• Journal of Internet of Things and Convergence
• /
• v.10 no.1
• /
• pp.69-75
• /
• 2024

This paper proposes an innovative cognitive IoT framework specifically designed for fog computing (FC) in the context of industrial Internet of Things (IIoT). The discourse in this paper is centered on the intricate design and functional architecture of the Cognitive IoT platform. A crucial feature of this platform is the integration of machine learning (ML) and artificial intelligence (AI), which enhances its operational flexibility and compatibility with a wide range of industrial applications. An exemplary application of this platform is highlighted through the Predictive Maintenance-as-a-Service (PdM-as-a-Service) model, which focuses on real-time monitoring of machine conditions. This model transcends traditional maintenance approaches by leveraging real-time data analytics for maintenance and management operations. Empirical results substantiate the platform's effectiveness within a fog computing milieu, thereby illustrating its transformative potential in the domain of industrial IoT applications. Furthermore, the paper delineates the inherent challenges and prospective research trajectories in the spheres of Cognitive IoT and Fog Computing within the ambit of Industrial Internet of Things (IIoT).

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.12
• /
• pp.505-518
• /
• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• Journal of the Korean Regional Science Association
• /
• v.39 no.4
• /
• pp.33-51
• /
• 2023

This study aims to investigate the changes in the employment structure of occupational groups by job characteristics and analyze the factors influencing wage premiums in local labor markets from 2010 to 2020. This study's analysis involves three primary steps. First, the occupational characteristics data from the Korea Network for Occupations and Workers are subjected to an exploratory factor analysis, and then a non-routine task intensity index is calculated by each occupations. Then, we conduct an exploratory analysis of changes in the distribution of employment by occupation from 2010 to 2020 by combining data from the Population Census with data from the Korean Labor and Income Panel Study to construct individual-level and regional-level data. Thirdly, we employ a hierarchical linear model to examine the individual-level and regional-level factors influencing wage premiums. Since 2010, the proportion of employment in occupations requiring non-routine task has continued to rise and now dominates the metropolitan labor market. Moreover, agglomeration effects resulting from urbanization produce a substantial wage premium for wage workers in occupations requiring non-routine tasks. This study seeks to provide policy implications to mitigate inequality and polarization in local labor markets by empirically analyzing the transition of occupational structure and wage inequality in relation to the local labor market context.

• Journal of Science Education
• /
• v.48 no.1
• /
• pp.1-14
• /
• 2024

The Korean Science Education Standards (KSES) were developed to support the establishment of a domestic national science curriculum to respond to future social and environmental changes as an action plan to improve scientific literacy in the context of science education. In this study, we analyzed the relationship between KSES and the 2022 revised middle science curriculum focusing its learning contents and learning objectives and sought effects of the successful implementation of the curriculum. As a result, the content system of the 2022 revised middle science curriculum was highly related to the categories of knowledge in KSES. Attempts to deal with the content related to the nature of science was also confirmed through content elements in science and society domains. In the case of achievement standards, it was focused on some areas of the performance expectations in KSES, but the level of statement of the achievement standards closely matched the level of middle school students as suggested by KSES. From these results, it was possible to confirm the high relationship between the 2022 revised middle science curriculum and KSES, as well as the possibility of using KSES as an international indicator for establishing future science education plans.

