Driven by both the“new engineering”initiative and the energy revolution,the traditional engineering education model can hardly meet the demand of the energy and electric power industry for diversified and interdisci...Driven by both the“new engineering”initiative and the energy revolution,the traditional engineering education model can hardly meet the demand of the energy and electric power industry for diversified and interdisciplinary outstanding engineers.Based on the“industry-university-research-application”four-in-one collaborative education concept,this paper constructs a new training system centered on classified cultivation and classified evaluation.The system aims to solve core problems such as homogeneous training,disconnection between industry and academia,single evaluation method,and insufficient faculty.Through measures including modular courses,the dual-tutor system,and diversified practical platforms,it realizes differentiated and precise talent training,so as to deliver outstanding engineers with the ability to“define problems,break through technologies,and create value”for the energy and electric power industry.展开更多
An Extended Kalman Filter（EKF） is commonly used to fuse raw Global Navigation Satellite System（GNSS） measurements and Inertial Navigation System（INS） derived measurements. However, the Conventional EKF（CEKF） s...An Extended Kalman Filter（EKF） is commonly used to fuse raw Global Navigation Satellite System（GNSS） measurements and Inertial Navigation System（INS） derived measurements. However, the Conventional EKF（CEKF） suffers the problem for which the uncertainty of the statistical properties to dynamic and measurement models will degrade the performance.In this research, an Adaptive Interacting Multiple Model（AIMM） filter is developed to enhance performance. The soft-switching property of Interacting Multiple Model（IMM） algorithm allows the adaptation between two levels of process noise, namely lower and upper bounds of the process noise. In particular, the Sage adaptive filtering is applied to adapt the measurement covariance on line. In addition, a classified measurement update strategy is utilized, which updates the pseudorange and Doppler observations sequentially. A field experiment was conducted to validate the proposed algorithm, the pseudorange and Doppler observations from Global Positioning System（GPS） and Bei Dou Navigation Satellite System（BDS） were post-processed in differential mode.The results indicate that decimeter-level positioning accuracy is achievable with AIMM for GPS/INS and GPS/BDS/INS configurations, and the position accuracy is improved by 35.8%, 34.3% and 33.9% for north, east and height components, respectively, compared to the CEKF counterpartfor GPS/BDS/INS. Degraded performance for BDS/INS is obtained due to the lower precision of BDS pseudorange observations.展开更多
In this paper, based on hourly precipitation observations in 1977e2013 in the Beijing area, China, hourly precipitation in summer (June?August) is classified into three categories: light (below the 50th percentile val...In this paper, based on hourly precipitation observations in 1977e2013 in the Beijing area, China, hourly precipitation in summer (June?August) is classified into three categories: light (below the 50th percentile values), moderate (the 50th to 95th percentile values), and heavy (above the 95th percentile values). Results reveal that both light and moderate precipitation decreased significantly during the research period and thereby caused the decrease in summer totals. By contrast, pronounced trends failed to be detected in the heavy category. Since 2004, the contribution of heavy rainfall to the summer total precipitation in the urban area increased as compared to the suburban area, which is opposite to light rainfall. There are obvious differences in the diurnal variations of classified precipitation. Light precipitation shows a double peak structure in the early morning and at night, while moderate and heavy rainfall show a single peak at night. Light precipitation at the early morning peak time decreased significantly in the whole Beijing area. Compared with the suburban area, light precipitation in the urban area occurred less frequently whereas heavy precipitation occurred more frequently at evening peak time after 2004. The asymmetry of the rainfall is obvious, especially, for heavy precipitation. The asymmetry of heavy precipitation events in the urban area exhibits a significant increasing trend.展开更多
A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages ...A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages by DWT. The lowest frequency subimage is compressed by scalar quantization and ADPCM. The high frequency subimages are compressed by CVQ to utilize the similarity among different resolutions while improving the edge quality and reducing computational complexity. The experimental results show that the proposed scheme has a better performance than JPEG, and a PSNR of reconstructed image is 31～33 dB with a rate of 0.2 bpp.展开更多
