• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.11-17
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• 2020

South Korea started to actively participate in the ODA project across Asia, Africa, the Middle East, CIS countries, and Latin America as it transitioned from a country receiving developmental aid to a donor country. As more and more recipient countries are looking into the e-government model of South Korea, a new approach to the Korean model is being investigated. Various promotions were made, ranging from the implementation of the e-government ODA project, review of its feasibility to evaluation of the results. In order to improve and maximize performance management OD projects, it is necessary to look into the analysis of its follow-up results. In this study, practical performance management and policy implications were explored, focusing on the e-government ODA project. In particular, a case study analysis was attempted with focus on the Nigerian e-government project promoted as part of the project. It focused on Korea's e-government linkage process, implementation procedures and strategies applied when establishing the e-government master plan and suggested the necessity of an approach suitable for new environmental changes. In terms of sustainability of the ODA project, it is necessary to build a Korean e-government model that reflects the new intelligence information technology.

• Journal of Convergence for Information Technology
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• v.10 no.11
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• pp.156-167
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• 2020

The purpose of this study is to analyze the influence of the mindset on stress and job performance. For the analysis, a questionnaire is conducted for cabin crew members in K airlines, and a total of 266 copies are used for the final analysis. To verify the hypotheses of the study, frequency analysis, exploratory factor analysis, reliability analysis, confirmatory factor analysis, measurement model analysis, validation of the measuremen model, and structural equation model analysis are used based on the questionnaire. First, it is confirmed that the mindset had a negative (-) effect on the cabin crew's role stress, reward stress and relationship stress. Second, it is found that cabin crew's reward stress have a negative (-) effect on job performance. On the other hand, relationship stress is found to have a positive influence on job performance and there is no significant result in effect with role stress. Third, the mindset showes a significant positive impact relationship on job performance. As a result, it is necessary to introduce a mindset intervention program so that it can be applied in practical work. These research results confirm the positive effects of mindsets and show that they contribute to organizational performance. In addition, it is necessary to prepare a program to change the mindset of airline cabin crew and to be applied in actual work.

• Journal of Convergence for Information Technology
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• v.11 no.11
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• pp.57-65
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• 2021

We propose a novel method to detect abnormal data of specific symptoms using deep learning in air pollution measurement system. Existing methods generally detect abnomal data by classifying data showing unusual patterns different from the existing time series data. However, these approaches have limitations in detecting specific symptoms. In this paper, we use DeepLab V3+ model mainly used for foreground segmentation of images, whose structure has been changed to handle one-dimensional data. Instead of images, the model receives time-series data from multiple sensors and can detect data showing specific symptoms. In addition, we improve model's performance by reducing the complexity of noisy form time series data by using 'piecewise aggregation approximation'. Through the experimental results, it can be confirmed that anomaly data detection can be performed successfully.

• Journal of Convergence for Information Technology
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• v.9 no.4
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• pp.1-7
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• 2019

The medical environment, combined with IT technology, is changing the paradigm for medical services from treatment to prevention. In particular, as ICT convergence digital healthcare technology is applied to hospital medical systems, infrastructure technologies such as big data, Internet of Things, and artificial intelligence are being used in conjunction with the cloud. In particular, as medical services are used with IT devices, the quality of medical services is increasingly improving to make them easier for users to access. Medical institutions seeking to incorporate IoT services into cloud health care environment services are trying to reduce hospital operating costs and improve service quality, but have not yet been fully supported. In this paper, a patient information collection model from hospital IoT system, which has established a cloud environment, is proposed. The proposed model prevents third parties from illegally eavesdropping and interfering with patients' biometric information through IoT devices attached to the patient's body at hospitals in cloud environments that have established hospital IoT systems. The proposed model allows clinicians to analyze patients' disease information so that they can collect and treat diseases associated with their eating habits through IoT devices. The analyzed disease information minimizes hospital work to facilitate the handling of prescriptions and care according to the patient's degree of illness.

• Journal of Convergence for Information Technology
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• v.11 no.6
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• pp.33-39
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• 2021

Speech recognition technology is being combined with deep learning and is developing at a rapid pace. In particular, voice recognition services are connected to various devices such as artificial intelligence speakers, vehicle voice recognition, and smartphones, and voice recognition technology is being used in various places, not in specific areas of the industry. In this situation, research to meet high expectations for the technology is also being actively conducted. Among them, in the field of natural language processing (NLP), there is a need for research in the field of removing ambient noise or unnecessary voice signals that have a great influence on the speech recognition recognition rate. Many domestic and foreign companies are already using the latest AI technology for such research. Among them, research using a convolutional neural network algorithm (CNN) is being actively conducted. The purpose of this study is to determine the non-voice section from the user's speech section through the convolutional neural network. It collects the voice files (wav) of 5 speakers to generate learning data, and utilizes the convolutional neural network to determine the speech section and the non-voice section. A classification model for discriminating speech sections was created. Afterwards, an experiment was conducted to detect the non-speech section through the generated model, and as a result, an accuracy of 94% was obtained.

