• The Journal of the Korea Contents Association
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• v.18 no.12
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• pp.405-420
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• 2018

As the intelligent vehicle market continues to develop relevant technologies and services for consumers, it is necessary to understand the characteristics of potential consumers. The purpose of this study is to identify and understand the types of potential consumers of intelligent vehicle using the Q-methodology. A Q-frame was constructed using thirty six statements from intelligent vehicle related literature concerning core technology, technology acceptance and personal consumption value, legal system and policy and social awareness. Q-sorting and in-depth interviews were conducted using thirty nine P-samples snowballed. Analysis produced four types of potential consumers for intelligent vehicle: Smart Car Consumer, Reasonable Consumer, Safety Car Consumer, and Smart Device Consumer. Smart Car Consumer value the vehicle capability of intelligent vehicle as most important while Reasonable Consumer focus upon the economics of intelligent vehicle. Safety Car Consumer recognize the safety of intelligent vehicle as most important while Smart Device Consumer highly value the IT functions provided by intelligent vehicles. Across these four different types of consumers, preventing injuries of intelligent vehicle drivers turned out to be the most common critical factor in assessing intelligent vehicle. Implications for the intelligent vehicle market is discussed at the end with further studies needed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.224-226
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• 2016

With the technical development and rapid increase of private demand, the new market for unmanned vehicle combined with the characteristics of 'unmanned automation' and 'vehicle' is rapidly growing. Even though the pilot driving is currently allowed in some countries, there is no country that has institutionalized the formal driving of self-driving cars. In case of the existing vehicles, safety incidents are frequently happening due to the frequent malfunction of the rear sensor, blind spot of the rear camera, or drivers' carelessness. Once such minor flaws are complemented, the relevant regulations for the commercialization of self-driving car and small drone could be relieved. Contrary to the ultrasonic and laser sensors used for the existing vehicles, this paper aims to attempt the distance measurement by using the depth sensor. A depth camera calculates the distance data based on the TOF method calculating the time difference by lighting laser or infrared light onto an object or area and then receiving the beam coming back. As this camera can obtain the depth data in the pixel unit of CCD camera, it can be used for collecting depth data in real-time. This paper suggests to solve problems mentioned above by using depth data in real-time and also to design the obstacle avoidance system through distance measurement.

• Safety and Health at Work
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• v.10 no.3
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• pp.377-383
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• 2019

Objectives: Exposure to fine particles in urban air has been associated with a number of negative health effects. High levels of fine particles have been detected at underground stations in big cities. We investigated the exposure conditions in four occupational groups in the Stockholm underground train system to identify high-exposed groups and study variations in exposure. Methods: $PM_1$ and $PM_{2.5}$ were measured during three full work shifts on 44 underground workers. Fluctuations in exposure were monitored by a real-time particle monitoring instrument, pDR, DataRAM. Qualitative analysis of particle content was performed using inductively coupled plasma mass spectrometry. Nitrogen dioxide was measured using passive monitors. Results: For all underground workers, the geometric mean (GM) of $PM_1$ was $18{\mu}g/m^3$ and of $PM_{2.5}$ was $37{\mu}g/m^3$. The particle exposure was highest for cleaners/platform workers, and the GM of $PM_1$ was $31.6{\mu}g/m^3$ [geometric standard deviation (GSD), 1.6] and of $PM_{2.5}$ was $76.5{\mu}g/m^3$ (GSD, 1.3); the particle exposure was lowest for ticket sellers, and the GM of $PM_1$ was $4.9{\mu}g/m^3$ (GSD, 2.1) and of $PM_{2.5}$ was $9.3{\mu}g/m^3$ (GSD, 1.5). The $PM_1$ and $PM_{2.5}$ levels were five times higher in the underground system than at the street level, and the particles in the underground had high iron content. The train driver's nitrogen dioxide exposure level was $64.1{\mu}g/m^3$ (GSD, 1.5). Conclusions: Cleaners and other platform workers were statistically significantly more exposed to particles than train drivers or ticket sellers. Particle concentrations ($PM_{2.5}$) in the Stockholm underground system were within the same range as in the New York underground system but were much lower than in several older underground systems around the world.

