• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.159-169
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• 2024

This paper proposes a new real-time fire monitoring and evacuation navigation system by integrating Augmented Reality (AR) technology with Internet of Things (IoT) technology. The proposed system collects temperature data through IoT temperature measurement devices installed in buildings and automatically transmits it to a MySQL cloud database via an IoT platform, enabling real-time and accurate data monitoring. Subsequently, the real-time IoT data is visualized on a 3D building model generated through Building Information Modeling (BIM), and the model is represented in the real world using AR technology, allowing intuitive identification of the fire origin. Furthermore, by utilizing Vuforia engine's Device Tracking and Area Targets features, the system tracks the user's real-time location and employs an enhanced A^* algorithm to find the optimal evacuation route among multiple exits. The paper evaluates the proposed system's practicality and demonstrates its effectiveness in rapid and safe evacuation through user experiments based on various virtual fire scenarios.

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1349-1360
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• 2017

This study was conducted to estimate the genetic parameters for common ketosis indicators (${\beta}$-hydroxybutyrate acid, BHBA; milk acetone), feed intake efficiency indicator (energy-corrected milk, ECM), and milk yield (MY) in Korean Holstein. A total of 75,072 monthly test-day records from 14,397 first parity cows were collected, between 2012 and 2016, from Korea animal improvement association enrolled farms. Variance components were estimated using a multiple trait random regression model. The heritability of BHBA and acetone levels ranged from 0.06 to 0.15 at different DIMs. The phenotypic and genetic correlations between BHBA and acetone were between 0.73 and 0.90, and between 0.93 and 0.98, respectively. The phenotypic correlation between BHBA and MY, between acetone and MY, between BHBA and ECM, and between acetone and ECM ranged from -0.18 to -0.05, -0.23 to -0.05, 0 to 0.10, and -0.09 to 0.01, respectively. Genetic correlation estimates between BHBA and MY, between acetone and MY, between BHBA and ECM, and between acetone and ECM also ranged from -0.55 to 0.05, -0.62 to -0.04, -0.10 to 0.11, and -0.20 to 0.00, respectively. We hope that these results would greatly assist in the improvement of ketosis disease in the local Holsteins.

• Journal of Information Processing Systems
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• v.16 no.1
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• pp.96-112
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• 2020

Solving the disclosure problem of sensitive information with the k-nearest neighbor query, location dummy technique, or interfering data in location-based services (LBSs) is a new research topic. Although they reduced security threats, previous studies will be ineffective in the case of sparse users or K-successive privacy, and additional calculations will deteriorate the performance of LBS application systems. Therefore, a model is proposed herein, which is based on geohash-encoding technology instead of latitude and longitude, memcached server cluster, encryption and decryption, and authentication. Simulation results based on PHP and MySQL show that the model offers approximately 10× speedup over the conventional approach. Two problems are solved using the model: sensitive information in LBS application is not disclosed, and the relationship between an individual and a track is not leaked.

• International conference on construction engineering and project management
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• 2017.10a
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• pp.301-312
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• 2017

Quality evaluation and control represent increasingly important concerns for construction quality management. There is an evident need for a standard data model to be used as the basis for computer-aided quality management. This study focuses on how to realize evaluation of construction quality based on BIM and database technology. In this paper, the reinforced concrete main structure is taken as an example, and the BP neural network evaluation model is established by inquiring current construction quality acceptance specification and evaluation standard. Furthermore, IFC standard is extended to integrate quality evaluation information and realize the mapping of evaluation information in BIM model, contributing to the visualization and transfer sharing of evaluation information. Furthermore, the conceptual entity model is designed to build quality evaluation database, and this paper select MySQL workbench system to achieve the establishment of the database. This study is organized to realize the requirement of visualization and data integration on construction quality evaluation which makes it more effective, convenient, intuitive, easy to find quality problems and provide more comprehensive and reliable data for the quality management of construction enterprises and official construction administratiors.