Feature extraction and selection from signals is a key issue for metal magnetic memory testing technique. In order to realize the classification of metal magnetic memory signals of welding defects, four fractal analys...Feature extraction and selection from signals is a key issue for metal magnetic memory testing technique. In order to realize the classification of metal magnetic memory signals of welding defects, four fractal analysis methods, such as box- counting, detrended fluctuation, minimal cover and rescaled-range analysis, were used to extract the feature signal after the original metal magnet memory signal was de-noising and differential processing, then the Karhunen-Lo^e transformation was adopted as classification tool to identify the defect signals. The result shows that this study can provide an efficient classification method for metal magnetic memory signal of welding defects.展开更多
In order to disclose present situation and problem of classified collection of municipal solid waste in Wanghua District of Fushun and ana- lyze its practicability, questionnaire was designed in this paper, random res...In order to disclose present situation and problem of classified collection of municipal solid waste in Wanghua District of Fushun and ana- lyze its practicability, questionnaire was designed in this paper, random research was adopted in Wanghua District, and statistic analysis of investi- gation result was conducted. This investigation could provide basis for popularizing classified collection of municipal solid waste in the whole nation.展开更多
Based on the data of the cases of severe convection weather such as hail,thunderstorm(thunderstorm gale)and short-time heavy precipitation in recent 10 years,the spatial and temporal distribution characteristics of di...Based on the data of the cases of severe convection weather such as hail,thunderstorm(thunderstorm gale)and short-time heavy precipitation in recent 10 years,the spatial and temporal distribution characteristics of different types of severe convection weather were analyzed.The results show that the frequency of severe convection weather tended to increase,of which short-time heavy precipitation and thunderstorm weather rose,and hail and thunderstorm gale weather decreased.Severe convection weather began to extend in late spring and early autumn.Typical cases were selected to analyze the evolution mechanism,and the conceptual models of severe convective weather caused by cold advection forcing,warm advection forcing and baroclinic frontogenesis were obtained.The key predictors for the potential prediction of severe convection weather were proposed,such as CAPE(convective available potential energy)for hail weather,UH index(maximum ascending helicity)for thunderstorm gale and PWV(precipitable water vapor)for short-time heavy precipitation.ERA5 data were used to get the forecast threshold of the key factor of classified severe convection weather,and it was verified that the threshold was available.Meanwhile,the causes of the error of failure cases were analyzed.For instance,the larger deviation of CAPE was caused by the 2 m deviation of temperature.Supplementary correction method and threshold were given to provide a reference for the objective forecast and early warning of severe convection weather.展开更多
Protected areas contain most of Burkina Faso’s plant biodiversity which confer different benefits for the communities. However, the composition of some of them remains unknown. In a context of overexploitation and cl...Protected areas contain most of Burkina Faso’s plant biodiversity which confer different benefits for the communities. However, the composition of some of them remains unknown. In a context of overexploitation and climate change, it is important to have a detailed knowledge of the vegetation of forests that have not been studied, such as Péni Classified Forest (PCF) to develop better preservation protocols. The aim of this study is to contribute to the knowledge of the flora of Burkina Faso. Phytosociological surveys were carried out in 213 plots, have identified 475 species distributed in 321 genera and 87 families. We identified during this study 201 woody species representing 38% of the woody flora of Burkina Faso. 64% of this flora is confined to shrub savannahs and 61% to tree savannahs. Among the vegetation units, shrub savannahs and tree savannahs have respectively 56.21% and 44.67% of very rare species. Poaceae (11.90%), Fabaceae-Faboideae (11.27%) and Rubiaceae (6.26%) are the most dominant families. The dominant biological types of the flora are phanerophytes (42.32%) and therophytes (30.32%), and Sudanian species (20.63%) are the best represented. Logging is the most frequent disturbance factor (100%) in the PCF. The PCF is a particular ecosystem with a great diversity but subject to many disturbances. Actions to strengthen its protection are necessary.展开更多
