Robust Discriminative Metric Learning for Image Representation

Metric learning has attracted significant attentions in the past decades, for the appealing advances in various realworld applications such as person re-identification and face recognition. Traditional supervised metric learning attempts to seek a discriminative metric, which could minimize the pairwise distance of within-class data samples, while maximizing the pairwise distance of data samples from various classes. However, it is still a challenge to build a robust and discriminative metric, especially for corrupted data in the real-world application. In this paper, we propose a Robust Discriminative Metric Learning algorithm (RDML) via fast low-rank representation and denoising strategy. To be specific, the metric learning problem is guided by a discriminative regularization by incorporating the pair-wise or class-wise information. Moreover, low-rank basis learning is jointly optimized with the metric to better uncover the global data structure and remove noise. Furthermore, fast low-rank representation is implemented to mitigate the computational burden and make sure the scalability on large-scale datasets. Finally, we evaluate our learned metric on several challenging tasks, e.g., face recognition/verification, object recognition, and image clustering. The experimental results verify the effectiveness of the proposed algorithm by comparing to many metric learning algorithms, even deep learning ones

Boost, Control, or Both of Korean Housing Market: 831 Countermeasures

Although the Korean government reported a housing supply ratio of more than 100% in the early 2000s, regional and class disparities in the Korean housing sector have not been correspondingly alleviated. Unfortunately, many Korean households are still enduring the economic burden caused by cyclical price variation, while many housing construction companies are on the verge of bankruptcy. To resolve the ever-expanding socioeconomic problems in the housing and real estate sector, the current Korean government proposed 831 Countermeasures, which has since met with much controversy. In an effort to address these issues, this paper utilizes a qualitative system dynamics model to elucidate and interrogate complex Korean housing mechanisms. By mapping bibliographical and experimental knowledge with causal loop diagrams, the positive and adverse effects of the 831 Countermeasures are also analyzed. Finally, based on the research findings, alternative policy guidelines are proposed that can be used to strengthen positive housing structures and obviate negative ones.

Requirements Analysis for Development of Off-Site Construction Project Management System: Focusing on Precast Concrete Construction

There has been increasing interest in the off-site construction (OSC) method in response to issues such as stagnant labor productivity, shortage of skilled workers, challenging site management, heightened safety and health-related regulations, and the push for carbon neutrality. Although efficient performance of an OSC project requires development of management techniques, and application of a management system that reflects the characteristics of the OSC projects, related technologies remain in their infancy. In this study, targeting precast concrete (PC) construction, which is one of the representative construction types of the OSC method, we derive the characteristics of OSC project management in six aspects: production place and time, production process, production method of construction, production method, production entity and facilities, and production environment. Based on this result, we further derived the requirements for developing an OSC project management system. Furthermore, based on the derived requirements, we constructed a system development scenario for the establishment of an installation plan and shipment requests. The managerial characteristics and requirements of the OSC project, presented in this study, provide the theoretical basis for developing OSC project management techniques, as well as guidance for the development of the OSC project management system in the future

Feasibility of using electrodermal activity responses to assess level of crowdedness of pedestrian paths

As urban populations grow, it's imperative to evaluate and enhance the quality of pedestrian paths from the user's perspective. Crowdedness, associated with discomfort and safety, is crucial in determining the overall walking quality and user experience. Previously utilized methods for measuring crowdedness, such as travel diaries and floating population surveys, were limited to collecting perceptual data from sporadic surveys with restricted spatial coverage. Similarly, methods based on CCTV or mobile service data have been used but present issues with blind spots and fail to consider pedestrian perspectives. Against this background, this study explores the feasibility of assessing crowdedness levels by measuring subjects' physiological responses in a laboratory setting based on visual images of real and virtual environments. This study hypothesizes that the amount of people or vehicles passing by affects the electrodermal activity (EDA) of pedestrians, indicating the comfort level of using the environment. Experimental EDA data were measured using a wearable device while the subjects were watching videos showing different pedestrian traffic flows. Representative EDA signal features (e.g., skin conductance responses) were extracted after data pre-processing. Noticeable changes in EDA responses are observed when subjects countered specific environmental variations, such as differing volumes of passing people, on pedestrian paths. The findings suggest that EDA data can be instrumental in differentiating crowdedness levels on pedestrian paths. This study contributes to the body of knowledge by demonstrating the potential of EDA data to characterize the crowdedness experienced by pedestrians. This aids in the development of a novel, quantitative method to gauge pedestrian path crowdedness and to discern contributing factors, such as path width

