Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance, HCI, object-based video compression, etc. One of the most successful moving o...Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance, HCI, object-based video compression, etc. One of the most successful moving object detection algorithms is based on Adaptive Gaussian Mixture Model （AGMM）. Although ACMM-hased object detection shows very good performance with respect to object detection accuracy, AGMM is very complex model requiring lots of floatingpoint arithmetic so that it should pay for expensive computational cost. Thus, direct implementation of the AGMM-based object detection for embedded DSPs without floating-point arithmetic HW support cannot satisfy the real-time processing requirement. This paper presents a novel rcal-time implementation of adaptive Gaussian mixture model-based moving object detection algorithm for fixed-point DSPs. In the proposed implementation, in addition to changes of data types into fixed-point ones, magnification of the Gaussian distribution technique is introduced so that the integer and fixed-point arithmetic can be easily and consistently utilized instead of real nmnher and floatingpoint arithmetic in processing of AGMM algorithm. Experimental results shows that the proposed implementation have a high potential in real-time applications.展开更多
Cognitive radio (CR) is a technology that provides a promising new way to improve the efficiency of the use of the electromagnetic spectrum that available. Spectrum sensing helps in the detection of spectrum holes (un...Cognitive radio (CR) is a technology that provides a promising new way to improve the efficiency of the use of the electromagnetic spectrum that available. Spectrum sensing helps in the detection of spectrum holes (unused channels of the band), and instantly move into vacant channels while avoiding occupied ones. An energy detector with baseband sampling for CR is presented with mathematical analyses for an additive white Gaussian noise (AWGN) channels. A brief overview of the energy detection based spectrum sensing for CR technology is introduced. Practical implementation issues on Texas Instruments TMS320C6713 floating point DSP board are presented. Novelties of this work came from a derivation of probability of detection and probability of false alarm for the baseband energy detector without including the sampling theorems and the associated approximation.展开更多
A Kalman filter which estimates unsteady laminar flow in a pipe is implemented on a real-time computing system. The plant model is the optimised finite element model of pipeline dynamics considering unsteady laminar f...A Kalman filter which estimates unsteady laminar flow in a pipe is implemented on a real-time computing system. The plant model is the optimised finite element model of pipeline dynamics considering unsteady laminar friction. A steady-state Kalman filter is built based on the model of pipeline dynamics. Pressure signals at both ends of a target section of a pipe are input to the model of pipeline dynamics, and as an output of the model an estimated pressure signal at a mid-point of the pipe is obtained. Difference between measured and estimated pressure signals at the mid-point is fed back to the model of pipeline dynamics to modify state variables of the model. According to the Kalman filter principle, the state variables of the model are adjusted so that they converge to real values. It is demonstrated that real-time implementation of the Kalman filter is possible with the sampling time of 0.1 ms.展开更多
Fast neutron flux measurements with high count rates and high time resolution have important applications in equipment such as tokamaks.In this study,real-time neutron and gamma discrimination was implemented on a sel...Fast neutron flux measurements with high count rates and high time resolution have important applications in equipment such as tokamaks.In this study,real-time neutron and gamma discrimination was implemented on a self-developed 500-Msps,12-bit digitizer,and the neutron and gamma spectra were calculated directly on an FPGA.A fast neutron flux measurement system with BC-501A and EJ-309 liquid scintillator detectors was developed and a fast neutron measurement experiment was successfully performed on the HL-2 M tokamak at the Southwestern Institute of Physics,China.The experimental results demonstrated that the system obtained the neutron and gamma spectra with a time accuracy of 1 ms.At count rates of up to 1 Mcps,the figure of merit was greater than 1.05 for energies between 50 keV and 2.8 MeV.展开更多
Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is pro...Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC, according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness.展开更多
