AIM:To develop different machine learning models to train and test diplopia images and data generated by the computerized diplopia test.METHODS:Diplopia images and data generated by computerized diplopia tests,along w...AIM:To develop different machine learning models to train and test diplopia images and data generated by the computerized diplopia test.METHODS:Diplopia images and data generated by computerized diplopia tests,along with patient medical records,were retrospectively collected from 3244 cases.Diagnostic models were constructed using logistic regression(LR),decision tree(DT),support vector machine(SVM),extreme gradient boosting(XGBoost),and deep learning(DL)algorithms.A total of 2757 diplopia images were randomly selected as training data,while the test dataset contained 487 diplopia images.The optimal diagnostic model was evaluated using test set accuracy,confusion matrix,and precision-recall curve(P-R curve).RESULTS:The test set accuracy of the LR,SVM,DT,XGBoost,DL(64 categories),and DL(6 binary classifications)algorithms was 0.762,0.811,0.818,0.812,0.858 and 0.858,respectively.The accuracy in the training set was 0.785,0.815,0.998,0.965,0.968,and 0.967,respectively.The weighted precision of LR,SVM,DT,XGBoost,DL(64 categories),and DL(6 binary classifications)algorithms was 0.74,0.77,0.83,0.80,0.85,and 0.85,respectively;weighted recall was 0.76,0.81,0.82,0.81,0.86,and 0.86,respectively;weighted F1 score was 0.74,0.79,0.82,0.80,0.85,and 0.85,respectively.CONCLUSION:In this study,the 7 machine learning algorithms all achieve automatic diagnosis of extraocular muscle palsy.The DL(64 categories)and DL(6 binary classifications)algorithms have a significant advantage over other machine learning algorithms regarding diagnostic accuracy on the test set,with a high level of consistency with clinical diagnoses made by physicians.Therefore,it can be used as a reference for diagnosis.展开更多
With the development of machine translation technology,automatic pre-editing has attracted increasing research attention for its important role in improving translation quality and efficiency.This study utilizes UAM C...With the development of machine translation technology,automatic pre-editing has attracted increasing research attention for its important role in improving translation quality and efficiency.This study utilizes UAM Corpus Tool 3.0 to annotate and categorize 99 key publications between 1992 and 2024,tracing the research paths and technological evolution of automatic pre-translation editing.The study finds that current approaches can be classified into four categories:controlled language-based approaches,text simplification approaches,interlingua-based approaches,and large language model-driven approaches.By critically examining their technical features and applicability in various contexts,this review aims to provide valuable insights to guide the future optimization and expansion of pre-translation editing systems.展开更多
We developed MaxQsaring,a novel universal framework integrating molecular descriptors,fingerprints,and deep-learning pretrained representations,to predict the properties of compounds.Applied to a case study of human e...We developed MaxQsaring,a novel universal framework integrating molecular descriptors,fingerprints,and deep-learning pretrained representations,to predict the properties of compounds.Applied to a case study of human ether-à-go-go-related gene(hERG)blockage prediction,MaxQsaring achieved state-of-the-art performance on two challenging external datasets through automatic optimal feature combinations,and successfully identified top 10 important interpretable features that could be used to model a high-accuracy decision tree.The models'predictions align well with empirical hERG optimization strategies,demonstrating their interpretability for practical utilities.Deep learning pre-trained representations have been demonstrated to exert a moderate influence on enhancing the performance of predictive models.Nevertheless,their impact on augmenting the generalizability of these models,particularly when applied to compounds possessing novel scaffolds,appears to be comparatively minimal.MaxQsaring excelled in the Therapeutics Data Commons(TDC)benchmarks,ranking first in 19 out of 22 tasks,showcasing its potential for universal accurate compound property prediction to facilitate a high success rate of early drug discovery,which is still a formidable challenge.展开更多
To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition a...To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.展开更多
