• Journal of KIISE:Software and Applications
• /
• v.28 no.2
• /
• pp.179-191
• /
• 2001

Comparison shopping is a merchant brokering process that finds the best price for the desired product from several Web-based online stores. To get a scalable comparison shopper, we need an agent that automatically constructs a simple information extraction procedure, called a wrapper, for each semi-structured store. Automatic construction of wrappers for HTML-based Web stores is difficult because HTML only defines how information is to be displayed, not what it means, and different stores employ different ways of manipulating customer queries and different presentation formats for displaying product descriptions. Wrapper induction has been suggested as a promising strategy for overcoming this heterogeneity. However, previous scalable comparison-shoppers such as ShopBot rely on a strong bias in the product descriptions, and as a result, many stores that do not confirm to this bias were unable to be recognized. This paper proposes a more scalable comparison-shopping agent named MORPHEUS. MORPHEUS presents a simple but robust inductive learning algorithm that antomatically constructs wrappers. The main idea of the proposed algorithm is to recognize the position and the structure of a product description unit by finding the most frequent pattern from the sequence of logical line information in output HTML pages. MORPHEUS successfully constructs correct wtappers for most stores by weakening a bias assumed in previous systems. It also tolerates some noises that might be present in production descriptions such as missing attributes. MORPHEUS generates the wrappers rapidly by excluding the pre-processing phase of removing redundant fragments in a page such as a header, a tailer, and advertisements. Eventually, MORPHEUS provides a framework from which a customized comparison-shopping agent can be organized for a user by facilitating the dynamic addition of new stores.

• Journal of Nutrition and Health
• /
• v.53 no.3
• /
• pp.255-270
• /
• 2020

Purpose: The purpose of this study was to identify the factors that influence the consumption of convenience foods among Korean adolescents. Methods: This study had a descriptive cross-sectional study. Data were obtained from the 15th (2019) Korea Youth Risk Behavior Web-based Survey, which involved a nationwide representative sample of 57,303 middle- and high-school students. Convenience-food consumption was defined by frequency of adolescents consuming convenience foods obtained from convenience stores, supermarkets, and cafeterias over the previous 7 days. The analyzed variables were related to sociodemographic, mental health, and health behavior. The Rao-Scott χ² test was applied to examine the difference in the rate of consuming convenience foods obtained from convenience stores according to each factor. Hierarchical logistic regression was conducted to examine the factors that influence convenience-food consumption among Korean adolescents. Results: It was found that 29.1% of Korean adolescents consumed convenience foods obtained from convenience store more than three times per week. The significant influencing factors were female sex; low subjective academic achievement, and subjective household economic status; high perceived stress; low subjective sleep sufficiency; experience of depression; suicidal ideation; lower physical activity; skipping breakfast; lower consumptions of fruit, milk, and vegetables; higher consumptions of soda drinks, sweet drinks, caffeine, and fast food; lower water intake; current smoking and drinking; drug use; and experience of violence. Conclusion: These findings provide a better understanding of the sociodemographic, mental-health, and health-behavior factors that influence the consumption of convenience foods among Korean adolescents. We suggest that differentiated policies, strategies, and nutrition education need to be developed and implemented, in order to address the above-mentioned factors and thereby reduce such behaviors among Korean adolescents.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.11 no.1
• /
• pp.41-54
• /
• 2013

Radionuclide sorption data is necessary for the safety assessment of radioactive waste disposal. However the use of sorption database is often limited due to the accessability. A web-based sorption database program named KAERI-SDB has been developed to provide information on the sorption of radionuclides onto geological media as a function of geochemical conditions. The development of KAERI-SDB was achieved by improving the performance of pre-existing sorption database program (SDB-21C) developed in 1998 and considering user's requirements. KAERI-SDB is designed that users can access it by using a web browser. Main functions of KAERI-SDB include (1) log-in/member join, (2) search and store of sorption data, and (3) chart expression of search results. It is expected that KAERI-SDB could be widely utilized in the safety assessment of radioactive waste disposal by enhancing the accessibility to users who wants to use sorption data. Moreover, KAERI-SDB opened to public would also improve the reliability and public acceptance on the radioactive waste disposal programs.

