This paper reviews the research progress on mold detection technologies in milk and dairy products,including rapid test sheet methods,molecular biological detection techniques,metabolomics detection techniques,enzyme-...This paper reviews the research progress on mold detection technologies in milk and dairy products,including rapid test sheet methods,molecular biological detection techniques,metabolomics detection techniques,enzyme-linked immunosorbent assay(ELISA),and microbial rapid photoelectric detection systems,aiming to provide optimal choices for mold detection.展开更多
A recent study by Nishizawa et al presented significant findings regarding the advantages of next-generation colonoscopes,specifically the CF-XZ1200 and CFEZ1500 models,in enhancing the adenoma and sessile serrated le...A recent study by Nishizawa et al presented significant findings regarding the advantages of next-generation colonoscopes,specifically the CF-XZ1200 and CFEZ1500 models,in enhancing the adenoma and sessile serrated lesion detection rates.As colorectal cancer remains a leading cause of cancer-related mortality globally,the implications of improved detection rates are substantial.This letter advocated the adoption of advanced colonoscopy technology,emphasizing the robust methodology of the study,including propensity score matching,which enhanced the validity of its conclusions.Notable improvements in image quality,facilitated by innovations such as 4 K resolution and texture enhancement imaging,enable endoscopists to identify even the smallest lesions,ultimately leading to improved patient outcomes.Given the compelling evidence presented,it is imperative for healthcare institutions to prioritize the integration of these advanced scopes into routine practice to enhance screening efficacy and reduce the burden of colorectal cancer.展开更多
This paper deeply explores oversampling technology and its applications in biomedical signal detection.It first expounds on the significance of oversampling technology in biomedical signal detection,and then analyzes ...This paper deeply explores oversampling technology and its applications in biomedical signal detection.It first expounds on the significance of oversampling technology in biomedical signal detection,and then analyzes the application strategies of oversampling technology in this field.On this basis,it details the specific applications of oversampling technology in electrophysiological signal detection,biomedical imaging signal processing,and other biomedical signal detections,and verifies its effectiveness through practical case analysis,aiming to provide certain references for relevant researchers.展开更多
With the rapid development of modern information technology,the Internet of Things(IoT)has been integrated into various fields such as social life,industrial production,education,and medical care.Through the connectio...With the rapid development of modern information technology,the Internet of Things(IoT)has been integrated into various fields such as social life,industrial production,education,and medical care.Through the connection of various physical devices,sensors,and machines,it realizes information intercommunication and remote control among devices,significantly enhancing the convenience and efficiency of work and life.However,the rapid development of the IoT has also brought serious security problems.IoT devices have limited resources and a complex network environment,making them one of the important targets of network intrusion attacks.Therefore,from the perspective of deep learning,this paper deeply analyzes the characteristics and key points of IoT intrusion detection,summarizes the application advantages of deep learning in IoT intrusion detection,and proposes application strategies of typical deep learning models in IoT intrusion detection so as to improve the security of the IoT architecture and guarantee people’s convenient lives.展开更多
Pseudomonas aeruginosa is an opportunistic pathogen widely distributed in the natural environment,which can cause a variety of infections,especially in people with low immunity and high pathogenicity.In recent years,s...Pseudomonas aeruginosa is an opportunistic pathogen widely distributed in the natural environment,which can cause a variety of infections,especially in people with low immunity and high pathogenicity.In recent years,significant progress has been made in the detection technology of Pseudomonas aeruginosa,covering traditional methods,molecular biology techniques,immunological methods and automated detection systems.Traditional methods such as the national standard method and the filter membrane method are easy to operate,but have the problems of long time consuming and limited sensitivity.Molecular biological techniques(such as PCR,gene cloning)and immunological methods(such as ELISA,colloidal gold immunochromatography)have significantly improved the sensitivity and specificity of detection,but they require high equipment and technology,and are expensive.Automated detection systems,such as VITEK 2 Compact and AutoMS 1000 mass spectrometry identification system,are excellent in improving detection efficiency and accuracy,but their high cost and complex operation process limit their wide application.In addition,the resistance of Pseudomonas aeruginosa to bacteriostatic agents further increases the difficulty of detection.In this paper,the development and application of immunological detection technology,molecular biological technology and immunological technology of Pseudomonas aeruginosa were reviewed,and the principles,advantages,disadvantages and research progress of various detection technologies of Pseudomonas aeruginosa were described,and the future development trend was prospected,in order to provide reference for the optimization and development of detection methods of Pseudomonas aeruginosa.展开更多
