• The Journal of Bigdata
• /
• v.1 no.1
• /
• pp.85-94
• /
• 2016

Traditional Anti-Money Laundering (AML) software applications monitor bank customer transactions on a daily basis using customer historical information and account profile data to provide a "whole picture" to bank management. With the advent of Big Data, these applications could be benefited from size, variety, and speed of unstructured data, which have not been used in AML applications before. This study analyses the weaknesses of a bank's current AML systems and proposes an AML systems taking advantage of Big Data. For example, early warning of AML risk can be improved by exposing identities and uncovering hidden relationships through predictive and entity analytics on real-time and outside data such as SNS data.

• Journal of Digital Contents Society
• /
• v.19 no.2
• /
• pp.377-383
• /
• 2018

Internet of Things (IoT) is producing various data as the smart environment comes. The IoT data collection is used as important data to judge systems's status. Therefore, it is important to monitor the anomaly state of the sensor in real-time and to detect anomaly data. However, it is necessary to convert the IoT data into a normalized data structure for anomaly detection because of the variety of data structures and protocols. Thus, we can expect a good quality effect such as accurate analysis data quality and service quality. In this paper, we propose an anomaly detection system based on big data from collected sensor data. The proposed system is applied to ensure anomaly detection and keep data quality. In addition, we applied the machine learning model of support vector machine using anomaly detection based on time-series data. As a result, machine learning using preprocessed data was able to accurately detect and predict anomaly.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.51 no.7
• /
• pp.149-154
• /
• 2014

Modern data computing developments have led to big improvements in graphic capabilities and there are many new possibilities for data displays. The visualization has proven effective for not only presenting essential information in vast amounts of data but also driving complex analyses. Big-data analytics and discovery present new research opportunities to the computer graphics and visualization community. In this paper, we discuss the patent analysis of big data visualization technology development in major countries. Especially, we analyzed 160 patent applications and registered patents in four countries on November 2012. According to the result of analysis provided by this paper, the text clustering analysis and 2D visualization are important and urgent development is needed to be oriented. In particular, due to the increase of use of smart devices and social networks in domestic, the development of three-dimensional visualization for Big Data can be seen very urgent.

• The Journal of Korean Association of Computer Education
• /
• v.23 no.1
• /
• pp.77-90
• /
• 2020

The purpose of the study is to provide educational implications for more effective Problem-based learning(PBL) by investigating students' learning types based on their online learning behaviors. A total of 1,341 students participated in the study, and they engaged in a six-week-long PBL program run by K University. For the study, participants' online activity data were collected. From the data, a total of 48 variables that represent their various online learning behaviors were extracted. Based on the variables, hierarchical cluster analysis was conducted to analyze learning types. Also, the differences in learning characteristics and achievements were investigated by considering types of learning. As a result, the learning types in online PBL were classified as 'high-level participation (cluster 1)', 'medium-level participation (cluster 2)', and 'low-level participation (cluster 3)'. In addition, the achievement level was found to be highest in 'high-level participation (cluster 1)' and lowest in 'low-level participation (cluster 3)'. Based on the results, the implications for improving online PBL were suggested.

• Annals of Clinical Neurophysiology
• /
• v.22 no.2
• /
• pp.92-103
• /
• 2020

Background: The purpose of this study was to identify the top-100 cited articles on genetic generalized epilepsy (GGE) published in journals that have made key contributions to the field of epilepsy. Methods: We searched the Web of Science website produced by Clarivate Analytics for articles on GGE, and sorted them according to the number of citations to identify the top-100 cited articles. We then manually reviewed the contents of the top-100 cited articles, which were designated as "citation classics". Results: The top-100 cited articles were published in 27 journals, with the largest proportion appearing in Epilepsia (19 articles). The articles originated from institutions in 17 countries, with 31 articles from the USA. The institution associated with the largest numbers of articles in the field of GGE was the University of Melbourne, Australia (9 articles). Panayiotopoulos C. P. was the first author of three articles, and was listed most frequently in the GGE citation classics. The publication years were concentrated in the 2000s, when 56 articles were published. The most-common study topics were genetics (35 articles) and neuroimaging (17 articles). Conclusions: This study has identified the top-100 cited articles on GGE. These citation classics represent the landmark articles on GGE, and they provide useful insights into international research leaders and the research trends in the field.

