A recent study by the Environmental Working Group reported the detection of hexavalent chromium (Cr(VI)) in tap water at 31 out of 35 states investigated in the United States. Even though Cr(III) is an essential eleme...A recent study by the Environmental Working Group reported the detection of hexavalent chromium (Cr(VI)) in tap water at 31 out of 35 states investigated in the United States. Even though Cr(III) is an essential element for human diet, Cr(VI) is a potential carcinogen. Previous work has clearly identified a linear trend of increasing risk of lung cancer mortality with increasing cumulative exposure to water soluble Cr(VI). Regardless, Cr(VI) is still not regulated or monitored in drinking water in the U.S. There is an existing method (EPA 218.6) for the analysis of Cr(VI), however, this analytical method does not addresses detailed sample preservation techniques and optimization process to achieve lowest detection limit possible. In this study, five buffer solutions with pH of 9 and above were compared to determine the most suitable buffer to preserve Cr(VI) in drinking water samples for an extended period of time. Results showed that the five buffers responded very differently to Cr(VI)-fortified drinking water. The best preserving reagent was found to be Ammonium Hydroxide + Ammonium Sulfate (pH 9.2) and Sodium Carbonate + Sodium Bicarbonate+ Ammonium Sulfate (pH 9.7), whereas a buffer solution with Sodium Hydroxide + Sodium Carbonate (pH 11.5+) resulted in a poor chromatographic resolution. A controlled study with a fortified Cr(III) at 1 ppb was also conducted to ensure no false positive detection of Cr(VI) due to the potential oxidation of Cr(III) during sample storage. The optimal preserving reagent identified from this study was compatible with the existing EPA method 218.6 using ion chroma-tography followed by post column reaction, with a method quantitation limit of 0.020 ppb and matrix spike recovery of ± 10%.展开更多
This paper discusses the steps about how to design and implement software based on lightning location system data and its localization map.The system contains four major modules such as real-time lightning monitoring,...This paper discusses the steps about how to design and implement software based on lightning location system data and its localization map.The system contains four major modules such as real-time lightning monitoring,historical query,lightning intensity zoning,lightning disaster statistics,etc.The system is able to automatically generate real-time lightning monitoring image,lightning animation,and lightning intensity zoning image,which contributes to the high accuracy of the calculation results and the efficiency of data analysis.The paper also points out the deficiencies of software life cycle management and proposes actionable solutions.展开更多
Using meteorological data of Anhui Meteorological Bureau,based on the multi-level fuzzy comprehensive analysis method,this paper preliminarily explores the main types and various influencing factors of regional meteor...Using meteorological data of Anhui Meteorological Bureau,based on the multi-level fuzzy comprehensive analysis method,this paper preliminarily explores the main types and various influencing factors of regional meteorological disasters related to hotel buildings in the Dabie Mountain Scenic Area,and puts forward suggestions on how to deal with the risk of meteorological disasters in the scenic area,in order to provide a better understanding of the Dabie Mountains.It provides a theoretical basis for better response to meteorological disaster decision-making in the development of the scenic spot,and also hopes to provide reference for other Dabie Mountain scenic spots in Hubei and Henan.The research results show that the main types of meteorological disasters faced by hotel buildings in the Dabie Mountain Scenic Area are:rainstorm,thunder and lightning,heavy fog,and snow disaster.The occurrence frequency of various disasters is higher than that of the plains,and the intensity is higher.Due to the high altitude of the hotel buildings,the soil resistivity has obvious mutation or stratification.The terrain surrounded by mountains on three sides often becomes a good conductor of lightning,and the risk of lightning strikes is high,and the lighting weather is frequent.The Dabie Mountain Scenic Area is prone to heavy fog,frost,snow disaster and other weather due to its high altitude,high air humidity and low temperature.Hotels in the Dabie Mountain Scenic Area should effectively deal with meteorological disasters and reduce losses by formulating disaster prevention plans,strengthening lightning protection engineering measures for hotel buildings,and regularly testing and maintaining the lightning protection devices installed in hotels.展开更多