Microsoft Kinect sensor has shown the research community that it's more than just an interactive gaming device, due to its multi-functional abilities and high reliability. In this work, online HIL (Hardware-in-the...Microsoft Kinect sensor has shown the research community that it's more than just an interactive gaming device, due to its multi-functional abilities and high reliability. In this work, online HIL (Hardware-in-the-Loop) experimental data are used to apply human motion imitation to a 2-degree of freedom Lego Mind storm NXT robotic arm. A model simulation of the dc motor used in this experiment is also present in this paper. The acquired input data from the Kinect sensor are processed in a closed loop PID controller with feedback from motors encoders. The applied algorithms solve the overlapping input problem, conducting a simultaneous control of both shoulder and elbow joints, and solving the overlapping input problem as well. The work in this paper is presented as a prototype to assure the applicability of the algorithms, for further development.展开更多
Traffic sign recognition (TSR, or Road Sign Recognition, RSR) is one of the Advanced Driver Assistance System (ADAS) devices in modern cars. To concern the most important issues, which are real-time and resource effic...Traffic sign recognition (TSR, or Road Sign Recognition, RSR) is one of the Advanced Driver Assistance System (ADAS) devices in modern cars. To concern the most important issues, which are real-time and resource efficiency, we propose a high efficiency hardware implementation for TSR. We divide the TSR procedure into two stages, detection and recognition. In the detection stage, under the assumption that most German traffic signs have red or blue colors with circle, triangle or rectangle shapes, we use Normalized RGB color transform and Single-Pass Connected Component Labeling (CCL) to find the potential traffic signs efficiently. For Single-Pass CCL, our contribution is to eliminate the “merge-stack” operations by recording connected relations of region in the scan phase and updating the labels in the iterating phase. In the recognition stage, the Histogram of Oriented Gradient (HOG) is used to generate the descriptor of the signs, and we classify the signs with Support Vector Machine (SVM). In the HOG module, we analyze the required minimum bits under different recognition rate. The proposed method achieves 96.61% detection rate and 90.85% recognition rate while testing with the GTSDB dataset. Our hardware implementation reduces the storage of CCL and simplifies the HOG computation. Main CCL storage size is reduced by 20% comparing to the most advanced design under typical condition. By using TSMC 90 nm technology, the proposed design operates at 105 MHz clock rate and processes in 135 fps with the image size of 1360 × 800. The chip size is about 1 mm2 and the power consumption is close to 8 mW. Therefore, this work is resource efficient and achieves real-time requirement.展开更多
The Internet of Things(IoT)and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients.Recognizing Medical-Related Human Activities(MRHA)is pivotal for he...The Internet of Things(IoT)and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients.Recognizing Medical-Related Human Activities(MRHA)is pivotal for healthcare systems,particularly for identifying actions critical to patient well-being.However,challenges such as high computational demands,low accuracy,and limited adaptability persist in Human Motion Recognition(HMR).While some studies have integrated HMR with IoT for real-time healthcare applications,limited research has focused on recognizing MRHA as essential for effective patient monitoring.This study proposes a novel HMR method tailored for MRHA detection,leveraging multi-stage deep learning techniques integrated with IoT.The approach employs EfficientNet to extract optimized spatial features from skeleton frame sequences using seven Mobile Inverted Bottleneck Convolutions(MBConv)blocks,followed by Convolutional Long Short Term Memory(ConvLSTM)to capture spatio-temporal patterns.A classification module with global average pooling,a fully connected layer,and a dropout layer generates the final predictions.The model is evaluated on the NTU RGB+D 120 and HMDB51 datasets,focusing on MRHA such as sneezing,falling,walking,sitting,etc.It achieves 94.85%accuracy for cross-subject evaluations and 96.45%for cross-view evaluations on NTU RGB+D 120,along with 89.22%accuracy on HMDB51.Additionally,the system integrates IoT capabilities using a Raspberry Pi and GSM module,delivering real-time alerts via Twilios SMS service to caregivers and patients.This scalable and efficient solution bridges the gap between HMR and IoT,advancing patient monitoring,improving healthcare outcomes,and reducing costs.展开更多
Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does no...Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does not represent an important parameter.However,in critical applications,this parameter represents a crucial aspect.One important sensing device used in IoT designs is the accelerometer.In most applications,the response time of the embedded driver software handling this device is generally not analysed and not taken into account.In this paper,we present the design and implementation of a predictable real-time driver stack for a popular accelerometer and gyroscope device family.We provide clear justifications for why this response time is extremely important for critical applications in the acquisition process of such data.We present extensive measurements and experimental results that demonstrate the predictability of our solution,making it suitable for critical real-time systems.展开更多
Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorith...Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control （AVC） algorithm for a flexible beam system simulated using the finite difference （FD） method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.展开更多
Language policies are of great significance to a nation’s stability,unity,and development.Uzbekistan’s language policies have reflected the political,economic,and cultural dynamics of different periods throughout hi...Language policies are of great significance to a nation’s stability,unity,and development.Uzbekistan’s language policies have reflected the political,economic,and cultural dynamics of different periods throughout historical changes,influencing social structures and ethnic relations.This paper summarizes the characteristics of Uzbekistan’s language policies in different eras:During the Tsarist Russian period,the Russification of language policies hindered the development of local languages;in the Soviet era,policies adopted a dual approach,promoting both Russian and prioritizing ethnic languages;after independence,Uzbekistan established Uzbek as the state language and emphasized foreign language education.The current language policy in Uzbekistan presents a complex landscape:While emphasizing the dominant role of the national language helps preserve its heritage,it may easily spark ethnic and political tensions;promoting pluralism and inclusivity brings benefits but faces challenges in balancing language statuses,resource allocation,management,and communication;modernization efforts encounter difficulties in standardizing dialects and foreign loanwords;and in international exchanges,there is a need to balance relations with global lingua francas.In conclusion,Uzbekistan’s language policies have undergone unique transformations and face numerous challenges.In-depth research is crucial for improving the country’s policies and enhancing China-Uzbekistan cooperation.Proactive measures are needed to address these challenges,ensuring the sustainability of language policies and fostering greater national prosperity.展开更多
Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds tha...Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.展开更多
Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation...Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.展开更多
Here,a novel real-time monitoring sensor that integrates the oxidation of peroxymonosulfate(PMS)and the in situ monitoring of the pollutant degradation process is proposed.Briefly,FeCo@carbon fiber(FeCo@CF)was utilize...Here,a novel real-time monitoring sensor that integrates the oxidation of peroxymonosulfate(PMS)and the in situ monitoring of the pollutant degradation process is proposed.Briefly,FeCo@carbon fiber(FeCo@CF)was utilized as the anode electrode,while graphite rods served as the cathode electrode in assembling the galvanic cell.The FeCo@CF electrode exhibited rapid reactivity with PMS,generating reactive oxygen species that efficiently degrade organic pollutants.The degradation experiments indicate that complete bisphenol A(BPA)degradation was achieved within 10 min under optimal conditions.The real-time electrochemical signal was measured in time during the catalytic reaction,and a linear relationship between BPA concentration and the real-time charge(Q)was confirmed by the equation ln(C0/C)=4.393Q(correlation coefficients,R^(2)=0.998).Furthermore,experiments conducted with aureomycin and tetracycline further validated the effectiveness of the monitoring sensor.First-principles investigation confirmed the superior adsorption energy and improved electron transfer in FeCo@CF.The integration of pollutant degradation with in situ monitoring of catalytic reactions offers promising prospects for expanding the scope of the monitoring of catalytic processes and making significant contributions to environmental purification.展开更多
The demand for Chinese-Western medicine collaboration has grown significantly,but current integration methods have substantial limitations.This article analyzes core issues in developing and implementing synergistic C...The demand for Chinese-Western medicine collaboration has grown significantly,but current integration methods have substantial limitations.This article analyzes core issues in developing and implementing synergistic Chinese-Western medicine clinical treatment strategies and explores the transformation from traditional integration to genuine synergistic models.We analyzed methodological obstacles in synergistic strategy development through literature review and theoretical analysis,and explored applications of intelligent technology in strategy development.Four core challenges were identified:(1)Treatment timing coordination difficulties caused by different decision-making approaches,with Chinese medicine using syndrome-based assessments and Western medicine relying on standardized measurements;(2)Treatment selection complexities when integrating different types of evidence,lacking frameworks for evaluating and combining diverse evidence sources;(3)Obstacles in incorporating patient preferences systematically,with inadequate assessment methods and unclear integration mechanisms;(4)Implementation barriers in translating synergistic strategies into clinical practice,requiring changes in organizational structures,workflows,and evaluation systems.Large language models(LLMs)and other intelligent technologies offer technical support for addressing these methodological challenges.This article examines current challenges in developing synergistic Chinese-Western medicine clinical strategies,analyzing the shift from traditional integration toward synergistic approaches and identifying four core methodological obstacles.Exploring intelligent technology applications provides insights to inform future research directions and clinical practice development in integrated healthcare delivery.展开更多