• The Korean Journal of Archival Studies
• /
• no.19
• /
• pp.103-151
• /
• 2009

Appraisal in electronic record environments is performed focusing on not content but function in which the records are created. Functional appraisal is practically supported in that electronic records composed of 0 and 1 of the bit-stream is unable to be evaluated individually. But the most important reason functional appraisal is performed in electronic record environments is that functional appraisal can select electronic records which assure business context and recordness, and need to run organization and perform business. In Korea, functional appraisal has adopted in course of renovation of national record and archive management system, but methods and logics of functional appraisal have numerous problems. To do so, this article discusses current appraisal system and methods of korea which has renovated confronting with electronic record environments, and then proposes the improvement directions on appraisal system and methods of Korea in electronic record environments from the perspective of long-term views. In this respect, this article proposes the improvement directions on current appraisal system and methods of Korea as follows. First, business functional analysis of each agency in functional appraisal should greatly strengthen. Second, it is necessary to devise proper methods for selecting primary values at current stage of electronic records, and to reinforce appraisal of records as knowledges and informations. Finally, functional appraisal, which inevitably carries out for appraising electronic records, has defects in aspect of selecting archives important in a national point of views. Therefore this article suggests the necessity of archival appraisal strategies that complement functional appraisal. This appraisal system is able to establish a base of the regime of archival appraisal which will harmonize primary value at current stage with secondary value at non-current stage in a national point of views.

• Cross-Cultural Studies
• /
• v.52
• /
• pp.165-194
• /
• 2018

Employing Fairclough's critical discourse analysis (CDA), the purpose of this study was to analyze linguistically significant features, intertextuality, and sociocultural practice focusing on selected editorials of The Global Times, $Hu{\acute{a}}nqi{\acute{u}}$ Shíbào on the 2018 United States-China Trade War. The editorial titled "With the strong will of 'the War to Resist America and Aid Chosun,' let us go through the trade war against America" focused on the use of 'war' related vocabulary in the frame of 'war.' First, "Trade War" and "War to Resist America and Aid Chosun" are examples that reveal metaphors and a war frame. Second, "Strategy" is used positively for China but negatively towards America. Third, various war related words are used. Fourth, cases of allusion illustrate war. Intertextuality in terms of discourse practice pertains to two findings. First, The Global Times, $Hu{\acute{a}}nqi{\acute{u}}$ Shíbào repeatedly uses the phrase 'equivalent revenge.' That is because the expression enables China to justify their counterattack and such war that China may wage can be interpreted as just counterattack much like a self-defense mechanism. Second, the expression, 'the counterattack is not intended but it is not fearful' is repeated in several editorials of the newspaper. The reasons are the following: 1) it is used to appeal to the public, 2) by invoking the feeling of fear, the public should be understand why they should unite, and 3) the expression, "it is not fearful" is used to preserve China's global image and "the counterattack is not intended" is used to signal China's will to America. The whole expression is a good example of intertextuality that repetitively illustrates the intended meaning of China in nine editorials in the newspaper within three months, March 23-June 17, 2018. Finally, sociocultural practice is manipulated through the editorial for disseminating the Chinese government's hegemonic ideology. First, it is clear that the core national project, "China Manufacturing 2025" cannot be abandoned. Second, by calling for "War to Resist America and Aid Chosun" the editorial is manipulated to condemn and intimidate America, avoid dissent of the people, appeal to the people, and empower the government. Third, China somehow wants to open up the possibility of negotiation with the United Sates.

• Journal of Intelligence and Information Systems
• /
• v.25 no.3
• /
• pp.201-220
• /
• 2019

Fake news has emerged as a significant issue over the last few years, igniting discussions and research on how to solve this problem. In particular, studies on automated fact-checking and fake news detection using artificial intelligence and text analysis techniques have drawn attention. Fake news detection research entails a form of document classification; thus, document classification techniques have been widely used in this type of research. However, document summarization techniques have been inconspicuous in this field. At the same time, automatic news summarization services have become popular, and a recent study found that the use of news summarized through abstractive summarization has strengthened the predictive performance of fake news detection models. Therefore, the need to study the integration of document summarization technology in the domestic news data environment has become evident. In order to examine the effect of extractive summarization on the fake news detection model, we first summarized news articles through extractive summarization. Second, we created a summarized news-based detection model. Finally, we compared our model with the full-text-based detection model. The study found that BPN(Back Propagation Neural Network) and SVM(Support Vector Machine) did not exhibit a large difference in performance; however, for DT(Decision Tree), the full-text-based model demonstrated a somewhat better performance. In the case of LR(Logistic Regression), our model exhibited the superior performance. Nonetheless, the results did not show a statistically significant difference between our model and the full-text-based model. Therefore, when the summary is applied, at least the core information of the fake news is preserved, and the LR-based model can confirm the possibility of performance improvement. This study features an experimental application of extractive summarization in fake news detection research by employing various machine-learning algorithms. The study's limitations are, essentially, the relatively small amount of data and the lack of comparison between various summarization technologies. Therefore, an in-depth analysis that applies various analytical techniques to a larger data volume would be helpful in the future.

