• International journal of advanced smart convergence
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• v.10 no.3
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• pp.41-50
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• 2021

The purpose of this study is to analyze various energy platforms using data in the US and to suggest directions and implications. Some of the leading energy platforms are selected and analyzed based on the opening platform model. We focus on the case analysis of the US utility companies. In case of the horizontal open platform, Green Button sponsor's 'Connect My Data (CMD)' driven by the government invites the utility companies to jointly develop the sponsor's data solution. In case of the vertical open platform, the certification program 'Share My Data (SMD)' allows backward compatibility, because the technical improvement is minimal. The utility companies benchmark Amazon's three-sided market mediation and prefer platform and category exclusivity. For the former, they have data analytics companies like Enervee, Opower and for the latter, they have electronics manufactures and energy service providers (ESPs) like Distributed Energy Resources (DERs). Based on this US case study, we suggest the energy platforms to open their platform for renewable energy supply, energy conservation, high-efficiency products, and residential DER dissemination. To successfully implement the government's energy transition policy, the US platforms should be benchmarked as a business model. Especially, it is needed for them to coordinate a platform ecosystem. To ensure trust in the products and services offered on the marketplace platform, platform's certification program is helpful.

• Journal of Arbitration Studies
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• v.31 no.2
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• pp.119-135
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• 2021

South Korea has the most advanced technology in the Fourth Industrial Revolution era because of its high-speed Internet commercialization. However, the industry is shrinking due to its various regulations in building and its utilization of personal information as big data. Currently, South Korea's personal data utilization business is in its early stages. In the era of the 4th Industrial Revolution, it is difficult for startups to use data. There are various causes here. Above all, legal regulations to protect personal information are emphasized. This study confirms that transactions of personal medical records through My Data can be made. Moreover, it confirms that there is a need for a mediating role between stakeholders. This study lacks statistical access in the process of performing stakeholder roles. However, personal medical records will be traded safely in the future, and new subjects will enter the market. Furthermore, the domestic bio-industry will develop. Through this study, various problems were derived in establishing Medical MyData in Korea. Moreover, it looks forward to continuing various studies in the health care sector in the future.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.1
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• pp.255-259
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• 2016

Background: Reliable and validated instruments are needed in order to study the quality of life in myeloma patients. This study aimed to translate and explore the psychometric properties of the European Organisation for Research and Treatment of Cancer (EORTC) myeloma module (QLQ-MY20) in Iranian patients. Materials and Methods: Two hundred and fifteen patients with multiple myeloma (MM) were recruited from Imam Khomeini Hospital, Tehran. A standard forward-backward translation procedure was implemented. Participating patients were asked to complete the EORTC QLQ-C30 and the QLQ-MY20 three times, at study entry, after two weeks, and again after three months. Data were tested for the range of measurement, internal consistency, test-retest reliability, known group comparison, responsiveness and factor structure. Results: Mean age of the patients was 60.7 years. No floor and ceiling effects were seen for the QLQ-MY20. Cronbach's ${\alpha}$ was greater than 0.80 for all three multi-item scales (ranging from 0.82 to 0.93). All four scales had test-retest reliability of 0.85 or greater. Results of the confirmatory factor analysis that the hypothesized 3-scale measurement model of the QLQ-MY20. Moreover, the Persian version for the QLQ-MY20 differentiated between subgroups of the patients in terms of beta-2 microglobulin, fracture and performance status. The responsiveness of the QLQ-MY20 to change over time was confirmed within 3 months. Conclusions: the results of our study indicate that our Iranian version of the QLQ-MY20 is a feasible, reliable and valid questionnaire for assessing the condition-specific quality of life of patients with MM.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.2
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• pp.175-181
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• 2006