• Journal of Convergence for Information Technology
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• v.11 no.2
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• pp.31-40
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• 2021

Blockchain technology is also actively studied in the real estate transaction field, and real estate transactions have various ways. In this paper, we propose a model that simplifies the authentication procedure of auction systems using Ethereum's Ether to solve the problem of offline court auctions. The proposed model is written in Ethereum's Solidity language, the court registers the sale date and the sale date with the DApp browser, and the bidder accesses the address of the individual's wallet created through Metamask's private key. The bidder then selects the desired sale and enters the bid price amount to participate in the auction. The bidder's record of the highest bid price for the sale he wants is written on the Ethereum test network as a smart contract. and creates a block. Finally, smart contracts written on the network are distributed by the court auction manager to all nodes in the blockchain network, and each node in the blockchain network can be viewed and contract verified. As a result of analyzing the smart contracts of the proposed model and the performance of the system, there are fees incurred due to the creation and use of Ether on platforms using Ethereum, and participation. Ether's changes in value affect the price of the sale, resulting in inconsistent fees in smart contracts each time. However, in future work, we issue our own tokens to solve the market volatility problem and commission problem with the value change of Ether, and refine complex court auction systems.

• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.36-41
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• 2021

Although the technology for prediction or analysis using artificial intelligence is constantly developing, a black-box problem does not interpret the decision-making process. Therefore, the decision process of the AI model can not be interpreted from the user's point of view, which leads to unreliable results. We investigated the problems of artificial intelligence and explainable artificial intelligence using Blockchain to solve them. Data from the decision-making process of artificial intelligence models, which can be explained with Blockchain, are stored in Blockchain with time stamps, among other things. Blockchain provides anti-counterfeiting of the stored data, and due to the nature of Blockchain, it allows free access to data such as decision processes stored in blocks. The difficulty of creating explainable artificial intelligence models is a large part of the complexity of existing models. Therefore, using the point cloud to increase the efficiency of 3D data processing and the processing procedures will shorten the decision-making process to facilitate an explainable artificial intelligence model. To solve the oracle problem, which may lead to data falsification or corruption when storing data in the Blockchain, a blockchain artificial intelligence problem was solved by proposing a blockchain-based explainable artificial intelligence model that passes through an intermediary in the storage process.

• Journal of Convergence for Information Technology
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• v.10 no.9
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• pp.229-236
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• 2020

The purpose of this study was to investigate the current status of unmet medical need using data from the Korea Health Panel study from 2009 to 2013 (excluding 2010), and to analyze the trends of unmet medical need and related factors. The subjects of this study were 11,598 in 2009, 11,035 in 2011, 10,584 in 2012, 10,099 in 2013, and 7,144 people in panel data, and conducted frequency analysis, chi-square test and generalized estimating equation. As a result of the analysis by year, it was found that women, under middle school graduation, medical aid, the lowest household income and low subjective health status experienced more unmet medical need. As a result of analysis using generalized estimating equation, women, under 40 years of age, under elementary school graduation, lowest quartile household income, subjective health status of less than 20 points, and activity restrictions are more likely to experience unmet medical need. Based on these results, we intend to provide basic data for establishing policies on the use of medical services.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.8
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• pp.49-58
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• 2016

In designing heterogeneous architecture based application-specific network-on-chips (NoCs), the opportunities of performance improvement would be expanded when applying asynchronous on-chip communication protocol. This is because the wire latency can be configured independently considering the wirelength of each link. In this paper, we develop the delay model of link-wire-length in asynchronous NoC and propose simulated annealing (SA) based floorplan-aware topology generation algorithm to optimize link-wirelengths. Incorporating the generated topology and the associated latency values across all links, we evaluate the performance using the floorplan-annotated sdf (standard delay format) file and RTL-synthesized gate-level netlist. Compared to TopGen, one of general topology generation algorithms, the experimental results show the reduction in latency by 13.7% and in execution time by 11.8% in average with regards to four applications.

• Journal of Convergence for Information Technology
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• v.7 no.1
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• pp.61-66
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• 2017

As the fourth industrial revolution becomes more popular and advanced services such as artificial intelligence and Internet of Things technology are widely commercialized, awareness of the importance of software is spreading. Recently, software education has been taught not only in elementary school and college but also in college. Also, there is a growing interest in computational thinking needed to solve problems through computing methodology and model. The purpose of this study is to design an app inventor course for non-majors software education based on computational thinking. As a result of the study, six detailed competencies of computational thinking were derived, and six detailed competencies were mapped to the app inventor learning elements. In addition, based on the computational thinking modeling, I designed an app inventor class for students who participated in IT curriculum of university liberal arts curriculum.