• KOREAN JOURNAL OF CROP SCIENCE
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• v.50 no.4
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• pp.268-275
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• 2005

Early predictions of crop yields call provide information to producers to take advantages of opportunities into market places, to assess national food security, and to provide early food shortage warning. The objectives of this study were to identify the most useful parameters for estimating yields and to compare two model selection methods for finding the 'best' model developed by multiple linear regression. This research was conducted in two 65ha corn/soybean rotation fields located in east central South Dakota. Data used to develop models were small temporal variability information (STVI: elevation, apparent electrical conductivity $(EC_a)$, slope), large temporal variability information (LTVI : inorganic N, Olsen P, soil moisture), and remote sensing information (green, red, and NIR bands and normalized difference vegetation index (NDVI), green normalized difference vegetation index (GDVI)). Second order Akaike's Information Criterion (AICc) and Stepwise multiple regression were used to develop the best-fitting equations in each system (information groups). The models with $\Delta_i\leq2$ were selected and 22 and 37 models were selected at Moody and Brookings, respectively. Based on the results, the most useful variables to estimate corn yield were different in each field. Elevation and $EC_a$ were consistently the most useful variables in both fields and most of the systems. Model selection was different in each field. Different number of variables were selected in different fields. These results might be contributed to different landscapes and management histories of the study fields. The most common variables selected by AICc and Stepwise were different. In validation, Stepwise was slightly better than AICc at Moody and at Brookings AICc was slightly better than Stepwise. Results suggest that the Alec approach can be used to identify the most useful information and select the 'best' yield models for production fields.

• Proceedings of the Korea Society of Environmental Toocicology Conference
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• 1993.06a
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• pp.4-5
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• 1993

Toxicity tests in our laboratory are conducted usually with mass-reared organisms. They are under the same environmentel conditions throughout seasons and are supplied at specific age. A total of 38 species of aquatic organisms are being reared. We have attempted to establish pruified strains or to select clones of various parthenogenic organisms. The merits or demerits of our culturing test organisms are discussed. The differences in the susceptibility among clones or strains of test organism are also discussed. For a single species test, algae, daphnia, fish are often used. However, we usually use early stages, but occasionally, adults fish are used for reproduction tests. As an another important aspect, the toxicity through food chains has been studied. In this study, we select a pair of species belonging different trophic levels. The differences between single species tests and multispecies tests will be discussed. Even a single species test intends to assess the effects of chemicals on ecosystem levels, however, this idea is not applicable to ecosystems. Single species tests with standard organisms and multispecies tests are contradictory in concept. One type of multispecles tests is indoor microcosms being composed of severel species artificially assembled, and another is composed of natural components (both indoor and outdoor). We have used three types of outdoor mesocosms using ponds and three types of artificial streams. The mesocosms is useful to not only to analyze the floral or faun61 changes but also to study the fate or behaviour of chemicals in naturd environments. Lastly, usefulness of the field observation or experiments or semi-field experiments will be discussed. This will enhance the exploitation of early warning systems utilizing indicator organisms or animal behaviour.aviour.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.753-756
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• 2015

Background: Red cell distribution width (RDW) is one of the standard parameters with blood cell counts. Much previous research has indicated that it increases in cases of systemic inflammation or cardiametabolic incident. However, information on the relation of RDW with solid tumors causing systemic inflammation is limited. In the present research, we examined the relation of RDW with malignant and benign lesions of the colon. Materials and Methods: 115 patients with colon polyps (group 1), and 30 with colon cancer (group 2) who were diagnosed histopathologically in our clinic between January 2010-January 2013 were scanned retrospectively. Patients with anemia, hematologic diseases and active inflammation were excluded. RDW, mean corpuscular volume (MCV), hemoglobin (Hgb) and platelet (Plt) measurements were recorded and their relations with the malignant and benign lesions of the colon were examined. Results: Both groups were similar in age and gender distribution. RDW values of patients with colon cancer were significantly higher than the patients with colon polyp (p=0,01). No significant differences were detected between the two groups in terms of MCV and Plt values (p>0,05). Conclusions: RDW can be used as an early warning biomarker for solid colon tumors. Further prospective research is required on the relations of cheap and easily measured RDW parameters with colon malignancies.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.909-916
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• 2024

The emergence of Building Information Modelling (BIM), reality data, Virtual Reality (VR), and Augmented Reality (AR) has significantly enhanced the collaboration between stakeholders in construction management. The utilization of VR/AR devices holds considerable potential for monitoring safety in complex and constrained working environments on the construction site. On the other hand, near-miss incidents remain an important early sign of struck-by accidents. However, research on early warning and prevention methods for this risk is still limited. This paper, therefore, presents a framework for on-site and off-site collaborative safety monitoring framework using augmented and virtual reality for near-miss incidents. In the proposed framework, three phases to develop a VR/AR-based safety monitoring system include (1) construction safety simulation environment, (2) localization-based interaction system, and (3) safety monitoring system. The system can undertake the processing of data and enables communication among disparate VR/AR devices. VR clients are observational tools and offer guidance, while the AR client stays onsite for construction tasks. All clients connect to a processing computer, which also works as a host. The system embedded in the AR device can trigger an alarm or receive signals from the VR client when a near-miss issue happens. Additionally, all device clients possess the capability to share data acquired from onsite monitoring cameras, thereby fostering effective discussions and decision-making. The efficacy of this cross-platform system has been validated through the implementation of an outdoor coordination case study.

