• Journal of KIISE
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• v.43 no.11
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• pp.1216-1222
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• 2016

The advent of large-scale web services has resulted in gradual increase in the amount of data used in those services. These big data are managed efficiently by DBMS such as MySQL and MariaDB, which use InnoDB engine as their storage engine, since InnoDB guarantees ACID and is suitable for handling large-scale data. To improve I/O performance, InnoDB caches data and index of its database through a buffer pool. It also supports multiple buffer pools to mitigate lock contentions. However, the multiple buffer pool scheme leads to the additional data consistency overhead. In this paper, we analyze the overhead of the multiple buffer pool scheme. In our experimental results, although multiple buffer pool scheme mitigates the lock contention by up to 46.3%, throughput of DMBS is significantly degraded by up to 50.6% due to increased disk I/O and fsync calls.

• International Journal of Advanced Culture Technology
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• v.10 no.1
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• pp.310-316
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• 2022

The smart tourism service provides services such as travel planning and tour guides to tourists using key technologies of the 4th industrial revolution, such as the Internet of Things, communication infrastructure, big data, artificial intelligence, AR/VR, and drones. We are developing smart tourism services such as recommended travel products, my travel itinerary, tourism information, and chatbots for tourists through the smart tourism app. In this paper, we develop a smart tourism service system that provides real-time location-based tourism information and weather information to tourists. The smart tourism service system consists of a smart tourism app, a smart tourism information system, and an IoT data collection device. The smart tourism information system receives weather information from the IoT data collection device installed in the tourist destination. The location-based smart tourism service is provided as a smart tourism app in the smart tourism information system according to the Beacon's UUID in the IoT data collection device. The smart tourism information system stores the Beacon's UUIDs received from tourists and provides a safe hiking service for tourists.

• Journal of Information Technology Services
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• v.21 no.3
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• pp.27-42
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• 2022

Open Data is an essential resource for the data industry. 'Act On Promotion Of The Provision And Use Of Public Data', enacted on July 30, 2013, mandates public institutions to manage the quality of Open Data and provide it to the public. Via such a legislation, the legal basis for the public to Open Data is prepared. Furthermore, public institutions are prohibited from developing and providing open data services that are duplicated or similar to those of the private sector, and private start-ups using open data are supported. However, as the demand for Open Data gradually increases, the cases of refusal to provide or interruption of Open Data held by public institutions are also increasing. Accordingly, the 'Open Data Mediation Committee' is established and operated so that the right to use data can be rescued through a simple dispute mediation procedure rather than complicated administrative litigation. The main issues dealt with in dispute settlement so far are usually the rights of third parties, such as open data including personal information, private information such as trade secrets, and copyrights. Plus, non-open data cannot be provided without the consent of the information subject. Rather than processing non-open data into open data through de-identification processing, positive results can be expected if consent is provided through active rights processing of the personal information subject. Not only can the Public Mydata Service be used by the information subject, but Open Data applicants will also be able to secure higher quality Open Data, which will have a positive impact on fostering the private data industry. This study derives a plan to establish a rights processing platform to enhance the usability of Open Data, including private information such as personal information, trade secrets, and copyright, which have become an issue when providing Open Data since 2014. With that, the proposals in this study are expected to serve as a stepping stone to revitalize private start-ups through the use of wide Open Data and improve public convenience through Public MyData services of information subjects.

• Electronics and Telecommunications Trends
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• v.4 no.1
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• pp.35-43
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• 1989

The evolution of telecommunications has raised the profile of many segments of the network that were not previously considered important. Until recently, basic telephony existed with the extension of passive cables without any particular user network interface. In the area of data communications, the introduction of flexible packet switching has allowed the network to evolve in a far more efficient manner. To overcome such separated network problems and business needs of both users and network providers, the integrated narrowband ISDN concept is being developed in most countries for implementation in the public switched telephone network (PSTN). The targets of ISDN, in my opinion, can be explained as follows : To the user, ISDN should provide the services at any time, at any place, through any media. To the business customer using PABX or LAN applications, ISDN should introduce customized services rapidly and also, ISDN should be developed by the modular hardware and software design approach in order for new services to be introduced rapidly and effectively. Software can be also developed by non-expert local staff to cater for adopting new user's service requirements immediately. Finally, ISDN will be able to increase business chances and benefit both users and operating companies.

• 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.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1643-1651
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• 2014

Social networking services (in short, SNS) allow users to share their own data with family, friends, and communities. Since there are many kinds of information that has been uploaded and shared through the SNS, the amount of information on the SNS keeps increasing exponentially. Particularly, Facebook has adopted some interesting features related to entertainment (e.g., movie, music and TV show). However, they do not consider contextual information of users for recommendation (e.g., time, location, and social contexts). Therefore, in this paper, we propose a novel approach for movie recommendation based on the integration of a variety contextual information (i.e., when the users watched the movies, where the users watched the movies, and who watched the movie with them). Thus, we developed a Facebook application (called MyMovieHistory) for recording the movie history of users and recommending relevant movies.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.135-142
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• 2015

Appearance and rapid growth of the social network services (SNS) have led to changes in the distribution structure of information. Consumers can obtain various information quickly via the social network services and companies make use of a new advertising channel in them. In order to increase the effect of publicity activities through the social network services, development and application of public relations strategy by evaluating and analyzing the results of the activities is required. In this paper, a method for developing a low cost system to evaluate and analyze the results of public relations through the social networks is proposed. The proposed method was verified through building and running a demo system to collect and analyze data in the Facebook fan pages using MySQL database and PHP script on a Linux server.