• Journal of the Korean Applied Science and Technology
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• v.36 no.1
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• pp.217-225
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• 2019

The aim of this study was determine to effect of shaft length and physical condition on golf driving performance(head speed, distance and direction). A range of drivers with length between 44 inch, 45 inch and 46 inch limit imposed by R&A rules limited were assembled and evaluated. Club head speed and drive distance and accuracy were determined three category 27 PGA pro golfer (handicaps 0, and height $170cm{\geq}171-175{\geq}175-180cm$) who golf performance. As a results follow : Head speed was significantly difference with 44, 45 between 46inch(p<.01). Distance was significantly difference with 44 between 46inch(p<.05). And direction was significantly difference with 44, 45inch between 46inch(p<.05). Head speed according to height was general similarity among shaft length in 170cm, 171-175cm. Distance were general similarity among shaft length in 170cm, and significantly difference with 44inch between 46inch in 171-175cm(p<.01), and significantly difference with 45inch between 46inch in 176-180cm(p<.05). Direction were significantly difference with 44inch between 46inch in 170cm(p<.05), but do not significantly difference with 44inch between 46inch in 176-180cm, 176-180cm. These results show that shaft length and height can affect head speed, distance and direction.

• Food Science and Industry
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• v.52 no.1
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• pp.40-51
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• 2019

For better understanding the relationship between consumers' perception and sensory characteristics of products, diverse types of rapid sensory profiling technique have been suggested as alternatives to conventional descriptive analysis. Among these, check-all-that-apply (CATA) method has gained popularity for studying consumers' perception and intuitive responses to products due to their simplicity, speed, and ease of use. CATA method has been used to gather consumers' perception derived from sensory characteristics of products as well as consumers' emotion responses to products in recent years. Moreover, many researchers reported that CATA method can be used to provide valuable information for product optimization by applying a penalty analysis and collecting responses to ideal product. Thus, this article reviews recent research using CATA in the field of sensory and consumer science and introduces practical applications to achieve various business objectives in food industry.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.21 no.6
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• pp.55-69
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• 2018

As disaster risk and climate change volatility increase, there are more efforts to adapt to disasters such as forest fires, floods, and landslides. Most of the research, however, is about influence of human activities on disaster and there is few research on disaster adaptation for species. Previous studies focusing on biodiversity in selecting conservation areas have not addressed threats of disaster in the habitats for species. The natural disasters sometimes play role of drivers of ecological successions in the long run, but they might cause serious problems for the conservation of vulnerable species which are endangered. The purpose of this study is to determine whether soil loss (SL) is effective in selecting habitat management areas for amphibians and reptiles. RUSLE model was used to calculate soil loss (SL) and the distribution of each species (SD) was computed with MaxEnt model to find out the biodiversity index. In order to select the habitat management area, we estimated the different results depending if value of soil loss was applied or not by using MARXAN, a conservation priority selection tool. With using MARXAN, conservation goals can be achieved according to the scenario objectives, and the study has been made to meet the minimum habitat area. Finally, the results are expressed in two; 1) the result of soil loss and biodiversity with MATRIX method and 2) the result of regional difference calculated with MARXAN conservation prioritization considering soil loss. The first result indicates that the area with high soil loss and low species diversity have lower conservation values and thus can be managed as natural disturbances. In the area where soil loss is high and species diversity is also high, it becomes where a disaster mitigation action should be taken for the species. According to the conservation priorities of the second result, higher effectiveness of conservation was obtained with fewer area when it considered SL in addition to SD, compared to when considered only biodiversity. When the SL was not taken into consideration, forest area with high distribution of species were important, but when SL considered, the agricultural area or downstream of the river were represented to be a major part of habitats. If more species data or disaster parameters other than soil loss are added as variables later, it could contribute as a reference material for decision-making to achieve various purposes.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.4
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• pp.15-34
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• 2019

