• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.661-683
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• 2001

There is a rapid increase in the use of digital video information in recent years, it becomes more important to manage video databases efficiently. The development of high speed data network and digital techniques has emerged new multimedia applications such as internet broadcasting, Video On Demand(VOD) combined with video data processing and computer. Video database should be construct for searching fast, efficient video be extract the accurate feature information of video with more massive and more complex characteristics. Video database are essential differences between video databases and traditional databases. These differences lead to interesting new issues in searching of video, data modeling. So, cause us to consider new generation method of database, efficient retrieval method of video. In this paper, We propose the construction and generation method of the video database based on contents which is able to accumulate the meaningful structure of video and the prior production information. And by the proposed the construction and generation method of the video database implemented the video database which can produce the new contents for the internet broadcasting centralized on the video database. For this production, We proposed the video indexing method which integrates the annotation-based retrieval and the content-based retrieval in order to extract and retrieval the feature information of the video data using the relationship between the meaningful structure and the prior production information on the process of the video parsing and extracting the representative key frame. We can improve the performance of the video contents retrieval, because the integrated video indexing method is using the content-based metadata type represented in the low level of video and the annotation-based metadata type impressed in the high level which is difficult to extract the feature information of the video at he same time.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.109-115
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• 2015

The new medical device technologies for bio-signal information and medical information which developed in various forms have been increasing. Information gathering techniques and the increasing of the bio-signal information device are being used as the main information of the medical service in everyday life. Hence, there is increasing in utilization of the various bio-signals, but it has a problem that does not account for security reasons. Furthermore, the medical image information and bio-signal of the patient in medical field is generated by the individual device, that make the situation cannot be managed and integrated. In order to solve that problem, in this paper we integrated the QR code signal associated with the medial image information including the finding of the doctor and the bio-signal information. bio-signal. System implementation environment for medical imaging devices and bio-signal acquisition was configured through bio-signal measurement, smart device and PC. For the ROI extraction of bio-signal and the receiving of image information that transfer from the medical equipment or bio-signal measurement, .NET Framework was used to operate the QR server module on Window Server 2008 operating system. The main function of the QR server module is to parse the DICOM file generated from the medical imaging device and extract the identified ROI information to store and manage in the database. Additionally, EMR, patient health information such as OCS, extracted ROI information needed for basic information and emergency situation is managed by QR code. QR code and ROI management and the bio-signal information file also store and manage depending on the size of receiving the bio-singnal information case with a PID (patient identification) to be used by the bio-signal device. If the receiving of information is not less than the maximum size to be converted into a QR code, the QR code and the URL information can access the bio-signal information through the server. Likewise, .Net Framework is installed to provide the information in the form of the QR code, so the client can check and find the relevant information through PC and android-based smart device. Finally, the existing medical imaging information, bio-signal information and the health information of the patient are integrated over the result of executing the application service in order to provide a medical information service which is suitable in medical field.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.77-83
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• 2015

Frequent pattern mining, which is one of the major areas actively studied in data mining, is a method for extracting useful pattern information hidden from large data sets or databases. Moreover, frequent pattern mining approaches have been actively employed in a variety of application fields because the results obtained from them can allow us to analyze various, important characteristics within databases more easily and automatically. However, traditional frequent pattern mining methods, which simply extract all of the possible frequent patterns such that each of their support values is not smaller than a user-given minimum support threshold, have the following problems. First, traditional approaches have to generate a numerous number of patterns according to the features of a given database and the degree of threshold settings, and the number can also increase in geometrical progression. In addition, such works also cause waste of runtime and memory resources. Furthermore, the pattern results excessively generated from the methods also lead to troubles of pattern analysis for the mining results. In order to solve such issues of previous traditional frequent pattern mining approaches, the concept of representative pattern mining and its various related works have been proposed. In contrast to the traditional ones that find all the possible frequent patterns from databases, representative pattern mining approaches selectively extract a smaller number of patterns that represent general frequent patterns. In this paper, we describe details and characteristics of pattern condensing techniques that consider the maximality or closure property of generated frequent patterns, and conduct comparison and analysis for the techniques. Given a frequent pattern, satisfying the maximality for the pattern signifies that all of the possible super sets of the pattern must have smaller support values than a user-specific minimum support threshold; meanwhile, satisfying the closure property for the pattern means that there is no superset of which the support is equal to that of the pattern with respect to all the possible super sets. By mining maximal frequent patterns or closed frequent ones, we can achieve effective pattern compression and also perform mining operations with much smaller time and space resources. In addition, compressed patterns can be converted into the original frequent pattern forms again if necessary; especially, the closed frequent pattern notation has the ability to convert representative patterns into the original ones again without any information loss. That is, we can obtain a complete set of original frequent patterns from closed frequent ones. Although the maximal frequent pattern notation does not guarantee a complete recovery rate in the process of pattern conversion, it has an advantage that can extract a smaller number of representative patterns more quickly compared to the closed frequent pattern notation. In this paper, we show the performance results and characteristics of the aforementioned techniques in terms of pattern generation, runtime, and memory usage by conducting performance evaluation with respect to various real data sets collected from the real world. For more exact comparison, we also employ the algorithms implementing these techniques on the same platform and Implementation level.

