• The Journal of Bigdata
• /
• v.7 no.1
• /
• pp.213-224
• /
• 2022

In logistics and distribution, Market Basket Analysis (MBA) is used as an important means to analyze the correlation between major sales products and to increase internal operational efficiency. In particular, the results of market basket analysis are used as important reference data for decision-making processes such as product purchase prediction, product recommendation, and product display structure in stores. With the recent development of e-commerce, the number of items handled by a single distribution and logistics company has rapidly increased, And the existing analytical methods such as Apriori and FP-Growth have slowed down due to the exponential increase in the amount of calculation and applied to actual business. There is a limit to examining important association rules to overcome this limitation, In this study, at the Main-Category level, which is the highest classification system of products, the utility item set mining technique that can consider the sales volume of products together was used to first select a group of products mainly sold together. Then, at the sub-category level, the types of products sold together were identified using FP-Growth. By using this sequential layer filtering technique, it may be possible to reduce the unnecessary calculations and to find practically usable rules for enhancing the effectiveness and profitability.

• International Journal of Highway Engineering
• /
• v.7 no.4 s.26
• /
• pp.151-162
• /
• 2005

Variable Message Sign (VMS), which provides drivers with direct information about state of traffic congestion and for prevent an accident, is the most effective method among the methods of providing information in Advanced Transportation Management System. Currently establishment and the VMS which is operated foundation lets in Guidelines on the use of Variable message sign (a book of the VMS) of 1999 November the Ministry Construction & Transportation, these contents mean main viewpoint on physical part such as message special quality variable (font, character size and line space, word interval) and position mainly among standard about establishment in general. But, it is true that using without effect verification on the character of VMS display and that using mode of stationary-centered. In this paper, it executed significance test to effort verification on the character of VMS display for more practical and effective information transmission based on the driver viewpoint For the researches; develop 3D-Simulation, select characteristics of driver's visual cognition behavior (the conspicuity, the legibility and the comprehensibility), evaluation each issue (day or night, 80km/h or 100km/h). Especially, that used the Eye Marker Recorder to measure of reading-time (legibility) thus, confirmed objectivity and reduce an observational error. The results showed that the conspicuity is Flashing> Stationary>Scroll. The legibility is not deference that Flashing between stationary form. Also the comprehensibility result showed that Flashing> Stationary>Stroll form.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_2
• /
• pp.1651-1669
• /
• 2023

Sea ice currently covers approximately 7% of the world's ocean area, primarily concentrated in polar and high-altitude regions, subject to seasonal and annual variations. It is very important to analyze the area and type classification of sea ice through time series monitoring because sea ice is formed in various types on a large spatial scale, and oil and gas exploration and other marine activities are rapidly increasing. Currently, research on the type and area of sea ice is being conducted based on high-resolution satellite images and field measurement data, but there is a limit to sea ice monitoring by acquiring field measurement data. High-resolution optical satellite images can visually detect and identify types of sea ice in a wide range and can compensate for gaps in sea ice monitoring using Geostationary Ocean Color Imager-II (GOCI-II), an ocean satellite with short time resolution. This study tried to find out the possibility of utilizing sea ice monitoring by training a rule-based machine learning model based on learning data produced using high-resolution optical satellite images and performing detection on GOCI-II images. Learning materials were extracted from Liaodong Bay in the Bohai Sea from 2021 to 2022, and a Random Forest (RF) model using GOCI-II was constructed to compare qualitative and quantitative with sea ice areas obtained from existing normalized difference snow index (NDSI) based and high-resolution satellite images. Unlike NDSI index-based results, which underestimated the sea ice area, this study detected relatively detailed sea ice areas and confirmed that sea ice can be classified by type, enabling sea ice monitoring. If the accuracy of the detection model is improved through the construction of continuous learning materials and influencing factors on sea ice formation in the future, it is expected that it can be used in the field of sea ice monitoring in high-altitude ocean areas.

• Journal of Intelligence and Information Systems
• /
• v.20 no.3
• /
• pp.93-108
• /
• 2014

To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.

• Journal of Korean Society of Forest Science
• /
• v.64 no.1
• /
• pp.52-63
• /
• 1984

This study was intended to identify 17 taxa. (5 varieties and 12 species) of the genus Acer in Korea on the basis of the shapes of stomata, the type of trichome on the different part of leaves, the shapes, arrangement and number of stele in cross section of petiole. The results obtained were summarized as follows; 11 The shape of guard cells of stomata in the genus Acer was anomcytical, and the size of the cells ranged from 10.25 to $21.00{\mu}$ in length and from 7.57 to $11.83{\mu}$ in width. 2) Eleven types of trichome on the leaf in the genus Acer were found; pilose, sericeous, velutinous, woolly, glabrate, puberulent, bladder hair, hispid, hirsute and uncinate. This characteristics also established a good criterion for identification of species. 3) The stele of petiole in the genus Acer was characterized by eustele and atactostele with polybranch, and the six groups of the shape of numerical change of stele; B>M=T, BM

• 한국지구물리탐사학회:학술대회논문집
• /
• 2004.08a
• /
• pp.104-117
• /
• 2004

Dmitri Donskoi, which went down during the Russo-Japanese War occurred 100 years ago, was found by using geophysical exploration techniques at the 400 m water depth of submarine valley off Jeodong of Ulleung Island. In the submarine area with the rugged seabed topography and volcanic seamounts, in particular, the reliable seabed images were acquired by using the mid-to-shallow Multibeam exploration technique The strength of corrosion (causticity) of the sunken Donskoi, measured by the electrochemical method, decreased to 2/5 compared with the original strength.

• The KIPS Transactions:PartD
• /
• v.13D no.7 s.110
• /
• pp.985-996
• /
• 2006

As the internet technologies develop, the geographic information system environment is changing to the web-based service. Since geospatial information of the existing Web-GIS services were developed independently, there is no interoperability to support diverse map formats. In spite of the same geospatial information object it can be used for various proposes that is duplicated in GIS separately. It needs intelligent strategies for optimal replica selection, which is identification of replication geospatial information objects. And for management of replication objects, OMG, GLOBE and GRID computing suggested related frameworks. But these researches are not thorough going enough in case of geospatial information object. This paper presents a model of location service, which is supported for optimal selection among replication and management of replication objects. It is consist of tree main services. The first is binding service which can save names and properties of object defined by users according to service offers and enable clients to search them on the service of offers. The second is location service which can manage location information with contact records. And obtains performance information by the Load Sharing Facility on system independently with contact address. The third is intelligent selection service which can obtain basic/performance information from the binding service/location service and provide both faster access and better performance characteristics by rules as intelligent model based on rough sets. For the validity of location service model, this research presents the processes of location service execution with Graphic User Interface.