• Journal of Intelligence and Information Systems
• /
• v.25 no.1
• /
• pp.85-107
• /
• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.33 no.4
• /
• pp.287-296
• /
• 2015

Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.2
• /
• pp.291-298
• /
• 2012

Objective: The aim of this study is to predict Korean text entry on touchscreens using ACT-R cognitive architecture. Background: Touchscreen application in devices such as satellite navigation devices, PDAs, mobile phones, etc. has been increasing, and the market size is expanding. Accordingly, there is an increasing interest to develop and evaluate the interface to enhance the user experience and increase satisfaction in the touchscreen environment. Method: In this study, Korean text entry performance in the touchscreen environment was analyzed using ACT-R. The ACT-R model considering the characteristics of the Korean language which is composed of vowels and consonants was established. Further, this study analyzed if the prediction of Korean text entry is possible through the ACT-R cognitive model. Results: In the analysis results, no significant difference on performance time between model prediction and empirical data was found. Conclusion: The proposed model can predict the accurate physical movement time as well as cognitive processing time. Application: This study is useful in conducting model-based evaluation on the text entry interface of the touchscreen and enabled quantitative and effective evaluation on the diverse types of Korean text input interfaces through the cognitive models.

• Transactions of Materials Processing
• /
• v.20 no.1
• /
• pp.11-16
• /
• 2011

Recently, according to the rapid development of display, many display applications, such as, cellular phone, navigation, monitor and LCD TV have been changed from CRT type to LCD type. BLU(Back Light Unit) is one of main parts in LCD unit and generally, it consists of a light source, a reflective sheet, a LGP(Light Guide Plate), a diffuser sheet, and two prism sheets. The most important component of BLU is a light guide plate, which diffuses the input light to the TFT-LCD module uniformly. The LGP is usually made by injection molding process, and it has numerous optical micro patterns on the surface. In the present study the micro-patterned stamper which has cylindrical shape was fabricated by using the UV-LiGA process. And the replication characteristics have been compared among three different kinds of injection molding process; general injection molding, injection/compression molding and RHCM(Rapid Heating and Cooling Molding). Average replication ratios of CIM and ICM were 19.1% and 64.6%, respectively. On the other hand, the average replication ratio of RHCM process showed the higher value of 98.4% among these. It show that maintaining the mold surface above $T_g$ could increase the replication ratio of micro patterns substantially.

• Journal of Electrical Engineering and Technology
• /
• v.6 no.6
• /
• pp.806-816
• /
• 2011

Interest about social security has recently increased in favor of safety for infrastructure. In addition, advances in computer vision and pattern recognition research are leading to video-based surveillance systems with improved scene analysis capabilities. However, such video surveillance systems, which are controlled by human operators, cannot actively cope with dynamic and anomalous events, such as having an invader in the corporate, commercial, or public sectors. For this reason, intelligent surveillance systems are increasingly needed to provide active social security services. In this study, we propose a core technique for intelligent surveillance system that is based on swarm robot technology. We present techniques for invader enclosing using swarm robots based on multiple distributed object environment. The proposed methods are composed of three main stages: location estimation of the object, specified object tracking, and decision of the cooperative behavior of the swarm robots. By using particle filter, object tracking and location estimation procedures are performed and a specified enclosing point for the swarm robots is located on the interactive positions in their coordinate system. Furthermore, the cooperative behaviors of the swarm robots are determined via the result of path navigation based on the combination of potential field and wall-following methods. The results of each stage are combined into the swarm robot-based invader-enclosing technique on multiple distributed object environments. Finally, several simulation results are provided to further discuss and verify the accuracy and effectiveness of the proposed techniques.

• The Korean Journal of Applied Statistics
• /
• v.22 no.6
• /
• pp.1177-1190
• /
• 2009

The traffic operating speed is one of important information to measure a road capacity. When we supply the information of the road of high traffic by using navigation, offering the present traffic information and the forecasted future information are the outstanding functions to serve the more accurate expected times and intervals. In this study, we proposed the traffic speed forecasting model using the accumulated traffic speed data of the road and highway and forecasted the average speed for each the road and high interval and each time interval using Fourier transformation and time series regression model with trigonometrical function. We also propose the proper method of missing data imputation and treatment for the outliers to raise an accuracy of the traffic speed forecasting and the speed grouping method for which data have similar traffic speed pattern to increase an efficiency of analysis.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.36S no.12
• /
• pp.10-19
• /
• 1999

Cellular Automata Neural Systems(CANS) are neural networks based on biological development and evolution. Each neuron of CANS has local connection and acts as a form of pulse according to the dynamics of the chaotic neuron. CANS are generated from initial cells according to the CA rule. In the previous study, to obtain the useful ability of CANS, we make the pattern of initial cells evolve. However, it is impossible to represent all solution space, so we propose an evolving method of CA rule to overcome this defect in this paper. DNA coding has the redundancy and overlapping of gene and is apt for the representation of the rule. In this paper, we show the general expression of CA rule and propose translation method from DNA code to CA rule. The effectiveness of the proposed scheme was verified by applying it to the navigation problem of autonomous mobile robot.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.27 no.12
• /
• pp.1053-1058
• /
• 2016

The eLoran(enhanced Long Range Navigation) transmitting antenna is analyzed for co-location with an AM transmitting antenna in an MF transmitting site. To compensate for the loading effect, the umbrella-type loading is applied for eLoran antenna. The validity of the co-location between the MF antenna and the eLoran antenna is verified through the simulation results of the radiation pattern and the return loss. Also, coupling including antenna matching circuit is analyzed to verify the effect of the transmitting circuit. The coupling between the LF and eLoran antenna is -53.3 dB at 100 kHz and -64.8 dB at 1,053 kHz, respectively.

• The Journal of the Acoustical Society of Korea
• /
• v.39 no.4
• /
• pp.279-285
• /
• 2020

The study on the temporal and spatial monitoring of passing vessels is important in terms of protection and management the marine ecosystem in the coastal area. In this paper, we propose the automatic detection technique of passing vessel by utilizing an artificial intelligence technology and broadband striation patterns which are characteristic of broadband noise radiated by passing vessel. Acoustic measurements to collect underwater noise spectrum images and ship navigation information were conducted in the southern region of Jeju Island in South Korea for 12 days (2016.07.15-07.26). And the convolution neural network model is optimized through learning and validation processes based on the collected images. The automatic detection performance of passing vessel is evaluated by precision (0.936), recall (0.830), average precision (0.824), and accuracy (0.949). In conclusion, the possibility of the automatic detection technique of passing vessel is confirmed by using an artificial intelligence technology, and a future study is proposed from the results of this study.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.25 no.6
• /
• pp.628-636
• /
• 2014

This paper describes the design and analysis of five-element planar array antenna of an anti-jamming satellite navigation system. We propose a design of multi-layer patch antenna for Global Positioning System(GPS) $L_1/L_2$ dual bands. The proposed antenna has two ports feeding network with a hybrid chip coupler for a broad bandwidth with Right-Handed Circular Polarization(RHCP). The measurement results show the bore-sight gains of 1.10 dBic($L_1$) and 0.37 dBic($L_2$) for the center element. The bore-sight gains of an edge element are 0.99 dBic($L_1$) and -0.57 dBic($L_2$). At a fixed elevation angle of $30^{\circ}$, antennas show average gains of -2.08 dBic ($L_1$) and -5.33 dBic($L_2$) for the center element, and average gains of -0.40 dBic($L_1$) and -2.09 dBic($L_2$) for the edge elements. The results demonstrate that the proposed array antenna is suitable for anti-jamming applications.