• Journal of Internet Computing and Services
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• v.16 no.1
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• pp.57-65
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• 2015

As information technology fusion is accelerated, the researches to improve the quality and productivity of crops inside a plant factory actively progress. Advanced growth environment management technology that can provide thermal environment and air flow suited to the growth of crops and considering the characteristics inside a facility is necessary to maximize productivity inside a plant factory. Currently running plant factories are designed to rely on experience or personal judgment; hence, design and operation technology specific to plant factories are not established, inherently producing problems such as uneven crop production due to the deviation of temperature and air flow and additional increases in energy consumption after prolonged cultivation. The optimization process has to be set up in advance for the arrangement of air flow devices and operation technology using computational fluid dynamics (CFD) during the design stage of a facility for plant factories to resolve the problems. In this study, the optimum arrangement and air flow of air circulation fans were investigated to save energy while minimizing temperature deviation at each point inside a plant factory using CFD. The condition for simulation was categorized into a total of 12 types according to installation location, quantity, and air flow changes in air circulation fans. Also, the variables of boundary conditions for simulation were set in the same level. The analysis results for each case showed that an average temperature of 296.33K matching with a set temperature and average air flow velocity of 0.51m/s suiting plant growth were well-maintained under Case 4 condition wherein two sets of air circulation fans were installed at the upper part of plant cultivation beds. Further, control of air circulation fan set under Case D yielded the most excellent results from Case D-3 conditions wherein air velocity at the outlet was adjusted to 2.9m/s.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.57-66
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• 2015

Considerable research efforts are being directed towards analyzing unstructured data such as text files and log files using commercial and noncommercial analytical tools. In particular, researchers are trying to extract meaningful knowledge through text mining in not only business but also many other areas such as politics, economics, and cultural studies. For instance, several studies have examined national pending issues by analyzing large volumes of text on various social issues. However, it is difficult to provide successful information services that can identify R&D documents on specific national pending issues. While users may specify certain keywords relating to national pending issues, they usually fail to retrieve appropriate R&D information primarily due to discrepancies between these terms and the corresponding terms actually used in the R&D documents. Thus, we need an intermediate logic to overcome these discrepancies, also to identify and package appropriate R&D information on specific national pending issues. To address this requirement, three methodologies are proposed in this study-a hybrid methodology for extracting and integrating keywords pertaining to national pending issues, a methodology for packaging R&D information that corresponds to national pending issues, and a methodology for constructing an associative issue network based on relevant R&D information. Data analysis techniques such as text mining, social network analysis, and association rules mining are utilized for establishing these methodologies. As the experiment result, the keyword enhancement rate by the proposed integration methodology reveals to be about 42.8%. For the second objective, three key analyses were conducted and a number of association rules between national pending issue keywords and R&D keywords were derived. The experiment regarding to the third objective, which is issue clustering based on R&D keywords is still in progress and expected to give tangible results in the future.

• Journal of Internet Computing and Services
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• v.15 no.4
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• pp.91-102
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• 2014