Currently,we have entered the era of artificial intelligence(AI).The rapid development and wide application of AI technology have exerted a profound impact on all fields of society.Against this backdrop,this paper con...Currently,we have entered the era of artificial intelligence(AI).The rapid development and wide application of AI technology have exerted a profound impact on all fields of society.Against this backdrop,this paper conducts an in-depth analysis focusing on general education in AI.First,it expounds the necessity of AI general education in cultivating the core literacy of vocational college students.Then,it puts forward effective implementation paths for such general education.The purpose is to provide valuable references for promoting the reform and innovative development of vocational education.展开更多
Oncology covers a wide range of knowledge and is more difficult compared to other clinical disciplines.Therefore,it is crucial to seek an efficient teaching method for oncology education.In recent years,China’s inter...Oncology covers a wide range of knowledge and is more difficult compared to other clinical disciplines.Therefore,it is crucial to seek an efficient teaching method for oncology education.In recent years,China’s internet technology has achieved rapid development.Massive Open Online Course(MOOC),a blended learning approach based on internet technology,has strong applicability to medical education.It can not only improve teaching quality but also promote further reform of the discipline.Based on this,our study searched for relevant research at home and abroad and reviewed the implementation path of integrating MOOC and blended learning in oncology education.This provides a theoretical foundation for the innovation of oncology teaching models,improves the level of oncology teaching,and lays a solid foundation for talent reserves in oncology departments.展开更多
In the wave of higher education internationalization,college students’career education is faced with problems such as inadequate integration of international elements in teaching content,insufficient depth of interna...In the wave of higher education internationalization,college students’career education is faced with problems such as inadequate integration of international elements in teaching content,insufficient depth of international cooperation in practical links,lack of international professional experience among the teaching staff,and insufficient emphasis on the cultivation of multicultural adaptability in the education model.Based on this,this paper deeply explores the new requirements put forward by internationalization for college students’career education and its diversified implementation paths from the perspective of higher education internationalization.It aims to build a comprehensive and multi-level career education system and improve students’international competitiveness through strategies such as constructing an internationalized curriculum system,expanding international cooperation practice projects,strengthening international exchanges and training for teachers,and integrating multicultural education.展开更多
基金supported by Soongsil University Research Fund and BK 21 of Korea
文摘Foreground moving object detection is an important process in various computer vision applications such as intelligent visual surveillance, HCI, object-based video compression, etc. One of the most successful moving object detection algorithms is based on Adaptive Gaussian Mixture Model （AGMM）. Although ACMM-hased object detection shows very good performance with respect to object detection accuracy, AGMM is very complex model requiring lots of floatingpoint arithmetic so that it should pay for expensive computational cost. Thus, direct implementation of the AGMM-based object detection for embedded DSPs without floating-point arithmetic HW support cannot satisfy the real-time processing requirement. This paper presents a novel rcal-time implementation of adaptive Gaussian mixture model-based moving object detection algorithm for fixed-point DSPs. In the proposed implementation, in addition to changes of data types into fixed-point ones, magnification of the Gaussian distribution technique is introduced so that the integer and fixed-point arithmetic can be easily and consistently utilized instead of real nmnher and floatingpoint arithmetic in processing of AGMM algorithm. Experimental results shows that the proposed implementation have a high potential in real-time applications.
