With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Further...With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.展开更多
Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrat...Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.展开更多
Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.Thi...Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.展开更多
Embedded printing is a highly promising approach for creating complex structures within a yield-stress support bath.However,the accurate prediction and control of printability remain fundamental challenges due to the ...Embedded printing is a highly promising approach for creating complex structures within a yield-stress support bath.However,the accurate prediction and control of printability remain fundamental challenges due to the complex interactions between inks and support baths.Here,we present an artificial intelligence(AI)-driven framework that interprets and predicts embedded printability using rheological data.Using a standardized workflow,we extracted 21 rheological descriptors and established 12 indicators to evaluate structural continuity and geometric fidelity.Interpretable machine learning models revealed that direction-dependent defects are governed by the synergistic interplay among ink yield stress,support bath zero shear viscosity,flow behavior index,and time constant.To enable the prediction of printability in a generalizable manner,we further developed a cascaded neural network,which achieved mean relative prediction errors below 15%across all indicators.Experimental validation using three-dimensional(3 D)-printed constructs and micro-computed tomography(μCT)reconstructions confirmed a strong correlation between predicted and actual fidelity.This work establishes a physics-informed,data-driven paradigm for decoding and optimizing embedded printing,offering broad applicability and providing a robust tool for the rapid pairing of suitable printable ink-support bath combinations.展开更多
Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame...Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame-work that uses Bidirectional Encoder Representations from Transformers(BERT)for contextual feature extraction and a multiple-window Convolutional Neural Network(CNN)for classification.To identify semantic nuances in email content,BERT embeddings are used,and CNN filters extract discriminative n-gram patterns at various levels of detail,enabling accurate spam identification.The proposed model outperformed Word2Vec-based baselines on a sample of 5728 labelled emails,achieving an accuracy of 98.69%,AUC of 0.9981,F1 Score of 0.9724,and MCC of 0.9639.With a medium kernel size of(6,9)and compact multi-window CNN architectures,it improves performance.Cross-validation illustrates stability and generalization across folds.By balancing high recall with minimal false positives,our method provides a reliable and scalable solution for current spam detection in advanced deep learning.By combining contextual embedding and a neural architecture,this study develops a security analysis method.展开更多
Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,inclu...Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.展开更多
In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the effor...In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the efforts of researchers and security experts to protect information systems from these attacks,the threat persists and the proposed solutions are not able to significantly stop the spread of ransomware attacks.The latest remarkable achievements of large language models(LLMs)in NLP tasks have caught the attention of cybersecurity researchers to integrate thesemodels into security threat detection.Thesemodels offer high embedding capabilities,able to extract rich semantic representations and paving theway formore accurate and adaptive solutions.In this context,we propose a new approach for ransomware detection based on an ensemblemethod that leverages three distinctLLMembeddingmodels.This ensemble strategy takes advantage of the variety of embedding methods and the strengths of each model.In the proposed solution,each embedding model is associated with an independently trainedMLP classifier.The predictions obtained are then merged using a weighted voting technique,assigning each model an influence proportional to its performance.This approach makes it possible to exploit the complementarity of representations,improve detection accuracy and robustness,and offer a more reliable solution in the face of the growing diversity and complexity of modern ransomware.展开更多
Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,transl...Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.展开更多