This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview ...This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview of a certain bridge construction project studied and acoustic non-destructive testing technology and the application of acoustic non-destructive testing technology in actual testing.This analysis hopes to provide some guidelines for acoustic non-destructive testing of modern concrete bridge projects.展开更多
Atrial fibrillation (AF) is the most common chronic arrhythmia in clinical practice, which can cause high disability and mortality with the progress of the disease. Many studies at home and abroad have shown that the ...Atrial fibrillation (AF) is the most common chronic arrhythmia in clinical practice, which can cause high disability and mortality with the progress of the disease. Many studies at home and abroad have shown that the incidence of atrial fibrillation gradually increases with age. Clinically, the onset of most AF patients is insidious, which is difficult to capture by routine electrocardiogram, and there is some difficulty in the diagnosis. In order to make the early diagnosis of atrial fibrillation more efficient and accurate, this paper reviews the current status and research progress of detection technology for atrial fibrillation at home and abroad, in order to provide a scientific basis for the early diagnosis of atrial fibrillation.展开更多
Gravitational wave detection has ushered in a new era of observing the universe, providing humanity with a novel window for cosmic cognition. This theoretical study systematically traces the developmental trajectory o...Gravitational wave detection has ushered in a new era of observing the universe, providing humanity with a novel window for cosmic cognition. This theoretical study systematically traces the developmental trajectory of gravitational wave detection technology and delves into its profound impact on cosmological research. From Einstein’s prediction in general relativity to LIGO’s groundbreaking discovery, the article meticulously delineates the key theoretical and technological milestones in gravitational wave detection, with particular emphasis on elucidating the principles and evolution of core detection technologies such as laser interferometers. The research thoroughly explores the theoretical application value of gravitational waves in verifying general relativity, studying the physics of compact celestial bodies like black holes and neutron stars, and precisely measuring cosmological parameters. The article postulates that gravitational wave observations may offer new research perspectives for addressing cosmological conundrums such as dark matter, dark energy, and early universe evolution. The study also discusses the scientific prospects of combining gravitational wave observations with electromagnetic waves, neutrinos, and other multi-messenger observations, analyzing the potential value of this multi-messenger astronomy in deepening cosmic cognition. Looking ahead, the article examines cutting-edge concepts such as space-based gravitational wave detectors and predicts potential developmental directions for gravitational wave astronomy. This research not only elucidates the theoretical foundations of gravitational wave detection technology but also provides a comprehensive theoretical framework for understanding the far-reaching impact of gravitational waves on modern cosmology.展开更多
Currently,there is significant attention placed on the construction,management,and maintenance of large service bridges.Within the realm of bridge maintenance management,the utilization of detection and monitoring tec...Currently,there is significant attention placed on the construction,management,and maintenance of large service bridges.Within the realm of bridge maintenance management,the utilization of detection and monitoring technology is indispensable.By employing these technologies,we can effectively identify any structural defects within the bridge,promptly uncover unknown risks,proactively establish maintenance strategies,and prevent the rapid deterioration of bridge conditions.This article aims to explore the advantages of applying bridge monitoring and testing technology and to discuss various methods for implementing detection and monitoring technology throughout the construction,management,and maintenance phases of large bridges.Ultimately,this will contribute to ensuring the safe operation of large bridges.展开更多
With the rapid development of drone technology,drones are increasingly used in urban environments,but they also bring many security risks,such as illegal reconnaissance,smuggling,and terrorist attacks.Therefore,it is ...With the rapid development of drone technology,drones are increasingly used in urban environments,but they also bring many security risks,such as illegal reconnaissance,smuggling,and terrorist attacks.Therefore,it is of great significance to study the anti-UAV technology in the urban environment.This paper analyzes the advantages and disadvantages of existing technologies and their applicability in the urban environment from the aspects of UAV detection,identification,and countermeasures,and discusses the future development trend of anti-UAV technology,aiming to provide a reference for urban safety protection.展开更多
In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At prese...In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.展开更多
