• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.5
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• pp.984-1003
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• 2020

The global fashion industry produces significant carbon emission and micro-plastics in oceans. Studies on sustainable design methods as such environmental issues in fashion are becoming intensely problematic. This study conducted a case study on 100 upcycle fashion brands to propose strategical upcycle fashion designs to compete in a sustainable fashion market. A literature review indicated that 3 types of textile wastes are generated as upcycling materials: post-producer, pre-consumer and post-consumer. Wastes are categorized together with 3 types of techniques: redesigning, reconstruction and handcrafting. This research derived 7 types of upcycle fashion designs that have the following features: to make luxury upcycle fashion products, to make sustainable grunge looks, to re-evaluate deadstocks, to recover vintage clothes, to convert waste into craft-arts, to offer solutions for damaged products, and to make zero-waste small fabric waste. The study results show that key drivers in the upcycle fashion design are the redesignability of materials and technique-related costs. This study implies that adopting appropriate design features can be a useful strategy for designers. New technologies will solve current problems and encourage them to design products in a new circular value system.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.705-711
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• 2022

Roadway lighting is an integral element of a highway system. Luminaires on roadways provide viewing conditions for drivers and pedestrians during nighttime in order to improve safety. It is time-consuming and labor-intensive to manually measure roadway illuminance at predetermined spots with a handheld illuminance meter. To improve the efficiency of illuminance measurement, a remote-control electrical cart and a drone were utilized to carry an illuminance meter for the measurements. The measurements were performed on the marked grid points along the pavement. To measure the illuminance manually, one person measures illuminance at each grid point with the handheld meter and another person records the illuminance value. To measure the illuminance with the remote-control cart, the illuminance meter is attached to the cart and it measures illuminance values continuously as the cart moves along the grid lines. With the drone, the meter records the illuminance continuously as the drone carries the meter and flies along the grid line. Because the drone can fly at different heights, the measurements can be done at different altitudes. The illuminance measurements using the cart and the drone are described in detail and compared with manual measurements in this paper. It is shown through this study that automated measurements can greatly improve the efficiency of roadway illuminance data measurements.

• Journal of Korean Society of Transportation
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• v.20 no.5
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• pp.23-31
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• 2002

The headway of vehicles entering an intersection is closely related with the saturation flow rate and is a basic parameter required for determining the saturation headway and the start-up lost delay. Since such headway value reflects the drivers' behaviors and features of the intersection, all intersections don't have an equal value, but are affected by number and location of their lanes, changing types, local characteristics and time zone. Accordingly, this study attempted to suggest proper values on the basis of data by investigating headway in lanes. Number of exclusive through lanes was divided into single lane, double lanes and triple lanes, the locations of lanes were divided into inside lane, central lane and outside lane. As a result of investigating the headway, single through lane, double through lanes-inside lane, and triple through lane-outside lane showed as 1.73 sec., 1.71 sec. and 1.93sec., respectively. The result of calculating the area factor of business areas by fixing 1.00 for the residental area and applying relation between headway and saturation flow rate was 0.96. In the case of start-up lost delay lead dual left turn and directional separation were 1.41 sec. and 3.27 sec., respectively, showing the great difference. Therefore, different start-up lost delay according to changing type should be applied.

• Management & Information Systems Review
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• v.4
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• pp.257-284
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• 2000

According as the drivers increase who have their cars, the comprehensive studies on the automobile for the traffic safety have been raised as the important problems. Visual Recognition System for radio-controled driving is a part of the sensor processor of Unmanned Autonomous Vehicle System. When a driver drives his car on an unknown highway or general road, it produces a model from the successively inputted road traffic information. The suggested Recognition System of the Road Traffic Safety Information Board is to recognize and distinguish automatically a Road Traffic Safety Information Board as one of road traffic information. The whole processes of Recognition System of the Road Traffic Safety Information Board suggested in this study are as follows. We took the photographs of Road Traffic Safety Information Board with a digital camera in order to get an image and normalize bitmap image file with a size of $200{\times}200$ byte with Photo Shop 5.0. The existing True Color is made up the color data of sixteen million kinds. We changed it with 256 Color, because it has large capacity, and spend much time on calculating. We have practiced works of 30 times with erosion and dilation algorithm to remove unnecessary images. We drawing out original image with the Region Splitting Technique as a kind of segmentation. We made three kinds of grouping(Attention Information Board, Prohibit Information Board, and Introduction Information Board) by RYB( Red, Yellow, Blue) color segmentation. We minimized the image size of board, direction, and the influence of rounding. We also minimized the Influence according to position. and the brightness of light and darkness with Eigen Vector and Eigen Value. The data sampling this feature value appeared after building the learning Code Book Database. The suggested Recognition System of the Road Traffic Safety Information Board firstly distinguished three kinds of groups in the database of learning Code Book, and suggested in order to recognize after comparing and judging the board want to recognize within the same group with Nearest Neighborhood Decision Making.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.125-144
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• 2022