In the context of the coordinated pursuit of"carbon peak and neutrality"objectives,alongside the strategy to establish a robust agricultural nation,the economic and social development of rural areas is under...In the context of the coordinated pursuit of"carbon peak and neutrality"objectives,alongside the strategy to establish a robust agricultural nation,the economic and social development of rural areas is undergoing a profound paradigm shift.The traditional rural division of labor pattern,which depends on tangible factors such as land,labor,and capital,has increasingly encountered developmental challenges characterized by diminishing marginal returns and a detrimental cycle of internal competition.The new quality productive force,centered on data,algorithms,green technologies,bioengineering,and clean energy,offers a potential pathway for the rural division of labor system to overcome the"low-level equilibrium".This force is characterized by attributes such as non-exclusivity,replicability,network collaboration,and ecological compatibility.This paper develops a three-dimensional collaborative analytical framework encompassing"technology,institution,and culture".It systematically elucidates the internal logic by which new quality productive forces drive the transformation of the rural division of labor from"quantitative factor matching"to"qualitative structural reorganization"through three principal mechanisms:technology embedding,institutional reconstruction,and cultural coupling.Furthermore,the study proposes corresponding policy recommendations,thereby offering theoretical insights to support the modernization of China s agriculture and rural areas,as well as the development of a strong agricultural country.展开更多
This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine t...This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine the transmission power of the DC and AC paths to simultaneously improve voltage quality and reduce losses.First,considering the embedded interconnected,unbalanced power structure of the distribution area,a power flow calculation method for EDC-LVDA that accounts for three-phase unbalanced compensation is introduced.This method accurately describes the power flow distribution characteristics under both AC and DC power allocation scenarios.Second,an optimization scheduling model for EDC-LVDA under three-phase unbalanced conditions is developed,incorporating network losses,voltage quality,DC link losses,and unbalance levels.The proposed model employs an improved particle swarm optimization(IPSO)two-layer algorithm to autonomously select different power allocation coefficients for the DC link and AC section under various operating conditions.This enables embedded economic optimization scheduling while maintaining compensation for unbalanced conditions.Finally,a case study based on the IEEE 13-node system for EDC-LVDA is conducted and tested.The results show that the proposed optimal operation method achieves a 100%voltage compliance rate and reduces network losses by 13.8%,while ensuring three-phase power balance compensation.This provides a practical solution for the modernization and upgrading of low-voltage power grids.展开更多
Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple ...Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple obesity with ACET in databases of the China National Knowledge Infrastructure （CNKI）, Wanfang Data system, and the China Biology Medicine disc （CBMDisc）. The Jadad Quality Scale was used in the evaluation of included studies. The outcome indicators were analyzed with the Review Manage 5.1 software. Results A total of 16 randomized controlled trials were included finally. The meta-analysis result showed that compared with the control group, there was statistically significance on the total efficiency of using ACET for simple obesity [OR=2.51, 95% confidence interval （1.74, 3.63）, Z=4.91, P〈0.000 01]. The analysis on the literature quality showed that there was only 2 article marked as 3 points. The other 25 articles marked ≤2 points. The quality of published articles was generally low. There were publication biases and the blinding method was seldom used, the losses of follow-up / drop oup / withdraw were reported with less. There were 27 acupoints used in the treatment, which mainly included Tianshu （天枢ST 25）, Zhongwan （中脘 CV 12）, Fenglong （丰隆 ST 40）, Shufen （水分 CV 9）, Qihai （气海 CV 6）, Sanyinjiao （三阴交 SP 6）, Zusnli （足三里 ST 36）, Ashi point, Daheng （大横 SP 25）. The five kinds of catgut embedding needle were injection needles ＋ acupuncture needle, specialized catgut embedding needle, spinal needle, triangular needle, and skin suture needle. Conclusion There is definite efficiency of using ACET in the treatment of simple obesity. However, the clinical efficiency still lacks of sufficient evidences. Therefore, further clinical research should be conducted in the providing of reliable evidences in the clinical decision-making in the future.展开更多
The embedded data acquistition technology in vehicle electronic system was discussed. This technology adopts the parallel working mode, gets vehicle electronic system data by communication. This technology can provide...The embedded data acquistition technology in vehicle electronic system was discussed. This technology adopts the parallel working mode, gets vehicle electronic system data by communication. This technology can provide us a lot of information on the electronic control unit, is very useful for the development of the vehicle electronic system, and can be used in diagnosis. The key points to this technology are the timer interrupt, A/D interrupt, communication interrupt and real time operation. This technology has been validated by the application in the electronic control mechanism transmission shifting system of the tank.展开更多
Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI,...Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI, Wanfang Database, VlP Database, and PubMed） were searched to identify relevant studies published before June 2027. The outcomes were resumption of menstruation and serum levels of testosterone （T）. The methodological quality of the included studies was judged using the Cochrane risk of bias tool. The overall level of evidence was judged by the Grading of Recommendations Assessment, Development, and Evaluation （GRADE） criteria. Results Twenty- five randomized controlled trials were included. ACE therapy significantly lowered serum T levels, and patients receiving ACE treatment reported resumption of menstruation. However, these results should be interpreted with caution due to a high risk of randomization and blinding bias, and likely publication bias. The level of evidence for resumption of menstruation and serum T levels was assessed as ＂low＂ and ＂low＂, respectively, using GRADE. Conclusion The current evidence on ACE therapy for PCOS is insufficient to draw firm conclusions due to the poor methodological quality. Future well- designed trials are needed to validate the therapeutic efficacy, safety, and mechanisms of ACE in patients with PCOS.展开更多
A system of number recognition with a graphic user interface （GUI） is implemented on the embedded development platform by using the fuzzy pattern recognition method. An application interface （API） of uC/ OS-Ⅱ is ...A system of number recognition with a graphic user interface （GUI） is implemented on the embedded development platform by using the fuzzy pattern recognition method. An application interface （API） of uC/ OS-Ⅱ is used to implement the features of multi-task concurrency and the communications among tasks. Handwriting function is implemented by the improvement of the interface provided by the platform. Fuzzy pattern recognition technology based on fuzzy theory is used to analyze the input of handwriting. A primary system for testing is implemented. It can receive and analyze user inputs from both keyboard and touch-screen. The experimental results show that the embedded fuzzy recognition system which uses the technology which integrates two ways of fuzzy recognition can retain a high recognition rate and reduce hardware requirements.展开更多
OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgu...OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgut embedding for simple obesity which were published from January 2015 to November 2020 were searched in Cochrane Central Register of Control Trials(Central), Pub Med, China Science and Technology Journal Database, China National Knowledge Infrastructure Database and Wanfang databases. And those that met the inclusion criteria were screened. Rev Man5.3 was used for Meta-analysis. The “Risk of Bias” tool was used to evaluate the quality of included studies. R studio software was used for the measurement of publication bias. RESULTS: A total of 33 studies were included for Metaanalysis, including 2685 patients with simple obesity. Meta-analysis results showed the comparison of effectiveness rate was relative risk(RR) = 1.12, 95%CI(1.08, 1.16), body mass index(BMI) was mean difference(MD) =-1.12, 95%CI(-2.09,-0.14), waist circumference was MD =-2.14, 95%CI(-4.22,-0.06), and body mass was MD =-2.36, 95%CI(-3.99,-0.73). On the basis of diet and exercise intervention, the effectiveness rate [RR = 1.12, 95%CI(1.05, 1.19)], BMI [MD =-0.88, 95%CI(-1.35,-0.40)], waist circumference [MD =-1.10, 95%CI(-4.27, 2.07)], and body mass [MD =-0.68, 95%CI(-2.90, 1.54)]. The risk of bias of included literatures was low. CONCLUSIONS: Acupoint catgut embedding therapy was slightly better than acupuncture therapy in most of the outcomes. Moreover, the treatment frequency of acupoint catgut embedding is less with larger stimulation intensity, which is more conducive to clinical promotion.展开更多
The software-based computer numerical control（CNC） system includes three types of tasks： periodic real-time tasks, aperiodic real-time tasks, and non-real-time tasks. The tasks are characterized by concurrency, hyb...The software-based computer numerical control（CNC） system includes three types of tasks： periodic real-time tasks, aperiodic real-time tasks, and non-real-time tasks. The tasks are characterized by concurrency, hybridization, and correlation, which make system implementation difficult. The conventional scheduling algorithm can not meet the demands of system implementation in the software-based CNC system completely. The uncertainty factors when running real-time tasks affect control performance by degrading manufacturing accuracy as a result of system resource and processor use restrictions. To address the technical difficulty of embedded