To ensure the safety and efficacy of Chinese herbs,it is of great significance to conduct rapid quality detection of Chinese herbs at every link of their supply chain.Spectroscopic technology can reflect the overall c...To ensure the safety and efficacy of Chinese herbs,it is of great significance to conduct rapid quality detection of Chinese herbs at every link of their supply chain.Spectroscopic technology can reflect the overall chemical composition and structural characteristics of Chinese herbs,with the multi-component and multitarget characteristics of Chinese herbs.This review took the genus Paris as an example,and applications of spectroscopic technology with machine learning(ML)in supply chain of the genus Paris from seeds to medicinal materials were introduced.The specific contents included the confirmation of germplasm resources,identification of growth years,cultivar,geographical origin,and original processing and processing methods.The potential application of spectroscopic technology in genus Paris was pointed out,and the prospects of combining spectroscopic technology with blockchain were proposed.The summary and prospects presented in this paper will be beneficial to the quality control of the genus Paris in all links of its supply chain,so as to rationally use the genus Paris resources and ensure the safety and efficacy of medication.展开更多
Detecting sitting posture abnormalities in wheelchair users enables early identification of changes in their functional status.To date,this detection has relied on in-person observation by medical specialists.However,...Detecting sitting posture abnormalities in wheelchair users enables early identification of changes in their functional status.To date,this detection has relied on in-person observation by medical specialists.However,given the challenges faced by health specialists to carry out continuous monitoring,the development of an intelligent anomaly detection system is proposed.Unlike other authors,where they use supervised techniques,this work proposes using unsupervised techniques due to the advantages they offer.These advantages include the lack of prior labeling of data,and the detection of anomalies previously not contemplated,among others.In the present work,an individualized methodology consisting of two phases is developed:characterizing the normal sitting pattern and determining abnormal samples.An analysis has been carried out between different unsupervised techniques to study which ones are more suitable for postural diagnosis.It can be concluded,among other aspects,that the utilization of dimensionality reduction techniques leads to improved results.Moreover,the normality characterization phase is deemed necessary for enhancing the system’s learning capabilities.Additionally,employing an individualized approach to the model aids in capturing the particularities of the various pathologies present among subjects.展开更多
This article analyzes the application strategies of Building Information Modeling(BIM)support technology in a first-class highway reconstruction and expansion project based on its actual situation.According to the bas...This article analyzes the application strategies of Building Information Modeling(BIM)support technology in a first-class highway reconstruction and expansion project based on its actual situation.According to the basic situation of BIM technology and its application goals in this project,it explores application strategies such as BIM model construction,BIM prefabricated structural model deepening and schedule simulation,BIM collision detection,and BIM tunnel pre-construction simulation.Through this analysis,it is hoped to provide a reference for the rational application of BIM support technology and ensure the high-quality and efficient completion of first-class highway reconstruction and expansion projects.展开更多
To meet the intelligent detection needs of underwater defects in large hydropower stations,the hydrodynamic performance of a bionic streamlined remotely operated vehicle containing a thruster protective net structure ...To meet the intelligent detection needs of underwater defects in large hydropower stations,the hydrodynamic performance of a bionic streamlined remotely operated vehicle containing a thruster protective net structure is numerically simulated via computational fluid dynamics and overlapping mesh technology.The results show that the entity model generates greater hydrodynamic force during steady motion,whereas the square net model experiences greater force and moment during unsteady motion.The lateral and vertical force coefficients of the entity model are 4.32 and 3.13 times greater than those of the square net model in the oblique towing test simulation.The square net model also offers better static and dynamic stability,with a 24.5%increase in dynamic stability,achieving the highest lift-to-drag ratio at attack angles of 6°∼8°.This research provides valuable insights for designing and controlling underwater defect detection vehicles for large hydropower stations.展开更多
Leaf disease identification is one of the most promising applications of convolutional neural networks(CNNs).This method represents a significant step towards revolutionizing agriculture by enabling the quick and accu...Leaf disease identification is one of the most promising applications of convolutional neural networks(CNNs).This method represents a significant step towards revolutionizing agriculture by enabling the quick and accurate assessment of plant health.In this study,a CNN model was specifically designed and tested to detect and categorize diseases on fig tree leaves.The researchers utilized a dataset of 3422 images,divided into four classes:healthy,fig rust,fig mosaic,and anthracnose.These diseases can significantly reduce the yield and quality of fig tree fruit.The objective of this research is to develop a CNN that can identify and categorize diseases in fig tree leaves.The data for this study was collected from gardens in the Amandi and Mamash Khail Bannu districts of the Khyber Pakhtunkhwa region in Pakistan.To minimize the risk of overfitting and enhance the model’s performance,early stopping techniques and data augmentation were employed.As a result,the model achieved a training accuracy of 91.53%and a validation accuracy of 90.12%,which are considered respectable.This comprehensive model assists farmers in the early identification and categorization of fig tree leaf diseases.Our experts believe that CNNs could serve as valuable tools for accurate disease classification and detection in precision agriculture.We recommend further research to explore additional data sources and more advanced neural networks to improve the model’s accuracy and applicability.Future research will focus on expanding the dataset by including new diseases and testing the model in real-world scenarios to enhance sustainable farming practices.展开更多
