• The Journal of Asian Finance, Economics and Business
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• v.7 no.4
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• pp.205-211
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• 2020

The study aims to assess factors affecting intention to purchase green products in Vietnam. The study employs samples from customers who have actually experienced green consumption in Vietnam. The samples were collected by convenient sampling methods. The survey obtained 206 responses with full information. The survey was conducted from October 2019 to January 2020. The measurement scale was a 5-point scale with 1- completely disagree and 5- strongly agree. This study employs factor analysis and structural equation modelling analysis. The results showed that the social and environment sustainability awareness have positive effects on altruism of customers who are interested in green consumption. Altruism also has the same direction on green purchase intention. Besides, the attitude toward buying green and health consciousness affects green purchase intention. At the same time, the altruism and attitude towards buying green products also influence positively on green purchase intention. Besides, the health consciousness positively affects attitude towards buying green products. The results show that the health consciousness has a negative impact on intention to purchase green products. The findings suggest that it is necessary to raise customers' health consciousness, customers' altruism from disseminating knowledge about environmental protection as well as society to enhance the green consumption in Vietnam.

• The Korean Journal of Financial Management
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• v.26 no.2
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• pp.181-201
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• 2009

This study is on the forecasting performance analysis of range volatility estimators(Parkinson, Garman and Klass, and Rogers and Satchell) relative to historical one using two-scale realized volatility estimator as a benchmark. American sub-prime mortgage loan shock to Korean stock markets happened in sample period(January 2, 2006~March 10, 2008), so the structural change somewhere within this period can make a huge influence on the results. Therefore sample was divided into two sub-samples by May 30, 2007 according to Zivot and Andrews unit root test results. As expected, the second sub-sample was much more volatile than the first sub-sample. As a result of forecasting performance analysis, Rogers and Satchell volatility estimator showed the best forecasting performance in the full sample and relatively better forecasting performance than other estimators in sub-samples. Range volatility estimators showed better forecasting performance than historical volatility estimator during the period before the outbreak of structural change(the first sub-sample). On the contrary, the forecasting performance of range volatility estimators couldn't beat that of historical volatility estimator during the period after this event(the second sub-sample). The main culprit of this result seems to be the increment of range volatility caused by that of intraday volatility after structural change.

• Structural Engineering and Mechanics
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• v.76 no.4
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• pp.479-489
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• 2020

This paper proposed a novel form of reinforced concrete (RC) shear wall confined with boundary columns. The structural effect of applying steel fiber reinforced concrete (SFRC) in the wall-column systems was studied. Three full-scale wall samples were constructed including two RC wall-RC column samples with different stirrup ratios and one RC wall-SFRC column sample. Low frequency cyclic testing was carried out to investigate the failure modes, hysteretic behavior, load-bearing capacity, ductility, stiffness degradation and energy dissipation. ABAQUS models were set up to simulate the structural behavior of tested samples, and good agreement was achieved between numerical simulation and experimental results. A further supplementary parametric study was conducted based on ABAQUS models. Both experimental and numerical results showed that increasing stirrup ratio in boundary columns did not affect much on load bearing capacity or stiffness degradation of the system. However, applying SFRC in boundary columns showed significant enhancement on load bearing capacity. Numerical simulation also shows that the structural performances of RC wall-SFRC column system were comparable to a wall-column system fully with SFRC.

• Geomechanics and Engineering
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• v.23 no.3
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• pp.227-244
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• 2020

Earthen structures have an excellent bioclimatic performance, but they are vulnerable against earthquakes. In order to investigate the edification process and costs, a full-scale rammed soil house was constructed in 2004. In 2016-2019, it was studied its seismic damage, durability and degradation process. During 2004-2016, the house presented a relatively good seismic performance (M_w=5.6-6.4). The damaged cover contributed in the fast deterioration of walls. In 2018 it was observed a partial collapse of one wall due to recent seismicity (M_w=5.6-6.1). The 15-year-old samples presented a reduced compressive strength (0.040 MPa) and a minimum moisture (1.38%). It is estimated that the existing house has approximately a remaining 20% of compressive strength with a degradation of about 5.4% (0.0109 MPa) per year (considering a time frame of 15 years) if compared to the new soil samples (0.2028 MPa, 3.52% of moisture). This correlation between moisture and compressive strength degradation was compared with the study of new soil samples at the same construction site and compared against the extracted samples from the 15-year-old house. At 7-14-days, the specimens presented a similar compressive strength as the degraded ones, but different moisture. Conversely, the 60-days specimens shown almost five times more strength as the existing samples for a similar moisture. It was observed in new rammed soil that the lower the water content, the higher the compressive/shear strength.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.219-227
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• 2023