Wireless sensor network forms the self-organization network, and transfers the information among sensor nodes that have computing technology ability and wireless communication ability. The recent sensor network is study for low-power, micro, low cost of node is proceeded. Recently, the research of application services in wireless sensor networks is proceeded. Therefore, in this paper, we design the prototype of the real-time information service that support a user the information of temperature, illumination etc. And, we implement the alarm application service fer the disaster prevention on Internet base on IPv4/IPv6. We develop the module of the extract information using the query processing based on TinyOS, and the module of the server's database using MySQL data base management system and JDBC. Additionally, we develop the client module that receive the real-time sensing data using ODBC in Internet based on IPv4/IPv6.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.207-213
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• 2022

MBTI(Myer Briggs Type Indicator) is an effective personality type test to intuitively identify and classify people's tendencies. Accordingly, there are active attempts to apply MBTI to the learning area, but research on creating new learning types using MBTI is insufficient. Therefore, this paper examines the factors that affect learning and implements new learning types MY,STI(MY, Study Type Indicator) by applying them to a machine learning algorithm that has these characteristics. Data were collected by conducting a learning type test made with Google Forms on 144 general people, and supervised learning was used during machine learning. As a result, the accuracies of MY,STI were 0.933, 0.866, 0.844, and 0.733 for each learning method, learning motivation, presence or absence of external stimulus, and learning time criteria, respectively.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.123-131
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• 2021

The Fourth Industrial Revolution was triggered by data-driven digital technologies such as AI and big data. There is a rapid movement to expand the scope of data utilization to the privacy area, which was considered only a protected area. Through the revision of the Data 3 Act, laws and systems were established that allow personal information to be freely transferred and utilized under their consent. But, it will be necessary to support the platform that encompasses the entire process from collecting personal information to managing and utilizing it. In this paper, we propose a platform model that can be applied to building mydata ecosystem using personal information. It describes the six essential functional requirements for building MyData platforms and the procedures and methods for implementing them. The six proposed essential features describe consent, sharing/downloading/ receipt of data, data collection and utilization, user authentication, API gateway, and platform services. We also illustrate the case of applying the MyData platform model to real-world, underprivileged mobility support services.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.12
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• pp.487-496
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• 2017

In MySQL InnoDB, there are two ways of storing data. One is to create a separate tablespace for each table and store it separately. Another is to store all table and index information in a single system tablespace. You can use this information to recover deleted data from the record. However, in most of the current database forensic studies, the former is actively researched and its structure is analyzed, whereas the latter is not enough to be used for forensics. Both approaches must be analyzed in terms of database forensics because their storage structures are different from each other. In this paper, we propose a method for recovering deleted records in a method of storing records in IBDATA file, which is a single system tablespace. First, we analyze the IBDATA file to reveal its structure. And introduce delete record recovery algorithm which extended to an unallocated page area which was not considered in the past. In addition, we show that the recovery rate is improved up to 68% compared with the existing method through verification using real data by implementing the algorithm as a tool.

• 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.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.195-200
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• 2002

We consider the Bernoulli two-armed bandit problem. It is well known that the my optic strategy is optimal when the prior distribution is concentrated at two points in the unit square. We investigate several cases in the unit square whether the my optic strategy is optimal or not. In general, the my optic strategy is not optimal when the prior distribution is not concentrated at two points in the unit square.

• The Mathematical Education
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• v.45 no.2 s.113
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• pp.177-189
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• 2006

This study focuses on the analysis of prospective elementary teachers' representation of trapezoid area and teacher educator's reflecting in the context of a mathematics course. In this study, I use my own teaching and classroom of prospective elementary teachers as the site for investigation. 1 examine the ways in which my own pedagogical content knowledge as a teacher educator influence and influenced by my work with students. Data for the study is provided by audiotape of class proceeding. Episode describes the ways in which the mathematics was presented with respect to the development and use of representation, and centers around trapezoid area. The episode deals with my gaining a deeper understanding of different types of representations-symbolic, visual, and language. In conclusion, I present two major finding of this study. First, Each representation influences mutually. Prospective elementary teachers reasoned visual representation from symbolic and language. And converse is true. Second, Teacher educator should be prepared proper mathematical language through teaching and learning with his students.