• Title/Summary/Keyword: Communication Model

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Organizational Innovation in the Korean Government via an ICT-based IKM Framework: A focus on the MOFA (정보통신기술 기반 지식정보관리 프레임워크를 통한 한국 정부 조직 혁신에 관한 탐구: 외교부를 중심으로)

  • Jin-kyung Lee
    • Journal of the Korean Society for information Management
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    • v.40 no.2
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    • pp.211-241
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    • 2023
  • With rapidly changing technological implementation of operating systems of businesses, the Ministry of foreign affairs (MOFA) of the Republic of Korea (ROK) has been undergoing digital transformation to its overall operations with the intent to innovate information and knowledge management (IKM) strategies since the mid-2000s. However, assessment as to the effectiveness of implemented IKM has been inadequately analyzed. This study aims to assess the concepts and limitations of the MOFA's current IKM strategies and the methods it employs to deliver its IKM framework, in light of strengthening the organizational ambidexterity and absorptive capacity, and also fostering organizational innovation through a qualitative study that involves interviews and analysis of reports from MOFA. The MOFA's IKM possesses dynamic capabilities to adapt to changing digital technologies. However, the institution's IKM is constrained by limitations associated with the utilization of the IKM system such as a structure that handles confidential documents and a lack of a collaborative system for IKM, and external limitations such as changes in the domestic political situation governing MOFA's priorities and the hierarchy of government organizations. Consequently, developing the organizational ambidexterity and absorptive capacity was not possible. To develop an IKM framework for organizational innovation, the MOFA must devise a way to minimize the impact of external changes by overcoming internal limitations. To that end, a detailed study on the development of a practically usable IKM system should include establishing a dialogue between job groups and enhancing employee competency in preparation for a changing environment.

Automatic Collection of Production Performance Data Based on Multi-Object Tracking Algorithms (다중 객체 추적 알고리즘을 이용한 가공품 흐름 정보 기반 생산 실적 데이터 자동 수집)

  • Lim, Hyuna;Oh, Seojeong;Son, Hyeongjun;Oh, Yosep
    • The Journal of Society for e-Business Studies
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    • v.27 no.2
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    • pp.205-218
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    • 2022
  • Recently, digital transformation in manufacturing has been accelerating. It results in that the data collection technologies from the shop-floor is becoming important. These approaches focus primarily on obtaining specific manufacturing data using various sensors and communication technologies. In order to expand the channel of field data collection, this study proposes a method to automatically collect manufacturing data based on vision-based artificial intelligence. This is to analyze real-time image information with the object detection and tracking technologies and to obtain manufacturing data. The research team collects object motion information for each frame by applying YOLO (You Only Look Once) and DeepSORT as object detection and tracking algorithms. Thereafter, the motion information is converted into two pieces of manufacturing data (production performance and time) through post-processing. A dynamically moving factory model is created to obtain training data for deep learning. In addition, operating scenarios are proposed to reproduce the shop-floor situation in the real world. The operating scenario assumes a flow-shop consisting of six facilities. As a result of collecting manufacturing data according to the operating scenarios, the accuracy was 96.3%.

An Examination of the Effectiveness of Crisis Response Strategies for Repairing Competence and Integrity Violations