文摘Cognitive radio (CR) is a technology that provides a promising new way to improve the efficiency of the use of the electromagnetic spectrum that available. Spectrum sensing helps in the detection of spectrum holes (unused channels of the band), and instantly move into vacant channels while avoiding occupied ones. An energy detector with baseband sampling for CR is presented with mathematical analyses for an additive white Gaussian noise (AWGN) channels. A brief overview of the energy detection based spectrum sensing for CR technology is introduced. Practical implementation issues on Texas Instruments TMS320C6713 floating point DSP board are presented. Novelties of this work came from a derivation of probability of detection and probability of false alarm for the baseband energy detector without including the sampling theorems and the associated approximation.
基金Supported by National Naturai Science Foundation of China （61273104, 61021002, 61104097）, and Projects of Major Interna-tional （Regional） Joint Research Program National Natural Science Foundation of China （61120106010）
文摘A Kalman filter which estimates unsteady laminar flow in a pipe is implemented on a real-time computing system. The plant model is the optimised finite element model of pipeline dynamics considering unsteady laminar friction. A steady-state Kalman filter is built based on the model of pipeline dynamics. Pressure signals at both ends of a target section of a pipe are input to the model of pipeline dynamics, and as an output of the model an estimated pressure signal at a mid-point of the pipe is obtained. Difference between measured and estimated pressure signals at the mid-point is fed back to the model of pipeline dynamics to modify state variables of the model. According to the Kalman filter principle, the state variables of the model are adjusted so that they converge to real values. It is demonstrated that real-time implementation of the Kalman filter is possible with the sampling time of 0.1 ms.
基金supported by the National Magnetic Confinement Fusion Program of China(No.2019YFE03020002)the National Natural Science Foundation of China(Nos.12205085 and12125502)。
文摘Fast neutron flux measurements with high count rates and high time resolution have important applications in equipment such as tokamaks.In this study,real-time neutron and gamma discrimination was implemented on a self-developed 500-Msps,12-bit digitizer,and the neutron and gamma spectra were calculated directly on an FPGA.A fast neutron flux measurement system with BC-501A and EJ-309 liquid scintillator detectors was developed and a fast neutron measurement experiment was successfully performed on the HL-2 M tokamak at the Southwestern Institute of Physics,China.The experimental results demonstrated that the system obtained the neutron and gamma spectra with a time accuracy of 1 ms.At count rates of up to 1 Mcps,the figure of merit was greater than 1.05 for energies between 50 keV and 2.8 MeV.
文摘Model predictive control (MPC) could not be deployed in real-time control systems for its computation time is not well defined. A real-time fault tolerant implementation algorithm based on imprecise computation is proposed for MPC, according to the solving process of quadratic programming (QP) problem. In this algorithm, system stability is guaranteed even when computation resource is not enough to finish optimization completely. By this kind of graceful degradation, the behavior of real-time control systems is still predictable and determinate. The algorithm is demonstrated by experiments on servomotor, and the simulation results show its effectiveness.
文摘Microsoft Kinect sensor has shown the research community that it's more than just an interactive gaming device, due to its multi-functional abilities and high reliability. In this work, online HIL (Hardware-in-the-Loop) experimental data are used to apply human motion imitation to a 2-degree of freedom Lego Mind storm NXT robotic arm. A model simulation of the dc motor used in this experiment is also present in this paper. The acquired input data from the Kinect sensor are processed in a closed loop PID controller with feedback from motors encoders. The applied algorithms solve the overlapping input problem, conducting a simultaneous control of both shoulder and elbow joints, and solving the overlapping input problem as well. The work in this paper is presented as a prototype to assure the applicability of the algorithms, for further development.
