• Smart Structures and Systems
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• v.17 no.4
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• pp.669-690
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• 2016

Advances in sensor technologies have led to the instrumentation of sensor networks for bridge monitoring and management. For a dense sensor network, enormous amount of sensor data are collected. The data need to be managed, processed, and interpreted. Data management issues are of prime importance for a bridge management system. This paper describes a data management infrastructure for bridge monitoring applications. Specifically, NoSQL database systems such as MongoDB and Apache Cassandra are employed to handle time-series data as well the unstructured bridge information model data. Standard XML-based modeling languages such as OpenBrIM and SensorML are adopted to manage semantically meaningful data and to support interoperability. Data interoperability and integration among different components of a bridge monitoring system that includes on-site computers, a central server, local computing platforms, and mobile devices are illustrated. The data management framework is demonstrated using the data collected from the wireless sensor network installed on the Telegraph Road Bridge, Monroe, MI.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.17-30
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• 2007

In recent years, pair programming has become a widely used approach for development of information systems. According to a worldwide survey, 35 percent of 104 development projects reported using pair programming. However, previous studies have shown rather mixed results in terms of the effectiveness of pair programming, comparing to individual or independent programming. This paper, therefore, uses a lab setting to control some of the variables that appear to have caused conflicting results in earlier studies. Writing SQL Queries for given problem statements is selected as the task the subjects to solve. One key issue addressed is the distribution of work load among the pair programmers and the independent programmers. Another is communication among co-workers as would occur in a real-world system development environment. The results of this study indicate there is no significant difference in task performance pair programming and independent programming.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.6
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• pp.645-651
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• 2019

At a time when large amounts of data are being poured out, there are many changes in software architecture or data storage patterns because of the nature of the data being written, rather more read-intensive than writing. Accordingly, in this paper, the query model of Command Query Responsibility Segmentation (CQRS) pattern separating the responsibilities of commands and queries is used to implement an efficient high-capacity data lookup system in users' requirements. This paper uses the 2018 temperature, humidity and precipitation data of the Korea Meteorological Administration Open API to store about 2.3 billion data suitable for RDBMS (PostgreSQL) and NoSQL (MongoDB). It also compares and analyzes the performance of systems with CQRS pattern applied from the perspective of the web server (Web Server) implemented and systems without CQRS pattern, the storage structure performance of each database, and the performance corresponding to the data processing characteristics.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.2
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• pp.94-99
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• 2016

Application layer attacks have for years posed an ever-serious threat to network security, since they always come after a technically legitimate connection has been established. In recent years, cyber criminals have turned to fully exploiting the web as a medium of communication to launch a variety of forbidden or illicit activities by spreading malicious automated software (auto-ware) such as adware, spyware, or bots. When this malicious auto-ware infects a network, it will act like a robot, mimic normal behavior of web access, and bypass the network firewall or intrusion detection system. Besides that, in a private and large network, with huge Hypertext Transfer Protocol (HTTP) traffic generated each day, communication behavior identification and classification of auto-ware is a challenge. In this paper, based on a previous study, analysis of auto-ware communication behavior, and with the addition of new features, a method for classification of HTTP auto-ware communication is proposed. For that, a Not Only Structured Query Language (NoSQL) database is applied to handle large volumes of unstructured HTTP requests captured every day. The method is tested with real HTTP traffic data collected through a proxy server of a private network, providing good results in the classification and detection of suspicious auto-ware web access.

• Journal of Information Technology Services
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• v.20 no.3
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• pp.1-12
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• 2021

Reactor Coolant Pump (RCP) is core part of nuclear power plant to provide the forced circulation of reactor coolant for the removal of core heat. Properly monitoring vibration of RCP is a key activity of a successful predictive maintenance and can lead to a decrease in failure, optimization of machine performance, and a reduction of repair and maintenance costs. Here, we developed real-time RCP Vibration Analysis System (VAS) that web based platform using NoSQL DB (Mongo DB) to handle vibration data of RCP. In this paper, we explain how to implement digital signal process of vibration data from time domain to frequency domain using Fast Fourier transform and how to design NoSQL DB structure, how to implement web service using Java spring framework, JavaScript, High-Chart. We have implement various plot according to standard of the American Society of Mechanical Engineers (ASME) and it can show on web browser based on HTML 5. This data analysis platform shows a upgraded method to real-time analyze vibration data and easily uses without specialist. Furthermore to get better precision we have plan apply to additional machine learning technology.

