Hallucination is a significant barrier to the utilization of large-scale language models or multimodal models. In this study, we collected 654 computer science papers with "hallucination" in the abstract from arXiv from December 2022 to January 2024 following the advent of Chat GPT and conducted frequency analysis, knowledge network analysis, and literature review to explore the latest trends in hallucination research. The results showed that research in the fields of "Computation and Language," "Artificial Intelligence," "Computer Vision and Pattern Recognition," and "Machine Learning" were active. We then analyzed the research trends in the four major fields by focusing on the main authors and dividing them into data, hallucination detection, and hallucination mitigation. The main research trends included hallucination mitigation through supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF), inference enhancement via "chain of thought" (CoT), and growing interest in hallucination mitigation within the domain of multimodal AI. This study provides insights into the latest developments in hallucination research through a technology-oriented literature review. This study is expected to help subsequent research in both engineering and humanities and social sciences fields by understanding the latest trends in hallucination research.
Journal of the Korea Academia-Industrial cooperation Society
/
v.18
no.10
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pp.88-96
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2017
The construction standards in Korea consist of design standards and specifications. They are provided by the national transportation electronic information center in file format, not in a DB, which may lead to their incomplete utilization and versatility, such as a lack of history management and reference functions. This also makes it difficult to cross-refer to standards and manage revision history. In this study, we developed a code management system for the national construction standards by analyzing domestic and overseas related systems, in order to pinpoint the problems in the current system and its development direction and, thus, to suggest a detailed plan for the design and implementation of a code management system. The developed system comprises four subsystems, namely a construction standards making system, construction standards service system, construction standards maintenance system and construction standards portal system. The results of this study are expected to improve the user's convenience by facilitating the revision, operation and history management of the complex and various construction standards, and to provide high-quality national construction standards by effectively supporting the revision and operation of the national construction standards with minimum duplication and conflicts.
KAERI has been operating an integral effect test facility, ATLAS (Advanced Thermal-Hydraulic Test Loop for Accident Simulation), for accident simulations of advanced PWRs. Regarding integral effect tests, a database for major design basis accidents has been accumulated and a Domestic Standard Problem (DSP) exercise using the ATLAS has been proposed and successfully performed. The ATLAS DSP aims at the effective utilization of an integral effect database obtained from the ATLAS, the establishment of a cooperative framework in the domestic nuclear industry, better understanding of thermal hydraulic phenomena, and an investigation of the potential limitations of the existing best-estimate safety analysis codes. For the first ATLAS DSP exercise (DSP-01), integral effect test data for a 100% DVI line break accident of the APR1400 was selected by considering its technical importance and by incorporating comments from participants. Twelve domestic organizations joined in this DSP-01 exercise. Finally, ten of these organizations submitted their calculation results. This ATLAS DSP-01 exercise progressed as an open calculation; the integral effect test data was delivered to the participants prior to the code calculations. The MARS-KS was favored by most participants but the RELAP5/MOD3.3 code was also used by a few participants. This paper presents all the information of the DSP-01 exercise as well as the comparison results between the calculations and the test data. Lessons learned from the first DSP-01 are presented and recommendations for code users as well as for developers are suggested.
KSCE Journal of Civil and Environmental Engineering Research
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v.32
no.5D
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pp.493-498
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2012
Korean construction companies have maintained stable market share based on high technology and cost competitiveness although international construction market has been stalled due to increasing global economy uncertainties. However, Korean construction companies have relied heavily on the general types of projects in Middle East and Asia although the portion of different types of projects such as Build-Transfer-Operate (BTO), Build-Transfer-Lease (BTL), and Public-Private-Partnership (PPP) has been increasing in the market. When delivering huge projects requiring contractors deal with activities from project planning to operation, securing finance sources and profitability is deemed critical. Therefore, Korean construction companies need more attentions on the construction market supported by Multilateral Development Banks. However, Korean construction companies have not utilized effective strategies for the market entry and also government supportive policies are not useful enough to help construction companies. This study aims both to analyze the contract structure of Korean construction companies for presenting critical factors that need to be prepared and to suggest various methods that can be applied to support construction companies that have much interest in the Multilateral Development Banks. According to the results of study, it is important that Korean government provide structural information system, make a specialized organization, prevent over-heating among Korean construction companies, and collaborate with Official Development Agency. In addition, it appeared that the fairness and financial stability of project have recognized main advantages of the Multilateral Development Banks.
Kim, Kyoung-Beom;Heo, Min-Hee;Jang, Ha-Eun;Noh, Jin-Won;Kim, Jang-Mook
Journal of Convergence for Information Technology
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v.12
no.5
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pp.159-167
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2022
At the present time, no systematic review has been conducted to report the project's outcomes or trends. This study systematically reviewed existing evidence related with community care pilot project. A total of 61 articles, including 18 original literatures and 43 review literatures were finally selected. For original literatures, the most frequent literatures focused on demand surveys (n=4) and model proposals (n=4), the utilization of touchpoint (n=3), space design and architectural model (n=3), manpower training and role establishment (n=2), followed by prioritizing objectives (n=1) and research trend study (n=1). For review literatures, the most frequent literature focused on the elderly (n=12) and relatively few literature on the disabled and mental illness (n=2). Since the pilot project for community care has been implemented for only about one year, the present study indicates that more future research is needed to the disabled, mental illness, and homeless should be conducted as well as elderly.