• Resources Recycling
• /
• v.32 no.1
• /
• pp.42-49
• /
• 2023

The glass ceramic secondary resource containing Li-Al-Si is used in inductor, fireproof glass, and transparent cookware and accounts for 14% of the total consumption of Li, which is the second most widely used after Li-ion batteries. Therefore, new Li resources should be explored when the demand for Li is exploding, and extensive research on Li recovery is needed. Herein, we recovered Li from fireproof Li-Al-Si glass ceramic, which is a new secondary resource containing Li. The fireproof glass among all Li-Al-Si glass ceramics was used as raw material that contained 1.5% Li, 9.4% Al, and 28.9% Si. The process for recovering Li from the fireproof glass was divided into two parts: (1) calcium salt roasting and (2) water leaching. In calcium salt roasting, a sample of fireproof glass was crushed and ground below 325 mesh. The leaching efficiency was compared based on the presence or absence of heat treatment of the fireproof glass. Moreover, the leaching rates based on the input ratios of calcium salt, Li-Al-Si glass, and ceramics and the leaching process based on calcium salt roasting temperatures were compared. In water leaching, the leaching and recovery rates of Li based on different temperatures, times, solid-liquid ratios, and number of continuous leaching stages were compared. The results revealed that fireproof glass ceramics containing Li-Al-Si should be heat treated to change phase to beta-type spodumene. CaCO₃ salt should be added at a ratio of 6:1 with glass ceramics containing Li-Al-Si, and then leached 4 times or more to achieve a recovery efficiency of Li over 98% from a solution containing 200 mg/L of Li.

• The Korean Journal of Air & Space Law and Policy
• /
• v.32 no.2
• /
• pp.101-127
• /
• 2017

Even with the most advanced aviation technology benefits, aircraft accidents are constantly occurring while air passenger transportation volume is expected to double in the next 15 years. Since it is not possible to secure aviation safety only by the post aircraft accident safety action of accident investigations, it has been recognized and consensus has been formed that proactive and predictive prevention measures are necessary. In this sense, the aviation safety management system (SMS) was introduced in 2008 and has been carried out in earnest since 2011. SMS is a proactive and predictive aircraft accident preventive measure, which is a mechanism to eliminate the fundamental risk factors by approaching organizational factors beyond technological factors and human factors related to aviation safety. The methodology is to collect hazards in all the sites required for aircraft operations, to build a database, to analyze the risks, and through managing risks, to keep the risks acceptable or below. Therefore, the improper implementation of SMS indicates that the aircraft accident prevention is insufficient and it is to be directly connected with the aircraft accident. Reports of duty performance related hazards including their own errors are essential and most important in SMS. Under the policy of just culture for voluntary reporting, the guarantee of information providers' anonymity, non-punishment and non-blame should be basically secured, but to this end, under-reporting is stagnant due to lack of trust in their own organizations. It is necessary for the accountable executive(CEO) and senior management to take a leading role to foster the safety culture initiating from just culture with the safety consciousness, balancing between safety and profit for the organization. Though a Ministry of Land, Infrastructure and Transport's order, "Guidance on SMS Implementation" states the training required for the accountable executive(CEO) and senior management, it is not legally binding. Thus it is suggested that the SMS training completion certificates of accountable executive(CEO) and senior management be included in SMS approval application form that is legally required by "Korea Aviation Safety Program" in addition to other required documents such as a copy of SMS manual. Also, SMS related items are missing in the aircraft accident investigation, so that organizational factors in association with safety culture and risk management are not being investigated. This hinders from preventing future accidents, as the root cause cannot be identified. The Aircraft Accident Investigation Manuals issued by ICAO contain the SMS investigation wheres it is not included in the final report form of Annex 13 to the Convention on International Civil Aviation. In addition, the US National Transportation Safety Board(NTSB) that has been a substantial example of the aircraft accident investigation for the other accident investigation agencies worldwide does not appear to expand the scope of investigation activities further to SMS. For these reasons, it is believed that investigation agencies conducting their investigations under Annex 13 do not include SMS in the investigation items, and the aircraft accident investigators are hardly exposed to SMS investigation methods or techniques. In this respect, it is necessary to include the SMS investigation in the organization and management information of the final report format of Annex 13. In Korea as well, in the same manner, SMS item should be added to the final report format of the Operating Regulation of the Aircraft and Railway Accident Investigation Board. If such legal and institutional improvement methods are complemented, SMS will serve the purpose of aircraft accident prevention effectively and contribute to the improvement of aviation safety in the future.