As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and cha...As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and challenges of big data analytics in anti-money laundering and financial fraud detection. The research begins by outlining the evolutionary trends of financial crimes and highlighting the new characteristics of the big data era. Subsequently, it systematically analyzes the application of big data analytics technologies in this field, including machine learning, network analysis, and real-time stream processing. Through case studies, the research demonstrates how these technologies enhance the accuracy and efficiency of anomalous transaction detection. However, the study also identifies challenges faced by big data analytics, such as data quality issues, algorithmic bias, and privacy protection concerns. To address these challenges, the research proposes solutions from both technological and managerial perspectives, including the application of privacy-preserving technologies like federated learning. Finally, the study discusses the development prospects of Regulatory Technology (RegTech), emphasizing the importance of synergy between technological innovation and regulatory policies. This research provides guidance for financial institutions and regulatory bodies in optimizing their anti-money laundering and fraud detection strategies.展开更多
Based on the limitations of traditional plant nutrient solution detection, a ZigBee plant nutrient solution detection system based on CC2530 was developed. This system uses CC2530 as the main control chip, DS18B20 as ...Based on the limitations of traditional plant nutrient solution detection, a ZigBee plant nutrient solution detection system based on CC2530 was developed. This system uses CC2530 as the main control chip, DS18B20 as the temperature sensor for temperature acquisition, PH electrode sensor for PH value acquisition. The experiment shows that this wireless control system equipped with temperature and pH detection sensor collects and samples the main nutrient solution parameters through the main controller, performs wireless communication transmission and terminal communication, and realizes the intelligent detection of plant nutrient solution parameters. This technique of applying wireless sensor network technology to plant factories greatly improves the reliability and stability of the nutrient monitoring system.展开更多
With the economic development and the popularity of application of electronic computer, electronic commerce has rapid development. More and more commerce and key business has been carried on the lnternet because Inter...With the economic development and the popularity of application of electronic computer, electronic commerce has rapid development. More and more commerce and key business has been carried on the lnternet because Internet has the features of interaction, openness, sharing and so on. However, during the daily commerce, people worry about the security of the network system. So a new technology which can detect the unusual behavior in time has been invented in order to protect the security of network system. The system of intrusion detection needs a lot of new technology to protect the data of the network system. The application of data mining technology in the system of intrusion detection can provide a better assistant to the users to analyze the data and improve the accuracy of the checking system.展开更多
With the rapid development of urban rail transit,passenger traffic is increasing,and obstacle violations are more frequent,and the safety of train operation under high-density traffic conditions is becoming more and m...With the rapid development of urban rail transit,passenger traffic is increasing,and obstacle violations are more frequent,and the safety of train operation under high-density traffic conditions is becoming more and more thought provoking.In order to monitor the train operating environment in real time,this paper first adopts multisensing technology based on machine vision and lidar,which is used to collect video images and ranging data of the track area in real time,and then it performs image preprocessing and division of regions of interest on the collected video.Then,the obstacles in the region of interest are detected to obtain the geometric characteristics and position information of the obstacles.Finally,according to the danger degree of obstacles,determine the degree of impact on the train operation,and use the signal system automatic response ormanual response mode to transmit the detection results to the corresponding train,so as to control the train operation.Through simulation analysis and experimental verification,the detection accuracy and control performance of the detection method are confirmed,which provides safety guarantee for the train operation.展开更多
基金Supported by Research Project on Food Detection Technology Innovation and Standard Integration 2024(YNXM-2024-FW-019).
