In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space...In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.展开更多
In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonne...In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.展开更多
This study examined public attitudes concerning the value of outdoor spaces which people use daily. Two successive analyses were performed based on data from common residents and college students in the city of Hangzh...This study examined public attitudes concerning the value of outdoor spaces which people use daily. Two successive analyses were performed based on data from common residents and college students in the city of Hangzhou, China. First, citizens registered various items constituting desirable values of residential outdoor spaces through a preliminary questionnaire. The result proposed three general attributes (functional, aesthetic and ecological) and ten specific qualities of residential outdoor spaces. An analytic hierarchy process (AHP) was applied to an interview survey in order to clarify the weights among these attributes and qualities. Second, principal factors were extracted from the ten specific qualities with principal component analysis (PCA) for both the common case and the campus case. In addition, the variations of respondents’ groups were classified with cluster analysis (CA) using the results of the PCA. The results of the AHP application found that the public prefers the functional attribute, rather than the aesthetic attribute. The latter is always viewed as the core value of open spaces in the eyes of architects and designers. Fur-thermore, comparisons of ten specific qualities showed that the public prefers the open spaces that can be utilized conveniently and easily for group activities, because such spaces keep an active lifestyle of neighborhood communication, which is also seen to protect human-regarding residential environments. Moreover, different groups of respondents diverge largely in terms of gender, age, behavior and preference.展开更多
In order to better blend green plum wine and study aromatic components of green plum wine,a qualitative analysis on aromatic components of soaked base liquor,green plum soaked wine,green plum juice,and fermented wine ...In order to better blend green plum wine and study aromatic components of green plum wine,a qualitative analysis on aromatic components of soaked base liquor,green plum soaked wine,green plum juice,and fermented wine of green plum juice by Head Space Solid-phase Microextraction( HS-SPME) and Gas Chromatograph Mass Spectrometer( GC-MS) was studied in this paper. Experiment results indicated that14,32,17,and 46 kinds of aromatic components were identified respectively from four samples. Different aromatic components determined the special flavor and taste of green plum wine. Unique aromatic components generated in soaking process include benzaldehyde,1-butanol,2-methyl-,S-(-),benzoic acid ethyl ester,and 5-( hydroxymethyl). Special aromatic components in green plum juice were furfural,phenylethyl alcohol,and benzyl alcohol. The aromatic components in fermented wine of green plum juice mainly included phenylethyl alcohol( 6. 941%,relative content of peak area,same below),1-butanol,3-methyl-( 6. 940%),octanoic acid,ethyl ester( 3. 734%),decanoic acid,ethyl ester( 2. 590%),hexanoic acid,ethyl ester( 2. 479%),ethyl 9-decenoate( 2. 080%),and 5-hydroxymethyl( 1. 756%). This study was expected to provide scientific basis and data reference for quality improvement of green plum wine.展开更多
To investigate the effect of planting date, spacing and seeding methods on disease development and yield components ofrice, a factorial experiment in randomized complete block design （RCBD） with four replications wa...To investigate the effect of planting date, spacing and seeding methods on disease development and yield components ofrice, a factorial experiment in randomized complete block design （RCBD） with four replications was conducted during 2011 plantingseason at Izzi Local Government Area （LGA） of Ebonyi State, Nigeria. This experiment was carried out with four levels of plantingdates （early June, late June, early July and late July）, three levels of spacing （15, 20 and 25 cm） and two levels of seeding method（direct seeding and seedling transplanting）. The studied traits included plant height （PH）, number of tillers （NT）, leaf area （LA）, rootlength （RL）, panicle length （PL）, 1,000 seed weight （SW）, disease incidence and severity. The result showed that all the factors hadsignificant effect on the parameters measured. Sowing in early July had the highest LA of 65.38 cm^2, PH of 122.00 cm, RL of 29.04cm and TN of 10.54, and the second largest PL of 25.08 cm and SW of 25.12 g. Also sowing in early July had the highest diseaseseverity of 3.21, followed by 3.14 which occurred in late July, while the least 2.17 occurred in early June. The direct seeding methodhad the highest disease incidence of 70.83%, followed by plant spacing of 15 cm × 15 cm which had the disease incidence of 69.72%,while sowing in early June had the least disease incidence of 57.50%. In conclusion, planting of rice in Southeastern Nigeria shouldbe done in early July, as the yield components were significantly better than in other dates though with the highest disease severity.展开更多