• Journal of Intelligence and Information Systems
• /
• v.22 no.1
• /
• pp.1-18
• /
• 2016

Owing to the extensive use of Web media and the development of the IT industry, a large amount of data has been generated, shared, and stored. Nowadays, various types of unstructured data such as image, sound, video, and text are distributed through Web media. Therefore, many attempts have been made in recent years to discover new value through an analysis of these unstructured data. Among these types of unstructured data, text is recognized as the most representative method for users to express and share their opinions on the Web. In this sense, demand for obtaining new insights through text analysis is steadily increasing. Accordingly, text mining is increasingly being used for different purposes in various fields. In particular, issue tracking is being widely studied not only in the academic world but also in industries because it can be used to extract various issues from text such as news, (SocialNetworkServices) to analyze the trends of these issues. Conventionally, issue tracking is used to identify major issues sustained over a long period of time through topic modeling and to analyze the detailed distribution of documents involved in each issue. However, because conventional issue tracking assumes that the content composing each issue does not change throughout the entire tracking period, it cannot represent the dynamic mutation process of detailed issues that can be created, merged, divided, and deleted between these periods. Moreover, because only keywords that appear consistently throughout the entire period can be derived as issue keywords, concrete issue keywords such as "nuclear test" and "separated families" may be concealed by more general issue keywords such as "North Korea" in an analysis over a long period of time. This implies that many meaningful but short-lived issues cannot be discovered by conventional issue tracking. Note that detailed keywords are preferable to general keywords because the former can be clues for providing actionable strategies. To overcome these limitations, we performed an independent analysis on the documents of each detailed period. We generated an issue flow diagram based on the similarity of each issue between two consecutive periods. The issue transition pattern among categories was analyzed by using the category information of each document. In this study, we then applied the proposed methodology to a real case of 53,739 news articles. We derived an issue flow diagram from the articles. We then proposed the following useful application scenarios for the issue flow diagram presented in the experiment section. First, we can identify an issue that actively appears during a certain period and promptly disappears in the next period. Second, the preceding and following issues of a particular issue can be easily discovered from the issue flow diagram. This implies that our methodology can be used to discover the association between inter-period issues. Finally, an interesting pattern of one-way and two-way transitions was discovered by analyzing the transition patterns of issues through category analysis. Thus, we discovered that a pair of mutually similar categories induces two-way transitions. In contrast, one-way transitions can be recognized as an indicator that issues in a certain category tend to be influenced by other issues in another category. For practical application of the proposed methodology, high-quality word and stop word dictionaries need to be constructed. In addition, not only the number of documents but also additional meta-information such as the read counts, written time, and comments of documents should be analyzed. A rigorous performance evaluation or validation of the proposed methodology should be performed in future works.