Over the past years,with the increasing enrollment of high school,vocational schools are facing great challenge for their existence and development,concerning the low proficiency of the students and great gap among th...Over the past years,with the increasing enrollment of high school,vocational schools are facing great challenge for their existence and development,concerning the low proficiency of the students and great gap among them.The traditional English teaching mode which employs the same teaching contents,same teaching methods and teaching aims cannot satisfy students with different English levels.Therefore,in order to change the present situation,this paper proposes a new English teaching mode:classified English teaching.In the new mode,different students will be taught by different materials,different methods and with different aims.It can stimulate students'enthusiasm in English learning,and make every student develop appropriately.展开更多
In the process of Higher Vocational classified examination enrollment reform,Jilin Province has adopted a diversified examination enrollment model and“cultural quality test+vocational skill test”evaluation method,an...In the process of Higher Vocational classified examination enrollment reform,Jilin Province has adopted a diversified examination enrollment model and“cultural quality test+vocational skill test”evaluation method,and established the“vocational education college entrance examination”system.This paper analyzes the important role and practical difficulties of“vocational skill test”in Higher Vocational classified examination,studies the existing problems,and puts forward to reasonably divide the proportion of“cultural quality test”and“vocational skill test”,sets diversified admission standards,scientifically sets up the assessment methods and contents of“vocational skill test”,further improves the“cultural quality test+vocational skill test”evaluation method and builds a classified examination and enrollment system more in line with the characteristics of vocational education.展开更多
In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, differen...In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, different from that in the 4G LTE system, the cyclic redundancy check(CRC) in polar decoding plays both error correction and error detection roles. Consequently, the false alarm rates(FAR) may not meet the system requirements(FAR<1.52 × 10^(−5)). In this paper, to mitigate the FAR in polar code blind detection, we attach a binary classifier after the polar decoder to further remove the false alarm results and meanwhile retain the correct DCI. This classifier works by tracking the squared Euclidean distance ratio(SEDR) between the received signal and hypothesis. We derive an analytical method to fast compute proper classification threshold that is implementation-friendly in practical use. Combining the well-designed classifier, we show that some very short CRC sequences can even be used to meet the FAR requirements. This consequently reduces the CRC overhead and contributes to the system error performance improvements.展开更多
The current journal is mainly focused in zoological systematics. According to Systematics Agenda 2000(1994), systematics is the science built on the following tasks: Taxonomy—the science of discovering, describing, a...The current journal is mainly focused in zoological systematics. According to Systematics Agenda 2000(1994), systematics is the science built on the following tasks: Taxonomy—the science of discovering, describing, and classifying species or groups of species(together termed taxa);Phylogenetic analysis—the discovery of the evolutionary relationships among a group of species;and Classification—the grouping of species, ultimately on the basis of evolutionary relationships.展开更多
Background:In the field of genetic diagnostics,DNA sequencing is an important tool because the depth and complexity of this field have major implications in light of the genetic architectures of diseases and the ident...Background:In the field of genetic diagnostics,DNA sequencing is an important tool because the depth and complexity of this field have major implications in light of the genetic architectures of diseases and the identification of risk factors associated with genetic disorders.Methods:Our study introduces a novel two-tiered analytical framework to raise the precision and reliability of genetic data interpretation.It is initiated by extracting and analyzing salient features from DNA sequences through a CNN-based feature analysis,taking advantage of the power inherent in Convolutional neural networks(CNNs)to attain complex patterns and minute mutations in genetic data.This study embraces an elite collection of machine learning classifiers interweaved through a stern voting mechanism,which synergistically joins the predictions made from multiple classifiers to generate comprehensive and well-balanced interpretations of the genetic data.Results:This state-of-the-art method