This work utilizes a statistical approach of Principal Component Ana-lysis(PCA)towards the detection of Methane(CH_(4))-Carbon Monoxide(CO)Poi-soning occurring in coal mines,forestfires,drainage systems etc.where the ...This work utilizes a statistical approach of Principal Component Ana-lysis(PCA)towards the detection of Methane(CH_(4))-Carbon Monoxide(CO)Poi-soning occurring in coal mines,forestfires,drainage systems etc.where the CH_(4) and CO emissions are very high in closed buildings or confined spaces during oxi-dation processes.Both methane and carbon monoxide are highly toxic,colorless and odorless gases.Both of the gases have their own toxic levels to be detected.But during their combined presence,the toxicity of the either one goes unidentified may be due to their low levels which may lead to an explosion.By using PCA,the correlation of CO and CH_(4) data is carried out and by identifying the areas of high correlation(along the principal component axis)the explosion suppression action can be triggered earlier thus avoiding adverse effects of massive explosions.Wire-less Sensor Network is deployed and simulations are carried with heterogeneous sensors(Carbon Monoxide and Methane sensors)in NS-2 Mannasim framework.The rise in the value of CO even when CH_(4) is below the toxic level may become hazardous to the people around.Thus our proposed methodology will detect the combined presence of both the gases(CH_(4) and CO)and provide an early warning in order to avoid any human losses or toxic effects.展开更多
基金Key Research and Development Plan of Shaanxi Province,China(No.2023-YBGY-330)。
文摘In an automatic bobbin management system that simultaneously detects bobbin color and residual yarn,a composite texture segmentation and recognition operation based on an odd partial Gabor filter and multi-color space hierarchical clustering are proposed.Firstly,the parameter-optimized odd partial Gabor filter is used to distinguish bobbin and yarn texture,to explore Garbor parameters for yarn bobbins,and to accurately discriminate frequency characteristics of yarns and texture.Secondly,multi-color clustering segmentation using color spaces such as red,green,blue(RGB)and CIELUV(LUV)solves the problems of over-segmentation and segmentation errors,which are caused by the difficulty of accurately representing the complex and variable color information of yarns in a single-color space and the low contrast between the target and background.Finally,the segmented bobbin is combined with the odd partial Gabor’s edge recognition operator to further distinguish bobbin texture from yarn texture and locate the position and size of the residual yarn.Experimental results show that the method is robust in identifying complex texture,damaged and dyed bobbins,and multi-color yarns.Residual yarn identification can distinguish texture features and residual yarns well and it can be transferred to the detection and differentiation of complex texture,which is significantly better than traditional methods.
基金The Pre-Research Foundation of National Ministries andCommissions (No9140A16050109DZ01)the Scientific Research Program of the Education Department of Shanxi Province (No09JK701)
文摘In order to overcome the shortcomings that the reconstructed spectral reflectance may be negative when using the classic principal component analysis （PCA）to reduce the dimensions of the multi-spectral data, a nonnegative constrained principal component analysis method is proposed to construct a low-dimensional multi-spectral space and accomplish the conversion between the new constructed space and the multispectral space. First, the reason behind the negative data is analyzed and a nonnegative constraint is imposed on the classic PCA. Then a set of nonnegative linear independence weight vectors of principal components is obtained, by which a lowdimensional space is constructed. Finally, a nonlinear optimization technique is used to determine the projection vectors of the high-dimensional multi-spectral data in the constructed space. Experimental results show that the proposed method can keep the reconstructed spectral data in [ 0, 1 ]. The precision of the space created by the proposed method is equivalent to or even higher than that by the PCA.
文摘This study examined public attitudes concerning the value of outdoor spaces which people use daily. Two successive analyses were performed based on data from common residents and college students in the city of Hangzhou, China. First, citizens registered various items constituting desirable values of residential outdoor spaces through a preliminary questionnaire. The result proposed three general attributes (functional, aesthetic and ecological) and ten specific qualities of residential outdoor spaces. An analytic hierarchy process (AHP) was applied to an interview survey in order to clarify the weights among these attributes and qualities. Second, principal factors were extracted from the ten specific qualities with principal component analysis (PCA) for both the common case and the campus case. In addition, the variations of respondents’ groups were classified with cluster analysis (CA) using the results of the PCA. The results of the AHP application found that the public prefers the functional attribute, rather than the aesthetic attribute. The latter is always viewed as the core value of open spaces in the eyes of architects and designers. Fur-thermore, comparisons of ten specific qualities showed that the public prefers the open spaces that can be utilized conveniently and easily for group activities, because such spaces keep an active lifestyle of neighborhood communication, which is also seen to protect human-regarding residential environments. Moreover, different groups of respondents diverge largely in terms of gender, age, behavior and preference.