• KIISE Transactions on Computing Practices
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• v.22 no.2
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• pp.77-82
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• 2016

This paper presents the development of the Korean medicine symptom diagnosis system. In the Korean medicine symptom diagnosis system, the patient explains their symptoms and an oriental doctor makes a diagnosis based on the symptoms. Natural language processing is required to make a diagnosis automatically through the patients' reports of symptoms. We use morphological analysis to get understandable information from the natural language itself. We developed a diagnosis system that consists of NoSQL document-oriented databases-MongoDB. NoSQL has better performance at unstructured and semi-structured data, rather than using Relational Databases. We collect patient symptom reports in MongoDB to refine difficult medical terminology and provide understandable terminology to patients.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.84-94
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• 2021

Graph databases have been developed to efficiently store and query graph data composed of vertices and edges to express relationships between objects. Since the query types of graph database show very different characteristics from traditional NoSQL databases, benchmarking tools suitable for graph databases to verify the performance of the graph database are needed. In this paper, we propose an efficient graph database benchmarking system that supports diversity in graph inputs and queries. The proposed system utilizes OrientDB to conduct benchmarking for graph databases. In order to support the diversity of input graphs and query graphs, we use LDBC that is an existing graph data generation tool. We demonstrate the feasibility and effectiveness of the proposed scheme through analysis of benchmarking results. As a result of performance evaluation, it has been shown that the proposed system can generate customizable synthetic graph data, and benchmarking can be performed based on the generated graph data.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.9
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• pp.2064-2072
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• 2015

To improve performance, most of Web Services produce and manage User Access Logs. Through the Access Logs, the record provides information about time when the most traffic happens and logs and which resource is mostly used. Then, the log can be used to analyze. However, in case of increasing high traffics of Web Services at the specific time, the performance of Web Service leads to deterioration because the number of processing User Access Logs is increasing rapidly. To solve this problem, we should improve the system performance, or tuning is needed, but it makes a problem cost a lot of money. Also, after it happens, it is not necessary to build such system by spending extra money. Therefore, this paper described the effective Web Service's performance as using improved User Access Log performance. Also, to process the newest data in bulk, this paper includes a method applying some parts of NoSQL using Redis.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.04a
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• pp.125-128
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• 2015

최근 GPS가 기본 탑재된 스마트폰이 활성화된 이후 대량의 GPS 궤적 데이터를 전자지도에 매칭하여 분석하는 요구가 대두되고 있다. 그러나 기존에 연구된 맵매칭 기법은 주로 내비게이션용 알고리즘으로 대량의 GPS궤적을 서버에서 분석하기에는 속도 및 시스템 성능의 이슈가 있다. 본 연구는 대표적인 분산 NoSQL DB인 하듐 에코시스템의 HBase를 이용한 맵매칭 시스템에 대한 연구이다. 맵매칭을 위한 전자지도를 HBase탑재하기 위한 테이블 사양을 정의하였고, HBase와 연동하여 분석하는 맵매칭 알고리즘을 제시하고 Java로 구현하여 분석하였다. 이를 통해 대량의 GPS궤적을 NoSQL 기반 방법론을 통하여 효율적으로 빅데이터를 분석하였다.

• Journal of Internet Computing and Services
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• v.20 no.5
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• pp.49-55
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• 2019

Organizations design and operate business process models to achieve their goals efficiently and systematically. With the advancement of IT technology, the number of items that computer systems can participate in and the process becomes huge and complicated. This phenomenon created a more complex and subdivide flow of business process.The process instances that contain workcase and events are larger and have more data. This is an essential resource for process mining and is used directly in model discovery, analysis, and improvement of processes. This event log is getting bigger and broader, which leads to problems such as capacity management and I / O load in management of existing row level program or management through a relational database. In this paper, as the event log becomes big data, we have found the problem of management limit based on the existing original file or relational database. Design and apply schemes to archive and analyze large event logs through Hadoop, an open source distributed file system, and HBase, a NoSQL database system.