• Journal of KIISE:Computer Systems and Theory
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• v.35 no.7
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• pp.354-360
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• 2008

Power-related issues have become important considerations in current generation microprocessor design. One of these issues is that of elevated on-chip temperatures. This has an adverse effect on cooling cost and, if not addressed suitably, on chip reliability. In this paper we investigate the general trade-offs between temporal and spatial hot spot mitigation schemes and thermal time constants, workload variations and microprocessor power distributions. By leveraging spatial and temporal heat slacks, our schemes enable lowering of on-chip unit temperatures by changing the workload in a timely manner with Operating System (OS) and existing hardware support.

• Journal of Electrical Engineering and Technology
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• v.1 no.1
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• pp.1-7
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• 2006

In an electricity market, the spot market is normally integrated with a forward or future market. The advantage of the forward market is to allow the market participants to deal in a part or the whole trading portfolio at a fix price in advance and to avoid risk associated to the uncertain price of the spot market. Japan has introduced a continuous auction base forward market from April 2005. This paper analyzes the Japanese forward market rules and operations, and introduces a new algorithm that may improve the efficiency of the market itself. The proposed algorithm enables us to give consideration to the specific characteristics of the power system and to integrate them in the auction mechanism. The benefits of the proposed algorithm are verified on an electronic simulation platform and the results described in this paper.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1287-1292
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• 2018

In case of fire, the information related with the fire need to be provided to fire fighters in order to extinguish the fire efficiently. However, existing fire detection systems have the problem not to provide the data of the fire to fire fighters visually. In this paper, we propose the fire spot system using a cloud server to solve this problem. In the proposed system, the sensors installed in a building collect the gas and temperature data and store them into the cloud database using a wireless network. For fire fighters in the field, the details and history of the fire spot are displayed visually on top of the blue print retrieved from the cloud database using a smart device.

• Korean Journal of Agricultural and Forest Meteorology
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• v.16 no.2
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• pp.114-124
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• 2014

For classifying fire damaged areas and analyzing burn severity of two large-fire areas damaged over 100 ha in 2011, three methods were employed utilized supervised classification, unsupervised classification and Normalized Difference Vegetation Index (NDVI). In this paper, the post-fire imageries of SPOT were used to compute the Maximum Likelihood (MLC), Minimum Distance (MIN), ISODATA, K-means, NDVI and to evaluate large-scale patterns of burn severity from 1 m to 5 m spatial resolutions. The result of the accuracy verification on burn severity from satellite images showed that average overall accuracy was 88.38 % and the Kappa coefficient was 0.8147. To compare the accuracy between burn severity and field survey at Uljin and Youngduk, two large fire sites were selected as study areas, and forty-four sampling plots were assigned in each study area for field survey. The burn severities of the study areas were estimated by analyzing burn severity (BS) classes from SPOT images taken one month after the occurrence of the fire. The applicability of composite burn index (CBI) was validated with a correlation analysis between field survey data and burn severity classified by SPOT5, and by their confusion matrix. The result showed that correlation between field survey data and BS by SPOT5 were closely correlated in both Uljin (r = -0.544 and p<0.01) and Youngduk (r = -0.616 and p<0.01). Thus, this result supported that the proposed burn severity analysis is an adequate method to measure burn severity of large fire areas in Korea.

• The Plant Pathology Journal
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• v.17 no.5
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• pp.264-270
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• 2001

The effects of leaf extracts of 14 different non-host plant species on in vitro conidial germination of Phaeoisariopsis personata, the causal organism of late leaf spot(LLS) of groundnut were evaluated. Aqueous and ethanol leaf extracts of Datura metel, Lawsonia inermis and aqueous leaf extracts of Sphaeranthus indicus at 25%(w/v) concentration completely inhibited the conidial germination of P. personata both at 24h and 48h after incubation. Aqueous leaf extracts of Blumea bifoliata, Eucalyptus globules, Ocimum sanctum and Pongamia pinnata, and ethanol leaf extracts of Azadirachta indica and S. indicus inhibited the conidial germination by >90%. Aqueous and ethanol leaf extract of L. inermis and S. indicus were highly inhibitory to conidial germination up to 1% concentration. Aqueous and ethanol leaf extracts of D. metel and ethanol leaf extract of A. indica were highly inhibitory to P. personata even at 0.01% (100 ppm) concentration. Ethanol leaf extract of A. indica up to $80^{\circ}$, aqueous leaf extracts of D. metel and S. indicus up to $100^{\circ}$, and L. inermis up to $60^{\circ}$, were highly stable and retained their fungitoxic effects. Extract of D. metel was antifungal even after 180 days when it was stored both at room temperature and $4^{\circ}$. Aqueous leaf extract of D. metel at 2% concentration effectively reduced the development of LLS by >60%, under greenhouse conditions both in prophylactic and simultaneous applications. Extracts of D. metel could be a potential economical and an eco-frendly alternative for control of late leaf spot, and its efficacy under field conditions is further being evaluated.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.115-127
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• 2018