文摘Traffic sign recognition (TSR, or Road Sign Recognition, RSR) is one of the Advanced Driver Assistance System (ADAS) devices in modern cars. To concern the most important issues, which are real-time and resource efficiency, we propose a high efficiency hardware implementation for TSR. We divide the TSR procedure into two stages, detection and recognition. In the detection stage, under the assumption that most German traffic signs have red or blue colors with circle, triangle or rectangle shapes, we use Normalized RGB color transform and Single-Pass Connected Component Labeling (CCL) to find the potential traffic signs efficiently. For Single-Pass CCL, our contribution is to eliminate the “merge-stack” operations by recording connected relations of region in the scan phase and updating the labels in the iterating phase. In the recognition stage, the Histogram of Oriented Gradient (HOG) is used to generate the descriptor of the signs, and we classify the signs with Support Vector Machine (SVM). In the HOG module, we analyze the required minimum bits under different recognition rate. The proposed method achieves 96.61% detection rate and 90.85% recognition rate while testing with the GTSDB dataset. Our hardware implementation reduces the storage of CCL and simplifies the HOG computation. Main CCL storage size is reduced by 20% comparing to the most advanced design under typical condition. By using TSMC 90 nm technology, the proposed design operates at 105 MHz clock rate and processes in 135 fps with the image size of 1360 × 800. The chip size is about 1 mm2 and the power consumption is close to 8 mW. Therefore, this work is resource efficient and achieves real-time requirement.
基金funded by the ICT Division of theMinistry of Posts,Telecommunications,and Information Technology of Bangladesh under Grant Number 56.00.0000.052.33.005.21-7(Tracking No.22FS15306)support from the University of Rajshahi.
文摘The Internet of Things(IoT)and mobile technology have significantly transformed healthcare by enabling real-time monitoring and diagnosis of patients.Recognizing Medical-Related Human Activities(MRHA)is pivotal for healthcare systems,particularly for identifying actions critical to patient well-being.However,challenges such as high computational demands,low accuracy,and limited adaptability persist in Human Motion Recognition(HMR).While some studies have integrated HMR with IoT for real-time healthcare applications,limited research has focused on recognizing MRHA as essential for effective patient monitoring.This study proposes a novel HMR method tailored for MRHA detection,leveraging multi-stage deep learning techniques integrated with IoT.The approach employs EfficientNet to extract optimized spatial features from skeleton frame sequences using seven Mobile Inverted Bottleneck Convolutions(MBConv)blocks,followed by Convolutional Long Short Term Memory(ConvLSTM)to capture spatio-temporal patterns.A classification module with global average pooling,a fully connected layer,and a dropout layer generates the final predictions.The model is evaluated on the NTU RGB+D 120 and HMDB51 datasets,focusing on MRHA such as sneezing,falling,walking,sitting,etc.It achieves 94.85%accuracy for cross-subject evaluations and 96.45%for cross-view evaluations on NTU RGB+D 120,along with 89.22%accuracy on HMDB51.Additionally,the system integrates IoT capabilities using a Raspberry Pi and GSM module,delivering real-time alerts via Twilios SMS service to caregivers and patients.This scalable and efficient solution bridges the gap between HMR and IoT,advancing patient monitoring,improving healthcare outcomes,and reducing costs.
文摘Along with process control,perception represents the main function performed by the Edge Layer of an Internet of Things(IoT)network.Many of these networks implement various applications where the response time does not represent an important parameter.However,in critical applications,this parameter represents a crucial aspect.One important sensing device used in IoT designs is the accelerometer.In most applications,the response time of the embedded driver software handling this device is generally not analysed and not taken into account.In this paper,we present the design and implementation of a predictable real-time driver stack for a popular accelerometer and gyroscope device family.We provide clear justifications for why this response time is extremely important for critical applications in the acquisition process of such data.We present extensive measurements and experimental results that demonstrate the predictability of our solution,making it suitable for critical real-time systems.
文摘Although computer architectures incorporate fast processing hardware resources, high performance real-time implementation of a complex control algorithm requires an efficient design and software coding of the algorithm so as to exploit special features of the hardware and avoid associated architecture shortcomings. This paper presents an investigation into the analysis and design mechanisms that will lead to reduction in the execution time in implementing real-time control algorithms. The proposed mechanisms are exemplified by means of one algorithm, which demonstrates their applicability to real-time applications. An active vibration control （AVC） algorithm for a flexible beam system simulated using the finite difference （FD） method is considered to demonstrate the effectiveness of the proposed methods. A comparative performance evaluation of the proposed design mechanisms is presented and discussed through a set of experiments.
基金the 2023 Open Project of the Kazakhstan Research Center at YiIi Normal University,Study on National Language Education Policy in Kazakhstan Under the Belt and Road Initiative(No.2023HSKSTYJYB007).