Gradient boosting decision tree(GBDT)machine learning(ML)method was adopted for the first time to automatically recognize and conduct quantitative statistical analysis of boundaries in bainitic microstructure using el...Gradient boosting decision tree(GBDT)machine learning(ML)method was adopted for the first time to automatically recognize and conduct quantitative statistical analysis of boundaries in bainitic microstructure using electron back-scatter diffraction(EBSD)data.In spite of lack of large sets of EBSD data,we were successful in achieving the desired accuracy and accomplishing the objective of recognizing the boundaries.Compared with a low model accuracy of<50%as using Euler angles or axis-angle pair as characteristic features,the accuracy of the model was significantly enhanced to about 88%when the Euler angle was converted to overall misorientation angle(OMA)and specific misorientation angle(SMA)and considered as important features.In this model,the recall score of prior austenite grain(PAG)boundary was~93%,high angle packet boundary(OMA>40°)was~97%,and block boundary was~96%.The derived outcomes of ML were used to obtain insights into the ductile-to-brittle transition(DBTT)behavior.Interestingly,ML modeling approach suggested that DBTT was not determined by the density of high angle grain boundaries,but significantly influenced by the density of PAG and packet boundaries.The study underscores that ML has a great potential in detailed recognition of complex multi-hierarchical microstructure such as bainite and martensite and relates to material performance.展开更多
Monitring pest populations in paddy fields is important to effectively implement integrated pest management.Light traps are widely used to monitor field pests all over the world.Most conventional light traps still inv...Monitring pest populations in paddy fields is important to effectively implement integrated pest management.Light traps are widely used to monitor field pests all over the world.Most conventional light traps still involve manual identification of target pests from lots of trapped insects,which is time-consuming,labor-intensive and error-prone,especially in pest peak periods.In this paper,we developed an automatic monitoring system for rice light-trap pests based on machine vision.This system is composed of an itelligent light trap,a computer or mobile phone client platform and a cloud server.The light trap firstly traps,kills and disperses insects,then collects images of trapped insects and sends each image to the cloud server.Five target pests in images are automatically identifed and counted by pest identification models loaded in the server.To avoid light-trap insects piling up,a vibration plate and a moving rotation conveyor belt are adopted to disperse these trapped insects.There was a close correlation(r=0.92)between our automatic and manual identification methods based on the daily pest number of one-year images from one light trap.Field experiments demonstrated the effectiveness and accuracy of our automatic light trap monitoring system.展开更多
A full automatic welding machine for spherical tanks' all position multi layer welds has been developed. This machine is mainly composed of a two dimension seam tracking system based on microcomputer's memor...A full automatic welding machine for spherical tanks' all position multi layer welds has been developed. This machine is mainly composed of a two dimension seam tracking system based on microcomputer's memory and a welding tractor as well as rail. The main features of the machine are: while welding the first layer of a seam, its microcomputer system can analyze and store the tracing information from a two dimension sensor, and control the welding head device to realize two dimension real time tracing; while welding the second layer up to the top layer of the seam, it can realize two dimension tracing based on the memorial data, automatically determine the layer number and continually sway the welding head. The welding test shows that the machine has good tracing and welding behavior, and is suitable for spherical tank's all position multi layer welds.展开更多
A novel hot rolled steel LG600A with the tensile strength exceeding 700 MPa was developed for automatic teller machine application. Thelow-cost C-Mn steel was microalloyed with：0.08 mass%- 0.12 mass% Ti rather than n...A novel hot rolled steel LG600A with the tensile strength exceeding 700 MPa was developed for automatic teller machine application. Thelow-cost C-Mn steel was microalloyed with：0.08 mass%- 0.12 mass% Ti rather than noble alloying elements, such as Nb, V, Mo, and Cu, etc. The novel steel had a good surface quality and welding property. After the hot rolled steel coils were leveled, the steel plates, the length of which was even down to 1 500 mm, had an excellent flatness. The effects of hot rolling parameters on mechanical per formance, m icrostructure and recrystallization behavior were studied. The metallurgical concept for the steel production was also discussed. The result shows that decreasing the finish rolling temperature, increasing cooling rate in the first cooling stage and decreasing the cooling rate in the last cooling stage, together with coiling at a modestly high coiling temperature all resulted in the refined grains and TiC precipitates, thereby improving the strength and toughness of this new steel greatly.展开更多