  • Sung, Yen-yi;Lee, Han-joon;Park, Jong-chul
    • Asia Marketing Journal
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    • v.15 no.1
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    • pp.129-154
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    • 2013
  • Product-harm crises, which are connected to defective or dangerous products, are perceived as the most common threats to a company. Product harm crises can distort long standing favorable equality perceptions, tarnish a company's reputation, cause major revenue and market-share losses, lead to costly product recalls, and devastate a carefully nurtured brand equity. However, in spite of the devastating impact of product-harm crises, little systematic research exists to asses its marketing consequences. So, the purpose of this study is to investigate how Koreans react to the crisis response in the aftermath of different crises(competence violation vs. integrity violation) and inspire additional research in crisis communication. This study has three main findings which run counter to the assumptions of Kim et al.(2007). Namely, the current study expands on the research of Kim et al. (2004, 2007) by examining how companies repair customers' trust and corporate attitude after crises. Different from previous studies, this study assumes that apology for an integrity-based crisis is the most appropriate way to repair consumer trust and corporate attitude. As for competence-based crisis, similarly, apology for competence-based crisis can be more successful repairing consumer trust and corporate attitude. Concerning silence strategy, remaining silent dose not admit or deny guilt right away, but instead of asking the perceiver to withhold judgment, suggesting that, silence could be expected to be superior to apology but inferior to denial. Finally, apology for competence violation will be expected to bemore effective than apology for integrity violation. Research conceptual model was as follows: According to the results, apology is found to be the most effective strategy to repair corporate attitude no matter the crisis is perceived as a violation of competence or integrity. Second, company may consider keeping silent as a desirable response because they does not admit nor deny responsibility but ask the public to withhold judgment. However, the result of this study shows that, in the overall crisis situations, silence strategy did not differ significantly from the denial strategy, which suggested that the public wants explanation instead of uncertainty. Third, there was the interaction effect between crisis type and crisis response strategies. In this study, apology is more effective for the competence violated situation in terms of regaining consumer trust and repairing their attitude toward company, while the apology's effectiveness is lower for the integrity-violated situation. More specifically, when the crisis is perceived due to company's lack of ability(competence violation), consumer's trust belief and attitude toward the company is more easily to repair when the company issued a sincere apology. Damaged product is perceived less intentional so participants are more likely to give the company second chance when they apology to the public. By contrast, exaggerated advertisement(integrity violation) is perceived intentionally and thus makes participants angrier toward the accused company. Although apology is perceived as the most effective strategy, when issuing apology, it also means the company admitted their intention. Therefore, in this kind of crisis situation, trust repair needs not only a sincere apology but additional efforts.

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Factors Influencing the Intention to Use Digital Technology in Education (학습에서 디지털기술 사용의도에 영향을 주는 요인에 대한 분석)

  • Jang, Moonkyoung
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.17 no.2
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    • pp.153-165
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    • 2022
  • The COVID-19 Pandemic incident forced all educational and learning activities to move online, so it is no longer an option to use information and communication technology for education and learning. Venture capital has made the largest investment ever in Edu-tech startups. This study investigates the factors influencing the intention to use digital technology in education, taking into account the Unified Theory of Acceptance and Use of Technology (UTAUT) along with digital literacy, which has become an essential ability in the digital age. As a result of the structural equation model analysis, we find that performance expectation, effort expectation, and social influence have a positive effect on the intention to use digital technology in education. Moreover, digital literacy has a positive effect on performance expectation, effort expectation, and social impact, but the direct effect on the intention to use digital technology on learning is not significant. Furthermore, to see the moderating effect of age, the results of multi-group analysis present that the differences between 10s and 60s, between 20s and 60s, between 30s and 60s on the path of social influence on the intention to use digital technology in education are significantly reduced. This study academically contributes to expanding the research on the factors affecting the intention to use digital technology in a specific situation of education by considering both digital literacy and Unified Theory of Acceptance and Use of Technology (UTAUT). In addition, it can be used as a practical guide to the factors to be considered for each age when making learning participants more actively use digital technology.

Predicting the splitting tensile strength of manufactured-sand concrete containing stone nano-powder through advanced machine learning techniques