文摘Language policies are of great significance to a nation’s stability,unity,and development.Uzbekistan’s language policies have reflected the political,economic,and cultural dynamics of different periods throughout historical changes,influencing social structures and ethnic relations.This paper summarizes the characteristics of Uzbekistan’s language policies in different eras:During the Tsarist Russian period,the Russification of language policies hindered the development of local languages;in the Soviet era,policies adopted a dual approach,promoting both Russian and prioritizing ethnic languages;after independence,Uzbekistan established Uzbek as the state language and emphasized foreign language education.The current language policy in Uzbekistan presents a complex landscape:While emphasizing the dominant role of the national language helps preserve its heritage,it may easily spark ethnic and political tensions;promoting pluralism and inclusivity brings benefits but faces challenges in balancing language statuses,resource allocation,management,and communication;modernization efforts encounter difficulties in standardizing dialects and foreign loanwords;and in international exchanges,there is a need to balance relations with global lingua francas.In conclusion,Uzbekistan’s language policies have undergone unique transformations and face numerous challenges.In-depth research is crucial for improving the country’s policies and enhancing China-Uzbekistan cooperation.Proactive measures are needed to address these challenges,ensuring the sustainability of language policies and fostering greater national prosperity.
文摘Taking Zhejiang Province as an example,this paper explores the mechanisms and implementation pathways through which the low-altitude economy drives the transformation and upgrading of the tourism industry.It finds that the low-altitude economy can effectively promote the development of high-end and diversified tourism in Zhejiang by innovating tourism formats,optimizing resource allocation,and enhancing tourist experiences.Besides,it analyzes the current development status of the low-altitude economy in Zhejiang and its potential for integration with tourism,revealing specific enabling pathways for tourism transformation,including low-altitude sightseeing,aviation tourism,and low-altitude sports.Finally,it proposes policy recommendations such as strengthening policy support,enhancing infrastructure development,and cultivating market entities.The findings aim to provide theoretical references and practical guidance for the high-quality development of tourism in Zhejiang Province.
文摘Real-time semantic segmentation tasks place stringent demands on network inference speed,often requiring a reduction in network depth to decrease computational load.However,shallow networks tend to exhibit degradation in feature extraction completeness and inference accuracy.Therefore,balancing high performance with real-time requirements has become a critical issue in the study of real-time semantic segmentation.To address these challenges,this paper proposes a lightweight bilateral dual-residual network.By introducing a novel residual structure combined with feature extraction and fusion modules,the proposed network significantly enhances representational capacity while reducing computational costs.Specifically,an improved compound residual structure is designed to optimize the efficiency of information propagation and feature extraction.Furthermore,the proposed feature extraction and fusion module enables the network to better capture multi-scale information in images,improving the ability to detect both detailed and global semantic features.Experimental results on the publicly available Cityscapes dataset demonstrate that the proposed lightweight dual-branch network achieves outstanding performance while maintaining low computational complexity.In particular,the network achieved a mean Intersection over Union(mIoU)of 78.4%on the Cityscapes validation set,surpassing many existing semantic segmentation models.Additionally,in terms of inference speed,the network reached 74.5 frames per second when tested on an NVIDIA GeForce RTX 3090 GPU,significantly improving real-time performance.
基金supported by the National Natural Science Foundation of China(No.22306076)the Natural Science Foundation of Jiangsu Province(No.BK20230676)the Natural Science Foundation of Jiangsu Higher Education Institutions of China(No.22KJB610011).