文摘This paper reviews the research progress on mold detection technologies in milk and dairy products,including rapid test sheet methods,molecular biological detection techniques,metabolomics detection techniques,enzyme-linked immunosorbent assay(ELISA),and microbial rapid photoelectric detection systems,aiming to provide optimal choices for mold detection.
文摘A recent study by Nishizawa et al presented significant findings regarding the advantages of next-generation colonoscopes,specifically the CF-XZ1200 and CFEZ1500 models,in enhancing the adenoma and sessile serrated lesion detection rates.As colorectal cancer remains a leading cause of cancer-related mortality globally,the implications of improved detection rates are substantial.This letter advocated the adoption of advanced colonoscopy technology,emphasizing the robust methodology of the study,including propensity score matching,which enhanced the validity of its conclusions.Notable improvements in image quality,facilitated by innovations such as 4 K resolution and texture enhancement imaging,enable endoscopists to identify even the smallest lesions,ultimately leading to improved patient outcomes.Given the compelling evidence presented,it is imperative for healthcare institutions to prioritize the integration of these advanced scopes into routine practice to enhance screening efficacy and reduce the burden of colorectal cancer.
文摘This paper deeply explores oversampling technology and its applications in biomedical signal detection.It first expounds on the significance of oversampling technology in biomedical signal detection,and then analyzes the application strategies of oversampling technology in this field.On this basis,it details the specific applications of oversampling technology in electrophysiological signal detection,biomedical imaging signal processing,and other biomedical signal detections,and verifies its effectiveness through practical case analysis,aiming to provide certain references for relevant researchers.
基金the research result of the 2022 Municipal Education Commission Science and Technology Research Plan Project“Research on the Technology of Detecting Double-Surface Cracks in Concrete Lining of Highway Tunnels Based on Image Blast”(KJQN02202403)the first batch of school-level classroom teaching reform projects“Principles Applications of Embedded Systems”(23JG2166)the school-level reform research project“Continuous Results-Oriented Practice Research Based on BOPPPS Teaching Model-Taking the‘Programming Fundamentals’Course as an Example”(22JG332).
文摘With the rapid development of modern information technology,the Internet of Things(IoT)has been integrated into various fields such as social life,industrial production,education,and medical care.Through the connection of various physical devices,sensors,and machines,it realizes information intercommunication and remote control among devices,significantly enhancing the convenience and efficiency of work and life.However,the rapid development of the IoT has also brought serious security problems.IoT devices have limited resources and a complex network environment,making them one of the important targets of network intrusion attacks.Therefore,from the perspective of deep learning,this paper deeply analyzes the characteristics and key points of IoT intrusion detection,summarizes the application advantages of deep learning in IoT intrusion detection,and proposes application strategies of typical deep learning models in IoT intrusion detection so as to improve the security of the IoT architecture and guarantee people’s convenient lives.
基金College Students’Innovation and Entrepreneurship Training Program Project(X202511049398)College Students’Innovation and Entrepreneurship Training Program Project(X202511049201)+1 种基金College Students’Innovation and Entrepreneurship Training Program Project(D202504071303298456)Hainan Vocational University of Science and Technology University-Level Scientific Research Funding Project(HKKY2024-87).
文摘Pseudomonas aeruginosa is an opportunistic pathogen widely distributed in the natural environment,which can cause a variety of infections,especially in people with low immunity and high pathogenicity.In recent years,significant progress has been made in the detection technology of Pseudomonas aeruginosa,covering traditional methods,molecular biology techniques,immunological methods and automated detection systems.Traditional methods such as the national standard method and the filter membrane method are easy to operate,but have the problems of long time consuming and limited sensitivity.Molecular biological techniques(such as PCR,gene cloning)and immunological methods(such as ELISA,colloidal gold immunochromatography)have significantly improved the sensitivity and specificity of detection,but they require high equipment and technology,and are expensive.Automated detection systems,such as VITEK 2 Compact and AutoMS 1000 mass spectrometry identification system,are excellent in improving detection efficiency and accuracy,but their high cost and complex operation process limit their wide application.In addition,the resistance of Pseudomonas aeruginosa to bacteriostatic agents further increases the difficulty of detection.In this paper,the development and application of immunological detection technology,molecular biological technology and immunological technology of Pseudomonas aeruginosa were reviewed,and the principles,advantages,disadvantages and research progress of various detection technologies of Pseudomonas aeruginosa were described,and the future development trend was prospected,in order to provide reference for the optimization and development of detection methods of Pseudomonas aeruginosa.