Today, there is increasing recognition of the importance of urban regeneration for better public places. Urban parks as a public area play an important role in harnessing its positive impact on people's well-being: where the standards and funding of/for the parks are getting worse. There is however less a focus on policy approach to park regeneration in the country. Neverthless, a few UK's cases of such innovative park management(PM) has shown successful park regeneration based on policy support. Therefore, the aim of this research is to draw policy implications by exploring a case of successful park regeneration. To address the aim, this research conducts an in-depth case study of 'Manor Fields Park, UK', digging into its PM structure and PM body 'Green Estate Ltd' in relation to relevant policy. The data is mainly collected by interviews including a group interview. The analytical framework 'Place-keeping(PK)' and its six dimensions are employed to determine the characteristics of MFP's PM structure. Resultingly, there is a significant shift in the approach to PM which stresses the principle of long-term and self-sustaining structure led by a non-profit organisation and strong impacts of policy. In this context, PK highlights significant drivers for parks regeneration particularly in terms of policy implications: 1)providing policy support to encourage non-profit organisations in PM, 2)extending community involvement in decision-making processes, 3)promoting income generation by community groups, 4)shifting public awareness of shared responsibility for PM, 5)completing regular park maintenance assessment by community groups, and 6)delivering low-maintenance approaches to PM. To support these implications, PM structure for successful parks regeneration does meet a holistic and multi-dimensional approach of place-keeping underlined by understanding policy contexts and rethinking current status quo of PM. Addressing these implications will shed light on urban PM in an era of austerity and ultimately contribute to improving people's well-being.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.156-172
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• 2020

The purpose of this study was to predict road surface temperature using high-resolution solar radiation data. The road surface temperature prediction model (RSTPM) was applied to predict road surface temperature; this model was developed based on the heat-balance method. In addition, using SOLWEIG (SOlar and LongWave Environmental Irradiance Geometry-model), the shadow patterns caused by the terrain effects were analyzed, and high-resolution solar radiation data with 10 m spatial resolution were calculated. To increase the accuracy of the shadow patterns and solar radiation, the day that was modeled had minimal effects from fog, clouds, and precipitation. As a result, shadow areas lasted for a long time at the entrance and exit of a tunnel, and in a high-altitude area. Furthermore, solar radiation clearly decreased in areas affected by shadows, which was reflected in the predicted road surface temperatures. It was confirmed that the road surface temperature should be high at topographically open points and relatively low at higher altitude points. The results of this study could be used to forecast the freezing of sections of road surfaces in winter, and to inform decision making by road managers and drivers.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.217-226
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• 2021

The use of personal mobility(PM) is increasing because of preading shared mobility, but, it causes risk of accidents and fear to pedestrians because of lack of sound. The purpose of this study is to find out the effects of the alert sound in PM and driving direction on risk perception of pedestrians, awareness on PM driver, and allowance for driving on each road. The 8 videos were produced from a pedestrian perspective, depending on the alert sound type(silent, vess, bell, voice) and direction of driving(front, back). After watching each video, participants completed surveys. There was a non-effect on the driving direction. Regardless of the alert sound type, all of the sounds reduced the risk perception. Also, the awareness of PM drivers and allowance for driving on each road were positive. This study found that PM needed an alert sound for pedestrian safety. We expect the results of the study to help improve awareness of PM and make policies and regulations.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.99-108
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• 2021

There are unrestricted conditions on the driver's face inside the vehicle, such as changes in lighting, partial occlusion and various changes in the driver's condition. In this paper, we propose a face identification system in an unrestricted vehicle environment. The proposed method uses a near-infrared (NIR) camera to minimize the changes in facial images that occur according to the illumination changes inside and outside the vehicle. In order to process a face exposed to extreme light, the normal face image is changed to a simulated overexposed image using mean and variance for training. Thus, facial classifiers are simultaneously generated under both normal and extreme illumination conditions. Our method identifies a face by detecting facial landmarks and aggregating the confidence score of each landmark for the final decision. In particular, the performance improvement is the highest in the class where the driver wears glasses or sunglasses, owing to the robustness to partial occlusions by recognizing each landmark. We can recognize the driver by using the scores of remaining visible landmarks. We also propose a novel robust rejection and a new evaluation method, which considers the relations between registered and unregistered drivers. The experimental results on our dataset, PolyU and ORL datasets demonstrate the effectiveness of the proposed method.