The diagnosis of cause of death (COD) or estimation of postmortem interval (PMI) is hard to perform using postmortem blood or other bodily fluids due to various biochemical changes that occur during the agonal phase or after death. To solve these problems, new paradigms and new analytical methods are needed. In this study, postmortem blood was fractionated with specific gravity 1.021, 1.029, 1.038, and 1.045, and the absorbance patterns of each sample of the 131 total cases (12 kinds of COD) were analyzed using a spectrometer. The absorbance was grouped into 9 patterns (ABS pattern 1 to 9) according to the wave length and the signal intensity. These patterns of postmortem blood were found to be distinctly different from the absorbance pattern of fresh blood. The analysis of ABS patterns is useful for the diagnosis of deaths due to acute or rapid bleeding, fire death, drowning and, in some cases, poisoning, but is not useful for the estimation of PMI.
The enhancement of the refractive index structure parameter $C_n^2$ often occurs where vertical gradients of virtual potential temperature ${\theta}_v$ and mixing ratio q have their maximum values. The $C_n^2$ can be a very useful parameter for estimating the convective boundary layer(CBL) height. The behavior of $C_n^2$ peaks, often used to locate the height of mixed layer, was investigated in the present study. In addition, a new method to determine the CBL height objectively using both $C_n^2$ and vertical air velocity variance ${\sigma}_w$ data of UHF radar was also suggested. The present analysis showed that the $C_n^2$ peaks in the backscatter intensity profiles often occurred not only at the top of the CBL but also at the top of a residual layer or at a cloud layer. The $C_n^2$ peaks corresponding to the CBL heights were slightly lower than the CBL heights derived from rawinsonde sounding data when vertical mixing owing to weak solar heating was not significant and the height of strong vertical ${\theta}_v$ gradients were not consistent with that of strong vertical q gradients. However, the $C_n^2$ peaks corresponding to the CBL heights were in good agreement with the rawinsonde-estimated CBL hegiths when vertical mixing owing to solar heating was significant and the vertical gradient of both ${\theta}_v$ and q in the entrainment zone was very strong. The maximum backscatter intensity method, which determines the height of $C_n^2$ peak as the CBL height, correctly estimated the CBL height when the $C_n^2$ profile had single peak, but this method erroneously estimated the CBL height when there was a residual layer or a cloud layer over the top of the CBL. The new method distinguished when there the CBL height from the peak due a cloud layer or a residual layer using both $C_n^2$ and ${\sigma}_w$ data, and correctly estimated the CBL height. As for estimation of diurnal variation of the CBL height, the new method backscatter intensity method even if the vertical profile of backscatter intensity had two peaks from the CBL height and a residual layer or a cloud layer.
The estimations of the surface rain intensity and rain-related physical variables derived from two independent Tropical Rainfall Measuring Mission (TRMM) satellite sensors, TRMM Microwave Imager (TMI) and Precipitation Radar (PR), were compared over four different oceans. The precipitating clouds developed most frequently in the warmest sea surface temperature (SST) region of the west Pacific, which is 1.5 times more frequent than in the east Pacific and the tropical Atlantic oceans. However, the east Pacific exhibited the most intense rain intensity for the convective and mixed rain types while the tropical Atlantic showed the most intense rain intensity for all TMI rainy pixels. It was found that the deviation of TMI-derived rain rate yielded a big difference in region-to-region and rain type-to-type if the PR rain intensity value is assumed to be closer to the truth. Furthermore, the deviation by rain types showed opposite signs between convective and non-convective rain types. It was found that the region-to-region deviation differences reached more than 200% even though the selected tropical oceans have relatively similar geophysical environments. Therefore, the validation for the microwave rain estimation needs to be performed according to both rain types and climate regimes, and it also requires more sophisticated TMI algorithm which reflects the locality of rainfall characteristics.
This paper proposes how to improve performance of the Korean document sentiment-classification system using semantic properties of the sentiment words. A sentiment word means a word with sentiment, and sentiment features are defined by a set of the sentiment words which are important lexical resource for the sentiment classification. Sentiment feature represents different sentiment intensity in general field and in specific domain. In general field, we can estimate the sentiment intensity using a snippet from a search engine, while in specific domain, training data can be used for this estimation. When the sentiment intensity of the sentiment features are estimated, it is called semantic orientation and is used to estimate the sentiment intensity of the sentences in the text documents. After estimating sentiment intensity of the sentences, we apply that to the weights of sentiment features. In this paper, we evaluate our system in three different cases such as general, domain-specific, and general/domain-specific semantic orientation using support vector machine. Our experimental results show the improved performance in all cases, and, especially in general/domain-specific semantic orientation, our proposed method performs 3.1% better than a baseline system indexed by only content words.
