• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.1-8
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• 2012

According that most integral imaging techniques have used rectangular lens array, this integrated distribution of light is recorded in the form of a rectangular grid. However, hexagonal lens array gives a more accurate approximation of ideal circular lens and provides higher pickup/display density than rectangular lens array[4]. Using the parallel processing technique in order to generate the elemental imaging for hexagonal lens array, each pixel that compose the elemental imaging should be determined to belong to the hexagonal lens. This process is output to the screen for every pixel in progress, and many computations are required. In this paper, we have proposed parallel processing method using an OpenCL to generate the elemental imaging for hexagonal lens array in 3D volume date. In the experimental result of proposed method show speed of 20~60 fps for hexagonal lens array of $20{\times}20$ sizes and input data of Male[$128{\times}256{\times}256$] volume data.

• Journal of the Korea Computer Graphics Society
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• v.16 no.4
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• pp.35-40
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• 2010

Due to the distribution of digital camera, many work for photo management has been studied. However, most work use a sequential grid layout which arranges photos considering one criterion of digital photo. This interface makes users have lots of scrolling and concentrate ability when they manage their photos. In this paper, we propose a clustering method based on a temporal sequence considering their color similarity in detail. First we cluster photos using Cooper's event clustering method. Second, we makes more detailed clusters from each clustered photo set, which are clustered temporal clustering before, using maximal clique finding algorithm of interval graph. Finally, we arrange each detailed dusters on a user screen with their overlap keeping their temporal sequence. In order to evaluate our proposed system, we conducted on user studies based on a simple questionnaire.

• Current Optics and Photonics
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• v.1 no.5
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• pp.474-490
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• 2017

Since the recent slowdown in the smartphone market, studies for wearable devices are briskly being carried out to find new markets, such as virtual reality devices. In this paper, a head-mounted display (HMD) which provides expanded virtual images before human eyes by enlarging images of a small display was designed, and the tolerance analysis method for a focus-adjustable HMD based on afocal optical systems was studied. There are two types of HMDs: a see-through type that allows the user to view the surroundings, and a see-close type where the user can only view the display screen; the former is used in this study. While designing the system, we allowed a lens within the system to be shifted to adjust its focus from +1 to -4 D (diopters). The yield of the designed systems was calculated by taking the worst-case scenario of a uniform distribution into account. Additionally, a longitudinal aberration was used rather than MTF for the tolerance analysis with respect to system performance. The sensitivity of the designed system was calculated by assigning a certain tolerance, and the focus lens shift was calculated to adjust the image surface variations resulting from the tolerance. The smaller the tolerance, the more expensive the unit price of the products. Very small tolerances may even be impossible to fabricate. Considering this, the appropriate tolerance was assigned; the maximum shift of the focus lens in which the image surface can be adjusted was obtained to find the changes in aberration and a good yield.

• The Journal of Information Systems
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• v.18 no.4
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• pp.41-57
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• 2009

Although financial information is a great influence upon determining of the group which use them, detection of management fraud and earning manipulation is a difficult task using normal audit procedures and corporate credit evaluation processes, due to the shortage of knowledge concerning the characteristics of management fraud, and the limitation of time and cost. These limitations suggest the need of systemic process for !he effective risk of earning manipulation for credit evaluators, external auditors, financial analysts, and regulators. Moot researches on management fraud have examined how various characteristics of the company's management features affect the occurrence of corporate fraud. This study examines financial characteristics of companies engaged in fraudulent financial reporting and suggests a model and system for detecting GAAP violations to improve reliability of accounting information and transparency of their management. Since the detection of management fraud has limited proven theory, this study used the detecting method of outlier(upper, and lower bound) financial ratio, as a real-field application. The strength of outlier detecting method is its use of easiness and understandability. In the suggested model, 14 variables of the 7 useful variable categories among the 76 financial ratio variables are examined through the distribution analysis as possible indicators of fraudulent financial statements accounts. The developed model from these variables show a 80.82% of hit ratio for the holdout sample. This model was developed as a financial outlier detecting system for a financial institution. External auditors, financial analysts, regulators, and other users of financial statements might use this model to pre-screen potential earnings manipulators in the credit evaluation system. Especially, this model will be helpful for the loan evaluators of financial institutes to decide more objective and effective credit ratings and to improve the quality of financial statements.

• Journal of Biosystems Engineering
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• v.29 no.1
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• pp.71-78
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• 2004

Real time and robust algorithm to extract the features of watermelon was developed from the remotely transmitted image of the watermelon. Features of the watermelon at the cultivation site such as size and shape including position are crucial to the successful tole-robotic operation and development of the cultivation data base. Algorithm was developed based on the concept of task sharing between the computer and the operator utilizing man-computer interface. Task sharing was performed based on the functional characteristics of human and computer. Identifying watermelon from the image transmitted from the cultivation site is very difficult because of the variable light condition and the complex image contents such as soil, mulching vinyl, straws on the ground, irregular leaves and stems. Utilizing operator's teaching through the touch screen mounted on the image monitor, the complex time consuming image processing process and instability of processing results in the watermelon identification has been avoided. Color and brightness characteristics were analyzed from the image area specified by the operator's teaching. Watermelon segmentation was performed using the brightness and color distribution of the specified imae processing area. Modified general Hough transform was developed to extract the shape, major and minor axes, and the position, of the watermelon. It took less than 100 msec of the image processing time, and was a lot faster than conventional approach. The proposed method showed the robustness and practicability in identifying watermelon from the wireless transmitted color image of the cultivation site.

