• Smart Media Journal
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• v.12 no.11
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• pp.95-102
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• 2023

Road accidents not only caused loss of human lives but also costed 3% of gross domestic product in most of the countries. The road accidents pose significant challenges to public safety and urban transportation management. There is a need to identify the high-risk area of accidents along with the critical day of week and vulnerable time period in order to implement effective preventive measures and optimizing the resource allocation. We collected 5,012 accident data from 대구교통종합정보. This study identified the high-risk locations, days of week, and time periods for accidents in Daegu and estimated the conditional probabilities of accidents occurring based on combinations of location, day of the week, and time period. The result is visualized in the form of dashboard in Tableau. This study holds substantial practical significance for urban planners, transportation authorities, and policymakers in Daegu to strategically allocate resources for traffic management, law enforcement, and targeted safety campaigns.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.290-293
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• 2021

In this paper, we implement a learning efficiency verification system to inspire learning motivation and help improve concentration by detecting the situation of the user studying. To this aim, data on learning attitude and concentration are measured by extracting the movement of the user's face or body through a real-time camera. The Jetson board was used to implement the real-time embedded system, and a convolutional neural network (CNN) was implemented for image recognition. After detecting the feature part of the object using a CNN, motion detection is performed. The captured image is shown in a GUI written in PYQT5, and data is collected by sending push messages when each of the actions is obstructed. In addition, each function can be executed on the main screen made with the GUI, and functions such as a statistical graph that calculates the collected data, To do list, and white noise are performed. Through learning efficiency checking system, various functions including data collection and analysis of targets were provided to users.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.87-98
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• 2012

Understanding agent's intent is an essential component of the human-computer interaction of ubiquitous computing. Because correct inference of subject's intention in ubiquitous computing system helps particularly to understand situations that involve collaboration among multiple agents or detection of situations that can pose a particular activity. This paper, inspired by people have a mechanism for interpreting one another's actions and for inferring the intentions and goals that underlie action, proposes an approach that allows a computing system to quickly recognize the intent of agents based on experience data acquired through prior capabilities of activities recognition. To proceed intention recognition, proposed method uses formulations of Hidden Markov Models (HMM) to model a system's prior experience and agents' action change, then makes for system infer intents in advance before the agent's actions are finalized while taking the perspective of the agent whose intent should be recognized. Quantitative validation of experimental results, while presenting an accurate rate, an early detection rate and a correct duration rate with detecting the intent of several people performing various activities, shows that proposed research contributes to implement effective intent recognition system.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.83-95
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• 2014

Hand posture recognition is an important technique to enable a natural and familiar interface in HCI(human computer interaction) field. In this paper, we introduce a hand posture recognition method by using a depth camera. Moreover, the hand posture recognition method is incorporated with MPEG-U based advanced user interaction (AUI) interface system, which can provide a natural interface with a variety of devices. The proposed method initially detects positions and lengths of all fingers opened and then it recognizes hand posture from pose of one or two hands and the number of fingers folded when user takes a gesture representing a pattern of AUI data format specified in the MPEG-U part 2. The AUI interface system represents user's hand posture as compliant MPEG-U schema structure. Experimental results show performance of the hand posture recognition and it is verified that the AUI interface system is compatible with the MPEG-U standard.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.6903-6908
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• 2015

Background: As smoking is the leading preventable cause of multiple diseases and premature cancer deaths, estimating the burden of cancer attributable to smoking has become the standard in documenting the adverse impact of smoking. In Indonesia, there is a dearth of studies assessing the economic costs of cancers related to smoking. This study aimed to estimate indirect mortality costs of premature cancer deaths and years of potential life lost (YPLL) attributable to smoking among the Indonesian population. Materials and Methods: A prevalence based method was employed. Using national data, we estimated smoking-attributable cancer mortality in 2013. Premature mortality costs and YPLL were estimated by calculating number of cancer deaths, life expectancy, annual income, and workforce participation rate. A human capital approach was used to calculate the present value of lifetime earnings (PVLE). A discount rate of 3% was applied. Results: The study estimated that smoking attributable cancer mortality was 74,440 (30.6% of total cancer deaths), comprised of 95% deaths in men and 5% in women. Cancers attributed to smoking wereresponsible for 1,207,845 YPLL. Cancer mortality costs caused by smoking accounted for USD 1,309 million in 2013. Among all cancers, lung cancer is the leading cause of death and economic burden. Conclusions: Cancers related to smoking pose an enormous economic burden in Indonesia. Therefore, tobacco control efforts need to be prioritized in order to prevent more losses to the nation. The data of this study are important for advocating national tobacco control policy.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.7
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• pp.279-286
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• 2021