文摘This article takes the actual construction project of a certain concrete bridge project as an example to analyze the application of acoustic non-destructive testing technology in its detection.It includes an overview of a certain bridge construction project studied and acoustic non-destructive testing technology and the application of acoustic non-destructive testing technology in actual testing.This analysis hopes to provide some guidelines for acoustic non-destructive testing of modern concrete bridge projects.
文摘Atrial fibrillation (AF) is the most common chronic arrhythmia in clinical practice, which can cause high disability and mortality with the progress of the disease. Many studies at home and abroad have shown that the incidence of atrial fibrillation gradually increases with age. Clinically, the onset of most AF patients is insidious, which is difficult to capture by routine electrocardiogram, and there is some difficulty in the diagnosis. In order to make the early diagnosis of atrial fibrillation more efficient and accurate, this paper reviews the current status and research progress of detection technology for atrial fibrillation at home and abroad, in order to provide a scientific basis for the early diagnosis of atrial fibrillation.
文摘Gravitational wave detection has ushered in a new era of observing the universe, providing humanity with a novel window for cosmic cognition. This theoretical study systematically traces the developmental trajectory of gravitational wave detection technology and delves into its profound impact on cosmological research. From Einstein’s prediction in general relativity to LIGO’s groundbreaking discovery, the article meticulously delineates the key theoretical and technological milestones in gravitational wave detection, with particular emphasis on elucidating the principles and evolution of core detection technologies such as laser interferometers. The research thoroughly explores the theoretical application value of gravitational waves in verifying general relativity, studying the physics of compact celestial bodies like black holes and neutron stars, and precisely measuring cosmological parameters. The article postulates that gravitational wave observations may offer new research perspectives for addressing cosmological conundrums such as dark matter, dark energy, and early universe evolution. The study also discusses the scientific prospects of combining gravitational wave observations with electromagnetic waves, neutrinos, and other multi-messenger observations, analyzing the potential value of this multi-messenger astronomy in deepening cosmic cognition. Looking ahead, the article examines cutting-edge concepts such as space-based gravitational wave detectors and predicts potential developmental directions for gravitational wave astronomy. This research not only elucidates the theoretical foundations of gravitational wave detection technology but also provides a comprehensive theoretical framework for understanding the far-reaching impact of gravitational waves on modern cosmology.
文摘Currently,there is significant attention placed on the construction,management,and maintenance of large service bridges.Within the realm of bridge maintenance management,the utilization of detection and monitoring technology is indispensable.By employing these technologies,we can effectively identify any structural defects within the bridge,promptly uncover unknown risks,proactively establish maintenance strategies,and prevent the rapid deterioration of bridge conditions.This article aims to explore the advantages of applying bridge monitoring and testing technology and to discuss various methods for implementing detection and monitoring technology throughout the construction,management,and maintenance phases of large bridges.Ultimately,this will contribute to ensuring the safe operation of large bridges.
文摘With the rapid development of drone technology,drones are increasingly used in urban environments,but they also bring many security risks,such as illegal reconnaissance,smuggling,and terrorist attacks.Therefore,it is of great significance to study the anti-UAV technology in the urban environment.This paper analyzes the advantages and disadvantages of existing technologies and their applicability in the urban environment from the aspects of UAV detection,identification,and countermeasures,and discusses the future development trend of anti-UAV technology,aiming to provide a reference for urban safety protection.
文摘In the aerospace field, residual stress directly affects the strength, fatigue life and dimensional stability of thin-walled structural components, and is a key factor to ensure flight safety and reliability. At present, research on residual stress at home and abroad mainly focuses on the optimization of traditional detection technology, stress control of manufacturing process and service performance evaluation, among which research on residual stress detection methods mainly focuses on the improvement of the accuracy, sensitivity, reliability and other performance of existing detection methods, but it still faces many challenges such as extremely small detection range, low efficiency, large error and limited application range.
