• Journal of Information Technology Services
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• v.15 no.4
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• pp.41-62
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• 2016

In Internet of Things (IoT) era, more diverse types of information are collected and the environment of information usage, distribution, and processing is changing. Recently, there have been a growing number of cases involving breach and infringement of personal information in IoT services, for examples, including data breach incidents of Web cam service or drone and hacking cases of smart connected car or individual monitoring service. With the evolution of IoT, concerns on personal information protection has become a crucial issue and thus the risk analysis and management method of personal information should be systematically prepared. This study shows risk factors in IoT regarding possible breach of personal information and infringement of privacy. We propose "a risk analysis framework of protecting personal information in IoT environments" consisting of asset (personal information-type and sensitivity) subject to risk, threats of infringement (device, network, and server points), and social impact caused from the privacy incident. To verify this proposed framework, we conducted risk analysis of IoT services (smart communication device, connected car, smart healthcare, smart home, and smart infra) using this framework. Based on the analysis results, we identified the level of risk to personal information in IoT services and suggested measures to protect personal information and appropriately use it.

• Journal of Korea Multimedia Society
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• v.20 no.5
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• pp.808-826
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• 2017

Most of conventional DSS's(Digital Signage Systems) have been built based on LAMP framework. Recent researches have shown that MEAN or MERN stack framework is simpler, more flexible, faster and more suitable for web-based application than LAMP stack framework. In this paper, we propose a design and implementation of MEARN (ME(A+R)N) stack-based real-time digital signage system, MR-DSS, which supports handing real-time tasks like urgent/instant messaging, system status monitoring and so on, efficiently in addition to conventional digital signage CMS service tasks. MR-DSCMS, CMS of MR-DSS, is designed to provide most of its normal services by REST APIs and real-time services like urgent/instant messaging by Socket.IO base under MEARN stack environment. In addition to architecture description of components composing MR-DSS, design and implementation issues are clarified in more detail. Through experimental testing, it is shown that 1) MR-DSS works functionally well, 2) the networking load performance of MR-DSCMS's REST APIs is better compared to a well-known open source Xibo CMS, and 3) real-time messaging via Socket.IO works much faster than REST APIs.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.2018-2043
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• 2022

Nowadays, COVID-19 infections are influencing our daily lives which have spread globally. The major symptoms' of COVID-19 are dry cough, sore throat, and fever which in turn to critical complications like multi organs failure, acute respiratory distress syndrome, etc. Therefore, to hinder the spread of COVID-19, a Computerized Doughty Predictor Framework (CDPF) is developed to yield benefits in monitoring the progression of disease from Chest CT images which will reduce the mortality rates significantly. The proposed framework CDPF employs Convolutional Neural Network (CNN) as a feature extractor to extract the features from CT images. Subsequently, the extracted features are fed into the Adaptive Dragonfly Algorithm (ADA) to extract the most significant features which will smoothly drive the diagnosing of the COVID and Non-COVID cases with the support of Doughty Learners (DL). This paper uses the publicly available SARS-CoV-2 and Github COVID CT dataset which contains 2482 and 812 CT images with two class labels COVID⁺ and COVI^-. The performance of CDPF is evaluated against existing state of art approaches, which shows the superiority of CDPF with the diagnosis accuracy of about 99.76%.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.115-129
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• 2022

Adopting Internet of Things (IoT)-based technologies in smart homes helps users analyze home appliances electricity consumption for better overall cost monitoring. The IoT application like smart home system (SHS) could suffer from large missing values gaps due to several factors such as security attacks, sensor faults, or connection errors. In this paper, a novel framework has been proposed to predict large gaps of missing values from the SHS home appliances electricity consumption time-series datasets. The framework follows a series of steps to detect, predict and reconstruct the input time-series datasets of missing values. A hybrid convolutional neural network-long short term memory (CNN-LSTM) neural network used to forecast large missing values gaps. A comparative experiment has been conducted to evaluate the performance of hybrid CNN-LSTM with its single variant CNN and LSTM in forecasting missing values. The experimental results indicate a performance superiority of the CNN-LSTM model over the single CNN and LSTM neural networks.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.855-862
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• 2022

Environmental stressors considerably influence the health and safety of humans and must thus be continuously monitored to enhance the urban environments and associated safety. Environmental stressors typically act as stimuli and lead to behavioral changes that can be easily identified. These behavioral responses can thus be used as indicators to clarify people's perceptions of environmental stressors. Therefore, in this study, a framework for assessing environmental stressors based on human behavioral responses was developed. A preliminary experiment was conducted to investigate the feasibility of the framework. Human behavioral and physiological data were collected using wearable sensors, and a survey was performed to determine the psychological responses. Humans were noted to consistently exhibit changes in the movement and speed in the presence of physical environmental stressors, as physiological and psychological responses. The results demonstrated the potential of using behavioral responses as indicators of the human perceptions toward environmental stressors. The proposed framework can be used for urban environment monitoring to enhance the quality and safety.