The pipeline all-position automatic welding machine system is a special welding system for automatically welding circumferential joint of pipeline on site, which has been widely used to the long-distance pipeline cons...The pipeline all-position automatic welding machine system is a special welding system for automatically welding circumferential joint of pipeline on site, which has been widely used to the long-distance pipeline construction projects due to the advantages of automatic control for welding parameters at all-position, moving speed of bugs and operating. In this paper, the key control technologies of PAWM all-position automatic welding machine （ developed by Pipeline Research Institute of CNPC） such us the automatic control system, control software, personal digital assistant （PDA） software and complex programmable logic device （ CPLD ） program as well us the control method of welding parameter have been described detailedly. With the higher welding quality, higher welding effwiency and lower labor intensity, PA WM all-position automatic welding machine has been successfully applied in many famous pipeline construction projects.展开更多
Automatic speaker recognition(ASR)systems are the field of Human-machine interaction and scientists have been using feature extraction and feature matching methods to analyze and synthesize these signals.One of the mo...Automatic speaker recognition(ASR)systems are the field of Human-machine interaction and scientists have been using feature extraction and feature matching methods to analyze and synthesize these signals.One of the most commonly used methods for feature extraction is Mel Frequency Cepstral Coefficients(MFCCs).Recent researches show that MFCCs are successful in processing the voice signal with high accuracies.MFCCs represents a sequence of voice signal-specific features.This experimental analysis is proposed to distinguish Turkish speakers by extracting the MFCCs from the speech recordings.Since the human perception of sound is not linear,after the filterbank step in theMFCC method,we converted the obtained log filterbanks into decibel(dB)features-based spectrograms without applying the Discrete Cosine Transform(DCT).A new dataset was created with converted spectrogram into a 2-D array.Several learning algorithms were implementedwith a 10-fold cross-validationmethod to detect the speaker.The highest accuracy of 90.2%was achieved using Multi-layer Perceptron(MLP)with tanh activation function.The most important output of this study is the inclusion of human voice as a new feature set.展开更多
In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(S...In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.展开更多
Algorithm of STA/LTA is frequently used in automatic signal detection, in which the range of detection threshold is （0, ∞）, the optimal threshold should be determined by experiment to make a balance between false d...Algorithm of STA/LTA is frequently used in automatic signal detection, in which the range of detection threshold is （0, ∞）, the optimal threshold should be determined by experiment to make a balance between false detection and missing detection. By using the theory of pattern recognition, a new algorithm for automatic signal detection based on support vector machine was proposed and the method of preprocess and pattern feature extraction were dis- cussed as well as the selection of kernel function for support vector machine. The detection performance of the new algorithm was analyzed by means of real seismic data. The experiments showed that the new method could simplify the selection of threshold and detect signal accurately. In addition to the better performance of anti-noise, the ratio of false detection could decrease 85% in comparison with that of STA/LTA.展开更多
An automatic monitoring method of the 3-D deformation is presented for crustal fault based on laser and machine vision. The laser source and screen are independently set up in the headwall and footwall, the collimated...An automatic monitoring method of the 3-D deformation is presented for crustal fault based on laser and machine vision. The laser source and screen are independently set up in the headwall and footwall, the collimated laser beam creates a circular spot on the screen, meanwhile, the industrial camera captures the tiny deformation of the crustal fault by monitoring the change of the spot position. This method significantly reduces the cost of equipment and labor, provides daily sampling to ensure high continuity of data. A prototype of the automatic monitoring system is developed, and a repeatability test indicates that the error of spot jitter can be minimized by consecutive samples. Meanwhile, the environmental correction model is determined to ensure that environmental changes do not disturb the system. Furthermore, the automatic monitoring system has been applied at the deformation monitoring station(KJX02) of China Beishan underground research laboratory, where continuous deformation monitoring is underway.展开更多
This paper deals with the structure, components, characteristics and work principle of a newly developed automatic arc welding machine for saddle joint seams on large diameter cylinders. The equations for designing th...This paper deals with the structure, components, characteristics and work principle of a newly developed automatic arc welding machine for saddle joint seams on large diameter cylinders. The equations for designing the geometry and dimensions of the cam controlling the moving locus of the welding torch have been derived. This welding machine has successfully been used in automatic welding saddle joint seams on boiler drums with good results and low cost.展开更多
