Management
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    • v.21 no.3
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    • pp.1-14
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    • 2004
  • Visualization of documents will help users when they do search similar documents. and all research in information retrieval addresses itself to the problem of a user with an information need facing a data source containing an acceptable solution to that need. In various contexts. adequate solutions to this problem have included alphabetized cubbyholes housing papyrus rolls. microfilm registers. card catalogs and inverted files coded onto discs. Many information retrieval systems rely on the use of a document surrogate. Though they might be surprise to discover it. nearly every information seeker uses an array of document surrogates. Summaries. tables of contents. abstracts. reviews, and MARC recordsthese are all document surrogates. That is, they stand infor a document allowing a user to make some decision regarding it. whether to retrieve a book from the stacks, whether to read an entire article, etc. In this paper another type of document surrogate is investigated using a grouping method of term list. lising Multidimensional Scaling Method (MDS) those surrogates are visualized on two-dimensional graph. The distances between dots on the two-dimensional graph can be represented as the similarity of the documents. More close the distance. more similar the documents.