The US National Science Foundation's National Ecological Observatory Network (NEON) is a continental-scale program intended to provide open data, samples, and infrastructure to understand changing ecosystems for a period of 30 years. NEON collects co-located measurements of drivers of environmental change and biological responses, using standardized methods at 81 field sites to systematically sample variability and trends to enable inferences at regional to continental scales. Alongside key atmospheric and environmental variables, NEON measures the biodiversity of many taxa, including microbes, plants, and animals, and collects samples from these organisms for long-term archiving and research use. Here we review the composition and use of NEON resources to date as a whole and specific to biodiversity as an exemplar of the potential of national research infrastructure to contribute to globally relevant outcomes. Since NEON initiated full operations in 2019, NEON has produced, on average, 1.4 M records and over 32 TB of data per year across more than 180 data products, with 85 products that include taxonomic or other organismal information relevant to biodiversity science. NEON has also collected and curated more than 503,000 samples and specimens spanning all taxonomic domains of life, with up to 100,000 more to be added annually. Various metrics of use, including web portal visitation, data download and sample use requests, and scientific publications, reveal substantial interest from the global community in NEON. More than 47,000 unique IP addresses from around the world visit NEON's web portals each month, requesting on average 1.8 TB of data, and over 200 researchers have engaged in sample use requests from the NEON Biorepository. Through its many global partnerships, particularly with the Global Biodiversity Information Facility, NEON resources have been used in more than 900 scientific publications to date, with many using biodiversity data and samples. These outcomes demonstrate that the data and samples provided by NEON, situated in a broader network of national research infrastructures, are critical to scientists, conservation practitioners, and policy makers. They enable effective approaches to meeting global targets, such as those captured in the Kunming-Montreal Global Biodiversity Framework.

• Clinics in Shoulder and Elbow
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• v.18 no.2
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• pp.61-67
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• 2015

Background: The purposes of the study were to examine rotator cuff tendon degeneration with respect to harvesting location, to determine a rationale for debridement of the torn end, and thus, to determine adequate debridement extent. Methods: Twenty-four patients with a full-thickness rotator cuff tear were included in the study. Tendon specimens were harvested during arthroscopic rotator cuff repair from three locations; from torn ends after minimal regularization of fraying (native end group, NE group), from torn ends after complete freshening of the frayed end (freshened end group, FE group), and from the macroscopically intact portion just distal to the musculotendinous junction (musculotendinous junction group, MTJ group). Control samples were harvested from patients admitted for surgery for proximal humerus fracture. Harvested samples were evaluated using a semi-quantitative grading scale. Results: Mean total degeneration scores in the NE group ($13.3{\pm}3.21$), the FE group ($12.5{\pm}2.30$), and in the MTJ group ($10.8{\pm}3.10$) were significantly higher than those in the normal control group ($5.0{\pm}2.87$; all p<0.001). Mean total degeneration score in the NE group was significantly higher than that in the MTJ group (p=0.012), but was not from that of the FE group. Mean total degeneration score in the FE group was not significantly different from that of the MTJ group. Conclusions: Tendon degeneration exists throughout the entire tendon to the macroscopically intact portion of full-thickness rotator cuff tear. Therefore, aggressive debridement to grossly normal appearing, bleeding tendon is unnecessary for enhancing healing after repair.

• Journal of Ecology and Environment
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• v.47 no.4
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• pp.187-192
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• 2023

The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.11-18
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• 2004

In this paper, an efficient model reduction scheme is presented for large scale dynamic systems. The method is founded on a modal analysis in which optimal eigenvalue is extracted from time samples of the given system response. The techniques we discuss are based on classical theory such as the Karhunen-Loeve expansion. Only recently has it been applied to structural dynamics problems. It consists in obtaining a set of orthogonal eigenfunctions where the dynamics is to be projected. Practically, one constructs a spatial autocorrelation tensor and then performs its spectral decomposition. The resulting eigenfunctions will provide the required proper orthogonal modes(POMs) or empirical eigenmodes and the correspondent empirical eigenvalues (or proper orthogonal values, POVs) represent the mean energy contained in that projection. The purpose of this paper is to compare the reduced order model using Karhunen-Loeve expansion with the full model analysis. A cantilever beam and a simply supported plate subjected to sinusoidal force demonstrated the validity and efficiency of the reduced order technique by K-L method.

• Proceedings of the Korea Institute of Applied Superconductivity and Cryogenics Conference
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• 2000.02a
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• pp.147-149
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• 2000

Samsung Superconducting Test Facility (SSTF) will be built at SAIT, Taejeon. The superconducting cables to be used for KSTAR magnets are going to be tested in SSTF. The background magnet in SSTF is needed to simulate harsh magnetic environment for testing short CICC samples as well as full-scale magnets. The main coils can make central magnetic field of up to 8 Tesla and the blip coils can maintain fast ramping rate of 20T/s. The cancellation coils reduce the disturbance of main coils due to blip coils. The magnetic field distribution of these coils has been obtained with finite element method as well as the direct integration method.