KIPS Transactions on Software and Data Engineering
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v.11
no.3
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pp.141-148
/
2022
Recently, reinforcement learning combined with deep neural network technology has achieved remarkable success in various fields such as board games such as Go and chess, computer games such as Atari and StartCraft, and robot object manipulation tasks. However, such deep reinforcement learning describes states, actions, and policies in vector representation. Therefore, the existing deep reinforcement learning has some limitations in generality and interpretability of the learned policy, and it is difficult to effectively incorporate domain knowledge into policy learning. On the other hand, dNL-RRL, a new relational reinforcement learning framework proposed to solve these problems, uses a kind of vector representation for sensor input data and lower-level motion control as in the existing deep reinforcement learning. However, for states, actions, and learned policies, It uses a relational representation with logic predicates and rules. In this paper, we present dNL-RRL-based policy learning for transportation mobile robots in a manufacturing environment. In particular, this study proposes a effective method to utilize the prior domain knowledge of human experts to improve the efficiency of relational reinforcement learning. Through various experiments, we demonstrate the performance improvement of the relational reinforcement learning by using domain knowledge as proposed in this paper.
In the past, satellite development required enormous budget and time, so only some developed countries possessed satellites. However, with the recent emergence of low-budget satellites such as micro-satellites, many countries around the world are participating in satellite development. Low-orbit and geostationary-orbit satellites are used in various fields such as environment and weather monitoring, precise change detection, and disasters. Recently, it has been actively used for monitoring through deep learning-based object-of-interest detection. Until now, Korea has developed satellites for national demand according to the space development plan, and the satellite image obtained through this is used for various purpose in the public and private sectors. Interest in satellite image is continuously increasing in Korea, and various contests are being held to discover ideas for satellite image application and promote technology development. In this special issue, we would like to introduce the topics that participated in the recently held 2022 Satellite Information Application Contest and research on the processing and utilization of KOMPSAT image data.
The software industry is a high value-added industry in the knowledge information age, and its importance is growing as it not only plays a key role in knowledge creation and utilization, but also secures global competitiveness. Among various SW available in today's business environment, Open Source Software(OSS) is rapidly expanding its activity area by not only leading software development, but also integrating with new information technology. Therefore, the purpose of this research is to empirically examine and analyze the effect of factors on the switching behavior to OSS. To accomplish the study's purpose, we suggest the research model based on "Push-Pull-Mooring" framework. This study empirically examines the two categories of antecedents for switching behavior toward OSS. The survey was conducted to employees at various firms that already switched OSS. A total of 268 responses were collected and analyzed by using the structural equational modeling. The results of this study are as follows; first, continuous maintenance cost, vender dependency, functional indifference, and SW resource inefficiency are significantly related to switch to OSS. Second, network-oriented support, testability and strategic flexibility are significantly related to switch to OSS. Finally, the results show that willingness to secures SW competitiveness has a moderating effect on the relationships between push factors and pull factor with exception of improved knowledge, and switch to OSS. The results of this study will contribute to fields related to OSS both theoretically and practically.
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.
With stabilization of the recent multi-GNSS infrastructure, and as multi-GNSS has been proven to be effective in improving the accuracy of the positioning performance in various industrial sectors. In this study, in view that SF(Single frequency) GNSS receivers are widely used due to the low costs, evaluate effectiveness of SF Real Time Point Positioning(SF-RT-PP) based on four multi-GNSS surveying methods with RTCM-SSR correction streams in static and kinematic modes, and also derive response challenges. Results of applying SSR correction streams, CNES presented good results compared to other SSR streams in 2D coordinate. Looking at the results of the SF-RT-PP surveying using SF signals from multi-GNSS, were able to identify the common cause of large deviations in the altitude components, as well as confirm the importance of signal bias correction according to combinations of different types of satellite signals and ionospheric delay compensation algorithm using undifferenced and uncombined observations. In addition, confirmed that the improvement of the infrastructure of Multi-GNSS allows SF-RT-SPP surveying with only one of the four GNSS satellites. In particular, in the case of code-based SF-RT-SPP measurements using SF signals from GPS satellites only, the difference in the application effect between broadcast ephemeris and SSR correction for satellite orbits/clocks was small, but in the case of ionospheric delay compensation, the use of SBAS correction information provided more than twice the accuracy compared to result of the Klobuchar model. With GPS and GLONASS, both the BDS and GALILEO constellations will be fully deployed in the end of 2020, and the greater benefits from the multi-GNSS integration can be expected. Specially, If RT-ionospheric correction services reflecting regional characteristics and SSR correction information reflecting atmospheric characteristics are carried out in real-time, expected that the utilization of SF-RT-PPP survey technology by multi-GNSS and various demands will be created in various industrial sectors.
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