文摘Here,a novel real-time monitoring sensor that integrates the oxidation of peroxymonosulfate(PMS)and the in situ monitoring of the pollutant degradation process is proposed.Briefly,FeCo@carbon fiber(FeCo@CF)was utilized as the anode electrode,while graphite rods served as the cathode electrode in assembling the galvanic cell.The FeCo@CF electrode exhibited rapid reactivity with PMS,generating reactive oxygen species that efficiently degrade organic pollutants.The degradation experiments indicate that complete bisphenol A(BPA)degradation was achieved within 10 min under optimal conditions.The real-time electrochemical signal was measured in time during the catalytic reaction,and a linear relationship between BPA concentration and the real-time charge(Q)was confirmed by the equation ln(C0/C)=4.393Q(correlation coefficients,R^(2)=0.998).Furthermore,experiments conducted with aureomycin and tetracycline further validated the effectiveness of the monitoring sensor.First-principles investigation confirmed the superior adsorption energy and improved electron transfer in FeCo@CF.The integration of pollutant degradation with in situ monitoring of catalytic reactions offers promising prospects for expanding the scope of the monitoring of catalytic processes and making significant contributions to environmental purification.
基金supported by the National Natural Science Foundation of China(No.82204931).
文摘The demand for Chinese-Western medicine collaboration has grown significantly,but current integration methods have substantial limitations.This article analyzes core issues in developing and implementing synergistic Chinese-Western medicine clinical treatment strategies and explores the transformation from traditional integration to genuine synergistic models.We analyzed methodological obstacles in synergistic strategy development through literature review and theoretical analysis,and explored applications of intelligent technology in strategy development.Four core challenges were identified:(1)Treatment timing coordination difficulties caused by different decision-making approaches,with Chinese medicine using syndrome-based assessments and Western medicine relying on standardized measurements;(2)Treatment selection complexities when integrating different types of evidence,lacking frameworks for evaluating and combining diverse evidence sources;(3)Obstacles in incorporating patient preferences systematically,with inadequate assessment methods and unclear integration mechanisms;(4)Implementation barriers in translating synergistic strategies into clinical practice,requiring changes in organizational structures,workflows,and evaluation systems.Large language models(LLMs)and other intelligent technologies offer technical support for addressing these methodological challenges.This article examines current challenges in developing synergistic Chinese-Western medicine clinical strategies,analyzing the shift from traditional integration toward synergistic approaches and identifying four core methodological obstacles.Exploring intelligent technology applications provides insights to inform future research directions and clinical practice development in integrated healthcare delivery.
文摘Currently,we have entered the era of artificial intelligence(AI).The rapid development and wide application of AI technology have exerted a profound impact on all fields of society.Against this backdrop,this paper conducts an in-depth analysis focusing on general education in AI.First,it expounds the necessity of AI general education in cultivating the core literacy of vocational college students.Then,it puts forward effective implementation paths for such general education.The purpose is to provide valuable references for promoting the reform and innovative development of vocational education.
基金Mechanism of Nanotechnology-driven Polyphyllin I in Sensitizing PD-1 Monoclonal Antibody in Breast Cancer(82204922)Nanotechnology-driven Polyphyllin I Affects Mitochondrial Homeostasis via Cuproptosis and Its Mechanism in Breast Cancer Treatment(ZZ18-YQ-022)。
文摘Oncology covers a wide range of knowledge and is more difficult compared to other clinical disciplines.Therefore,it is crucial to seek an efficient teaching method for oncology education.In recent years,China’s internet technology has achieved rapid development.Massive Open Online Course(MOOC),a blended learning approach based on internet technology,has strong applicability to medical education.It can not only improve teaching quality but also promote further reform of the discipline.Based on this,our study searched for relevant research at home and abroad and reviewed the implementation path of integrating MOOC and blended learning in oncology education.This provides a theoretical foundation for the innovation of oncology teaching models,improves the level of oncology teaching,and lays a solid foundation for talent reserves in oncology departments.
文摘In the wave of higher education internationalization,college students’career education is faced with problems such as inadequate integration of international elements in teaching content,insufficient depth of international cooperation in practical links,lack of international professional experience among the teaching staff,and insufficient emphasis on the cultivation of multicultural adaptability in the education model.Based on this,this paper deeply explores the new requirements put forward by internationalization for college students’career education and its diversified implementation paths from the perspective of higher education internationalization.It aims to build a comprehensive and multi-level career education system and improve students’international competitiveness through strategies such as constructing an internationalized curriculum system,expanding international cooperation practice projects,strengthening international exchanges and training for teachers,and integrating multicultural education.