• Journal of Korean Society of Water and Wastewater
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• v.19 no.2
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• pp.117-124
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• 2005

Appropriate removal of pollutants from combined sewer overflows(CSOs) and stormwater runoff is of primary concern to watershed managers trying to meet water quality standards even under a wet weather condition. Harmful substances associated with particles besides TSS and BOD are subjected to removal prior to discharge into the natural waters. Effectiveness of five major hydrodynamic separation technologies, Vortechs, Downstream Defender including Storm King for CSOs control, CDS, Stormceptor, and IHS, were evaluated in this study. There is not sufficient information for accurate evaluation of the removal efficiency for the pollutants from the stormwater runoff and CSOs. Based upon limited engineering data, however, all technologies were found to be effective in separation of heavy particles and floating solids. Technologies utilizing screens seem to have advantage in the treatment capacity than the other technologies relied fully on hydrodynamic behavior. The IHS system seems to have a strong potential in application for control of CSOs because of unique hydrodynamic behavior as well as a flexibility in opening size of the screens. Size of the particulate matter in the CSOs and stormwater runoff is found to be the most important parameter in selection of the type of the hydrodynamic separators. There exists an upper limit in the solids removal efficiency of a hydrodynamic separator, which is strongly dependent upon the particle size distribution of the CSOs and stormwater runoff.

• Journal of Internet of Things and Convergence
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• v.8 no.6
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• pp.85-92
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• 2022

Demand for big data analysis and AI developers is increasing, but there is a lack of an education base to supply them. In this paper, by developing a cloud-based artificial intelligence education platform, the goal was to establish an environment in which practical practical training can be efficiently learned at low cost at educational institutions and IT companies. The development of the education platform was carried out by planning scenarios for each user, architecture design, screen design, implementation of development functions, and hardware construction. This training platform consists of a containerized workload, service management platform, lecture and development platform for instructors and students, and secured cloud stability through real-time alarm system and age test, CI/CD development environment, and reliability through docker image distribution. The development of this education platform is expected to expand opportunities to enter new businesses in the education field and contribute to fostering working-level human resources in the AI and big data fields.

• The Journal of the Korea Contents Association
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• v.21 no.8
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• pp.403-412
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• 2021

As the number of mobile apps increases exponentially, automation of tests performed in the app development process is becoming more important. Until the app is released, iterative verification is performed through various types of tests, and this study was conducted focusing on the GUI test among various types of tests. This study is meaningful in that it can contribute to the stable app distribution of the developer by suggesting the development direction of the GUI test. To develop Android's GUI test tool, I collected basic data before presenting the development method by researching Android's UI controls and Material design guideline. After that, for the existing GUI test automation tool, two tools based on screen capture test and four tools based on source code analysis test were studied. Through this, it was found that existing GUI test tools don't consider visual design, usability, and component arrangement. In order to supplement the shortcomings of existing tools, a new GUI test automation tool development method was presented based on the basic data previously studied.

• Journal of Preventive Medicine and Public Health
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• v.55 no.3
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• pp.297-306
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• 2022

Objectives: The incidence of cardiovascular disease (CVD) mortality is increasing in developing countries. This study aimed to decompose the socioeconomic inequality of CVD in Iran. Methods: This cross-sectional population-based study was conducted on 20 519 adults who enrolled in the Ardabil Non-Communicable Disease cohort study. Principal component analysis and multivariable logistic regression were used, respectively, to estimate socioeconomic status and to describe the relationships between CVD prevalence and the explanatory variables. The relative concentration index, concentration curve, and Blinder-Oaxaca decomposition model were used to measure and decompose the socioeconomic inequality. Results: The overall age-adjusted prevalence of CVD was 8.4% in northwest Iran. Multivariable logistic regression showed that older adults, overweight or obese adults, and people with hypertension and diabetes were more likely to have CVD. Moreover, people with low economic status were 38% more likely to have CVD than people with high economic status. The prevalence of CVD was mainly concentrated among the poor (concentration index, -0.077: 95% confidence interval, -0.103 to -0.060), and 78.66% of the gap between the poorest and richest groups was attributed to differences in the distribution of the explanatory variables included in the model. Conclusions: The most important factors affecting inequality in CVD were old age, chronic illness (hypertension and diabetes), marital status, and socioeconomic status. This study documented stark inequality in the prevalence of CVD, wherein the poor were more affected than the rich. Therefore, it is necessary to implement policies to monitor, screen, and control CVD in poor people living in northwest Iran.

• The Journal of the Convergence on Culture Technology
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• v.8 no.3
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• pp.571-580
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• 2022

Marine deposited waste is a major cause of problems such as a lot of damage and an increase in the estimated amount of garbage due to abandoned fishing grounds caused by ghost fishing. In this paper, we implement a real-time marine deposited waste detection artificial intelligence system to understand the actual conditions of waste fishing gear usage, distribution, loss, and recovery, and study methods for performance improvement. The system was implemented using the yolov5 model, which is an excellent performance model for real-time object detection, and the 'data screening process' and 'class segmentation' method of learning data were applied as performance improvement methods. In conclusion, the object detection results of datasets that do screen unnecessary data or do not subdivide similar items according to characteristics and uses are better than the object recognition results of unscreened datasets and datasets in which classes are subdivided.