• Korean Journal of Construction Engineering and Management
• /
• v.18 no.5
• /
• pp.20-31
• /
• 2017

As global interests in the 4th Industrial Revolution have recently increased, it becomes critical for the construction industry to pro-actively cope with it. For effective actions, the construction industry needs to make active use of 4th Industrial Revolution technologies based on the up-to-date understanding of the trends of construction technology development employing the 4th Industrial Revolution technologies. The objective of the study is to investigate and identify key trends of ICT construction technology development over the last ten years based on Big Data Analytics. The study identifies eleven key trends and discusses that ICT construction technology development has not been as active as expected and software technologies have been less developed compared to hardware technologies.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.33 no.12B
• /
• pp.1123-1130
• /
• 2008

Baby's diseases diagnosis has inconvenient for received direct coming to help that order expression ability was insufficiency which consciousness situation concern about the infant health because of birth rate and decrease the marriage rate and divorce rate. So in this paper through the infant crying sound about home a foundation which infant diseases develop the system comparison normal infant with take a infant that analysis the extract the voice analytics component. Especially this paper propose about the methodology for development system that infant cold, infant pneumonia, infant asthma among extract the crying sound feature part for infant respiratory diseases discussion the most easy has involved the infant. So infant respiratory put case stimulus diseases about all voice organs and experiment the analysis method through the bandwidth about phonetics analysis component that comparison normal infant with take a respiratory infant. Through these method, we were extracted to results that infant's frequency bandwidth suffering from respiratory diseases than a normal infant is short.

• Proceedings of the KIEE Conference
• /
• 2007.07a
• /
• pp.127-129
• /
• 2007

Since the competitive market environment was introduced into the electric power industry, the structure of the industry has been changing from vertically integrated system to functionally unbundled and decentralized system composed of multiple (decision-making) market participants. So the market participants such as Gencos or LSE (load serving entity) need to forecast the market clearing price and thus build their offer or bidding strategies. Not just these market players but also a market operator is required to perform market analysis and ensure simulation capability to manage and monitor the competitive electricity market. For fulfilling the demand for market simulation, many global venders like GE, Henwood, Drayton Analytics, CRA, etc. have developed and provided electricity market simulators. Most of these simulators are based on the optimization formulation which has been used mainly for the least cost resource planning in the centralized power system planning and operation. From this standpoint, it seems somehow inevitable to face many challenges on modeling competitive market based on the method of traditional market simulators. In this paper, we propose a kind of new method, which is MAS based market simulation. The agent based model has already been introduced in EMCAS, one of commercial market simulators, but there may be various ways of modeling agent. This paper, in particular, seeks to introduce an model for MAS based market simulator.

• Journal of Evidence-Based Herbal Medicine
• /
• v.3 no.1
• /
• pp.1-7
• /
• 2010

While herbal medicine including mineral herbal medicine mostly provides microelements to the human body thanks to abundant metallic elements, its harmfulness has been raised due to elements of heavy metals. Harmfulness of mineral herbal medicine needs to be analyzed quantitatively as well as qualitatively so that specificity of herbal medicine including mineral herbal medicine can be reflected. Consequently, the following aims should be set up to mineral herbal medicine, REALGAR, standard processing of REALGAR and the standards of processed drugs should be secured. On the basis of the results of this study, the reasonable measures to develop the processing method and the test method for heavy metals were presented. Such measures are expected to give the following results. First, consumers may take food and medicine without anxiety, and food and medicine may be effectively managed, and the national service may be improved, and also safety against heavy metals may be publicized. Second, as the principal ingredients and microelements of mineral herbal medicine are qualitatively analyzed, such results are expected to contribute to the advance of national analytics for herbal medicine.

• Journal of Convergence for Information Technology
• /
• v.11 no.9
• /
• pp.214-220
• /
• 2021

With the rapid spread of smartphones, it has become common to listen to music everywhere, just like background music in life, so it is necessary to create a music database that can make recommendations according to individual circumstances and conditions. This paper proposes a music recommendation model through social media. Since emotions, situations, time of day, weather, etc. are included in hashtags, it is possible to build a social media-based database that reflects the opinions of various people with collective intelligence. We use web crawling to collect and categorize different hashtags from posts with music title hashtags to use real listeners' opinions about music in a database. Data from social media is used to create a music database, and music is classified in a different way from collaborative filtering, which is mainly used by existing music platforms.