• Journal of KIBIM
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• v.9 no.2
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• pp.11-20
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• 2019

The use of drones and laser scanners have the potential to drastically reduce the time and costs of conventional techniques employed for field survey of cultural heritage buildings. Moreover, point cloud data can be utilized to create an as-built Building Information Model (BIM), providing a repository for consistent operations information. However, BIM creation is not a requisite for heritage buildings, and their technological possibilities and barriers have not been documented. This research explored the processes required to convert a heritage university building to a BIM model, using existing off-the-shelf software applications. Point cloud data was gathered from drones for the exterior, while a laser scanner was employed for the interior of the building. The point clouds were preprocessed and used as references for the geometry of the building elements, including walls, slabs, windows, doors, and staircases. The BIM model was subsequently created for the individual elements using existing and custom libraries. The model was used to extract 2D CAD drawings that met the requirements of Korea's heritage preservation specifications. The experiment showed that technical improvements were needed to overcome issues of occlusion, modeling errors due to modeler's subjective judgements and point cloud data cleaning and filtering techniques.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.205-212
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• 2019

With the rapid spread of mobile phones, users are continuously interested in using the mobile phone in connection with personal activities. Also, increasingly users want to share (transmit and receive) and save data more easily and simply in the mobile environment. This paper suggests motion recognition of mobile phone to share personal information with any people located within a certain distance using location-based service with GCM service. The suggested application is based on Google Cloud Messaging which enables asynchronous communication with the mobile applications executed in Android operating system. The requirements of light-weight mechanism can be satisfied as it is possible to access sharing of personal information easily, simply and in real time through all mobile devices anywhere.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.5
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• pp.249-258
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• 2019

In the cyber-physical system, big data collected from numerous sensors and IoT devices is transferred to the Cloud for processing and analysis. When transferring data to the Cloud, merging data into one single file is more efficient than using the data in the form of split files. However, current merging and splitting operations are performed at the user-level and require many I / O requests to memory and storage devices, which is very inefficient and time-consuming. To solve this problem, this paper proposes kernel-level partitioning and combining operations. At the kernel level, splitting and merging files can be done with very little overhead by modifying the file system metadata. We have designed the proposed algorithm in detail and implemented it in the Linux Ext4 file system. In our experiments with the real Cloud storage system, our technique has achieved a transfer time of up to only 17% compared to the case of transferring split files. It also confirmed that the time required can be reduced by up to 0.5% compared to the existing user-level method.

• Journal of Navigation and Port Research
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• v.46 no.5
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• pp.458-470
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• 2022

As the 4th industrial revolution progresses, the application of several cutting-edge technologies such as the Internet of Things, big data, and mixed reality (MR) in relation to autonomous ships is being considered in the maritime logistics field. The aim of this study was to apply the concept of a digital twin model based on Human Machine Interaction (HMI) including a digital twin model and the role of an operator to a ship. The role of the digital twin is divided into information provision, support, decision, and implementation. The role of the operator is divided into operation, decision-making, supervision, and standby. The system constituting the ship was investigated. The digital twin system that could be applied to the ship was also investigated. The cloud-based digital twin system architecture that could apply investigated applications was divided into ship data collection (part 1), cloud system (part 2), analysis system/ application (part 3), and MR/mobile system (part 4). A Mixed Reality device HoloLens was used as an HMI equipment to perform a simulation test of a digital twin system of an 8 m battery-based electric propulsion ship.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.91-100
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• 2023

Pervasive computing is characterized by a key characteristic that affects the operating environment of services and users. It places more emphasis on dynamic environments where available resources continuously vary without prior knowledge of their availability, while in static environments the services provided to users are determined in advance. At the same time, Cloud computing paradigm introduced flexibility of use according to the user's profile and needs. In this paper, we aimed to provide Context-Aware Transactional Service applications with solutions so that it can be integrated and invoked like any service in the digital ecosystem. Being able to compose is not enough, each service and application must be able to offer a well-defined behavior. This behavior must be controlled to meet the dynamicity and adaptability necessary for the new user's requirements. The motivation in this paper is to offer design patterns that will provide a maximum of automatism in order to guarantee short reaction times and minimal human intervention. Our proposal includes a cloud service model by developing a PaaS service that allows CATS adaptation. A new specification for the validation of CATS model has been also introduced using the ACTA formalism.