• Journal of Information Processing Systems
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• v.19 no.2
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• pp.240-257
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• 2023

The industrial Internet of Things (IIoT) is characterized by intelligent connection, real-time data processing, collaborative monitoring, and automatic information processing. The heterogeneous IIoT devices require a high data rate, high reliability, high coverage, and low delay, thus posing a significant challenge to information security. High-performance edge and cloud servers are a good backup solution for IIoT devices with limited capabilities. However, privacy leakage and network attack cases may occur in heterogeneous IIoT environments. Cloud-based multi-party computing is a reliable privacy-protecting technology that encourages multiparty participation in joint computing without privacy disclosure. However, the default cloud selection method does not meet the heterogeneous IIoT requirements. The server can be dishonest, significantly increasing the probability of multi-party computation failure or inefficiency. This paper proposes a blockchain and smart contract-based optimized cloud node selection framework. Different participants choose the best server that meets their performance demands, considering the communication delay. Smart contracts provide a progressive request mechanism to increase participation. The simulation results show that our framework improves overall multi-party computing efficiency by up to 44.73%.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.426-431
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• 2011

The quality of performance evaluation on engineering consultants that provide design-related technical services is difficult to be measured, and only a handful of papers discussed the quality during the design stage. Although design cost is relatively far less than construction cost for a project, the decisions made in the design phase have a significant impact on the final products of the project, especially for large public construction projects. Therefore, this research focuses on reviewing and then establishing a performance evaluation framework for the consulting firms that execute detailed design and provide technical services for the Taipei Rapid Transit Systems (TRTS). By interviewing experts, this study first established a set of indicators to evaluate these firms' performance. Then, those indicators were incorporated into the four aspects of balanced scorecard (BSC) to establish the architecture of the evaluation mechanism. The weight of each indicator was calculated by analytic hierarchy process (AHP) from a survey conducted among experts. The results showed that the top-three indicators were quantity take-off, functions conformity, and budgeting. The framework of performance evaluation established by this study can be applied to measure service performance during the design stage. It not only facilitates the monitoring of consulting firms, but also helps to reduce unnecessary change orders and disputes during the construction stage.

• Nuclear Engineering and Technology
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• v.39 no.2
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• pp.123-128
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• 2007

In order to apply a static fault-tree (FT) method to a system or a plant whose configuration changes dynamically, condition gates and a post processing method are used to effectively accommodate these changes. An operator's performance change, which can be caused by these configuration changes, should also be considered to assess the risk to a plant in a more realistic manner. This study aims to develop an integrated framework to accommodate various configuration changes and their effect on an operator’s performance by using the FT model. We applied a condition-based human reliability assessment (CBHRA) method to consider various conditions endured by an operator. That is, we integrated the CBHRA method with the conventional post processing method for modeling the system configuration changes. The effect of the condition monitoring systems installed in a plant is also considered. In this study, we show an example application of the integrated framework to a probabilistic safety assessment for the shutdown phase of a nuclear power plant.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.4
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• pp.314-322
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• 2006

Despite its brilliant success, Six Sigma has suffered from two shortcomings, namely, the lack of a systematic method to identify the right projects in the "Define" stage and to sustain the improvement in the "Control" stage. The integration of Six Sigma and Business Process Management(BPM) seems to be a promising way to overcome the shortcomings of Six Sigma. This paper first reviews the existing efforts on this issue, and then proposes a framework for an effective integration of Six Sigma and BPM. The framework consists of five phases - DEFINE, EXECUTE, MONITOR, ANALYZE, and IMPROVE(DEMAI). A detailed description on the procedural model is also presented.

• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.124-126
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• 2002

Voice over Internet Protocol(VoIP) is expected to be a major application on the Internet in the future This paper propose an approach to VoIP that uses Differentiated Service and Multi-protocol Label Switching(MPLS) to provide quantitative QoS guarantees over an IP network. An algorithm that determines QoS-constrained routes is proposed and a framework that uses such an algorithm for traffic engineering is outlined. the key component of this framework is a Centralize Resource Manager(CRM) responsible for monitoring and managing resources within the network and making all decisions to route／reroute traffic according to QoS requirement