基金funded by the Special Program for the Major Science and Technology Projects of Yunnan Province,China(Grant No.:202202AE090001).
文摘To ensure the safety and efficacy of Chinese herbs,it is of great significance to conduct rapid quality detection of Chinese herbs at every link of their supply chain.Spectroscopic technology can reflect the overall chemical composition and structural characteristics of Chinese herbs,with the multi-component and multitarget characteristics of Chinese herbs.This review took the genus Paris as an example,and applications of spectroscopic technology with machine learning(ML)in supply chain of the genus Paris from seeds to medicinal materials were introduced.The specific contents included the confirmation of germplasm resources,identification of growth years,cultivar,geographical origin,and original processing and processing methods.The potential application of spectroscopic technology in genus Paris was pointed out,and the prospects of combining spectroscopic technology with blockchain were proposed.The summary and prospects presented in this paper will be beneficial to the quality control of the genus Paris in all links of its supply chain,so as to rationally use the genus Paris resources and ensure the safety and efficacy of medication.
基金FEDER/Ministry of Science and Innovation-State Research Agency/Project PID2020-112667RB-I00 funded by MCIN/AEI/10.13039/501100011033the Basque Government,IT1726-22+2 种基金by the predoctoral contracts PRE_2022_2_0022 and EP_2023_1_0015 of the Basque Governmentpartially supported by the Italian MIUR,PRIN 2020 Project“COMMON-WEARS”,N.2020HCWWLP,CUP:H23C22000230005co-funding from Next Generation EU,in the context of the National Recovery and Resilience Plan,through the Italian MUR,PRIN 2022 Project”COCOWEARS”(A framework for COntinuum COmputing WEARable Systems),N.2022T2XNJE,CUP:H53D23003640006.
文摘Detecting sitting posture abnormalities in wheelchair users enables early identification of changes in their functional status.To date,this detection has relied on in-person observation by medical specialists.However,given the challenges faced by health specialists to carry out continuous monitoring,the development of an intelligent anomaly detection system is proposed.Unlike other authors,where they use supervised techniques,this work proposes using unsupervised techniques due to the advantages they offer.These advantages include the lack of prior labeling of data,and the detection of anomalies previously not contemplated,among others.In the present work,an individualized methodology consisting of two phases is developed:characterizing the normal sitting pattern and determining abnormal samples.An analysis has been carried out between different unsupervised techniques to study which ones are more suitable for postural diagnosis.It can be concluded,among other aspects,that the utilization of dimensionality reduction techniques leads to improved results.Moreover,the normality characterization phase is deemed necessary for enhancing the system’s learning capabilities.Additionally,employing an individualized approach to the model aids in capturing the particularities of the various pathologies present among subjects.
文摘This article analyzes the application strategies of Building Information Modeling(BIM)support technology in a first-class highway reconstruction and expansion project based on its actual situation.According to the basic situation of BIM technology and its application goals in this project,it explores application strategies such as BIM model construction,BIM prefabricated structural model deepening and schedule simulation,BIM collision detection,and BIM tunnel pre-construction simulation.Through this analysis,it is hoped to provide a reference for the rational application of BIM support technology and ensure the high-quality and efficient completion of first-class highway reconstruction and expansion projects.
基金supported by the National Key R&D Program of China(Grant No.2022YFB4703401).
文摘To meet the intelligent detection needs of underwater defects in large hydropower stations,the hydrodynamic performance of a bionic streamlined remotely operated vehicle containing a thruster protective net structure is numerically simulated via computational fluid dynamics and overlapping mesh technology.The results show that the entity model generates greater hydrodynamic force during steady motion,whereas the square net model experiences greater force and moment during unsteady motion.The lateral and vertical force coefficients of the entity model are 4.32 and 3.13 times greater than those of the square net model in the oblique towing test simulation.The square net model also offers better static and dynamic stability,with a 24.5%increase in dynamic stability,achieving the highest lift-to-drag ratio at attack angles of 6°∼8°.This research provides valuable insights for designing and controlling underwater defect detection vehicles for large hydropower stations.
基金the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025).