The new model Hitachi fully automatic washing machine is made by the Shanghai Hitachi Shangling Machinery Co. Ltd, using Japanese Hitachi technology and equipment. The product adopts a smooth, clean and abrasion-corro...The new model Hitachi fully automatic washing machine is made by the Shanghai Hitachi Shangling Machinery Co. Ltd, using Japanese Hitachi technology and equipment. The product adopts a smooth, clean and abrasion-corrosion-proof tub made of stainless titanium alloy steel. The wash tub has a large capacity and does not damage the clothing. The rotation speed is 900 per minute. The drying ability is 10％ higher than original展开更多
Automatic image annotation(AIA)has become an important and challenging problem in computer vision due to the existence of semantic gap.In this paper,a novel support vector machine with mixture of kernels(SVM-MK)for au...Automatic image annotation(AIA)has become an important and challenging problem in computer vision due to the existence of semantic gap.In this paper,a novel support vector machine with mixture of kernels(SVM-MK)for automatic image annotation is proposed.On one hand,the combined global and local block-based image features are extracted in order to reflect the intrinsic content of images as complete as possible.On the other hand,SVM-MK is constructed to shoot for better annotating performance.Experimental results on Corel dataset show that the proposed image feature representation method as well as automatic image annotation classifier,SVM-MK,can achieve higher annotating accuracy than SVM with any single kernel and mi-SVM for semantic image annotation.展开更多
Soya-bean milk has been a favorite drink for the Chinese people since ancient times. With the development of health consciousness, this low heat, low fat and highly nutritious natural drink has become popular. However...Soya-bean milk has been a favorite drink for the Chinese people since ancient times. With the development of health consciousness, this low heat, low fat and highly nutritious natural drink has become popular. However, backward production technology and a shortage of marketing channels have prevented people from having easy access to fresh soya-bean milk. The Qingzhou brand automatic household soya-bean milk machine developed by the Qingzhou Trade Company in Beijing is produced展开更多
The all position automatic welding machine system is the special welding system for pipeline girth automatic welding on site, which has been widely used in the long distance pipeline construction projects due to the a...The all position automatic welding machine system is the special welding system for pipeline girth automatic welding on site, which has been widely used in the long distance pipeline construction projects due to the advantages of automatic control for welding parameters at all position, moving speed of bugs and operating. This automatic pipeline welding system has been successfully used in several main pipeline projects in China, and has been approved by the constructors with the benefits of higher quality passing rate, higher welding efficiency and lower labor intensity.展开更多
The application of PLC technology can effectively improve the automation and intelligence of the cleaning machine. In this paper, PLC for the automatic transformation of the cleaning machine and its practical applicat...The application of PLC technology can effectively improve the automation and intelligence of the cleaning machine. In this paper, PLC for the automatic transformation of the cleaning machine and its practical application are explored. From the basic working principle of the cleaning machine, the transformation process of the cleaning machine after the introduction of PLC technology is introduced. Based on this, the problems existing in the practice process of the automatic cleaning machine and the solutions to the related problems are analyzed, so as to promote the automation of the power plant cleaning.展开更多
With the rapid development of social economy,the society has entered into a new stage of development,especially in new media under the background of rapid development,makes the importance of news and information to ge...With the rapid development of social economy,the society has entered into a new stage of development,especially in new media under the background of rapid development,makes the importance of news and information to get the comprehensive promotion,and in order to further identify the positive and negative news,should be fully using machine learning methods,based on the emotion to realize the automatic classifying of news,in order to improve the efficiency of news classification.Therefore,the article first makes clear the basic outline of news sentiment classification.Secondly,the specific way of automatic classification of news emotion is deeply analyzed.On the basis of this,the paper puts forward the concrete measures of automatic classification of news emotion by using machine learning.展开更多
基金Supported by National Natural Science Foundation of China(No.82074524)Harbin Medical University Graduate Research and Practice Innovation Project(No.YJSCX2023-50HYD).