• Korean Journal of Computational Design and Engineering
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• v.17 no.2
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• pp.79-90
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• 2012

In digital virtual manufacturing simulation, Digital Human widely used to optimal workplace design, enhancing worker safety in the workplace, and improving product quality. However, the case of ergonomics simulation solutions to support digital human modeling, Optimal DHM (Digital Human Model) data needed to develop and perform DHM will collect information related to the production process. So simulation developer has burden of collecting information. In this study, to overcome the limitations of existing solutions, we proposed the ADAGIO(Automated Digital humAn model development for General assembly usIng Ontology) framework. The ADAGIO framework was developed for DHM ontology to support optimal deployment of digital virtual environment and in order to ensure consistency of simulation components that are required for simulation modeling was made of a library.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.984-987
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• 2018

In an Internet of Thing (IoT) environment, entities with different attributes and capacities are going to be connected in a highly connected fashion. Specifically, not only the mechanical and electronic devices but also other entities such as people, locations and applications are connected to each other. Understanding and managing these connections play an important role for businesses, which identify opportunities for new IoT services. Traditional approach for storing and querying IoT data is used of a relational database management system (RDMS) such as MySQL or MSSQL. However, using RDMS is not flexible and sufficient for handling heterogeneous IoT data because these data have deeply complex relationships which require nested queries and complex joins on multiple tables. In this paper, we propose a graph model for constructing a graph database of heterogeneous IoT data. Graph databases are purposely-built to store highly connected data with nodes representing entities and edges representing the relationships between these entities. Our model fuses social graph, spatial graph, and things graph, and incorporates the relationships among them. We then present a case study which applies our model for representing data from a Smart Campus using Neo4J platform. Through the results of querying to answer real questions in Smart Campus management, we show the viability of our model.

• East Asian Journal of Business Economics (EAJBE)
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• v.3 no.4
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• pp.9-15
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• 2015

The exchange rate is a very important macro variable that has influence on the whole economy and has, therefore, been the topic of many discussions amongst policymakers, academics and other economic agents. The issue of whether to have a fixed, pegged or floating exchange rate regime was highly debated during the 1970s. The purpose of this paper is to investigate what factors determine the exchange rate in Somalia. Quantitative research methodology has been employed to develop regression model using time series data for the period of 12 years. The regression model has been developed based on Quantity theory of money, purchasing power parity and uncovered interest rate parity theory. Somalia is on the countries where the highest exchange rate volatility exists; for example in 2012, the rate jumped 29% percent and two weak later dropped 21%, when Turkish humanitarian aid agencies injected the market a lot of U.S dollar. Based on my study using regression model for time series data of 12 years, the four factors are mainly attributable for the exchange rate volatility of Somalia; these factors include the balance of payment, inflation rate, money supply (mostly come from remittance and NGOs) and Bank profits.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.989-1003
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• 2021

With the recent increase in the types of services provided by Internet companies, collection of various types of data has become a necessity. Data collectors corresponding to web services profit by collecting users' data indiscriminately and providing it to the associated services. However, the data provider remains unaware of the manner in which the data are collected and used. Furthermore, the data collector of a web service consumes web resources by generating a large amount of web traffic. This traffic can damage servers by causing service outages. In this study, we propose a website search engine that employs a system that controls user information using blockchains and builds its database based on the recorded information. The system is divided into three parts: a collection section that uses proxy, a management section that uses blockchains, and a search engine that uses a built-in database. This structure allows data sovereigns to manage their data more transparently. Search engines that use blockchains do not use internet bots, and instead use the data generated by user behavior. This avoids generation of traffic from internet bots and can, thereby, contribute to creating a better web ecosystem.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.368-371
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• 1999

In this paper, we propose a neural network processor architecture with on-chip learning and with reconfigurability according to the data dependencies of the algorithm applied. For the neural network model applied, the proposed architecture can be configured into either SIMD or SRA(Systolic Ring Array) without my changing of on-chip configuration so as to obtain a high throughput. However, changing of system configuration can be controlled by user program. To process activation function, which needs amount of cycles to get its value, we design it by using PWL(Piece-Wise Linear) function approximation method. This unit has only single latency and the processing ability of non-linear function such as sigmoid gaussian function etc. And we verified the processing mechanism with EBP(Error Back-Propagation) model.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.683-690
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• 2004

MND(Ministry of National Defense) has developed .nm AF(Ministry of National Defense Architecture Framework) to guarantee interoperability among defense information systems. Users can easily and consistently develop architecture products through MND AF. There is necessity for development if CADM(Core Architecture Data Model), which facilitate exchange, integration, and comparison for architecture data, to store architecture data from architecture products and reuse them. We developed CADM from defining entities and relationships that satisfy data requirement of each architecture product from MND AF. After we developed architecture products about MIMS(Military Intelligence Management System), and inserted these architecture data to CADM repository. we verified CADM entities and relationships through query. Through CABM which provides common data model for the whole my architectures, interoperability and integration among defense information systems ran be improved, and integrated defense information resources efficiently can be managed.