system implementation, a novel fuzzy feedback scheduling algorithm based on output jitter of key real-time tasks for a software-based CNC system is proposed. Time characteristics, such as sampling jitter, input-output jitter, and non-schedulability are discussed, followed by quantification through simulations of the impact of time characteristics on manufacturing accuracy. On the basis of this research, the scheduler architecture is designed, and then the algorithm table is calculated. When the system resource changes, the key periodic real-time tasks meet their deadlines by means of dynamically adjusting the task period. The simulated results show that the machining precision rises by an order of magnitude for the proposed scheduler in resource-constrained software-based CNC systems. Moreover, unlike conventional feedback scheduling methods, the algorithm in this paper does not rely on the availability of task execution times and is easy to implement while incurring only a small overhead.展开更多
Aimed at the deficiencies of resources based time Petri nets （RBTPN） in doing scheduling analysis for distributed real-time embedded systems, the assemblage condition of complex scheduling sequences is presented to ...Aimed at the deficiencies of resources based time Petri nets （RBTPN） in doing scheduling analysis for distributed real-time embedded systems, the assemblage condition of complex scheduling sequences is presented to easily compute scheduling length and simplify scheduling analysis. Based on this, a new hierarchical RBTPN model is proposed. The model introduces the definition of transition border set, and represents it as an abstract transition. The abstract transition possesses all resources of the set, and has the highest priority of each resource; the cxecution time of abstract transition is the longest time of all possible scheduling sequences. According to the characteristics and assemblage condition of RBTPN, the refinement conditions of transition border set are given, and the conditions ensure the correction of scheduling analysis. As a result, it is easy for us to understand the scheduling model and perform scheduling analysis.展开更多
OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental...OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental Medicine Advanced Searching Integrated System,KoreaMed,Korean Studies Information Service System,Science-on,Research Information Sharing Service,Korea Citation Index,Korea Traditional Knowledge Portal,China Network Knowledge Infrastructure Database,Wanfang Database,Chinese Science and Technology Journal Database,and Chinese Biology Medicine Database,from inception to November 2021 without language limitation.The assessment was performed according to the guidelines of Animal Research:Reporting of in vivo experiments;and Metaanalysis was performed using Reviewer Manager 5.4.1 software.RESULTS:Twenty-four studies involving 813 animals were selected.Meta-analysis showed that ACE was beneficial for weight control[n=40,MD=-50.63,95%CI(-57.59,-43.67),P<0.00001,I 2=0%]and reduced the Lee index[n=40,MD=-18.79,95%CI(-20.01,-17.57),P<0.00001,I 2=0%].However,when efficacy of ACE was compared with that of manual acupuncture,electroacupuncture,or oilistat therapy,statistical difference was not observed between the two groups.CONCLUSIONS:This systematic review suggests that ACE may be efficacious in treating obesity.Moreover,the analyses highlighted the necessity to perform welldesigned,higher-quality experiments.展开更多
Optical fiber acceleration seismometer as an important instrument can offer high sensitivity, anti-jamming and non-touched advantage which has an extensive application field. Its signal processing ability will decide ...Optical fiber acceleration seismometer as an important instrument can offer high sensitivity, anti-jamming and non-touched advantage which has an extensive application field. Its signal processing ability will decide whole system’s performance to some extent because it will affect directly the factors such as resolving power, precision and dynamic range. The signal processing is usually realized by analog circuits which was more inferior in stability, flexibility and anti-jamming to digital processing system. A digital processing system of optical fiber acceleration seismometer has been designed based on the embedded system design scheme. Synthetic-heterodyne demodulation has been studied, and signal processing has been realized. The double processors of ARM and DSP are employed to implement respectively the system control and signal processing, and to provide the output interfaces such as LCD, DAC and Ethernet interface. This system can vary with the measured signal in real time and linearly, and its work frequency bandwidth is between 10Hz and 1kHz. The system has better anti-jamming ability and can work normally when the SNR is 40dB.展开更多