The purpose of this research is to perform the consumer typological study of integrated emerging digital advertisement, where IT and advertisement industry were fused, and to propose the theoretical definition about consumer characteristic which is in need for collection of related market subdivision strategy in perspective of business marketing. For this, the Q methodology, the 'subjectivity' research of qualitative perspective, which discovers new theory by interpreting subjective system of thinking, preference, opinion, and recognition of inner side of respondents, was applied and analyzed. Compared to previous quantitative research that pursues hypothesis verification, this Q methodology is not dependent on operational definition proposed by researcher but pursues for analytic study completely reflecting objective testimony of respondents. For this reason, Q study analyzes in-depth the actual consumer type, which can be found at the initial market formation stage of new service, therefore this study is applicable for theorizing the consumer character as a mean of advanced research. This study extracted thirty 'IT integrated digital advertisement type (Q sample)' from thorough literature research and interviews, and eventually discovered a total four consumer types from analyzing each Q sorting research data of 40 respondents (P sample). Moreover, by interpreting subdivided intrinsic characteristic of each group, the four types were named as 'multi-channel digital advertisement pursuit type', 'emotional advertisement pursuit type', 'new media advertisement pursuit type', and Web 2.0 advertisement pursuit type'. The analysis result of this study is being expected for its value of usage as advanced research of academic and industrial research with the emerging digital advertisement industry as a subject, and as basic research in the field of R&D, Marketing program and the field of designing the advertisement creative strategy and related policy.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.29-38
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• 2015

The Energy Storage System stores electricity for later use. This system can store electricity from legacy electric power systems or renewable energy systems into a battery device when demand is low. When there is high electricity demand, it uses the electricity previously stored and enables efficient energy usage and stable operation of the electric power system. It increases the energy usage efficiency, stabilizes the power supply system, and increases the utilization of renewable energy. The recent increase in the global interest for efficient energy consumption has increased the need for an energy storage system that can satisfy both the consumers' demand for stable power supply and the suppliers' demand for power demand normalization. In general, an energy storage system consists of a Power Conditioning System, a Battery Management System, a battery cell and peripheral devices. The specifications of the subsystems that form the energy storage system are manufacturer dependent. Since the core component interfaces are not standardized, there are difficulties in forming and operating the energy storage system. In this paper, the design of the profile structure for energy storage system and realization of private profiling system for energy storage system is presented. The profiling system accommodates diverse component settings that are manufacturer dependent and information needed for effective operation. The settings and operation information of various PCSs, BMSs, battery cells, and other peripheral device are analyzed to define profile specification and structure. A profile adapter software that can be applied to energy storage system is designed and implemented. The profiles for energy storage system generated by the profile authoring tool consist of a settings profile and operation profile. Setting profile consists of configuration information for energy device what composes energy saving system. To be more specific, setting profile has three parts of category as information for electric control module, sub system, and interface for communication between electric devices. Operation profile includes information in relation to the method in which controls Energy Storage system. The profiles are based on standard XML specification to accommodate future extensions. The profile system has been verified by applying it to an energy storage system and testing charge and discharge operations.

• Journal of Internet Computing and Services
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• v.22 no.4
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• pp.83-98
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• 2021

The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.

• Journal of Internet Computing and Services
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• v.22 no.2
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• pp.109-121
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• 2021

As the global COVID-19 pandemic is prolonged, the Corona Blue phenomenon, combined with COVID-19 and blue, is intensifying. The purpose of this study is to analyze the current trend of Corona Blue in consideration of the possibility of increasing mental illness and the need for countermeasures, especially after COVID-19. This study tried to find out the relationship between stress and leisure activities before and after COVID-19 by using Corona Blue news article analysis through the topic modeling method, and questionnaire find out the help of stress and leisure activities. This study was compared and analyzed using two research methods. First, a total of 363 news articles were analyzed through topic modeling based on newspaper articles from January 2020, when COVID- 19 was upgraded to the "border" stage, until September, where the social distancing stage was strengthened to stage 2.5 in Korea. As a result of the study, a total of 28 topics were extracted, and similar topics were grouped into 7 groups: mental-demic, generational spread, causes of depression acceleration, increased fatigue, attitude to coping with long-term wars, changes in consumption, and efforts to overcome depression. Second, the SPSS statistical program was used to analyze the level of stress change according to leisure activities before/after COVID-19 and the main help according to leisure activities. As a result of the study, it was confirmed that the average difference in stress reduction according to participation in leisure activities before COVID-19 was larger than after COVID-19. Also, leisure activities were found to be effective in stress relief even after COVID-19. In addition, if the main help from leisure activities before COVID-19 was the meaning of relaxation and recharging through physical and social activities. After COVID-19, psychological roles such as mood swings through nature, outdoor activities, or intellectual activities were found to play a large part. As such, in this study, it was confirmed that understanding the current status of Corona Blue and coping with leisure in extreme stress situations has a positive effect. It is expected that this research can serve as a basis for preparing realistic and desirable leisure policies and countermeasures to overcome Corona Blue.