Recently, We are carrying out a policy of physical distancing of at least 1m from each other to prevent the spreading of COVID-19 disease in public places. In this paper, we propose a method for measuring distances between people in real time and an automation system that recognizes objects that are within 1 meter of each other from stereo images acquired by drones or CCTVs according to the estimated distance. A problem with existing methods used to estimate distances between multiple objects is that they do not obtain three-dimensional information of objects using only one CCTV. his is because three-dimensional information is necessary to measure distances between people when they are right next to each other or overlap in two dimensional image. Furthermore, they use only the Bounding Box information to obtain the exact coordinates of human existence. Therefore, in this paper, to obtain the exact two-dimensional coordinate value in which a person exists, we extract a person's key point to detect the location, convert it to a three-dimensional coordinate value using Stereo Vision and Camera Calibration, and estimate the Euclidean distance between people. As a result of performing an experiment for estimating the accuracy of 3D coordinates and the distance between objects (persons), the average error within 0.098m was shown in the estimation of the distance between multiple people within 1m.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.9 no.8
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• pp.783-790
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• 2019

Cognitive science attempts to explain human intelligence on the basis of success of artificial neural network, which is called connectionism. The neural network, e.g., deep learning, seemingly promises connectionism to go beyond what it is. But those(Fodor & Pylyshyn, Fodor, & McLaughlin) who advocate classical computationalism, or symbolism claim that connectionism must fail since it cannot represent the relation between human thoughts and human language. The neural network lacks systematicity, so any output of neural network is at best association or accidental combination of data plugged in input units. In this paper, I first introduce structure of artificial neural network and what connectionism amounts to. Second, I shed light on the problem of systematicity the classical computationalists pose for the connectionists. Third, I briefly introduce how those who advocate connectionism respond to the criticism while noticing Smolensky's theory of vector product. Finally, I examine the debate of computationalism and connectionism on systematicity, and show how the problem of systematicity contributes to the development of connectionism and computationalism both.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.5
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• pp.243-250
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• 2016

Recently, public interest in virtual reality (VR) and augmented reality (AR) has increased. Therefore, computer graphics-related research has been actively conducted. This has included research on virtual space related to human posture implementation. However, such research has focused on general posture in humans. This paper presents a system with reference to the basic posture in sports climbing and the inverse kinematics method for generating the positions and behavior of virtual characteristics in a three-dimensional virtual space. The simulation based on the inverse kinematics method, produced with an inverse kinematics solver and initial pose animation from motion capture, provides realistic and natural movement. We designed a simulation system to generate correct posture and motions similar to those in sports climbing by applying the basic procedure of sports climbing. The simulation system provides help for producing content about sports climbing, such as learning programs for novice climbers and sports climbing games.

• Journal of the Korea Computer Graphics Society
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• v.19 no.4
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• pp.13-22
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• 2013

A motion capture system is widely used in movies, computer game, and computer animation industries because it allows for creating realistic human motions efficiently. The inertial motion capture system has several advantages over more popular vision-based systems in terms of the required space and cost. However, it suffers from low accuracy due to the relatively high noise levels of the inertial sensors. In particular, the accelerometer used for measuring gravity direction loses the accuracy when the sensor is moving with non-zero linear acceleration. In this paper, we propose a method to remove the linear acceleration component from the accelerometer data in order to improve the accuracy of measuring gravity direction. In addition, we develop a simple method to calibrate the joint axis of a link to which an inertial sensor belongs as well as the position of a sensor with respect to the link. The calibration enables attaching inertial sensors in an arbitrary position and orientation with respect to a link.

• Journal of Korea Multimedia Society
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• v.3 no.1
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• pp.23-33
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• 2000

In this paper, we describe an algorithm which can extract human faces with natural pose from complex backgrounds. This method basically adopts the concept that facial region has the nearly same gray level for all pixels within appropriately scaled blocks. Based on the idea, we develop a hierarchial process that first, a block image data with pyramid structure of input image is generated, and some candidate regions for facial regions in the block image are Quickly determined, then finally the detailed facial features; organs are decided. To find the features easily, we introduce a local gray level transform which emphasizes dark and small regions, and estimate the geometrical triangle constraints among the facial features. The merit of our method is that we can be freed from the parameter assignment problem since the algorithm utilize a simple brightness computation, consequently robust systems not being depended on specific parameter values can be easily constructed.