This study aims to propose management strategies of ventilation paths for improving urban thermal environments. For this purpose, Gimhae-si in Gyeongsangnamdo was selected as a study area. We analyzed hot spots and cool spots in Gimhae by using Landsat 8 satellite image data and spatial statistical analysis, and finally derived the vulnerable areas to thermal environment. In addition, the characteristics of ventilation paths including wind direction and wind speed were analyzed by using data of the wind resource map provided by Korea Meteorological Administration. As a result, it was found that a lot of hot spots were similar to those with weak wind such as Jinyoung-eup, Jillye-myeon, Juchon-myeon and the downtown area. Based on the analysis, management strategies of ventilation paths in Gimhye were presented as follows. Jinyoung-eup and Jillye-myeon with hot spot areas and week wind areas have a strong possibility that hot spot areas will be extended and strengthened, because industrial areas are being built. Hence, climate-friendly urban and architectural plans considering ventilation paths is required in these areas. In Juchon-myeon, where industrial complexes and agricultural complexes are located, climate-friendly plans are also required because high-rise apartment complexes and an urban development zone are planned, which may induce worse thermal environment in the future. It is expected that a planning of securing and enlarging ventilation paths will be established for climate-friendly urban management. and further the results will be utilized in urban renewal and environmental planning as well as urban basic plans. In addition, we expect that the results can be applied as basic data for climate change adaptation plan and the evaluation system for climate-friendly urban development of Gimhye.

• Management & Information Systems Review
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• v.31 no.4
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• pp.287-307
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• 2012

We empirically examine the price discovery dynamics among the VKOSPI, the KOSPI200 spot, and the KOSPI200 futures markets. The analysis employs the vector-autoregression, Granger causality, impulse response function, and variance decomposition using both daily data from 2009. 04. 13 to 2011. 12. 30 and 1 minute data from the bull market, bear market, and the flat period. The main results are as follows; First, the lead lag relationships between KOSPI200 spot(futures) yield VKOSPI returns could not be found from the daily data analysis. But KOSPI200 spot(futures) have a predictive power for VKOSPI from 1 minute data. Especially KOSPI200 spot(futures) and VKOSPI show the bi-directional effects to each other during the return rising period Second, We chose the VAR(1) the model in daily data but adopt the VAR(3) model in the one minute data to determine the lead lag time. We know that there is predictability during the very short period Third, Spot returns and futures returns makes no difference in daily data results. According to the one minite data results, VKOSPI returns have a predictive power for KOSPI200 spot return, but have no predictive power for KOSPI200 futures return.

• Management & Information Systems Review
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• v.35 no.2
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• pp.1-12
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• 2016

In this study, price discovery between the KOSPI200 spot, and leveraged ETFs(Leveraged KODEX, Leveraged TIGER, Leveraged KStar) is investigated using the vector error correction model(VECM). The main findings are as follows. Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot are cointegrated in most cases. There is no interrelations between the movement of Leveraged KODEX(Leveraged TIGER, Leveraged KStar) and KOSPI200 spot markets in case of daily data. Namely, in daily data, Leveraged KODEX(Leveraged TIGER, Leveraged KStar) doesn't plays more dominant role in price discovery than the KOSPI200 spot.

• Journal of Information Processing Systems
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• v.16 no.4
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• pp.750-759
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• 2020

The wide application of various integrated location-based services (LBS social) and tourism application (app) has generated a large amount of trajectory space data. The trajectory data are used to identify popular tourist attractions with high density of tourists, and they are of great significance to smart service and emergency management of scenic spots. A hot spot analysis method is proposed, based on spatial clustering of trajectory stop points. The DBSCAN algorithm is studied with fast clustering speed, noise processing and clustering of arbitrary shapes in space. The shortage of parameters is manually selected, and an improved method is proposed to adaptively determine parameters based on statistical distribution characteristics of data. DBSCAN clustering analysis and contrast experiments are carried out for three different datasets of artificial synthetic two-dimensional dataset, four-dimensional Iris real dataset and scenic track retention point. The experiment results show that the method can automatically generate reasonable clustering division, and it is superior to traditional algorithms such as DBSCAN and k-means. Finally, based on the spatial clustering results of the trajectory stay points, the Getis-Ord Gi* hotspot analysis and mapping are conducted in ArcGIS software. The hot spots of different tourist attractions are classified according to the analysis results, and the distribution of popular scenic spots is determined with the actual heat of the scenic spots.

• Asian Journal of Turfgrass Science
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• v.25 no.1
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• pp.43-47
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• 2011

Creeping bentgrass (Agrosis stolonifera L.) is regarded to be the most widely used cool-season turf grass species grown on golf greens and fairways in temperate climates of North America. Creeping bentgrass is highly susceptible to the fungal disease 'dollar spot' caused by Sclerotinia homoeocarpa. Dollar spot is a foliar disease favored by conditions of high humidity, warm days, and cool nights. Studies using Aliette Signature (Fosetyl Aluminum formulated with a green pigment) mixed with another broad-spectrum fungicide do not always provide additional visual quality benefits compared to the fungicide alone. The exact mechanism for improved summer visual quality, when it occurs, is not known. Fertility management and environment likely contribute. The object of this study is to evaluate fungicide strategies for control of dollar spot and effect on visual quality during summer and on an L-93/G-2 creeping bentgrass green. Nine fungicide combinations were used for this study. Disease control and visual quality by fungicides was evaluated on an established G-2/L-93 creeping bentgrass green at 3-hole Sunshine Golf Course in Lemont, IL. All fungicide combination showed excellent dollar spot suppression except Fore throughout the study. Visual quality of greens by addition of Aliette Signature is enhanced when bentgrass growth is compromised and slow. Dollar spot levels in Fore plots increased to 30% on 14 August, and was no different than untreated plots. Unacceptable quality by Fore was due to lack of dollar spot control.