Due to its superior geographical environment,the Lu’an area is rich in characteristic meteorological tourism resources.In order to make better use of the meteorological tourism advantages in the Lu’an area and creat...Due to its superior geographical environment,the Lu’an area is rich in characteristic meteorological tourism resources.In order to make better use of the meteorological tourism advantages in the Lu’an area and create a characteristic tourism industry,based on observation data of meteorological observation station in the Lu’an area and literature data during 1990-2020,spass software was used for statistical analysis.The distribution rule of meteorological tourism resources in the Lu’an area was explored,and meteorological tourism resources in the Lu’an area were preliminary grasped.The results show that the human comfort index grade of tourism meteorology in the Lu’an area is good,and the suitable travel time can be as long as 227 d and above in a whole year.It is possible to develop characteristic tourism resources such as prediction of cloud sea,rime and flowering index in the Dabie Mountain area and the Pihe River basin,and it can also be used for the development of wet and comfortable composite health resort tourism climate.The local tourism department can integrate the above meteorological conditions to formulate eco-tourism routes or meteorological characteristic tourism routes,develop tourism meteorological service products in a targeted manner,and further promote the development and utilization of meteorological tourism resources in Lu’an.展开更多
Weeds that grow among crops are undesirable plants and have adversely affected crop growth and yield.Therefore,the study explores corn identification and positioning methods based on machine vision.The ultra-green fea...Weeds that grow among crops are undesirable plants and have adversely affected crop growth and yield.Therefore,the study explores corn identification and positioning methods based on machine vision.The ultra-green feature algorithm and maximum betweenclass variance method(OTSU)were used to segment maize corn,weeds,and land;the segmentation effect was significant and can meet the following shape feature extraction requirements.Finally,the identification and positioning of corn were achieved by morphological reconstruction and pixel projection histogram method.The experiment reveals that when a weeding robot travels at a speed of 1.6 km/h,the recognition accuracy can reach 94.1%.The technique used in this study is accessible for normal cases and can make a good recognition effect;the accuracy and real-time requirements of robot recognition are improved and reduced the calculation time.展开更多
Lycium barbarum commonly known as wolfberry or Goji is considered an important ingredient in Japanese,Korean,Vietnamese,and Chinese food and medicine.It is cultivated extensively in these countries and is usually harv...Lycium barbarum commonly known as wolfberry or Goji is considered an important ingredient in Japanese,Korean,Vietnamese,and Chinese food and medicine.It is cultivated extensively in these countries and is usually harvested manually,which is laborintensive and tedious task.To improve the efficiency of harvesting and reduce manual labor,automatic harvesting technology has been investigated by many researchers in recent years.In this paper,an autonomous navigation algorithm using visual cues and fuzzy control is proposed for Wolfberry orchards.At first,we propose a new weightage(2.4B-0.9G-R)to convert a color image into a grayscale image for better identification of the trunk of Lycium barbarum,the minimum positive circumscribed rectangle is used to describe the contours.Then,using the contour points the least square method is used to fit the navigation line and a region of interest(ROI)is computed that improves the realtime accuracy of the system.Finally,a set of fuzzy controllers,for pneumatic steering system,is designed to achieve real-time autonomous navigation in wolfberry orchard.Static image experiments show that the average accuracy rate of the algorithm is above 90%,and the average time consumption is approximately 162 ms,with good robustness and real-time performance.The experimental results show that when the speed is 1 km/h,the maximum lateral deviation is less than 6.2 cm and the average lateral deviation is 2.9 cm,which meets the requirements of automatic picking of wolfberry picking robot in real-world environments.展开更多