  • Manish Kewalramani;Hanan Samadi;Adil Hussein Mohammed;Arsalan Mahmoodzadeh;Ibrahim Albaijan;Hawkar Hashim Ibrahim;Saleh Alsulamy
    • Advances in nano research
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    • v.16 no.4
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    • pp.375-394
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    • 2024
  • The extensive utilization of concrete has given rise to environmental concerns, specifically concerning the depletion of river sand. To address this issue, waste deposits can provide manufactured-sand (MS) as a substitute for river sand. The objective of this study is to explore the application of machine learning techniques to facilitate the production of manufactured-sand concrete (MSC) containing stone nano-powder through estimating the splitting tensile strength (STS) containing compressive strength of cement (CSC), tensile strength of cement (TSC), curing age (CA), maximum size of the crushed stone (Dmax), stone nano-powder content (SNC), fineness modulus of sand (FMS), water to cement ratio (W/C), sand ratio (SR), and slump (S). To achieve this goal, a total of 310 data points, encompassing nine influential factors affecting the mechanical properties of MSC, are collected through laboratory tests. Subsequently, the gathered dataset is divided into two subsets, one for training and the other for testing; comprising 90% (280 samples) and 10% (30 samples) of the total data, respectively. By employing the generated dataset, novel models were developed for evaluating the STS of MSC in relation to the nine input features. The analysis results revealed significant correlations between the CSC and the curing age CA with STS. Moreover, when delving into sensitivity analysis using an empirical model, it becomes apparent that parameters such as the FMS and the W/C exert minimal influence on the STS. We employed various loss functions to gauge the effectiveness and precision of our methodologies. Impressively, the outcomes of our devised models exhibited commendable accuracy and reliability, with all models displaying an R-squared value surpassing 0.75 and loss function values approaching insignificance. To further refine the estimation of STS for engineering endeavors, we also developed a user-friendly graphical interface for our machine learning models. These proposed models present a practical alternative to laborious, expensive, and complex laboratory techniques, thereby simplifying the production of mortar specimens.

A Study on the Perceived Value and Intention of Use of Mobile Shopping Apps Using Value-Based Adoption Model (VAM) (가치기반수용모델(VAM)을 활용한 모바일 쇼핑 앱의 지각된 가치와 사용의도에 관한 연구)

  • Jhee, Seon Young;Kim, Mun-Ki;Han, Sang-Lin
    • Journal of Service Research and Studies
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    • v.14 no.2
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    • pp.101-116
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    • 2024
  • As the spread of smartphones has become more common and the utilization rate has increased, the mobile shopping market is also growing and expectations for related industries are also increasing. Mobile shopping apps are converging with various industries such as fashion, beauty, and lifestyle, and competition among companies to increase the number of users is intensifying with the activation of non-face-to-face. Accordingly, in this study, a study on the perceived value and intention to use mobile shopping apps was conducted based on a VAM. In order to test the hypothesis of this study, a questionnaire was conducted on 266 people who had used a mobile shopping app and it was used for analysis. Looking at the results, it was confirmed that both usefulness and enjoyment among the perceived benefit of mobile shopping apps have a positive (+) effect on the perceived value. However, it was found that the technicality and perceived risk among the perceived sacrifices of mobile shopping apps did not significantly affect the perceived value. Finally, it was confirmed that the perceived value of the mobile shopping app had a positive (+) effect on the intention to use. Through this study, we would like to examine the factors that can affect perceived value and usage intention in the mobile shopping app industry, which is increasingly competitive among companies along with the rapid growth of mobile technology and market, and suggest practical implications for related companies and officials to establish efficient strategies to further increase mobile shopping app users.

Sound Engine for Korean Traditional Instruments Using General Purpose Digital Signal Processor (범용 디지털 신호처리기를 이용한 국악기 사운드 엔진 개발)