was further tested by carrying out an empirical analysis on a variants'dataset of DNA sequences taken from patients affected by breast cancer,juxtaposed with a control group composed of healthy people.Thus,the integration of CNNs with a voting-based ensemble of classifiers returned outstanding outcomes,with performance metrics accuracy,precision,recall,and F1-scorereaching the outstanding rate of 0.88,outperforming previous models.Conclusions:This dual accomplishment underlines the transformative potential that integrating deep learning techniques with ensemble machine learning might provide in real added value for further genetic diagnostics and prognostics.These results from this study set a new benchmark in the accuracy of disease diagnosis through DNA sequencing and promise future studies on improved personalized medicine and healthcare approaches with precise genetic information.展开更多
Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions f...Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera angles.This research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)videos.The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale images.The YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further processing.The joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are included.These features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity classification.Real-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing methods.In particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.展开更多
Metal-organic frameworks(MOFs)have garnered widespread attention due to their designability and diversity[1].Customization has always been a pursuit of chemists and materials scientists[2].Topology provides a means of...Metal-organic frameworks(MOFs)have garnered widespread attention due to their designability and diversity[1].Customization has always been a pursuit of chemists and materials scientists[2].Topology provides a means of abstracting the complex structures of MOFs by identifying and classifying the fundamental building units and connection patterns,simplifying the understanding of MOF structures[3].展开更多
文摘Driven by both the“new engineering”initiative and the energy revolution,the traditional engineering education model can hardly meet the demand of the energy and electric power industry for diversified and interdisciplinary outstanding engineers.Based on the“industry-university-research-application”four-in-one collaborative education concept,this paper constructs a new training system centered on classified cultivation and classified evaluation.The system aims to solve core problems such as homogeneous training,disconnection between industry and academia,single evaluation method,and insufficient faculty.Through measures including modular courses,the dual-tutor system,and diversified practical platforms,it realizes differentiated and precise talent training,so as to deliver outstanding engineers with the ability to“define problems,break through technologies,and create value”for the energy and electric power industry.
基金co-supported by the National Key Research and Development Program of China(No.2016YFC0803103)Beijing Advanced Innovation Center for Future Urban Design(No.UDC2016050100)Beijing Postdoctoral Research Foundation
文摘An Extended Kalman Filter（EKF） is commonly used to fuse raw Global Navigation Satellite System（GNSS） measurements and Inertial Navigation System（INS） derived measurements. However, the Conventional EKF（CEKF） suffers the problem for which the uncertainty of the statistical properties to dynamic and measurement models will degrade the performance.In this research, an Adaptive Interacting Multiple Model（AIMM） filter is developed to enhance performance. The soft-switching property of Interacting Multiple Model（IMM） algorithm allows the adaptation between two levels of process noise, namely lower and upper bounds of the process noise. In particular, the Sage adaptive filtering is applied to adapt the measurement covariance on line. In addition, a classified measurement update strategy is utilized, which updates the pseudorange and Doppler observations sequentially. A field experiment was conducted to validate the proposed algorithm, the pseudorange and Doppler observations from Global Positioning System（GPS） and Bei Dou Navigation Satellite System（BDS） were post-processed in differential mode.The results indicate that decimeter-level positioning accuracy is achievable with AIMM for GPS/INS and GPS/BDS/INS configurations, and the position accuracy is improved by 35.8%, 34.3% and 33.9% for north, east and height components, respectively, compared to the CEKF counterpartfor GPS/BDS/INS. Degraded performance for BDS/INS is obtained due to the lower precision of BDS pseudorange observations.
基金This work was supported by the National Natural Science Foundation of China (41575094) and Special Scientific Research Fund of Meteorological Public Welfare Profession of China (GYHY201506014).