Vibration propagated from seismic sources has damping according to distance and amplification and reduction characteristic in different regions according to topography and geological structure. The vibration propagated from the seismic source to the bedrock is largely affected by the damping according to the separation distance, which can be simply estimated through the damping equation. However, it is important to grasp geological information by location because vibration estimation transmitted to the surface are affected by the natural period of the soil located above the bedrock. Geotechnical investigation data are needed to estimate the seismic intensity based on geological information. If there is no Vs profile, the standard penetration tests are mainly used to determine the soil parameters. The Integrated DB Center of National Geotechnical Information manages the geotechnical survey data performed on the domestic ground, and there is the standard penetration test information of 400,000 holes. In this study, the possibility of quantitation the amplification coefficient for each region was examined to calculated the physical interactive seismic intensity based on geotechnical information. At this time, the shear wave column diagram was generated from the SPT-N value and ground response analysis was performed in the target area. The site coefficients for each zone and the seismic intensity distribution for the seismic motion present a significant difference according to the analysis method and the regional setting.
Tao Zhang;Zhiying Wang;Yaming Li;Bohan Zhou;Yifan Liu;Jinquan Li;Ruijun Wang;Qi Lv;Chun Li;Yanjun Zhang;Rui Su
Animal Bioscience
/
v.37
no.7
/
pp.1168-1176
/
2024
Objective: As a charismatic species, cashmere goats have rich genetic resources. In the Inner Mongolia Autonomous Region, there are three cashmere goat varieties named and approved by the state. These goats are renowned for their high cashmere production and superior cashmere quality. Therefore, it is vitally important to protect their genetic resources as they will serve as breeding material for developing new varieties in the future. Methods: Three breeds including Inner Mongolia cashmere goats (IMCG), Hanshan White cashmere goats (HS), and Ujimqin white cashmere goats (WZMQ) were studied. IMCG were of three types: Aerbas (AEBS), Erlangshan (ELS), and Alashan (ALS). Nine DNA samples were collected for each population, and they were genomically re-sequenced to obtain high-depth data. The genetic diversity parameters of each population were estimated to determine selection intensity. Principal component analysis, phylogenetic tree construction and genetic differentiation parameter estimation were performed to determine genetic relationships among populations. Results: Samples from the 45 individuals from the five goat populations were sequenced, and 30,601,671 raw single nucleotide polymorphisms (SNPs) obtained. Then, variant calling was conducted using the reference genome, and 17,214,526 SNPs were retained after quality control. Individual sequencing depth of individuals ranged from 21.13× to 46.18×, with an average of 28.5×. In the AEBS, locus polymorphism (79.28) and expected heterozygosity (0.2554) proportions were the lowest, and the homologous consistency ratio (0.1021) and average inbreeding coefficient (0.1348) were the highest, indicating that this population had strong selection intensity. Conversely, ALS and WZMQ selection intensity was relatively low. Genetic distance between HS and the other four populations was relatively high, and genetic exchange existed among the other four populations. Conclusion: The Inner Mongolia cashmere goat (AEBS type) population has a relatively high selection intensity and a low genetic diversity. The IMCG (ALS type) and WZMQ populations had relatively low selection intensity and high genetic diversity. The genetic distance between HS and the other four populations was relatively high, with a moderate degree of differentiation. Overall, these genetic variations provide a solid foundation for resource identification of Inner Mongolia Autonomous Region cashmere goats in the future.
Magazine of the Korean Society of Agricultural Engineers
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v.29
no.4
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pp.59-72
/
1987
Although long-term runoff analysis is important as much as flood analysis in the design of water works, the technological level of the former is relatively lower than that of the latter. In this respect, the precise estimation model for the volume of successive runoff should he developed as soon as possible. Up to now, in Korea, Gajiyama's formula has been widely used in long-term runoff analysis, which has many problems in applying in real situation. On the other hand, in flood analysis, unit hydrograph method has been exclusively used. Therefore, this study aims at trying to apply unit hydrograph method in long-term runoff analysis for the betterment of its estimation. Four test catchment areas were selected ; Maesan area in Namlum river as a representative area of Han river system, Cheongju area in Musim river as one of Geum river system, Hwasun area in Hwasun river as one of Yongsan river system, and Supyung area in Geum river as one of Nakdong river system. In the analysis of unit hydrograph, seperation of effective rainfall was carried out firstly. Considering that effective rainfall and moisture condition of catchrnent area are inside and outside of a phenomenon respectively and the latter is not considered in the analysis, Initial base flow(qb)was selected as an index of moisture condition. At the same time, basic equation(Eq.7) was established, in which qb can take a role as a parameter in relating between cumulative rainfall(P) and cumulative loss of rainfall(Ld). Based on the above equation, computer program for estimation model of qbwas seperately developed according to the range of qb, Developed model was applied to measured hydrographs and hyetographs for total 10 years in 4 test areas and effective rainfall was estimated. Estimation precision of model was checked as shown in Tab- 6 and Fig.8. In the next stage, based on the estimated effective rainfall(R) and runoff(Qd), a runoff distribution ratio was calculated for each teat area using by computerised least square method and used in making unit hydrographs in each test area. Significance of induced hydrographs was tested by checking the relative errors between estimated and measured runoff volume(Tab-9, 10). According to the results, runoff estimation error by unit hydrograph itself was merely 2 or 3 %, but other 2 or 3 % of error proved to be transferred error in the seperation of effective rainfall. In this study, special attentioning point is that, in spite of different river systems and forest conditions of test areas, standardized unit hydrographs for them have very similar curve shape, which can be explained by having similar catchinent characteristics such as stream length, catchinent area, slope, and vegetation intensity. That fact should be treated as important factor ingeneralization of unit hydrograph method.