Korean public rental housing for residential stability of the younger population: analysis of policy impacts using system dynamics

To alleviate the burden of high residential costs for the younger population, the Korean government has recently implemented a public rental housing program for those who are vulnerable in their residential conditions and endure low quality of life. This program is not yet fully effective in achieving its policy aim because of lengthy construction periods and consistent vacancies (despite high demand). To address this issue, policy guidelines are sought. This study comprehensively models supply and demand of public rental housing and analyzes the effects of diverse policies on the rental housing system behaviour. To represent the rental housing system, system dynamics is applied which consists of continuous simulation based on causal relationships among variables encompassing their time-lagged effects (and in which system variables are highly interdependent). By testing the effects of policy variables of public rental housing delivery strategies upon the system, the developed model provides an in-depth understanding of policy impacts towards achieving a desired policy objective (in this case to accommodate more public rental housing demands by minimizing vacancy rates). The results provide guidelines for developing detailed policies for more efficient public rental housing project delivery, which can contribute to alleviating the residential problems of the younger population

Dynamic modeling for apartment brand management in the housing market

A company’s brand can be considered its most valuable asset. The known impact of branding has inspired a number of Korean construction companies to initiate a new marketing strategy, apartment branding, in the competitive market since the 1990s. As a result, the market-leading brands had stronger sales performances over non-branded apartments in the same residential district. However, major companies with well-known apartment brands still face challenges in managing brand equity constructs, particularly brand loyalty, due to the distinctive characteristics of constructed products (i.e., durability and costliness). To address this issue, this research develops qualitative system dynamics models to analyze the core mechanisms and problems of apartment brand equity building process and proposes long-term managerial strategies to overcome the problem of obtaining apartment brand loyalty. The research outcome is expected to support the strategic decision-making processes of apartment brand managers and to provide implications for further branding applications in other metropolitan areas anticipating a sharp increase in apartments

Protective effect of Korean Red Ginseng against chemotherapeutic drug-induced premature catagen development assessed with human hair follicle organ culture model

Background: Chemotherapy-induced alopecia (CIA) is one of the most distressing side effects for patients undergoing chemotherapy. This study evaluated the protective effect of Korean Red Ginseng (KRG) on CIA in a well-established in vitro human hair follicle organ culture model as it occurs in vivo. Methods: We examined whether KRG can prevent premature hair follicle dystrophy in a human hair follicle organ culture model during treatment with a key cyclophosphamide metabolite, 4-hydroperoxycyclophosphamide (4-HC). Results: 4-HC inhibited human hair growth, induced premature catagen development, and inhibited proliferation and stimulated apoptosis of hair matrix keratinocytes. In addition, 4-HC increased p53 and Bax protein expression and decreased Bcl2 protein expression. Pretreatment with KRG protected against 4-HC-induced hair growth inhibition and premature catagen development. KRG also suppressed 4-HC-induced inhibition of matrix keratinocyte proliferation and stimulation of matrix keratinocyte apoptosis. Moreover, KRG restored 4-HC-induced p53 and Bax/Bcl2 expression. Conclusion: Overall, our results indicate that KRG may protect against 4-HC-induced premature catagen development through modulation of p53 and Bax/Bcl2 expression

KOREAN REAL ESTATE MARKET AND BOSTING POLICIES: FOCUSING ON MORTGAGE LOANS

The Korean real estate market is currently slowing down due to the global economic crisis, which resulted from subprime mortgage crisis in the United States. In response, the Korean government has adopted various policies in an attempt to deregulate real estate speculation. For example, the Loan to value ratio (LTV) has been increased in order to stimulate housing supply, demand, and housing transactions. However, these policies could potentially result in a mortgage crisis due to an increase in over-amplified and high-risk derivatives in Korea`s secondary mortgage market. Consequently, the housing market could fall into such deep confusion that it will be even more difficult to perform empirically based housing market forecasting. Therefore, a comprehensive and systematic method is required to analyze the real estate financial market and the causal relationships between market influence factors. With an integrated perspective and an application of a system dynamics methodology, this paper proposes Korean Real Estate and Mortgage Market dynamics models based on the fundamental principles and causal loops of housing markets, which are determined by the economic activities of consumers, financial agencies, and real estate financing investors. The potential effects of the Korean government`s deregulation policies are also considered by focusing on the main factor of these policies: the mortgage loan.