• Science of Emotion and Sensibility
• /
• v.12 no.4
• /
• pp.433-442
• /
• 2009

People are tending to buy products through the Internet rather than purchasing them from the store. Some of the consumers give their feedback on line such as reviews, replies, comments, and blogs after they purchased the products. People are also likely to get some information through the Internet. Therefore, companies and public institutes have been facing this situation where they need to collect and analyze reviews or public opinions for them because many consumers are interested in other's opinions when they are about to make a purchase. However, most of the people's reviews on web site are too numerous, short and redundant. Under these circumstances, the emotion scanning system of text documents on the web is rising to the surface. Extracting writer's opinions or subjective ideas from text exists labeled words like GI(General Inquirer) and LKB(Lexical Knowledge base of near synonym difference) in English, however Korean language is not provided yet. In this paper, we labeled positive, negative, and neutral attribute at 4 POS(part of speech) which are noun, adjective, verb, and adverb in Korean dictionary. We extract construction patterns of emotional words and relationships among words in sentences from a large training set, and learned them. Based on this knowledge, comments and reviews regarding products are classified into two classes polarities with positive and negative using SO-PMI, which found the optimal condition from a combination of 4 POS. Lastly, in the design of the system, a flexible user interface is designed to add or edit the emotional words, the construction patterns related to emotions, and relationships among the words.

• The KIPS Transactions:PartB
• /
• v.9B no.1
• /
• pp.1-6
• /
• 2002

Many customers consult the Internet before making purchase goods and using contents. The systems in the Internet could store a lot of data and classify the data into information to get relationship between a company and customers. To do that, let's consider a knowledge-assisted hybrid system that utilizes individually a customer's preference to make an optimal solution in the his/her decision making. The knowledge made by using the preference is employed to select an domain set appropriate to him/her business, and the process of selecting definitely provides the customer some benefits: elimination of discomfort from unknown information and reduction of costs and search time for forming an suitable domain set. To effectively adopt individual customer's preference and actively adapt change of business situation, this study propose an architecture of the system which includes rule presentations and an inference engine, and integrates a knowledge-based component into a quadratic programming component. In the experimental results, it is found that a knowledge-assisted hybrid system implemented by this idea is more flexible than existing systems in extension of knowledge about an customer's preference and goes beyond the traditional models.

• Journal of Convergence for Information Technology
• /
• v.8 no.5
• /
• pp.77-83
• /
• 2018

A modular robot that memorizes motion can be easily created and operated because it expresses by hand. However, since there is not enough storage space in the module to store the user-created operation, it is impossible to reuse the created operation, and when the modular robot again memorizes the operation, it changes to another operation. There is no main controller capable of operating a plurality of modular robots at the same time, and thus there is a disadvantage that the user must input directly to the modular robot. To overcome these disadvantages, a remote controller has been proposed that can be operated in the surrounding smart devices by designing web server and component based software using wired and wireless network. In the proposed method, various types of structures are created by connecting to a modular robot, and the reconstructed operation is performed again after storing, and the usefulness is confirmed by regenerating the stored operation effectively. In addition, the reliability of the downloaded trajectory data is verified by analyzing the difference between the trajectory data and the actual trajectory. In the future, the trajectory stored in the remote controller will be standardized using the artificial intelligence technique, so that the operation of the modular robot will be easily implemented.

