• Journal of The Korean Association of Information Education
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• v.18 no.1
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• pp.25-33
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• 2014

Due to the recent development of educational robot hardwares, processing speed and scalability have been greatly improved. Thus, the robot hardwares that are compatible with temperature sensor for MBL and gyro sensor made a data logging possible. Students can conduct an experiment on scientific research and prediction, collecting and data analysis with robots that can process data logging. Therefore this research constructed and adopted science project class that introduced a Smart r-Learning that utilizes Class SNS and smartphone. As a result of applying a data logging smart r-Learning to elementary school 5th graders, it has shown that the students' logical thinking ability four of the six areas have been improved in t-test.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1655-1673
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• 2018

Mobile computing environment is subject to the constraints of bounded network bandwidth, frequently encountered disconnections, insufficient battery power, and system asymmetry. To meet these constraints and to gain high scalability, data broadcasting has been proposed on data transmission techniques. However, updates made to the database in any broadcast cycle are deferred to the next cycle in order to appear to mobile clients with lower data currency. The main goal of this paper is to enhance the transaction performance processing and database currency. The main approach involves decomposing the main broadcast cycle into a number of sub-cycles, where data items are broadcasted as they were originally sequenced in the main cycle while appearing in the most current versions. A concurrency control method AOCCRBSC is proposed to cope well with the cycle decomposition. The proposed method exploits predeclaration and adapts the AOCCRB method by customizing prefetching, back-off, and partial backward and forward validation techniques. As a result, more than one of the conflicting transactions is allowed to commit at the server in the same broadcast cycle which empowers the processing of both update and read-only transactions and improves data currency.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.1
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• pp.223-228
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• 2015

Korean climate becoming increasingly subtropical by climate warming makes local heavy rainfall frequently. To avoid damages from the local heavy rainfall, we need a forecasting service for a great number of clients. However, there is not the framework for the service based on wireless data broadcasting yet. In this paper, we design and implement a service framework for local heavy rainfall forecasting using wireless data broadcast. The developed service framework has scalability that can adopt various data scheduling and indexing schemes. We show the efficiency of the proposed framework to forecast local heavy rainfall through a simulation study.

• The Journal of the Korea institute of electronic communication sciences
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• v.5 no.6
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• pp.672-677
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• 2010

Recently, the efficient management system for large-scale sensor data has been required due to the increasing deployment of large-scale sensor networks. In this paper, we propose a cloud-based sensor data management system with low cast, high scalability, and efficiency. Sensor data in sensor networks are transmitted to the cloud through a cloud-gateway. At this point, outlier detection and event processing is performed. Transmitted sensor data are stored in the Hadoop HBase, distributed column-oriented database, and processed in parallel by query processing module designed as the MapReduce model. The proposed system can be work with the application of a variety of platforms, because processed results are provided through REST-based web service.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.6
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• pp.2078-2094
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• 2015

Now a days, Efficient processing of Broadcast Queries is of critical importance with the ever-increasing deployment and use of mobile technologies. BQs have certain unique characteristics that the traditional spatial query processing in centralized databases does not address. In novel query processing technique, by maintaining high scalability and accuracy, latency is reduced considerably in answering BQs. Novel approach is based on peer-to-peer sharing, which enables us to process queries without delay at a mobile host by using query results cached in its neighboring mobile peers. We design and evaluate cooperative caching techniques to efficiently support data access in ad hoc networks. We first propose two schemes: Cache Data, which caches the data, and Cache Path, which caches the data path. After analyzing the performance of those two schemes, we propose a hybrid approach (Hybrid Cache), which can further improve the performance by taking advantage of Cache Data and Cache Path while avoiding their weaknesses. Cache replacement policies are also studied to further improve the performance. Simulation results show that the proposed schemes can significantly reduce the query delay and message complexity when compared to other caching schemes.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.11
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• pp.461-470
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• 2013

This paper proposes high speed kernel data collection method for analysis of memory workload, using technique of direct access to process's memory management structure. The conventional analysis tools have a slower data collection speed and they are lack of scalability due to collection only formalized memory information. The proposed method collects kernel data much faster than the conventional methods using technique of direct collect to process's memory information, page table, page structure in the memory management structure, and it can collect data which user wanted. We collect memory management data of the running process, and analyze its memory workload.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.107-115
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• 2022

Recently, big data applications need another database different from the Relation database. NoSQL databases are used to save and handle massive amounts of data. NoSQL databases have many advantages over traditional databases like flexibility, efficiently processing data, scalability, and dynamic schemas. Most of the current applications are based on the web, and the size of data is in increasing. NoSQL databases are expected to be used on a more and large scale in the future. However, NoSQL suffers from many security issues, and one of them is access control. Many recent applications need Fine-Grained Access control (FGAC). The integration of the NoSQL databases with FGAC will increase their usability in various fields. It will offer customized data protection levels and enhance security in NoSQL databases. There are different NoSQL database models, and a document-based database is one type of them. In this research, we choose the CouchDB NoSQL document database and develop an access control mechanism that works at a fain-grained level. The proposed mechanism uses role-based access control of CouchDB and restricts read access to work at the document level. The experiment shows that our mechanism effectively works at the document level in CouchDB with good execution time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.574-576
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• 2021

It is necessary to introduce micro-service techniques when constructing large-scale operating systems or systems that take into account scalability. Kafka is a message queue with the pub/sub model, which has features that are well applied to distributed environments and is also suitable for microservices in that it can utilize various data sources. In this paper, we propose a data sharing method for educational video sharing services using Apache's Kafka. The proposed system builds a Kafka cluster for the educational video sharing service to share various data, and also uses a spark cluster to link with recommendation systems based on similarities in educational videos. We also present a way to share various data sources, such as files, various DBMS, etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.232-234
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• 2012

NMEA2000 international standards was developed for real-time communication among sensors and devices in ships. This paper describes analysis of NMEA2000 network protocols and implementation of a gateway for wireless data services in NMEA2000 networks. For scalability of the network, developed gateway didn't participate in NMEA2000 network but simply relayed data between wireless devices and the network.

• Journal of Electrical Engineering and Technology
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• v.6 no.4
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• pp.573-579
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• 2011

To meet the scalability and performance requirements of data analyses, which often involve voluminous data, efficient parallel or concurrent algorithms and frameworks are essential. We present a high-performance Korean morphological analyzer which employs the MapReduce framework on the graphics processing unit (GPU). MapReduce is a programming framework introduced by Google to aid the development of web search applications on a large number of central processing units (CPUs). GPUs are designed as a special-purpose co-processor. Their programming interfaces are typically formulated for graphics applications. Compared to CPUs, GPUs have greater computation power and memory bandwidth; however, GPUs are more difficult to program because of the design of their architectures. The performance of the Korean morphological analyzer using the MapReduce framework on the GPU is evaluated in comparison with the CPU-based model. The proposed Korean Morphological analyzer shows promising scalable performance on distributed computing with the GPU.