The automatic classification of apple tree organs is of great significance for automatic pruning of apple trees,automatic picking of apple fruits,and estimation of fruit yield.How-ever,there are some problems of dense...The automatic classification of apple tree organs is of great significance for automatic pruning of apple trees,automatic picking of apple fruits,and estimation of fruit yield.How-ever,there are some problems of dense foliage,partial occlusion and clustering of apple fruits.All of the problems above would contribute to the difficulties of organs classification and yield estimation of the apple trees.In this paper a method based on Color and Shape Multi-features Fusion and Support Vector Machine(SVM)for 3D apple tree organs classifi-cation and yield estimation was proposed.The method was designed for dwarf and densely planted apple trees at the early and late maturity stages.196-dimensional feature vectors composed with Red Green Blue(RGB),Hue Saturation Value(HSV),Curvatures,Fast Point Feature Histogram(FPFH),and Spin Image were extracted firstly.And then the SVM based on linear kernel function was trained,after that the trained SVM was used for apple tree organs classification.Then the position weighted smoothing algorithm was used for clas-sified apple tree organs smoothing.Then the agglomerative hierarchical clustering algo-rithm was used to recognize single apple fruit for yield estimation.On the same training and test set the experimental results showed that the SVM based on linear kernel function outperformed the KNN algorithm and Ensemble algorithm.The Recall,Precision and F1 score of the proposed method for yield estimation were 93.75%,96.15%and 94.93%respec-tively.In summary,to solve the problems of apple tree organs classification and yield esti-mation in natural apple orchard,a novelty method based on multi-features fusion and SVM was proposed and achieve good performance.Moreover,the proposed method could pro-vide technical support for automatic apple picking,automatic pruning of fruit trees,and automatic information acquisition and management in orchards.展开更多
The degree of pest damage evaluation on corps in the field environment is very important for precision spraying pesticides.In this paper,we proposed an image processing method to identify the wormholes in the image of...The degree of pest damage evaluation on corps in the field environment is very important for precision spraying pesticides.In this paper,we proposed an image processing method to identify the wormholes in the image of broccoli seedlings,and then to evaluate the damage of the broccoli seedlings by pests.The broccoli seedlings were taken as the research object.The ratio of wormhole areas to broccoli seedling leaves areas(Rw)was used to describe the pest damage degree.An algorithm was developed to calculate the ratio of wormhole areas to broccoli seedling leaves areas.Firstly,broccoli seedling leaves were segmented from the background and the area of the leaves was obtained.There were some holes in segmentation results due to pest damage and other reasons.Then,a classifier based on machine learning was developed to classify the wormholes and other holes.Twenty-four features,including color features and shape features of the holes,were used to develop classifiers.After identifying wormholes from images,the area of the wormholes was obtained and the degree of pest damage to broccoli seedling was calculated.The determination coefficient(R2)between the algorithm calculated pest damage degree and manually labeled pest damage degree was 0.85.The root-mean-square error(d)was 0.02.Results demonstrated that the color and shape were able to effectively segment wormholes from leaves of broccoli seedlings and evaluate the degree of pest damage.This method could provide references for precision spraying pesticides.展开更多
文摘A recent study by the Environmental Working Group reported the detection of hexavalent chromium (Cr(VI)) in tap water at 31 out of 35 states investigated in the United States. Even though Cr(III) is an essential element for human diet, Cr(VI) is a potential carcinogen. Previous work has clearly identified a linear trend of increasing risk of lung cancer mortality with increasing cumulative exposure to water soluble Cr(VI). Regardless, Cr(VI) is still not regulated or monitored in drinking water in the U.S. There is an existing method (EPA 218.6) for the analysis of Cr(VI), however, this analytical method does not addresses detailed sample preservation techniques and optimization process to achieve lowest detection limit possible. In this study, five buffer solutions with pH of 9 and above were compared to determine the most suitable buffer to preserve Cr(VI) in drinking water samples for an extended period of time. Results showed that the five buffers responded very differently to Cr(VI)-fortified drinking water. The best preserving reagent was found to be Ammonium Hydroxide + Ammonium Sulfate (pH 9.2) and Sodium Carbonate + Sodium Bicarbonate+ Ammonium Sulfate (pH 9.7), whereas a buffer solution with Sodium Hydroxide + Sodium Carbonate (pH 11.5+) resulted in a poor chromatographic resolution. A controlled study with a fortified Cr(III) at 1 ppb was also conducted to ensure no false positive detection of Cr(VI) due to the potential oxidation of Cr(III) during sample storage. The optimal preserving reagent identified from this study was compatible with the existing EPA method 218.6 using ion chroma-tography followed by post column reaction, with a method quantitation limit of 0.020 ppb and matrix spike recovery of ± 10%.