文摘In this paper, based on hourly precipitation observations in 1977e2013 in the Beijing area, China, hourly precipitation in summer (June?August) is classified into three categories: light (below the 50th percentile values), moderate (the 50th to 95th percentile values), and heavy (above the 95th percentile values). Results reveal that both light and moderate precipitation decreased significantly during the research period and thereby caused the decrease in summer totals. By contrast, pronounced trends failed to be detected in the heavy category. Since 2004, the contribution of heavy rainfall to the summer total precipitation in the urban area increased as compared to the suburban area, which is opposite to light rainfall. There are obvious differences in the diurnal variations of classified precipitation. Light precipitation shows a double peak structure in the early morning and at night, while moderate and heavy rainfall show a single peak at night. Light precipitation at the early morning peak time decreased significantly in the whole Beijing area. Compared with the suburban area, light precipitation in the urban area occurred less frequently whereas heavy precipitation occurred more frequently at evening peak time after 2004. The asymmetry of the rainfall is obvious, especially, for heavy precipitation. The asymmetry of heavy precipitation events in the urban area exhibits a significant increasing trend.
文摘A new remote sensing image coding scheme based on the wavelet transform and classified vector quantization (CVQ) is proposed. The original image is first decomposed into a hierarchy of 3 layers including 10 subimages by DWT. The lowest frequency subimage is compressed by scalar quantization and ADPCM. The high frequency subimages are compressed by CVQ to utilize the similarity among different resolutions while improving the edge quality and reducing computational complexity. The experimental results show that the proposed scheme has a better performance than JPEG, and a PSNR of reconstructed image is 31～33 dB with a rate of 0.2 bpp.
基金This work was supported by Tianjin Natural Science Foundation （No. 11JCYBJC06000） and Specialized Research Fund for the Doctoral Program of Higher Education of China （No. 20100032120019）.
文摘Feature extraction and selection from signals is a key issue for metal magnetic memory testing technique. In order to realize the classification of metal magnetic memory signals of welding defects, four fractal analysis methods, such as box- counting, detrended fluctuation, minimal cover and rescaled-range analysis, were used to extract the feature signal after the original metal magnet memory signal was de-noising and differential processing, then the Karhunen-Lo^e transformation was adopted as classification tool to identify the defect signals. The result shows that this study can provide an efficient classification method for metal magnetic memory signal of welding defects.
文摘In order to disclose present situation and problem of classified collection of municipal solid waste in Wanghua District of Fushun and ana- lyze its practicability, questionnaire was designed in this paper, random research was adopted in Wanghua District, and statistic analysis of investi- gation result was conducted. This investigation could provide basis for popularizing classified collection of municipal solid waste in the whole nation.
基金Supported by the Open-end Funds of Key Laboratory for Disaster Prevention and Mitigation of Qinghai Province(QFZ-2021-Z04)。
文摘Based on the data of the cases of severe convection weather such as hail,thunderstorm(thunderstorm gale)and short-time heavy precipitation in recent 10 years,the spatial and temporal distribution characteristics of different types of severe convection weather were analyzed.The results show that the frequency of severe convection weather tended to increase,of which short-time heavy precipitation and thunderstorm weather rose,and hail and thunderstorm gale weather decreased.Severe convection weather began to extend in late spring and early autumn.Typical cases were selected to analyze the evolution mechanism,and the conceptual models of severe convective weather caused by cold advection forcing,warm advection forcing and baroclinic frontogenesis were obtained.The key predictors for the potential prediction of severe convection weather were proposed,such as CAPE(convective available potential energy)for hail weather,UH index(maximum ascending helicity)for thunderstorm gale and PWV(precipitable water vapor)for short-time heavy precipitation.ERA5 data were used to get the forecast threshold of the key factor of classified severe convection weather,and it was verified that the threshold was available.Meanwhile,the causes of the error of failure cases were analyzed.For instance,the larger deviation of CAPE was caused by the 2 m deviation of temperature.Supplementary correction method and threshold were given to provide a reference for the objective forecast and early warning of severe convection weather.
