• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.4
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• pp.163-172
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• 2022

This study investigates the IPI (Information Protection Intention) of DHS (Digital Healthcare Service) providers by introducing PMT (Protection Motivation Theory). This study examines the effects of protection motivation, such as threat appraisal and coping appraisal, on IPI, such as ICI(Induction Control Intention) and SDI(Self Defense Intention). The research model, based on the PMT, adopted severity, vulnerability, reaction efficacy and self-efficacy as independent variables. The research model was validated through quantitative research, a survey of 222 DHS providers in South Korea, using structural equation modeling. The results show that (1) a clear awareness of the consequences of security threats increases the understanding of DHS providers on the severity of closure of healthcare information, and thus may decreases abuse of DHS by providers; (2) user confidence and satisfaction on the security system may make them be confident that they can handle the closure of healthcare information by themselves; and (3) although DHS providers are realizing the consequences of closure of healthcare information, they think that they are unlikely to encounter such situations. As a result of this study, venture companies that provide DHS need to provide contents that can continuously increase providers' security level in order to increase providers' information protection intention. It suggests that IPI is important through trust of healthcare service providers.

• The Journal of the Acoustical Society of Korea
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• v.26 no.6
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• pp.250-258
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• 2007

Current speech recognition technology s achieved high performance with the development of hardware devices, however it is insufficient for some applications where high reliability is required, such as voice control of powered wheelchairs for disabled persons. For the system which aims to operate powered wheelchairs safely by voice in real environment, we need to consider that non-voice commands such as user s coughing, breathing, and spark-like mechanical noise should be rejected and the wheelchair system need to recognize the speech commands affected by disability, which contains specific pronunciation speed and frequency. In this paper, we propose non-voice rejection method to perform voice/non-voice classification using both YIN based fundamental frequency(F0) extraction and reliability in preprocessing. We adopted a multi-template dictionary and acoustic modeling based speaker adaptation to cope with the pronunciation variation of inarticulately uttered speech. From the recognition tests conducted with the data collected in real environment, proposed YIN based fundamental extraction showed recall-precision rate of 95.1% better than that of 62% by cepstrum based method. Recognition test by a new system applied with multi-template dictionary and MAP adaptation also showed much higher accuracy of 99.5% than that of 78.6% by baseline system.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.2
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• pp.225-249
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• 2024

The purpose of this study is to develop an evaluation tool for map-based data visualization platforms and to conduct heuristic usability evaluations on existing platforms representing inter-regional information. We compared and analyzed the usability evaluation criteria of map-based platforms from the previous studies along with Nielsen's (1994) 10 usability evaluation principles. We proposed nine evaluation criteria, including (1) visibility, (2) representation of the real world, (3) consistency and standards, (4) user control and friendliness, (5) flexibility, (6) design, (7) compatibility, (8) error prevention and handling, and (9) help provision and documentation. Additionally, to confirm the effectiveness of the proposed criteria, four experts was invited to evaluate five domestic and international map-based data visualization platforms. As a result, the experts were able to rank the usability of the five platforms using the proposed map-based data visualization usability evaluation criteria, which included quantified scores and subjective opinions. The results of this study are expected to serve as foundational material for the future development and evaluation of map-based visualization platforms.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.180-185
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• 2003

The increase of traffic over a bridge has been emerged as one of the most severe problems in view of bridge maintenance, since the load effect caused by the vehicle passage over the bridge has brought out a long-term damage to bridge structure, and it is nearly impossible to maintain operational serviceability of bridge to user's satisfactory level without any concern on bridge maintenance at the phase of completion. Moreover, bridge maintenance operation should be performed by regular inspection over the bridge to prevent structural malfunction or unexpected accidents front breaking out by monitoring on cracks or deformations during service. Therefore, technical breakthrough related to this uninterested field of bridge maintenance leading the public to the turning point of recognition is desperately needed. This study has the aim of development on automated inspection system to lower surface of bridge superstructures to replace the conventional system of bridge inspection with the naked eye, where the monitoring staff is directly on board to refractive or other type of maintenance .vehicles, with which it is expected that we can solve the problems essentially where the results of inspection are varied to change with subjective manlier from monitoring staff, increase stabilities in safety during the inspection, and make contribution to construct data base by providing objective and quantitative data and materials through image processing method over data captured by cameras. By this system it is also expected that objective estimation over the right time of maintenance and reinforcement work will lead enormous decrease in maintenance cost.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.15 no.4
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• pp.277-301
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• 2020

This study surveyed 503 adults to examine the effect of gaming disorder classification, recently announced by World Health Organization(WHO), when it is applied to Korean game market. Considering the difference in respondents' background knowledge on gaming disorder, half of the respondents were randomly assigned to read an informative news article describing WHO's decision and its expected effect on domestic game industry. Based on previous literature of gaming disorder, we categorized respondents into a normal-use group and a potentially problematic-use group. As a result of analyses, it was found that the gaming disorder classification would yield overall reduction of game-related consumption in terms of gaming time(24%), game cost(28%), the number of games(22%), etc. The potentially problematic group showed higher willingness to pay for gaming than the normal group did, even if the game cost presumably increases due to the gaming disorder classification. A similar outcome was observed in those with high stress levels. This implies that the policy to solve game addiction problems may ironically lead to unexpected cost increases to the target group of the policy. Hence, problematic groups, especially, highly stressful people and the people with the lack of self-control, need to be considered when the gaming disorder classification policy is established. Furthermore, the informative news article had the preventive effect on the attitude and the intention of the people with moderate or high self-control capacity, but not to the people with gaming-additive tendencies, Again, this finding confirms the necessity of the tweezers policy to refine target groups by their characteristics and prepare for differentiated policies. When the gaming disorder classification is simply adopted with no consideration of domestic circumstances, irreversible loss could affect Korean game users, game industries, and related companies. This calls for urgent cooperation between academia, government, and industry to set up appropriate measures to deal with the gaming disorder classification.