基金Supported by 2018 Construction Project of Meteorological Guarantee Project for Prevention and Control of Mountain Torrents,Heilongjiang Meteorological Disaster Prevention Technology Center(HGZ2018G0035)
文摘This paper discusses the steps about how to design and implement software based on lightning location system data and its localization map.The system contains four major modules such as real-time lightning monitoring,historical query,lightning intensity zoning,lightning disaster statistics,etc.The system is able to automatically generate real-time lightning monitoring image,lightning animation,and lightning intensity zoning image,which contributes to the high accuracy of the calculation results and the efficiency of data analysis.The paper also points out the deficiencies of software life cycle management and proposes actionable solutions.
基金Supported by High-level Talent Scientific Research Start-up Project of West Anhui University,China(WGKQ2021045)。
文摘Using meteorological data of Anhui Meteorological Bureau,based on the multi-level fuzzy comprehensive analysis method,this paper preliminarily explores the main types and various influencing factors of regional meteorological disasters related to hotel buildings in the Dabie Mountain Scenic Area,and puts forward suggestions on how to deal with the risk of meteorological disasters in the scenic area,in order to provide a better understanding of the Dabie Mountains.It provides a theoretical basis for better response to meteorological disaster decision-making in the development of the scenic spot,and also hopes to provide reference for other Dabie Mountain scenic spots in Hubei and Henan.The research results show that the main types of meteorological disasters faced by hotel buildings in the Dabie Mountain Scenic Area are:rainstorm,thunder and lightning,heavy fog,and snow disaster.The occurrence frequency of various disasters is higher than that of the plains,and the intensity is higher.Due to the high altitude of the hotel buildings,the soil resistivity has obvious mutation or stratification.The terrain surrounded by mountains on three sides often becomes a good conductor of lightning,and the risk of lightning strikes is high,and the lighting weather is frequent.The Dabie Mountain Scenic Area is prone to heavy fog,frost,snow disaster and other weather due to its high altitude,high air humidity and low temperature.Hotels in the Dabie Mountain Scenic Area should effectively deal with meteorological disasters and reduce losses by formulating disaster prevention plans,strengthening lightning protection engineering measures for hotel buildings,and regularly testing and maintaining the lightning protection devices installed in hotels.
基金Supported by High-level Talent Scientific Research Start-up Project of West Anhui University,China(WGKQ2021045)。
文摘Due to its superior geographical environment,the Lu’an area is rich in characteristic meteorological tourism resources.In order to make better use of the meteorological tourism advantages in the Lu’an area and create a characteristic tourism industry,based on observation data of meteorological observation station in the Lu’an area and literature data during 1990-2020,spass software was used for statistical analysis.The distribution rule of meteorological tourism resources in the Lu’an area was explored,and meteorological tourism resources in the Lu’an area were preliminary grasped.The results show that the human comfort index grade of tourism meteorology in the Lu’an area is good,and the suitable travel time can be as long as 227 d and above in a whole year.It is possible to develop characteristic tourism resources such as prediction of cloud sea,rime and flowering index in the Dabie Mountain area and the Pihe River basin,and it can also be used for the development of wet and comfortable composite health resort tourism climate.The local tourism department can integrate the above meteorological conditions to formulate eco-tourism routes or meteorological characteristic tourism routes,develop tourism meteorological service products in a targeted manner,and further promote the development and utilization of meteorological tourism resources in Lu’an.
基金the National Key Research and Development Program of China[Grant numbers:2019YFB1312303].
文摘Weeds that grow among crops are undesirable plants and have adversely affected crop growth and yield.Therefore,the study explores corn identification and positioning methods based on machine vision.The ultra-green feature algorithm and maximum betweenclass variance method(OTSU)were used to segment maize corn,weeds,and land;the segmentation effect was significant and can meet the following shape feature extraction requirements.Finally,the identification and positioning of corn were achieved by morphological reconstruction and pixel projection histogram method.The experiment reveals that when a weeding robot travels at a speed of 1.6 km/h,the recognition accuracy can reach 94.1%.The technique used in this study is accessible for normal cases and can make a good recognition effect;the accuracy and real-time requirements of robot recognition are improved and reduced the calculation time.
基金This work was supported by The National Key Research and Development Program of China(2016YFD0701501)supported by the Fundamental Research Funds for the Central Universi-tiesThe National Science Foundation Program of China(51975574).