文摘Protected areas contain most of Burkina Faso’s plant biodiversity which confer different benefits for the communities. However, the composition of some of them remains unknown. In a context of overexploitation and climate change, it is important to have a detailed knowledge of the vegetation of forests that have not been studied, such as Péni Classified Forest (PCF) to develop better preservation protocols. The aim of this study is to contribute to the knowledge of the flora of Burkina Faso. Phytosociological surveys were carried out in 213 plots, have identified 475 species distributed in 321 genera and 87 families. We identified during this study 201 woody species representing 38% of the woody flora of Burkina Faso. 64% of this flora is confined to shrub savannahs and 61% to tree savannahs. Among the vegetation units, shrub savannahs and tree savannahs have respectively 56.21% and 44.67% of very rare species. Poaceae (11.90%), Fabaceae-Faboideae (11.27%) and Rubiaceae (6.26%) are the most dominant families. The dominant biological types of the flora are phanerophytes (42.32%) and therophytes (30.32%), and Sudanian species (20.63%) are the best represented. Logging is the most frequent disturbance factor (100%) in the PCF. The PCF is a particular ecosystem with a great diversity but subject to many disturbances. Actions to strengthen its protection are necessary.
文摘Over the past years,with the increasing enrollment of high school,vocational schools are facing great challenge for their existence and development,concerning the low proficiency of the students and great gap among them.The traditional English teaching mode which employs the same teaching contents,same teaching methods and teaching aims cannot satisfy students with different English levels.Therefore,in order to change the present situation,this paper proposes a new English teaching mode:classified English teaching.In the new mode,different students will be taught by different materials,different methods and with different aims.It can stimulate students'enthusiasm in English learning,and make every student develop appropriately.
基金This work was supported by the Social Science Project of the 13th Five-Year Plan of Jilin Provincial Department of Education under Grant no.JJKH20200635SKthe 2019 Vocational Education and Adult Education Teaching Reform Research Project of Jilin Provincial Department of Education under Grant nos.2019ZCZ067,2019ZCY413 and 2019ZCY414.
文摘In the process of Higher Vocational classified examination enrollment reform,Jilin Province has adopted a diversified examination enrollment model and“cultural quality test+vocational skill test”evaluation method,and established the“vocational education college entrance examination”system.This paper analyzes the important role and practical difficulties of“vocational skill test”in Higher Vocational classified examination,studies the existing problems,and puts forward to reasonably divide the proportion of“cultural quality test”and“vocational skill test”,sets diversified admission standards,scientifically sets up the assessment methods and contents of“vocational skill test”,further improves the“cultural quality test+vocational skill test”evaluation method and builds a classified examination and enrollment system more in line with the characteristics of vocational education.
基金supported in part by National Natural Science Foundation of China(No.62471054)in part by National Natural Science Foundation of China(No.92467301)+3 种基金in part by the National Natural Science Foundation of China(No.62201562)in part by the National Natural Science Foundation of China(No.62371063)in part by the National Natural Science Foundation of China(No.62321001)in part by Liaoning Provincial Natural Science Foundation of China(No.2024–BSBA–51).
文摘In 5G new radio(NR), polar codes are adopted for e MBB downlink control channels where the blind detection is employed in user equipment(UE) to identify the correct downlink control information(DCI). However, different from that in the 4G LTE system, the cyclic redundancy check(CRC) in polar decoding plays both error correction and error detection roles. Consequently, the false alarm rates(FAR) may not meet the system requirements(FAR<1.52 × 10^(−5)). In this paper, to mitigate the FAR in polar code blind detection, we attach a binary classifier after the polar decoder to further remove the false alarm results and meanwhile retain the correct DCI. This classifier works by tracking the squared Euclidean distance ratio(SEDR) between the received signal and hypothesis. We derive an analytical method to fast compute proper classification threshold that is implementation-friendly in practical use. Combining the well-designed classifier, we show that some very short CRC sequences can even be used to meet the FAR requirements. This consequently reduces the CRC overhead and contributes to the system error performance improvements.