• Journal of Internet Computing and Services
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• v.14 no.6
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• pp.71-84
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• 2013

Log data, which record the multitude of information created when operating computer systems, are utilized in many processes, from carrying out computer system inspection and process optimization to providing customized user optimization. In this paper, we propose a MongoDB-based unstructured log processing system in a cloud environment for processing the massive amount of log data of banks. Most of the log data generated during banking operations come from handling a client's business. Therefore, in order to gather, store, categorize, and analyze the log data generated while processing the client's business, a separate log data processing system needs to be established. However, the realization of flexible storage expansion functions for processing a massive amount of unstructured log data and executing a considerable number of functions to categorize and analyze the stored unstructured log data is difficult in existing computer environments. Thus, in this study, we use cloud computing technology to realize a cloud-based log data processing system for processing unstructured log data that are difficult to process using the existing computing infrastructure's analysis tools and management system. The proposed system uses the IaaS (Infrastructure as a Service) cloud environment to provide a flexible expansion of computing resources and includes the ability to flexibly expand resources such as storage space and memory under conditions such as extended storage or rapid increase in log data. Moreover, to overcome the processing limits of the existing analysis tool when a real-time analysis of the aggregated unstructured log data is required, the proposed system includes a Hadoop-based analysis module for quick and reliable parallel-distributed processing of the massive amount of log data. Furthermore, because the HDFS (Hadoop Distributed File System) stores data by generating copies of the block units of the aggregated log data, the proposed system offers automatic restore functions for the system to continually operate after it recovers from a malfunction. Finally, by establishing a distributed database using the NoSQL-based Mongo DB, the proposed system provides methods of effectively processing unstructured log data. Relational databases such as the MySQL databases have complex schemas that are inappropriate for processing unstructured log data. Further, strict schemas like those of relational databases cannot expand nodes in the case wherein the stored data are distributed to various nodes when the amount of data rapidly increases. NoSQL does not provide the complex computations that relational databases may provide but can easily expand the database through node dispersion when the amount of data increases rapidly; it is a non-relational database with an appropriate structure for processing unstructured data. The data models of the NoSQL are usually classified as Key-Value, column-oriented, and document-oriented types. Of these, the representative document-oriented data model, MongoDB, which has a free schema structure, is used in the proposed system. MongoDB is introduced to the proposed system because it makes it easy to process unstructured log data through a flexible schema structure, facilitates flexible node expansion when the amount of data is rapidly increasing, and provides an Auto-Sharding function that automatically expands storage. The proposed system is composed of a log collector module, a log graph generator module, a MongoDB module, a Hadoop-based analysis module, and a MySQL module. When the log data generated over the entire client business process of each bank are sent to the cloud server, the log collector module collects and classifies data according to the type of log data and distributes it to the MongoDB module and the MySQL module. The log graph generator module generates the results of the log analysis of the MongoDB module, Hadoop-based analysis module, and the MySQL module per analysis time and type of the aggregated log data, and provides them to the user through a web interface. Log data that require a real-time log data analysis are stored in the MySQL module and provided real-time by the log graph generator module. The aggregated log data per unit time are stored in the MongoDB module and plotted in a graph according to the user's various analysis conditions. The aggregated log data in the MongoDB module are parallel-distributed and processed by the Hadoop-based analysis module. A comparative evaluation is carried out against a log data processing system that uses only MySQL for inserting log data and estimating query performance; this evaluation proves the proposed system's superiority. Moreover, an optimal chunk size is confirmed through the log data insert performance evaluation of MongoDB for various chunk sizes.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.6
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• pp.373-380
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• 2022

Today, customer satisfaction is the most important issue for Vietnamese banks. There are numerous factors that influence bank customers' satisfaction. The study investigates the factors that influence customer satisfaction with deposit services at the Vietnam Bank for Agriculture and Rural Development (Agribank) in Bac Giang province, Vietnam, and analyses the impact of each component. The authors used 5-point Likert scales to assess whether elements were related to the factors determining consumer satisfaction with Agribank's deposit service. To perform this study, exploratory factor analysis (EFA) and multiple regression were used to find factors determining customer satisfaction with Agribank services. Customers that use deposit services at Agribank in Bac Giang province, Vietnam, provided samples of 300 survey questionnaires for this study. SPSS software is used to examine the data. Customers' satisfaction with Agribank's deposit service is influenced by six factors, including reliability, responsiveness, service capabilities, empathy, tangible means, and service price, according to the study. This finding also offers some recommendations for improving service quality in local Vietnamese banks to gain a competitive advantage.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.3
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• pp.289-300
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• 2010

Recently, diverse information which are location, call history, SMS history, photographs, and video can be collected constantly from mobile devices such as cellular phone, smart phone, and PDA. There are many researchers who study services for searching and abstraction of personal daily life with contextual information in mobile environment. In this paper, we introduce MyLifeBrowser which is developed in our previous work. Also, we explain LPS and correction of GPS coordinates as extensions of previous work and show LPS performance test and evaluate the performance of expanded keywords. MyLifeBrowser which provides searching personal information in mobile device and support of detecting related information according to a fragmentary keyword and common knowledge in ConceptNet. It supports the functionality of searching related locations using Bayesian network that is designed by the authors. In our experiment, we visualize real data through MyLifeBrowser and show the feasibility of LPS server and expanded keywords using both Bayesian network and ConceptNet.