文摘AIM:To develop different machine learning models to train and test diplopia images and data generated by the computerized diplopia test.METHODS:Diplopia images and data generated by computerized diplopia tests,along with patient medical records,were retrospectively collected from 3244 cases.Diagnostic models were constructed using logistic regression(LR),decision tree(DT),support vector machine(SVM),extreme gradient boosting(XGBoost),and deep learning(DL)algorithms.A total of 2757 diplopia images were randomly selected as training data,while the test dataset contained 487 diplopia images.The optimal diagnostic model was evaluated using test set accuracy,confusion matrix,and precision-recall curve(P-R curve).RESULTS:The test set accuracy of the LR,SVM,DT,XGBoost,DL(64 categories),and DL(6 binary classifications)algorithms was 0.762,0.811,0.818,0.812,0.858 and 0.858,respectively.The accuracy in the training set was 0.785,0.815,0.998,0.965,0.968,and 0.967,respectively.The weighted precision of LR,SVM,DT,XGBoost,DL(64 categories),and DL(6 binary classifications)algorithms was 0.74,0.77,0.83,0.80,0.85,and 0.85,respectively;weighted recall was 0.76,0.81,0.82,0.81,0.86,and 0.86,respectively;weighted F1 score was 0.74,0.79,0.82,0.80,0.85,and 0.85,respectively.CONCLUSION:In this study,the 7 machine learning algorithms all achieve automatic diagnosis of extraocular muscle palsy.The DL(64 categories)and DL(6 binary classifications)algorithms have a significant advantage over other machine learning algorithms regarding diagnostic accuracy on the test set,with a high level of consistency with clinical diagnoses made by physicians.Therefore,it can be used as a reference for diagnosis.
基金supported by Chunhui Collaborative Research Project funded by the Ministry of Education of China[Grant No.202200490]Humanities and Social Sciences Research Project funded by the Ministry of Education of China[Grant No.23YJAZH139].
文摘With the development of machine translation technology,automatic pre-editing has attracted increasing research attention for its important role in improving translation quality and efficiency.This study utilizes UAM Corpus Tool 3.0 to annotate and categorize 99 key publications between 1992 and 2024,tracing the research paths and technological evolution of automatic pre-translation editing.The study finds that current approaches can be classified into four categories:controlled language-based approaches,text simplification approaches,interlingua-based approaches,and large language model-driven approaches.By critically examining their technical features and applicability in various contexts,this review aims to provide valuable insights to guide the future optimization and expansion of pre-translation editing systems.
基金supported in part by the National Key R&D Program of China(Grant No.:2023YFF1205103)the National Natural Science Foundation of China(Grant No.:220330010)the Anhui’s Plans for Major Provincial Science&Technology Projects,China(Grant No.:202303a07020009).
文摘We developed MaxQsaring,a novel universal framework integrating molecular descriptors,fingerprints,and deep-learning pretrained representations,to predict the properties of compounds.Applied to a case study of human ether-à-go-go-related gene(hERG)blockage prediction,MaxQsaring achieved state-of-the-art performance on two challenging external datasets through automatic optimal feature combinations,and successfully identified top 10 important interpretable features that could be used to model a high-accuracy decision tree.The models'predictions align well with empirical hERG optimization strategies,demonstrating their interpretability for practical utilities.Deep learning pre-trained representations have been demonstrated to exert a moderate influence on enhancing the performance of predictive models.Nevertheless,their impact on augmenting the generalizability of these models,particularly when applied to compounds possessing novel scaffolds,appears to be comparatively minimal.MaxQsaring excelled in the Therapeutics Data Commons(TDC)benchmarks,ranking first in 19 out of 22 tasks,showcasing its potential for universal accurate compound property prediction to facilitate a high success rate of early drug discovery,which is still a formidable challenge.