• Journal of Bio-Environment Control
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• v.15 no.4
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• pp.296-305
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• 2006

The heterogeneity of crop transpiration is important to clearly understand the microclimate mechanisms and to efficiently handle the water resource in greenhouses. A computational fluid dynamic program (Fluent CFD version 6.2) was developed to study the internal climate and crop transpiration distributions of greenhouses. Additionally, the global solar radiation model and a crop heat exchange model were programmed together. Those models programmed using $C^{++}$ software were connected to the CFD main module using the user define function (UDF) technology. For the developed CFD validity, a field experiment was conducted at a $17{\times}6 m^2$ plastic-covered mechanically ventilated single-span greenhouse located at Pusan in Korea. The CFD internal distributions of air temperature, relative humidity, and air velocity at 1m height were validated against the experimental results. The CFD computed results were in close agreement with the measured distributions of the air temperature, relative humidity, and air velocity along the greenhouse. The averaged errors of their CFD computed results were 2.2%,2.1%, and 7.7%, respectively.

• The Journal of Society for e-Business Studies
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• v.22 no.2
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• pp.137-152
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• 2017

The decline in the price of IT devices and the development of the Internet have created a new field called Internet of Things (IoT). IoT, which creates new services by connecting all the objects that are in everyday life to the Internet, is pioneering new forms of business that have not been seen before in combination with Big Data. The prospect of IoT can be said to be unlimited in its utilization. In addition, studies of standardization organizations for smooth connection of these IoT devices are also active. However, there is a part of this study that we overlook. In order to control IoT equipment or acquire information, it is necessary to separately develop interworking issues (IP address, Wi-Fi, Bluetooth, NFC, etc.) and related application software or apps. In order to solve these problems, existing research methods have been conducted on augmented reality using GPS or markers. However, there is a disadvantage in that a separate marker is required and the marker is recognized only in the vicinity. In addition, in the case of a study using a GPS address using a 2D-based camera, it was difficult to implement an active interface because the distance to the target device could not be recognized. In this study, we use 3D Depth recognition camera to be installed on smartphone and calculate the space coordinates automatically by linking the distance measurement and the sensor information of the mobile phone without a separate marker. Coordination inquiry finds equipment of IoT and enables information acquisition and control of corresponding IoT equipment. Therefore, from the user's point of view, it is possible to reduce the burden on the problem of interworking of the IoT equipment and the installation of the app. Furthermore, if this technology is used in the field of public services and smart glasses, it will reduce duplication of investment in software development and increase in public services.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.6
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• pp.60-74
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• 2018

This study was to investigate the pedestrian's thermal environments in the North Sidewalk of E-W Street during summer heatwave. We carried out detailed measurements with four human-biometeorological stations on Dongjin Street, Jinju, Korea ($N35^{\circ}10.73{\sim}10.75^{\prime}$, $E128^{\circ}55.90{\sim}58.00^{\prime}$, elevation: 50m). Two of the stations stood under one row street tree and hedge(One-Tree), two row street tree and hedge (Two-Tree), one of the stations stood under shelter and awning(Shelter), while the other in the sun (Sunlit). The measurement spots were instrumented with microclimate monitoring stations to continuously measure microclimate, radiation from the six cardinal directions at the height of 1.1m so as to calculate the Universal Thermal Climate Index (UTCI) from 24th July to 21th August 2018. The radiant temperature of sidewalk's elements were measured by the reflective sphere and thermal camera at 29th July 2018. The analysis results of 9 day's 1 minute term human-biometeorological data absorbed by a man in standing position from 10am to 4pm, and 1 day's radiant temperature of sidewalk elements from 1:16pm to 1:35pm, showed the following. The shading of street tree and shelter were mitigated heat stress by the lowered UTCI at mid and late summer's daytime, One-Tree and Two-Tree lowered respectively 0.4~0.5 level, 0.5~0.8 level of the heat stress, Shelter lowered respectively 0.3~1.0 level of the heat stress compared with those in the Sunlit. But the thermal environments in the One-Tree, Two-Tree and Shelter during the heat wave supposed to user "very strong heat stress" while those in the Sunlit supposed to user "very strong heat stres" and "exterme heat stress". The main heat load temperature compared with body temperature ($37^{\circ}C$) were respectively $7.4^{\circ}C{\sim}21.4^{\circ}C$ (pavement), $14.7^{\circ}C{\sim}15.8^{\circ}C$ (road), $12.7^{\circ}C$ (shelter canopy), $7.0^{\circ}C$ (street funiture), $3.5^{\circ}C{\sim}6.4^{\circ}C$ (building facade). The main heat load percentage were respectively 34.9%~81.0% (pavement), 9.6%~25.2% (road), 24.8% (shelter canopy), 14.1%~15.4% (building facade), 5.7% (street facility). Reducing the radiant temperature of the pavement, road, building surfaces by shading is the most effective means to achieve outdoor thermal comfort for pedestrians in sidewalk. Therefore, increasing the projected canopy area and LAI of street tree through the minimal training and pruning, building dense roadside hedge are essential for pedestrians thermal comfort. In addition, thermal liner, high reflective materials, greening etc. should be introduced for reducing the surface temperature of shelter and awning canopy. Also, retro-reflective materials of building facade should be introduced for the control of reflective sun radiation. More aggressively pavement watering should be introduced for reducing the surface temperature of sidewalk's pavement.