文摘The current journal is mainly focused in zoological systematics. According to Systematics Agenda 2000(1994), systematics is the science built on the following tasks: Taxonomy—the science of discovering, describing, and classifying species or groups of species(together termed taxa);Phylogenetic analysis—the discovery of the evolutionary relationships among a group of species;and Classification—the grouping of species, ultimately on the basis of evolutionary relationships.
文摘Background:In the field of genetic diagnostics,DNA sequencing is an important tool because the depth and complexity of this field have major implications in light of the genetic architectures of diseases and the identification of risk factors associated with genetic disorders.Methods:Our study introduces a novel two-tiered analytical framework to raise the precision and reliability of genetic data interpretation.It is initiated by extracting and analyzing salient features from DNA sequences through a CNN-based feature analysis,taking advantage of the power inherent in Convolutional neural networks(CNNs)to attain complex patterns and minute mutations in genetic data.This study embraces an elite collection of machine learning classifiers interweaved through a stern voting mechanism,which synergistically joins the predictions made from multiple classifiers to generate comprehensive and well-balanced interpretations of the genetic data.Results:This state-of-the-art method was further tested by carrying out an empirical analysis on a variants'dataset of DNA sequences taken from patients affected by breast cancer,juxtaposed with a control group composed of healthy people.Thus,the integration of CNNs with a voting-based ensemble of classifiers returned outstanding outcomes,with performance metrics accuracy,precision,recall,and F1-scorereaching the outstanding rate of 0.88,outperforming previous models.Conclusions:This dual accomplishment underlines the transformative potential that integrating deep learning techniques with ensemble machine learning might provide in real added value for further genetic diagnostics and prognostics.These results from this study set a new benchmark in the accuracy of disease diagnosis through DNA sequencing and promise future studies on improved personalized medicine and healthcare approaches with precise genetic information.
基金funded by the Open Access Initiative of the University of Bremen and the DFG via SuUB Bremen.Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2024R348),Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Human Activity Recognition(HAR)in drone-captured videos has become popular because of the interest in various fields such as video surveillance,sports analysis,and human-robot interaction.However,recognizing actions from such videos poses the following challenges:variations of human motion,the complexity of backdrops,motion blurs,occlusions,and restricted camera angles.This research presents a human activity recognition system to address these challenges by working with drones’red-green-blue(RGB)videos.The first step in the proposed system involves partitioning videos into frames and then using bilateral filtering to improve the quality of object foregrounds while reducing background interference before converting from RGB to grayscale images.The YOLO(You Only Look Once)algorithm detects and extracts humans from each frame,obtaining their skeletons for further processing.The joint angles,displacement and velocity,histogram of oriented gradients(HOG),3D points,and geodesic Distance are included.These features are optimized using Quadratic Discriminant Analysis(QDA)and utilized in a Neuro-Fuzzy Classifier(NFC)for activity classification.Real-world evaluations on the Drone-Action,Unmanned Aerial Vehicle(UAV)-Gesture,and Okutama-Action datasets substantiate the proposed system’s superiority in accuracy rates over existing methods.In particular,the system obtains recognition rates of 93%for drone action,97%for UAV gestures,and 81%for Okutama-action,demonstrating the system’s reliability and ability to learn human activity from drone videos.
基金supported by the National Natural Science Foundation of China(22101039,22471027,22311530679)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China(22021005)the Fundamental Research Funds for the Central Universities(DUT24LK004).
文摘Metal-organic frameworks(MOFs)have garnered widespread attention due to their designability and diversity[1].Customization has always been a pursuit of chemists and materials scientists[2].Topology provides a means of abstracting the complex structures of MOFs by identifying and classifying the fundamental building units and connection patterns,simplifying the understanding of MOF structures[3].