When a variable message signs (VMS) system displays false information related to traffic safety caused by malicious attacks, it could pose a serious risk to drivers. If the normal message patterns displayed on the VMS system are learned, it would be possible to detect and respond to the anomalous messages quickly. This paper proposes a method for detecting anomalous messages by learning the normal patterns of messages using a bi-directional generative pre-trained transformer (GPT) network. In particular, the proposed method was trained using the normal messages and their system parameters to minimize the corresponding negative log-likelihood (NLL) values. After adequate training, the proposed method could detect an anomalous message when its NLL value was larger than a pre-specified threshold value. The experiment results showed that the proposed method could detect malicious messages and cases when the system error occurs.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.11
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• pp.537-542
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• 2017

Aggressive driving is a major cause of car accidents. Previous studies have mainly analyzed young driver's aggressive driving tendency, yet they were only done through pure clustering or classification technique of machine learning. However, since elderly people have different driving habits due to their fragile physical conditions, it is necessary to develop a new method such as enhancing the characteristics of driving data to properly analyze aggressive driving of elderly drivers. In this study, acceleration data collected from a smartphone of a driving vehicle is analyzed by a newly proposed ECA(Enhanced Clustering method for Acceleration data) technique, coupled with a conventional clustering technique (K-means Clustering, Expectation-maximization algorithm). ECA selects high-intensity data among the data of the cluster group detected through K-means and EM in all of the subjects' data and models the characteristic data through the scaled value. Using this method, the aggressive driving data of all youth and elderly experiment participants were collected, unlike the pure clustering method. We further found that the K-means clustering has higher detection efficiency than EM method. Also, the results of K-means clustering demonstrate that a young driver has a driving strength 1.29 times higher than that of an elderly driver. In conclusion, the proposed method of our research is able to detect aggressive driving maneuvers from data of the elderly having low operating intensity. The proposed method is able to construct a customized safe driving system for the elderly driver. In the future, it will be possible to detect abnormal driving conditions and to use the collected data for early warning to drivers.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.287-296
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• 2015

Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.1
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• pp.13-31
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• 2019

Green spaces are recognised for the benefits. They bring to the quality of people's lives. However, since the 1980s there has been a general increase in poorly-managed green spaces. In an attempt to address this issue, green space policy has changed its focus on green space management through the gradual introduction of green space evaluation tools, such as the Green Flag Award (GFA). The GFA, as an established green space evaluation tool in the UK, reflects a shift in policy drivers of green spaces management. However, there is a lack of research investigating the contextualisation between a wide range of policy contexts and such green space evaluation tools (the GFA in this study). The aims of this study are therefore to explore the development of green space evaluation since the late 1990s, with respect to the growth of the GFA and its impact on other evaluation tools across the UK and several countries. To address the aims, this study employs in-depth literature reviews on UK green space policy mainly conducted by government. In addition, case studies are presented, focusing on the GFA and independent green space evaluation tools intrinsically derived from the GFA in the UK's cities and Nordic countries. Results show that based on the awareness of the severity of declining standards of green spaces, newly emerging policy arrangements have been adopted to address negative issues, which affect the standard of green spaces such as the transfer of responsibility for green space management, the implementation of Compulsory Competitive Tendering and ongoing budget cuts. Significantly, the GFA's indicators reflect the emerging changes of economic and social contexts associated with green spaces management where, in particular, the prospect of continuous budget cuts, which encourages communities to become involved in green space management. The GFA has widely contributed to leading such UK's cities and other countries to be able to create their independent green space evaluation tools in different approaches based on stakeholders' (mainly community) involvement in the decision-making process of green space evaluation. In conclusion, this study implies that successful green space evaluation tools do embody the value of green spaces and address drivers of emerging green space management with correspondence to the context of policy arrangements. Importantly, stakeholders have an opportunity to be involved in a partnership in the decision-making process through some green space evaluation tools. It is hoped that for well-managed green spaces this study will contribute valuable knowledge to our existing understanding of green space management in an era of austerity.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.27-34
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• 2010