基金The National Natural Science Foundation of China(No.51175267)the Natural Science Foundation of Jiangsu Province(No.BK2010481)+2 种基金the Ph.D.Programs Foundation of Ministry of Education of China(No.20113219120004)China Postdoctoral Science Foundation(No.20100481148)the Postdoctoral Science Foundation of Jiangsu Province(No.1001004B)
文摘To realize high-precision automatic measurement of two-dimensional geometric features on parts, a cooperative measurement system based on machine vision is constructed. Its hardware structure, functional composition and working principle are introduced. The mapping relationship between the feature image coordinates and the measuring space coordinates is established. The method of measuring path planning of small field of view （FOV） images is proposed. With the cooperation of the panoramic image of the object to be measured, the small FOV images with high object plane resolution are acquired automatically. Then, the auxiliary measuring characteristics are constructed and the parameters of the features to be measured are automatically extracted. Experimental results show that the absolute value of relative error is less than 0. 03% when applying the cooperative measurement system to gauge the hole distance of 100 mm nominal size. When the object plane resolving power of the small FOV images is 16 times that of the large FOV image, the measurement accuracy of small FOV images is improved by 14 times compared with the large FOV image. It is suitable for high-precision automatic measurement of two-dimensional complex geometric features distributed on large scale parts.
基金financially supported by the National Key Research and Development Program of China(No.2017YFB0304900)。
文摘Gradient boosting decision tree(GBDT)machine learning(ML)method was adopted for the first time to automatically recognize and conduct quantitative statistical analysis of boundaries in bainitic microstructure using electron back-scatter diffraction(EBSD)data.In spite of lack of large sets of EBSD data,we were successful in achieving the desired accuracy and accomplishing the objective of recognizing the boundaries.Compared with a low model accuracy of<50%as using Euler angles or axis-angle pair as characteristic features,the accuracy of the model was significantly enhanced to about 88%when the Euler angle was converted to overall misorientation angle(OMA)and specific misorientation angle(SMA)and considered as important features.In this model,the recall score of prior austenite grain(PAG)boundary was~93%,high angle packet boundary(OMA>40°)was~97%,and block boundary was~96%.The derived outcomes of ML were used to obtain insights into the ductile-to-brittle transition(DBTT)behavior.Interestingly,ML modeling approach suggested that DBTT was not determined by the density of high angle grain boundaries,but significantly influenced by the density of PAG and packet boundaries.The study underscores that ML has a great potential in detailed recognition of complex multi-hierarchical microstructure such as bainite and martensite and relates to material performance.
基金Supported by the Fundamental Public Welfare Research Program of Zhejiang Provincial Natural Science Foundation,China(LGN18C140007 and Y20C140024)the National High Technology Research and Development Program of China(863 Program,2013AA102402)the Agricultural Science and Technology Innovation Program of Chinese Academy of Agricultural Sciences.
文摘Monitring pest populations in paddy fields is important to effectively implement integrated pest management.Light traps are widely used to monitor field pests all over the world.Most conventional light traps still involve manual identification of target pests from lots of trapped insects,which is time-consuming,labor-intensive and error-prone,especially in pest peak periods.In this paper,we developed an automatic monitoring system for rice light-trap pests based on machine vision.This system is composed of an itelligent light trap,a computer or mobile phone client platform and a cloud server.The light trap firstly traps,kills and disperses insects,then collects images of trapped insects and sends each image to the cloud server.Five target pests in images are automatically identifed and counted by pest identification models loaded in the server.To avoid light-trap insects piling up,a vibration plate and a moving rotation conveyor belt are adopted to disperse these trapped insects.There was a close correlation(r=0.92)between our automatic and manual identification methods based on the daily pest number of one-year images from one light trap.Field experiments demonstrated the effectiveness and accuracy of our automatic light trap monitoring system.
文摘A full automatic welding machine for spherical tanks' all position multi layer welds has been developed. This machine is mainly composed of a two dimension seam tracking system based on microcomputer's memory and a welding tractor as well as rail. The main features of the machine are: while welding the first layer of a seam, its microcomputer system can analyze and store the tracing information from a two dimension sensor, and control the welding head device to realize two dimension real time tracing; while welding the second layer up to the top layer of the seam, it can realize two dimension tracing based on the memorial data, automatically determine the layer number and continually sway the welding head. The welding test shows that the machine has good tracing and welding behavior, and is suitable for spherical tank's all position multi layer welds.
