• International journal of advanced smart convergence
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• v.8 no.3
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• pp.7-12
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• 2019

This study aimed that certain risk factors are linked to the risk of developing depression and decreasing quality of life. This study was implemented using data from the 6th and 7th Korea National Health and Nutritional Examination Survey. The National Health and Nutrition Survey consist of health surveys, screenings, and nutrition surveys. Among the risk factors, data on adult diseases such as depression, hypertension, arthritis, diabetes, cataract, glaucoma, and macular degeneration were used. In total, 12,768 adults over 20 years of age were selected, of whom 520 were diagnosed with depression. The most common risk factors in adults over 20 years of age were hypertension, arthritis, cataract, diabetes, depression, glaucoma, and macular degeneration. Their risk factors were analyzed if these were associated with depression and quality of life. The results revealed that hypertension, arthritis, diabetes, cataract, glaucoma, and macular degeneration were predictors for the occurrence of depression in adults. The factors associated with the highest risk for depression were arthritis and glaucoma. Furthermore, the study investigated the effect of certain factors on the quality of life; the factor associated with the greatest impact on quality of life was arthritis. This study verified that the aforementioned factors were related to the risk of developing depression and decreasing quality of life.

• International journal of advanced smart convergence
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• v.8 no.3
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• pp.54-60
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• 2019

In this paper, a localization system for indoor objects is proposed. The proposed system consists of Beacons, LED Cells, Main Cell Controller (MCC), and Display. A Beacon is attached at each indoor object, and each LED cell has Beacon Scanner and VLC Transmitter. The Visual Light Communications (VLC) and Power Line Communications (PLC) methods are used to communicate the signals for localization of indoor objects. And the proposed system is designed, and implemented as a prototype. To certify that our propose d system can exactly localize a given indoor object, we take test for the implemented system as a p rototype. Here the location of the given indoor object is known. Test is done in two ways. The first is to check the operation of the detail of the system, and the second is the position recognition of i ndoor object. The second is the test of the implemented system to correctly detect the location of the indoor object with Beacon, while the object with Beacon is moved from location C to A. The experimental result shows that the system is exactly detect the moving locations. The system has the advantages of using previously installed power lines, and it does not need to use LAN lines or optical cables. The proposed system is usefully applied to indoor object localization area.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.77-87
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• 2019

One of important concerns in information security is to control information flow. It is whether to protect confidential information from being leaked, or to protect trusted information from being tainted. In this paper, we present Piosk (Physical blockage of Information flow Kiosk) that addresses both the problems practically. Piosk can forestall and prevent the leakage of information, and defend inner tangible assets against a variety of malwares as well. When a visitor who carries a re-writable portable storage device, must insert the device into Piosk installed next to the security gate. Then, Piosk scans the device at the very moment, and detects & repairs malicious codes that might be exist. After that, Piosk writes the contents (including sanitized ones) on a new read-only portable device such as a compact disk. By doing so, the leakage of internal information through both insiders and outsiders can be prevented physically. We have designed and prototyped Piosk. The experimental verification of the Piosk prototype implementation reveals that, Piosk can accurately detect every malware at the same detection level as Virus Total and effectively prevent the leakage of internal information. In addition, we compare Piosk with the state-of-the-art methods and describe the special advantages of Piosk over existing methods.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.102-108
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• 2019

Big data was associated with three key concepts, volume, variety, and velocity. Securities and investment services produce and store a large data of text/numbers. They have also the most data per company on the average in the US. Gartner found that the demand for big data in finance was 25%, which was the highest. Therefore securities and investment companies produce the largest data such as text/numbers, and have the highest demand. And insurance companies and credit card companies are using big data more actively than banking companies in Korea. Researches on the use of big data in securities and investment companies have been found to be insignificant. We surveyed 22 major securities and investment companies in Korea for activating big data. We can see they actively use AI for investment recommend. As for big data of securities and investment companies, we studied open API. Of the major 22 securities and investment companies, only six securities and investment companies are offering open APIs. The user OS is 100% Windows, and the language used is mainly VB, C#, MFC, and Excel provided by Windows. There is a difficulty in real-time analysis and decision making since developers cannot receive data directly using Hadoop, the big data platform. Development manuals are mainly provided on the Web, and only three companies provide as files. The development documentation for the file format is more convenient than web type. In order to activate big data in the securities and investment fields, we found that they should support Linux, and Java, Python, easy-to-view development manuals, videos such as YouTube.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.211-217
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• 2019

This study is designed to reduce worker fatigue, improve efficiency and provide a functional working environment based on previous studies that pain occurs in the shoulder area, especially the upper trapezius muscle, when the keyboard height is not appropriate. In this study, the height of the keyboard is four, the height of the elbow and desk is the same height, the height of the desk is 3cm lower than the elbow, the height of the desk is 6cm high, and the height is 9cm high. When working on the keyboard, the wrist and forerunner were organized into four groups of 10 people so that the height was different for each group. When the height of the keyboard is given in various ways compared to the height of the elbow of the subject, it is verified whether there is a difference in the RMS (Root Mean Square) of the upper trapezius muscle. The results of this study showed that the muscle activity of the upper trapezius muscle cap was significant only in the left and right keyboard height -4cm, 0cm, +4cm, +8cm group, but the difference in muscle activity was not significant in the rest group. The first study will require a study of the control of the factors affecting the tension of the subjects, the measurement of muscle activity against various muscles, and whether the length of the shoulder and fingertips of the subject affect muscle activity according to the keyboard type.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.155-161
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• 2019