During the past 10 years, sales of luxury goods increased significantly to more than US$ 130 billion in 2007. In this industry, more than half of the revenue comes from Asia where the average income has risen significantly, and the demand for luxury products is forecast to grow rapidly. Purchasing luxury brands appears to be an intriguing social phenomenon that is profitable for companies in this region. As a newly developed country, Korea is one of the most attractive luxury markets in Asia. Currently, a total of 120 luxury fashion brands have entered the Korean market, primarily in luxury districts in Seoul where the competition is fierce. The purposes of this study are to: (1) identify antecedents of attitude toward luxury brands, (2) examine the effect of attitudes toward luxury brands on customer equity, (3) determine the impact of attitudes toward luxury brands on customer lifetime value, and (4) investigate the influence of customer equity on customer life time value. Previous studies have examined materialism, social need, experiential need, need for uniqueness, conformity, and fashion involvement as antecedents of attitude toward luxury brands. Richins and Dowson (1992) suggested that that materialism influences consumption behavior relative to quantity of goods purchased. Nueno and Quelch (1998) reported that the ownership of luxury brands conveys information related to the owner's social status, communicates an image of success and prestige, and is a determinant of purchase behavior. Experiential need is recognized as an important aspect of consumption, especially for new products developed to meet consumer demand. Since luxury goods, by definition are relatively scarce, ownership of these types of products may fulfill consumers' need for uniqueness. In this study, value equity, relationship equity, and brand equity are examined as drivers of customer equity. The sample (n = 114) was undergraduate and graduate students at two private women's universities in Seoul, Korea. Data collection was conducted using a self-administered questionnaire survey in March, 2009. Data analysis included descriptive statistics, factor analysis, reliability analysis, and regression analysis using SPSS 15.0 software. Data analysis resulted in a number of conclusions. First, experiential need and fashion involvement positively influence participants' attitude toward luxury brands. Second, attitude toward luxury brands positively influences brand equity, followed by value equity and relationship equity. However, there is no significant relationship between attitude toward luxury brand and customer lifetime value. Finally, relationship equity positively influences customer lifetime value. In conclusion, young consumers are an important potential consumer group that tries different brands to discover the ones most suitable for them. Luxury marketers that use effective marketing strategies to attract and engender loyalty among this potentially lucrative consumer group may increase customer equity and lifetime value.

• Food Science and Preservation
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• v.21 no.5
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• pp.618-626
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• 2014

The physicochemical characteristics and consumer perceptions of two Fuji cultivars (Fuji and Royal Fuji) with six different size groups (3D: 30~39, 4D: 40~49, 5D: 50~59, 6D: 60~69, 7D: 70~79, and 8D: 80~89 apples/15 kg) were investigated to identify the ideal size and the drivers of consumer acceptability of apples. For the physicochemical characteristics, the weight, volume, specific volume, L, a, and b colors, hardness, pH, acidity, and brix of apples were measured. A total of 100 consumers were asked to mark the intensity of the characteristics (size, redness, glossiness, surface roughness, apple odor, apple flavor, sweetness, sourness, hardness, crunchiness, and toughness) to determine the ideal characteristics of apples before they were asked to taste the apple products. The consumers evaluated the apple samples in terms of their appearance, odor, flavor, texture, and overall acceptability; the consumers' intent to purchase such apples and willingness to pay for them; and the intensity of the aforementioned characteristics. Compared to the ideal characteristics of apples, the actual apple samples were rated low in their apple odor, apple flavor, acidity, sweetness, hardness, and crispness. The ideal size of the apples was between 4D and 5D. Their overall acceptability was highly affected by their flavor, followed by their texture, odor, and appearance. The acceptability of the appearance was highly correlated with the glossiness (r = 0.80), volume, weight, redness (r = 0.73), and size (r = 0.72). The consumer acceptability of the apples increased with the decreased pH and the increased Brix, hardness, and color b values of the peeled apples. The apple flavor, sweetness, hardness, crispiness, juiciness, and toughness during mastication were noted as sensory drivers of consumer acceptability.