文摘A novel hot rolled steel LG600A with the tensile strength exceeding 700 MPa was developed for automatic teller machine application. Thelow-cost C-Mn steel was microalloyed with：0.08 mass%- 0.12 mass% Ti rather than noble alloying elements, such as Nb, V, Mo, and Cu, etc. The novel steel had a good surface quality and welding property. After the hot rolled steel coils were leveled, the steel plates, the length of which was even down to 1 500 mm, had an excellent flatness. The effects of hot rolling parameters on mechanical per formance, m icrostructure and recrystallization behavior were studied. The metallurgical concept for the steel production was also discussed. The result shows that decreasing the finish rolling temperature, increasing cooling rate in the first cooling stage and decreasing the cooling rate in the last cooling stage, together with coiling at a modestly high coiling temperature all resulted in the refined grains and TiC precipitates, thereby improving the strength and toughness of this new steel greatly.
文摘The pipeline all-position automatic welding machine system is a special welding system for automatically welding circumferential joint of pipeline on site, which has been widely used to the long-distance pipeline construction projects due to the advantages of automatic control for welding parameters at all-position, moving speed of bugs and operating. In this paper, the key control technologies of PAWM all-position automatic welding machine （ developed by Pipeline Research Institute of CNPC） such us the automatic control system, control software, personal digital assistant （PDA） software and complex programmable logic device （ CPLD ） program as well us the control method of welding parameter have been described detailedly. With the higher welding quality, higher welding effwiency and lower labor intensity, PA WM all-position automatic welding machine has been successfully applied in many famous pipeline construction projects.
基金This work was supported by the GRRC program of Gyeonggi province.[GRRC-Gachon2020(B04),Development of AI-based Healthcare Devices].
文摘Automatic speaker recognition(ASR)systems are the field of Human-machine interaction and scientists have been using feature extraction and feature matching methods to analyze and synthesize these signals.One of the most commonly used methods for feature extraction is Mel Frequency Cepstral Coefficients(MFCCs).Recent researches show that MFCCs are successful in processing the voice signal with high accuracies.MFCCs represents a sequence of voice signal-specific features.This experimental analysis is proposed to distinguish Turkish speakers by extracting the MFCCs from the speech recordings.Since the human perception of sound is not linear,after the filterbank step in theMFCC method,we converted the obtained log filterbanks into decibel(dB)features-based spectrograms without applying the Discrete Cosine Transform(DCT).A new dataset was created with converted spectrogram into a 2-D array.Several learning algorithms were implementedwith a 10-fold cross-validationmethod to detect the speaker.The highest accuracy of 90.2%was achieved using Multi-layer Perceptron(MLP)with tanh activation function.The most important output of this study is the inclusion of human voice as a new feature set.
基金Projects(61471370,61401479)supported by the National Natural Science Foundation of China
文摘In order to improve measurement accuracy of moving target signals, an automatic target recognition model of moving target signals was established based on empirical mode decomposition(EMD) and support vector machine(SVM). Automatic target recognition process on the nonlinear and non-stationary of Doppler signals of military target by using automatic target recognition model can be expressed as follows. Firstly, the nonlinearity and non-stationary of Doppler signals were decomposed into a set of intrinsic mode functions(IMFs) using EMD. After the Hilbert transform of IMF, the energy ratio of each IMF to the total IMFs can be extracted as the features of military target. Then, the SVM was trained through using the energy ratio to classify the military targets, and genetic algorithm(GA) was used to optimize SVM parameters in the solution space. The experimental results show that this algorithm can achieve the recognition accuracies of 86.15%, 87.93%, and 82.28% for tank, vehicle and soldier, respectively.
文摘Algorithm of STA/LTA is frequently used in automatic signal detection, in which the range of detection threshold is （0, ∞）, the optimal threshold should be determined by experiment to make a balance between false detection and missing detection. By using the theory of pattern recognition, a new algorithm for automatic signal detection based on support vector machine was proposed and the method of preprocess and pattern feature extraction were dis- cussed as well as the selection of kernel function for support vector machine. The detection performance of the new algorithm was analyzed by means of real seismic data. The experiments showed that the new method could simplify the selection of threshold and detect signal accurately. In addition to the better performance of anti-noise, the ratio of false detection could decrease 85% in comparison with that of STA/LTA.
基金supported by Earthquake Sciences Spark Programs of China Earthquake Administration(No.XH22020YA)Science Innovation Fund granted by the First Monitoring and Application Center of China Earthquake Administration(No.FMC202309).