We introduces a mobile robot that can navigate on a power transmission line arranged in bundled conductors. The designs of the proposed robot are performed for navigation on bundled conductors, and the navigation method for bundled conductors and obstacle avoidance are presented. The robot consists of 13 degrees of freedom (DOF) with a symmetrical structure for the left and right parts, including the four wheel joints. The navigation method is designed using a combination of three motion primitives such as linear motion of counterbalancing box, linear motion of robot arm, and rotational motion of wheel part. To examine the performance of the proposed robot, navigation simulations are conducted using $ADAMS^{TM}$. The robot navigations were simulated on obstacle environments that consisted of two- and four-conductor bundles. Based on the simulation results, the performance of the proposed robot was reviewed through the analysis of the trajectories of end-effectors. We confirmed that the proposed robot was capable of achieving optimal navigation on bundled conductors that included obstacles.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.162-169
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• 2019

Facial rigging technology has been developing more and more since the 21st century. Facial rigging of various methods is still attempted and a technique of capturing the geometry in real time recently also appears. Currently Modern CG is produced image which is hard to distinguish from actual photograph. However, this kind of technology still requires a lot of equipment and cost. The purpose of this study is to perform facial rigging using muscle simulation instead of using such equipment. Original muscle simulations were made primarily for use in the body of a creature. In this study, however, we use muscle simulations for facial rigging to create a more realistic creature-like effect. To do this, we used Ziva Dynamics' Ziva VFX muscle simulation software. We also develop a method to overcome the disadvantages of muscle simulation. Muscle simulation can not be applied in real time and it takes time to simulate. It also takes a long time to work because the complex muscles must be connected. Our study have solved this problem using blendshape and we want to show you how to apply our method to face rig.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.132-139
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• 2019

We address the problem about forecasting the direction of stock price movement in the Korea market. Recently, the deep neural network is popularly applied in this area of research. In deep neural network systems, proper parameter initialization reduces training time and improves the performance of the model. Therefore, in our study, we propose a novel parameter initialization technique and apply this technique for the stock price movement prediction model. Specifically, we design a framework which consists of two models: a base model and a main prediction model. The base model constructed with LSTM is trained by using the large data which is generated by a large amount of the stock data to achieve optimal parameters. The main prediction model with the same architecture as the base model uses the optimal parameter initialization. Thus, the main prediction model is trained by only using the data of the given stock. Moreover, the stock price movements can be affected by other related information in the stock market. For this reason, we conducted our research with two types of inputs. The first type is the stock features, and the second type is a combination of the stock features and the Korea Composite Stock Price Index (KOSPI) features. Empirical results conducted on the top five stocks in the KOSPI list in terms of market capitalization indicate that our approaches achieve better predictive accuracy and F1-score comparing to other baseline models.

• International journal of advanced smart convergence
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• v.8 no.2
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• pp.8-17
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• 2019

The main purpose of this study isto explore the potential of affective computing (AC) platforms in education through two phases ofresearch: Phase I - platform analysis and Phase II - classification of academic emotions. In Phase I, the results indicate that the existing affective analysis platforms can be largely classified into four types according to the emotion detecting methods: (a) facial expression-based platforms, (b) biometric-based platforms, (c) text/verbal tone-based platforms, and (c) mixed methods platforms. In Phase II, we conducted an in-depth analysis of the emotional experience that a learner encounters in online video-based learning in order to establish the basis for a new classification system of online learner's emotions. Overall, positive emotions were shown more frequently and longer than negative emotions. We categorized positive emotions into three groups based on the facial expression data: (a) confidence; (b) excitement, enjoyment, and pleasure; and (c) aspiration, enthusiasm, and expectation. The same method was used to categorize negative emotions into four groups: (a) fear and anxiety, (b) embarrassment and shame, (c) frustration and alienation, and (d) boredom. Drawn from the results, we proposed a new classification scheme that can be used to measure and analyze how learners in online learning environments experience various positive and negative emotions with the indicators of facial expressions.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.84-91
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• 2018

In this paper, we simulated three different HV systems and analyzed of each vacuum characteristics by VacCAD modelling. In each of modelled vacuum systems, selection of chamber materials, combination of rough pump with high vacuum pump and conductance of roughing line (diameter and length) were proposed as system variables. In the modelling of chamber materials, the pumping times to ultimate pressures of different chamber materials (stainless steel, aluminum) were compared by the variations of chamber volume. In this model, the effects of outgassing dependent on the chamber materials was also simulated and aluminum was estimated to optimum chamber materials. It was also obtained that modelling of vane and roots pump with diffusion pump and diameter, length of $50{\times}250$ [mm]roughing line were characterized as optimum variables to reach the ultimate pressure of 10E-7 [mbar] most effectively. Optimum design factors for vacuum characteristics of modelled vacuum system were achieved by VacCAD simulations. Feasibility of VacCAD as vacuum simulator was verified and applications of VacCAD expected to be increased to fields in vacuum needed.