文摘Lycium barbarum commonly known as wolfberry or Goji is considered an important ingredient in Japanese,Korean,Vietnamese,and Chinese food and medicine.It is cultivated extensively in these countries and is usually harvested manually,which is laborintensive and tedious task.To improve the efficiency of harvesting and reduce manual labor,automatic harvesting technology has been investigated by many researchers in recent years.In this paper,an autonomous navigation algorithm using visual cues and fuzzy control is proposed for Wolfberry orchards.At first,we propose a new weightage(2.4B-0.9G-R)to convert a color image into a grayscale image for better identification of the trunk of Lycium barbarum,the minimum positive circumscribed rectangle is used to describe the contours.Then,using the contour points the least square method is used to fit the navigation line and a region of interest(ROI)is computed that improves the realtime accuracy of the system.Finally,a set of fuzzy controllers,for pneumatic steering system,is designed to achieve real-time autonomous navigation in wolfberry orchard.Static image experiments show that the average accuracy rate of the algorithm is above 90%,and the average time consumption is approximately 162 ms,with good robustness and real-time performance.The experimental results show that when the speed is 1 km/h,the maximum lateral deviation is less than 6.2 cm and the average lateral deviation is 2.9 cm,which meets the requirements of automatic picking of wolfberry picking robot in real-world environments.
基金This research was funded by National Natural Science Foun-dation of China(31601217)the National Key Research and Development Program of China(2017YFD0701303).
文摘The automatic classification of apple tree organs is of great significance for automatic pruning of apple trees,automatic picking of apple fruits,and estimation of fruit yield.How-ever,there are some problems of dense foliage,partial occlusion and clustering of apple fruits.All of the problems above would contribute to the difficulties of organs classification and yield estimation of the apple trees.In this paper a method based on Color and Shape Multi-features Fusion and Support Vector Machine(SVM)for 3D apple tree organs classifi-cation and yield estimation was proposed.The method was designed for dwarf and densely planted apple trees at the early and late maturity stages.196-dimensional feature vectors composed with Red Green Blue(RGB),Hue Saturation Value(HSV),Curvatures,Fast Point Feature Histogram(FPFH),and Spin Image were extracted firstly.And then the SVM based on linear kernel function was trained,after that the trained SVM was used for apple tree organs classification.Then the position weighted smoothing algorithm was used for clas-sified apple tree organs smoothing.Then the agglomerative hierarchical clustering algo-rithm was used to recognize single apple fruit for yield estimation.On the same training and test set the experimental results showed that the SVM based on linear kernel function outperformed the KNN algorithm and Ensemble algorithm.The Recall,Precision and F1 score of the proposed method for yield estimation were 93.75%,96.15%and 94.93%respec-tively.In summary,to solve the problems of apple tree organs classification and yield esti-mation in natural apple orchard,a novelty method based on multi-features fusion and SVM was proposed and achieve good performance.Moreover,the proposed method could pro-vide technical support for automatic apple picking,automatic pruning of fruit trees,and automatic information acquisition and management in orchards.
文摘The degree of pest damage evaluation on corps in the field environment is very important for precision spraying pesticides.In this paper,we proposed an image processing method to identify the wormholes in the image of broccoli seedlings,and then to evaluate the damage of the broccoli seedlings by pests.The broccoli seedlings were taken as the research object.The ratio of wormhole areas to broccoli seedling leaves areas(Rw)was used to describe the pest damage degree.An algorithm was developed to calculate the ratio of wormhole areas to broccoli seedling leaves areas.Firstly,broccoli seedling leaves were segmented from the background and the area of the leaves was obtained.There were some holes in segmentation results due to pest damage and other reasons.Then,a classifier based on machine learning was developed to classify the wormholes and other holes.Twenty-four features,including color features and shape features of the holes,were used to develop classifiers.After identifying wormholes from images,the area of the wormholes was obtained and the degree of pest damage to broccoli seedling was calculated.The determination coefficient(R2)between the algorithm calculated pest damage degree and manually labeled pest damage degree was 0.85.The root-mean-square error(d)was 0.02.Results demonstrated that the color and shape were able to effectively segment wormholes from leaves of broccoli seedlings and evaluate the degree of pest damage.This method could provide references for precision spraying pesticides.