• Journal of Information Technology Applications and Management
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• v.30 no.6
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• pp.91-111
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• 2023

This study aims to identify the influencing factors of intention to use cloud services using the SEM-ANN two-step approach. In previous studies of SEM-ANN, SEM presented R² and ANN presented MSE(mean squared error), so analysis performance could not be compared. In this study, R² and MSE were calculated and presented by SEM and ANN, respectively. Then, analysis performance was compared and feature importances were compared by sensitivity analysis. As a result, the ANN default model improved R² by 2.87 compared to the PLS model, showing a small Cohen's effect size. The ANN optimization model improved R² by 7.86 compared to the PLS model, showing a medium Cohen effect size. In normalized feature importances, the order of importances was the same for PLS and ANN. The contribution of this study, which links structural equation modeling to artificial intelligence, is that it verified the effect of improving the explanatory power of the research model while maintaining the order of importance of independent variables.

• Annual Conference of KIPS
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• 2018.10a
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• pp.39-42
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• 2018

Log analysis and monitoring have a significant importance in most of the systems. Log management has core importance in applications like distributed applications, cloud based applications, and applications designed for big data. These applications produce a large number of log files which contain essential information. This information can be used for log analytics to understand the relevant patterns from varying log data. However, they need some tools for the purpose of parsing, storing, and visualizing log informations. "Elasticsearch, Logstash, and Kibana"(ELK Stack) is one of the most popular analyzing tools for log management. For the ingestion of log files configuration files have a key importance, as they cover all the services needed to input, process, and output the log files. However, creating configuration files is sometimes very complicated and time consuming in many applications as it requires domain expertise and manual creation. In this paper, an auto configuration module for Logstash is proposed which aims to auto generate the configuration files for Logstash. The primary purpose of this paper is to provide a mechanism, which can be used to auto generate the configuration files for corresponding log files in less time. The proposed module aims to provide an overall efficiency in the log management system.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06b
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• pp.41-43
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• 2011

Cyber-Physical Systems are tight integration of computation, networking and physical objects to sense, monitor, and control the physical world. This paper presents a novel architecture that combines two next generation technologies i.e. cyber-physical systems and Cloud computing to develop a ubiquitous healthcare based infrastructure. Through this infrastructure, patients and elderly people get remote assistance, monitoring of their health conditions and medication while living in proximity of home. Consequently, this leads to major cost savings. However, there are various challenges that need to be overcome before building such systems. These challenges include making system real-time responsive, reliability, stability and privacy. Therefore, in this paper, we propose an architecture that deals with these challenges.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.3
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• pp.129-137
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• 2020

Kubernetes is one of the most widely used tool in cloud computing environments. It m anages POD as a basic operational unit, providing a isolated environments through container tech nology. Basically, its scheduler properly allocates POD, considering the utilizations of CPUs, mem ories and volumes on hosts. In our work, we develop a customized scheduling framework additio nally considering network resources. In the framework, we can monitor the dynamic variations of resources and make it possible to utilize the resources for the scheduler. This framework offers not only observing necessary information but also visualizing the data to scheduler for providing convenience.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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• pp.2718-2731
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• 2019

Conjunctive keyword search encryption is an important technique for protecting sensitive data that is outsourced to cloud servers. However, the process of searching outsourced data may facilitate the leakage of sensitive data. Thus, an efficient data search approach with high security is critical. To solve this problem, an efficient conjunctive keyword search scheme based on ciphertext-policy attribute-based encryption is proposed for cloud storage environment. This paper proposes an efficient mechanism for removing the secure channel and resisting off-line keyword-guessing attacks. The storage overhead and the computational complexity are regardless of the number of keywords. This scheme is proved adaptively secure based on the decisional bilinear Diffie-Hellman assumption in the standard model. Finally, the results of theoretical analysis and experimental simulation show that the proposed scheme has advantages in security, storage overhead and efficiency, and it is more suitable for practical applications.