文摘An automatic monitoring method of the 3-D deformation is presented for crustal fault based on laser and machine vision. The laser source and screen are independently set up in the headwall and footwall, the collimated laser beam creates a circular spot on the screen, meanwhile, the industrial camera captures the tiny deformation of the crustal fault by monitoring the change of the spot position. This method significantly reduces the cost of equipment and labor, provides daily sampling to ensure high continuity of data. A prototype of the automatic monitoring system is developed, and a repeatability test indicates that the error of spot jitter can be minimized by consecutive samples. Meanwhile, the environmental correction model is determined to ensure that environmental changes do not disturb the system. Furthermore, the automatic monitoring system has been applied at the deformation monitoring station(KJX02) of China Beishan underground research laboratory, where continuous deformation monitoring is underway.
文摘This paper deals with the structure, components, characteristics and work principle of a newly developed automatic arc welding machine for saddle joint seams on large diameter cylinders. The equations for designing the geometry and dimensions of the cam controlling the moving locus of the welding torch have been derived. This welding machine has successfully been used in automatic welding saddle joint seams on boiler drums with good results and low cost.
文摘The new model Hitachi fully automatic washing machine is made by the Shanghai Hitachi Shangling Machinery Co. Ltd, using Japanese Hitachi technology and equipment. The product adopts a smooth, clean and abrasion-corrosion-proof tub made of stainless titanium alloy steel. The wash tub has a large capacity and does not damage the clothing. The rotation speed is 900 per minute. The drying ability is 10％ higher than original
基金Supported by the National Basic Research Priorities Programme(No.2007CB311004)the National Natural Science Foundation of China(No.61035003,60933004,60903141,60970088,61072085)
文摘Automatic image annotation(AIA)has become an important and challenging problem in computer vision due to the existence of semantic gap.In this paper,a novel support vector machine with mixture of kernels(SVM-MK)for automatic image annotation is proposed.On one hand,the combined global and local block-based image features are extracted in order to reflect the intrinsic content of images as complete as possible.On the other hand,SVM-MK is constructed to shoot for better annotating performance.Experimental results on Corel dataset show that the proposed image feature representation method as well as automatic image annotation classifier,SVM-MK,can achieve higher annotating accuracy than SVM with any single kernel and mi-SVM for semantic image annotation.
文摘Soya-bean milk has been a favorite drink for the Chinese people since ancient times. With the development of health consciousness, this low heat, low fat and highly nutritious natural drink has become popular. However, backward production technology and a shortage of marketing channels have prevented people from having easy access to fresh soya-bean milk. The Qingzhou brand automatic household soya-bean milk machine developed by the Qingzhou Trade Company in Beijing is produced
文摘The all position automatic welding machine system is the special welding system for pipeline girth automatic welding on site, which has been widely used in the long distance pipeline construction projects due to the advantages of automatic control for welding parameters at all position, moving speed of bugs and operating. This automatic pipeline welding system has been successfully used in several main pipeline projects in China, and has been approved by the constructors with the benefits of higher quality passing rate, higher welding efficiency and lower labor intensity.
文摘The application of PLC technology can effectively improve the automation and intelligence of the cleaning machine. In this paper, PLC for the automatic transformation of the cleaning machine and its practical application are explored. From the basic working principle of the cleaning machine, the transformation process of the cleaning machine after the introduction of PLC technology is introduced. Based on this, the problems existing in the practice process of the automatic cleaning machine and the solutions to the related problems are analyzed, so as to promote the automation of the power plant cleaning.
文摘With the rapid development of social economy,the society has entered into a new stage of development,especially in new media under the background of rapid development,makes the importance of news and information to get the comprehensive promotion,and in order to further identify the positive and negative news,should be fully using machine learning methods,based on the emotion to realize the automatic classifying of news,in order to improve the efficiency of news classification.Therefore,the article first makes clear the basic outline of news sentiment classification.Secondly,the specific way of automatic classification of news emotion is deeply analyzed.On the basis of this,the paper puts forward the concrete measures of automatic classification of news emotion by using machine learning.