  • Kang, Myeong-Su;Cho, Sang-Jin;Kwon, Sun-Deok;Chong, Ui-Pil
    • The Journal of the Acoustical Society of Korea
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    • v.28 no.3
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    • pp.229-238
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    • 2009
  • This paper describes a sound engine of Korean traditional instruments, which are the Gayageum and Taepyeongso, by using a TMS320F2812. The Gayageum and Taepyeongso models based on commuted waveguide synthesis (CWS) are required to synthesize each sound. There is an instrument selection button to choose one of instruments in the proposed sound engine, and thus a corresponding sound is produced by the relative model at every certain time. Every synthesized sound sample is transmitted to a DAC (TLV5638) using SPI communication, and it is played through a speaker via an audio interface. The length of the delay line determines a fundamental frequency of a desired sound. In order to determine the length of the delay line, it is needed that the time for synthesizing a sound sample should be checked by using a GPIO. It takes $28.6{\mu}s$ for the Gayageum and $21{\mu}s$ for the Taepyeongso, respectively. It happens that each sound sample is synthesized and transferred to the DAC in an interrupt service routine (ISR) of the proposed sound engine. A timer of the TMS320F2812 has four events for generating interrupts. In this paper, the interrupt is happened by using the period matching event of it, and the ISR is called whenever the interrupt happens, $60{\mu}s$. Compared to original sounds with their spectra, the results are good enough to represent timbres of instruments except 'Mu, Hwang, Tae, Joong' of the Taepyeongso. Moreover, only one sound is produced when playing the Taepyeongso and it takes $21{\mu}s$ for the real-time playing. In the case of the Gayageum, players usually use their two fingers (thumb and middle finger or thumb and index finger), so it takes $57.2{\mu}s$ for the real-time playing.

Performance of Passive UHF RFID System in Impulsive Noise Channel Based on Statistical Modeling (통계적 모델링 기반의 임펄스 잡음 채널에서 수동형 UHF RFID 시스템의 성능)

  • Jae-sung Roh
    • Journal of Advanced Navigation Technology
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    • v.27 no.6
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    • pp.835-840
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    • 2023
  • RFID(Radio Frequency Identification) systems are attracting attention as a key component of Internet of Things technology due to the cost and energy efficiency of application services. In order to use RFID technology in the IoT application service field, it is necessary to be able to store and manage various information for a long period of time as well as simple recognition between the reader and tag of the RFID system. And in order to read and write information to tags, a performance improvement technology that is strong and reliable in poor wireless channels is needed. In particular, in the UHF(Ultra High Frequency) RFID system, since multiple tags communicate passively in a crowded environment, it is essential to improve the recognition rate and transmission speed of individual tags. In this paper, Middleton's Class A impulsive noise model was selected to analyze the performance of the RFID system in an impulsive noise environment, and FM0 encoding and Miller encoding were applied to the tag to analyze the error rate performance of the RFID system. As a result of analyzing the performance of the RFID system in Middleton's Class A impulsive noise channel, it was found that the larger the Gaussian noise to impulsive noise power ratio and the impulsive noise index, the more similar the characteristics to the Gaussian noise channel.

Enhancing Empathic Reasoning of Large Language Models Based on Psychotherapy Models for AI-assisted Social Support (인공지능 기반 사회적 지지를 위한 대형언어모형의 공감적 추론 향상: 심리치료 모형을 중심으로)

  • Yoon Kyung Lee;Inju Lee;Minjung Shin;Seoyeon Bae;Sowon Hahn
    • Korean Journal of Cognitive Science
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    • v.35 no.1
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    • pp.23-48
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    • 2024
  • Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

A Case Study on Regional Tourism Innovation through Smart Tourism: Focusing on Incheon Smart Tourism City Project (스마트관광을 활용한 지역관광 혁신사례 연구: 인천 스마트관광도시를 중심으로)

  • Han, Hani;Chung, Namho
    • Knowledge Management Research
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    • v.25 no.1
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    • pp.67-88
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    • 2024
  • Smart tourism aims to maximize the utilization of local tourism resources, effectively manages cities and contributes to improving communication and quality of life between tourists and residents. Therefore, smart tourism emphasizes synergistic collaboration, considering both residents and tourists. This study explores smart tourism interaction and roles in enhancing regional competitiveness. By conducting thorough examination, focusing on integrating the four key elements of smart tourism city (smart experience, smart convenience, smart accessibility, and smart platform) with local residents, local businesses, regional resources, and ecosystem to foster positive synergies, Incheon smart tourism city project was employed as a single case study design. Research results indicate that the collaborative model of a smart tourism city positively impacts service satisfaction and strengthens regional tourism competitiveness. Building upon these results, this study aims to contribute to the development of smart tourism cities by proposing directions for future development and emphasizing the enhancement of regional competitiveness through the integration of smart technology and local tourism.