• The Journal of Engineering Geology
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• v.24 no.2
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• pp.191-199
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• 2014

We describe a method for detecting slope instability in flume tests using pore pressure and water content data in conjunction with a statistical control chart analysis. Specifically, we conducted univariate statistical analysis on x-MR control chart data (pore pressure and water content) collected at several points along the flume slope, which we separated into three parts: upper, middle, and lower. To assess our results in the context of landslide forecasting and warning systems, we applied control limit lines at $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$ levels of uncertainty. In doing so, we observed that dispersion time varies depending on the control limit line used. Moreover, the detection of instabilities is highly dependent on the position and type of sensor. Our findings indicate that different characteristics of the data on various factors predict slope failure differently and these characteristics can be identified by univariate statistical analysis. Therefore, we suggest that a univariate statistical approach is an effective method for the early detection of slope instability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.5006-5022
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• 2017

Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

• Journal of international Conference on Electrical Machines and Systems
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• v.3 no.4
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• pp.428-432
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• 2014

Rotating machines are an integral part of large electrical power machinery in most of the industries. Any degradation or outages in the rotating electric machinery can result in significant losses in productivity. It is critical to monitor the equipment for any degradation's so that it can serve as an early warning for adequate maintenance activities and repair. Prior research and field studies have indicated that the rotating machines have a particular type of signal structure during the initial start-up transient. A machine performance can be studied based on the effect of degradation in signal parameters. In this paper a data-acquisition system and the FFT algorithm has been design and model using the MATLAB and Simulink. The implementation had been carried out on the TMS320 DSP Processor and various testing and verification of the machine performance had been carried out. The results show good agreement with expected results for both simulated and real-time data. The real-time data from AC water pumps which have rotating motors built-in were collected and analysed. The FFT algorithm provides frequency response and based on this frequency response performance of the machine had been measured.The FFT algorithm provides only approximation about the machine performances.

• Molecular & Cellular Toxicology
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• v.4 no.3
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• pp.199-204
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• 2008

The bio-molecules involved in defense mechanisms can be used as efficient biomarkers for physiological changes in organisms caused by both of internal and external stress. Thus, the expression level of genes which encoding such molecules serve as critical 'early warning system' for environmental assessment as well as health diagnosis of biological organisms. In this study, Cytochrome P450, Heat shock protein 90, Ubiquitin and ${\beta}$-actin gene were isolated for the first time from a red alga Gracilaria textorii. The quantitative differential gene expression analyses of three genes, GteCYP1A, GteHsp90 and Gte-UB, were carried out in G. textorii sporophytes collected from two different localities, polluted Sujeong (Masan, Korea) and potentially unpolluted Danggeum (Daemaemuldo Is., Korea). The transcripts of all three tested genes were highly expressed in the Sujeong population. The results suggest: 1) the Sujeong site was more polluted than the Danggeum site; 2) G. textorii could be applicable to marine environment monitoring in coastal regions.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.689-692
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• 1996

The environment surrounded by industries is represented by the 3Cs : Customers, Competition, and Changes. The 3Cs drive industries to pursue external business targets such as customer's needs and marketplaces with BPR (Business Process Reengineering). BPR addresses core business process. One of these core business processes is product development. This product development process has been reengineered by the concept of CE (Concurrent Engineering). The aim of the paper is to build frameworks of CE to clarify the CE concept. This paper begins with investigating the product development process from the perspectives of three drivers: cost, quality and speed. CE frameworks are then followed. The first frmework is concerned with the CE definition and thus three keyphrases are extracted : from the outset, concurrent design and systematic approach. Concerned with the CE implementation, the second framework is composed of five components: generalist & specialist, cross-function team, enabling tools & techniques, success metrics, and total visibility. This paper concludes that the CE practice is hard to achieve because of the 'dont't-tell-them-early' attitude of upstream people, and the 'wait-and-see' attitude of downstream people. As resolution, a change management program is recommended that changes an employees mind-set. This paper also supposes computer systems which facilitate and keep automatic track of the CE process as engineered. Finally it gives a warning that computer systems alone do not guarantee success without being preceded by process re-engineering.

• Journal of Korea Technology Innovation Society
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• v.1 no.1
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• pp.117-124
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• 1998

Corporations are pursuing maximum returns from their R&D investment. They are also interested in sound measures to quantify returns. In fact, they use various measures and criteria for measuring returns from the R&D investment. But the fundamental problem is that there is no generic and widely acceptable measures and criteria. To make things more complicated, measures are very powerful and influential to the people in the corporations. Herbert Simon already indicated that people do many things but people usually do their best for the only tasks which are measured. Many researchers, like Chester(1995), are interested in R&D productivity measures and risks because what the company measures really influence R&D people and output. This article present design concepts of the R&D project selection and evaluation system in POSCO(Pohang Iron & Steel Company). This is an output extract from the 6-month joint activities with POSRI(POSCO Research Institute) researchers and POSCO R&D personnel. Process changes, new organizations and new selection and evaluation criteria are developed to improve R&D performance and to enhance technology management of the POSCO. This article covers new selection and evaluation criteria only. We would like to share our experience about how we redesign the selection and evaluation of R&D projects. We also bring insights how we seamlessly integrate 4 different project selection and evaluation steps as a whole. We hope that this case will give you a clue to improve your R&D management.