Mesoscale soil moisture measurement from the promising Cosmic-Ray Neutron Probe (CRNP) is expected to bridge the gap between large scale microwave remote sensing and point-based in-situ soil moisture observations. Traditional calibration based on $N_0$ method is used to convert neutron intensity measured at the CRNP to field scale soil moisture. However, the static calibration parameter $N_0$ used in traditional technique is insufficient to quantify long term soil moisture variation and easily influenced by different time-variant factors, contributing to the high uncertainties in CRNP soil moisture product. Consequently, in this study, we proposed a modified traditional calibration method, so-called Dynamic-$N_0$ method, which take into account the temporal variation of $N_0$ to improve the CRNP based soil moisture estimation. In particular, a nonlinear regression method has been developed to directly estimate the time series of $N_0$ data from the corrected neutron intensity. The $N_0$ time series were then reapplied to generate the soil moisture. We evaluated the performance of Dynamic-$N_0$ method for soil moisture estimation compared with the traditional one by using a weighted in-situ soil moisture product. The results indicated that Dynamic-$N_0$ method outperformed the traditional calibration technique, where correlation coefficient increased from 0.70 to 0.72 and RMSE and bias reduced from 0.036 to 0.026 and -0.006 to $-0.001m^3m^{-3}$. Superior performance of the Dynamic-$N_0$ calibration method revealed that the temporal variability of $N_0$ was caused by hydrogen pools surrounding the CRNP. Although several uncertainty sources contributed to the variation of $N_0$ were not fully identified, this proposed calibration method gave a new insight to improve field scale soil moisture estimation from the CRNP.
KIPS Transactions on Computer and Communication Systems
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v.6
no.9
/
pp.369-376
/
2017
Recently, an RSSI-based fingerprinting localization technology has been widely used in indoor location-based services. In the conventional fingerprinting method, as many APs as possible are used to increase the accuracy of location estimation. In another study, a part of APs having the strongest RSSI signal intensity are selected and used to reduce the time spent for positioning. However, it does not reflect the influence of RSSI occurred from the changes of the surrounding environments such as human movement or moving obstacles in a real environment. The environmental changes may cause the difference between the predicted RSSI signal strength value and the measured value, and thus occur an unpredictable error in the position estimation. Therefore, in order to mitigate the error caused by environmental factors, it is necessary to select APs suitable for indoor positioning estimation considering the changes in the surrounding environments. In this paper, we propose a method to select stable APs considering the influence of surrounding environments and derive a suitable positioning algorithm. In addition, we compare and analyze the performance of the proposed method with that of the existing AP selection methods through experiments.
Maurillo, Pennie Rose Anne R.;Jung, Hyeon-Ji;Lee, Seon-Ha;Ha, Dong-Ik
The Journal of The Korea Institute of Intelligent Transport Systems
/
v.12
no.3
/
pp.114-128
/
2013
Greenhouse gas emissions have been an important issue in different countries because of their effects on global warming. The government has to organize greenhouse gas reduction measures suitable to regional characteristics by establishing annual implementation plans and comprehensive policies based on the UNFCCC. The transportation sector is one of the major contributors of air pollution; hence increasing need to estimate current and future traffic emissions precisely. Under these circumstances, a number of emission models have been developed recently. However, current methods of estimation cannot carry out effective analyses because it does not reflect vehicle movement characteristics. This study aims to present a new method for calculating road traffic emissions in Goyang city. A travel demand model is utilized to carry out GHG emission estimates according the traffic data (fleet composition, vehicle kilometers travelled, traffic intensity, road type, emission factors and speed). This study evaluates two approaches to estimate the road traffic emissions in Goyang City: Pollution-Emis and the Handbook of Emission Factors for Road Transport (HBEFA v.3.1) which is representative of the "average speed" and the "traffic situation" model types. The evaluation of results shows that the proposed emission estimation method may be a good practice if vigilant implementation of model inputs is observed.
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