• The KIPS Transactions:PartA
• /
• v.15A no.1
• /
• pp.53-60
• /
• 2008

Streaming media has contributed to a significant amount of today's Internet Traffic. Like traditional web objects, rich media objects can benefit from proxy caching, but caching streaming media is more of challenging than caching simple web objects, because the streaming media have features such as huge size and high bandwidth. And to support various bandwidth requirements for the heterogeneous ubiquitous devices, a transcoding proxy is usually necessary to provide not only adapting multimedia streams to the client by transcoding, but also caching them for later use. The traditional proxy considers only a single version of the objects, whether they are to be cached or not. However the transcoding proxy has to evaluate the aggregate effect from caching multiple versions of the same object to determine an optimal set of cache objects. And recent researches about multimedia caching frequently store initial parts of videos on the proxy to reduce playback latency and archive better performance. Also lots of researches manage the contents with segments for efficient storage management. In this paper, we define the 9-events of transcoding proxy using 4-atomic events. According to these events, the transcoding proxy can define the next actions. Then, we also propose the segment-based caching policy for the transcoding proxy system. The performance results show that the proposing policy have a low delayed start time, high byte-hit ratio and less transcoding data.

• Journal of KIISE:Computing Practices and Letters
• /
• v.9 no.6
• /
• pp.646-661
• /
• 2003

It is not easy that we visualize the large volume data stored in the every client computers of the web environment. One solution is as follows. First we compress volume data, second store that in the database server, third transfer that to client computer, fourth visualize that with direct-volume-rendering in the client computer. In this case, we usually use wavelet transform for compressing large data. This paper reports the experiments for acquiring the wavelet bases and the compression ratios fit for the above processing paradigm. In this experiments, we compress the volume data Engine, CThead, Bentum into 50%, 10%, 5%, 1%, 0.1%, 0.03% of the total data respectively using Harr, Daubechies4, Daubechies12 and Daubechies20 wavelets, then visualize that with direct-volume-rendering, afterwards evaluate the images with eyes and image comparison metrics. When compression ratio being low the performance of Harr wavelet is better than the performance of the other wavelets, when compression ratio being high the performance of Daubechies4 and Daubechies12 is better than the performance of the other wavelets. When measuring with eyes the good compression ratio is about 1% of all the data, when measuring with image comparison metrics, the good compression ratio is about 5-10% of all the data.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.9
• /
• pp.2093-2099
• /
• 2015

To prevent damage to the cargo, monitoring and remote management for reefer containers is necessary. The currently used remote monitoring service is the Power Cable Transmission(PCT) system, which is recommended by the International Maritime Organization(IMO). However, this system is not widely used because it requires a separate PCT infrastructure and is susceptible to data loss problems. To solve this problem, this study introduces the "IoT-based reefer container management system", The proposed system which is attached to reefer container collects and transmits data on the temperature, status and location of reefer container to middleware using RS-232 communication and WCDMA/GSM communication. Middleware is store the data received in the database and provide information to user in real time through the web and mobile program. At this time, users able to change setting temperature in real time from a distant place through the web program. This study tested by transit about shipment of strawberries to monitor and analyze and check the system's overall effectiveness.

• Journal of Internet Computing and Services
• /
• v.21 no.6
• /
• pp.95-104
• /
• 2020

In this paper, we propose the real time indoor air quality monitoring and controlling platform on cloud using IoT sensor data such as PM10, PM2.5, CO2, VOCs, temperature, and humidity which has direct or indirect impact to indoor air quality. The system is connected to air ventilator to manage and optimize the indoor air quality. The proposed system has three main parts; First, IoT data collection service to measure, and collect indoor air quality in real time from IoT sensor network, Second, Big data processing pipeline to process and store the collected data on cloud platform and Finally, Big data analysis and visualization service to give real time insight of indoor air quality on mobile and web application. For the implication of the proposed system, IoT sensor kits are installed on three different public day care center where the indoor pollution can cause serious impact to the health and education of growing kids. Analyzed results are visualized on mobile and web application. The impact of ventilation system to indoor air quality is tested statistically and the result shows the proper optimization of indoor air quality.