文摘Leaf disease identification is one of the most promising applications of convolutional neural networks(CNNs).This method represents a significant step towards revolutionizing agriculture by enabling the quick and accurate assessment of plant health.In this study,a CNN model was specifically designed and tested to detect and categorize diseases on fig tree leaves.The researchers utilized a dataset of 3422 images,divided into four classes:healthy,fig rust,fig mosaic,and anthracnose.These diseases can significantly reduce the yield and quality of fig tree fruit.The objective of this research is to develop a CNN that can identify and categorize diseases in fig tree leaves.The data for this study was collected from gardens in the Amandi and Mamash Khail Bannu districts of the Khyber Pakhtunkhwa region in Pakistan.To minimize the risk of overfitting and enhance the model’s performance,early stopping techniques and data augmentation were employed.As a result,the model achieved a training accuracy of 91.53%and a validation accuracy of 90.12%,which are considered respectable.This comprehensive model assists farmers in the early identification and categorization of fig tree leaf diseases.Our experts believe that CNNs could serve as valuable tools for accurate disease classification and detection in precision agriculture.We recommend further research to explore additional data sources and more advanced neural networks to improve the model’s accuracy and applicability.Future research will focus on expanding the dataset by including new diseases and testing the model in real-world scenarios to enhance sustainable farming practices.
文摘As financial criminal methods become increasingly sophisticated, traditional anti-money laundering and fraud detection approaches face significant challenges. This study focuses on the application technologies and challenges of big data analytics in anti-money laundering and financial fraud detection. The research begins by outlining the evolutionary trends of financial crimes and highlighting the new characteristics of the big data era. Subsequently, it systematically analyzes the application of big data analytics technologies in this field, including machine learning, network analysis, and real-time stream processing. Through case studies, the research demonstrates how these technologies enhance the accuracy and efficiency of anomalous transaction detection. However, the study also identifies challenges faced by big data analytics, such as data quality issues, algorithmic bias, and privacy protection concerns. To address these challenges, the research proposes solutions from both technological and managerial perspectives, including the application of privacy-preserving technologies like federated learning. Finally, the study discusses the development prospects of Regulatory Technology (RegTech), emphasizing the importance of synergy between technological innovation and regulatory policies. This research provides guidance for financial institutions and regulatory bodies in optimizing their anti-money laundering and fraud detection strategies.
文摘Based on the limitations of traditional plant nutrient solution detection, a ZigBee plant nutrient solution detection system based on CC2530 was developed. This system uses CC2530 as the main control chip, DS18B20 as the temperature sensor for temperature acquisition, PH electrode sensor for PH value acquisition. The experiment shows that this wireless control system equipped with temperature and pH detection sensor collects and samples the main nutrient solution parameters through the main controller, performs wireless communication transmission and terminal communication, and realizes the intelligent detection of plant nutrient solution parameters. This technique of applying wireless sensor network technology to plant factories greatly improves the reliability and stability of the nutrient monitoring system.
文摘With the economic development and the popularity of application of electronic computer, electronic commerce has rapid development. More and more commerce and key business has been carried on the lnternet because Internet has the features of interaction, openness, sharing and so on. However, during the daily commerce, people worry about the security of the network system. So a new technology which can detect the unusual behavior in time has been invented in order to protect the security of network system. The system of intrusion detection needs a lot of new technology to protect the data of the network system. The application of data mining technology in the system of intrusion detection can provide a better assistant to the users to analyze the data and improve the accuracy of the checking system.
基金supported by The National Natural Science Foundation of China(52072214)the Independent Research Fund for the Central Universities(XJ2020004701)。
文摘With the rapid development of urban rail transit,passenger traffic is increasing,and obstacle violations are more frequent,and the safety of train operation under high-density traffic conditions is becoming more and more thought provoking.In order to monitor the train operating environment in real time,this paper first adopts multisensing technology based on machine vision and lidar,which is used to collect video images and ranging data of the track area in real time,and then it performs image preprocessing and division of regions of interest on the collected video.Then,the obstacles in the region of interest are detected to obtain the geometric characteristics and position information of the obstacles.Finally,according to the danger degree of obstacles,determine the degree of impact on the train operation,and use the signal system automatic response ormanual response mode to transmit the detection results to the corresponding train,so as to control the train operation.Through simulation analysis and experimental verification,the detection accuracy and control performance of the detection method are confirmed,which provides safety guarantee for the train operation.