基金Supported by Talent Introduction Project of Sichuan University of Science&Engineering(2012RC142015RC14)
文摘In order to better blend green plum wine and study aromatic components of green plum wine,a qualitative analysis on aromatic components of soaked base liquor,green plum soaked wine,green plum juice,and fermented wine of green plum juice by Head Space Solid-phase Microextraction( HS-SPME) and Gas Chromatograph Mass Spectrometer( GC-MS) was studied in this paper. Experiment results indicated that14,32,17,and 46 kinds of aromatic components were identified respectively from four samples. Different aromatic components determined the special flavor and taste of green plum wine. Unique aromatic components generated in soaking process include benzaldehyde,1-butanol,2-methyl-,S-(-),benzoic acid ethyl ester,and 5-( hydroxymethyl). Special aromatic components in green plum juice were furfural,phenylethyl alcohol,and benzyl alcohol. The aromatic components in fermented wine of green plum juice mainly included phenylethyl alcohol( 6. 941%,relative content of peak area,same below),1-butanol,3-methyl-( 6. 940%),octanoic acid,ethyl ester( 3. 734%),decanoic acid,ethyl ester( 2. 590%),hexanoic acid,ethyl ester( 2. 479%),ethyl 9-decenoate( 2. 080%),and 5-hydroxymethyl( 1. 756%). This study was expected to provide scientific basis and data reference for quality improvement of green plum wine.
文摘To investigate the effect of planting date, spacing and seeding methods on disease development and yield components ofrice, a factorial experiment in randomized complete block design （RCBD） with four replications was conducted during 2011 plantingseason at Izzi Local Government Area （LGA） of Ebonyi State, Nigeria. This experiment was carried out with four levels of plantingdates （early June, late June, early July and late July）, three levels of spacing （15, 20 and 25 cm） and two levels of seeding method（direct seeding and seedling transplanting）. The studied traits included plant height （PH）, number of tillers （NT）, leaf area （LA）, rootlength （RL）, panicle length （PL）, 1,000 seed weight （SW）, disease incidence and severity. The result showed that all the factors hadsignificant effect on the parameters measured. Sowing in early July had the highest LA of 65.38 cm^2, PH of 122.00 cm, RL of 29.04cm and TN of 10.54, and the second largest PL of 25.08 cm and SW of 25.12 g. Also sowing in early July had the highest diseaseseverity of 3.21, followed by 3.14 which occurred in late July, while the least 2.17 occurred in early June. The direct seeding methodhad the highest disease incidence of 70.83%, followed by plant spacing of 15 cm × 15 cm which had the disease incidence of 69.72%,while sowing in early June had the least disease incidence of 57.50%. In conclusion, planting of rice in Southeastern Nigeria shouldbe done in early July, as the yield components were significantly better than in other dates though with the highest disease severity.
文摘This work utilizes a statistical approach of Principal Component Ana-lysis(PCA)towards the detection of Methane(CH_(4))-Carbon Monoxide(CO)Poi-soning occurring in coal mines,forestfires,drainage systems etc.where the CH_(4) and CO emissions are very high in closed buildings or confined spaces during oxi-dation processes.Both methane and carbon monoxide are highly toxic,colorless and odorless gases.Both of the gases have their own toxic levels to be detected.But during their combined presence,the toxicity of the either one goes unidentified may be due to their low levels which may lead to an explosion.By using PCA,the correlation of CO and CH_(4) data is carried out and by identifying the areas of high correlation(along the principal component axis)the explosion suppression action can be triggered earlier thus avoiding adverse effects of massive explosions.Wire-less Sensor Network is deployed and simulations are carried with heterogeneous sensors(Carbon Monoxide and Methane sensors)in NS-2 Mannasim framework.The rise in the value of CO even when CH_(4) is below the toxic level may become hazardous to the people around.Thus our proposed methodology will detect the combined presence of both the gases(CH_(4) and CO)and provide an early warning in order to avoid any human losses or toxic effects.