In stroke rehabilitation,rehabilitation equipments can help with the training.But traditional equipments are not convenient to carry,which limits patients to use related rehabilitation techniques.To solve this kind of...In stroke rehabilitation,rehabilitation equipments can help with the training.But traditional equipments are not convenient to carry,which limits patients to use related rehabilitation techniques.To solve this kind of problem,a new embedded rehabilitation system based on brain computer interface(BCI)is proposed in this paper.The system is based on motor imagery(MI)therapy,in which electroencephalogram(EEG)is evoked by grasping motor imageries of left and right hands,then collected by a wearable device.The EEG is transmitted to a Raspberry Pie processing unit through Bluetooth and decoded as the instructions to control the equipment extension.Users experience the limb movement through the visual feedback so as to achieve active rehabilitation.A pilot study shows that the user can control the movement of the rehabilitation equipment through his mind,and the equipment is convenient to carry.The study provides a new way to stroke rehabilitation.展开更多
基金supported by the National Natural Science Foundation of China under Grant 62471493supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066。
文摘With the rapid development of intelligent cyber-physical systems(ICPS),diverse services with varying Quality of Service(QoS)requirements have brought great challenges to traditional network resource allocation.Furthermore,given the open environment and a multitude of devices,enhancing the security of ICPS is an urgent concern.To address these issues,this paper proposes a novel trusted virtual network embedding(T-VNE)approach for ICPS based combining blockchain and edge computing technologies.Additionally,the proposed algorithm leverages a deep reinforcement learning(DRL)model to optimize decision-making processes.It employs the policygradient-based agent to compute candidate embedding nodes and utilizes a breadth-first search(BFS)algorithm to determine the optimal embedding paths.Finally,through simulation experiments,the efficacy of the proposed method was validated,demonstrating outstanding performance in terms of security,revenue generation,and virtual network request(VNR)acceptance rate.
基金supported by the National Key R&D Program of China(Grant No.2021YFA1001000)the National Natural Science Foundation of China(Grant Nos.82111530212,U23A20282,and 61971255)+2 种基金the Natural Science Founda-tion of Guangdong Province(Grant No.2021B1515020092)the Shenzhen Bay Laboratory Fund(Grant No.SZBL2020090501014)the Shenzhen Science,Technology and Innovation Commission(Grant Nos.KJZD20231023094659002,JCYJ20220530142809022,and WDZC20220811170401001).
文摘Neural organoids and confocal microscopy have the potential to play an important role in microconnectome research to understand neural patterns.We present PLayer,a plug-and-play embedded neural system,which demonstrates the utilization of sparse confocal microscopy layers to interpolate continuous axial resolution.With an embedded system focused on neural network pruning,image scaling,and post-processing,PLayer achieves high-performance metrics with an average structural similarity index of 0.9217 and a peak signal-to-noise ratio of 27.75 dB,all within 20 s.This represents a significant time saving of 85.71%with simplified image processing.By harnessing statistical map estimation in interpolation and incorporating the Vision Transformer–based Restorer,PLayer ensures 2D layer consistency while mitigating heavy computational dependence.As such,PLayer can reconstruct 3D neural organoid confocal data continuously under limited computational power for the wide acceptance of fundamental connectomics and pattern-related research with embedded devices.
文摘Unmanned aerial vehicles(UAVs),especially quadcopters,have become indispensable in numerous industrial and scientific applications due to their flexibility,lowcost,and capability to operate in dynamic environments.This paper presents a complete design and implementation of a compact autonomous quadcopter capable of trajectory tracking,object detection,precision landing,and real-time telemetry via long-range communication protocols.The system integrates an onboard flight controller running real-time sensor fusion algorithms,a vision-based detection system on a companion single-board computer,and a telemetry unit using Long Range(LoRa)communication.Extensive flight tests were conducted to validate the system’s stability,communication range,and autonomous capabilities.Potential applications in law enforcement,agriculture,search and rescue,and environmental monitoring are also discussed.
基金supported by the National Natural Science Foundation of China(Nos.52305314 and U21A20394)the Beijing Natural Science Foundation(Nos.7252285 and L246001)the National Key Research and Development Program of China(No.2023YFB4605800)。
文摘Embedded printing is a highly promising approach for creating complex structures within a yield-stress support bath.However,the accurate prediction and control of printability remain fundamental challenges due to the complex interactions between inks and support baths.Here,we present an artificial intelligence(AI)-driven framework that interprets and predicts embedded printability using rheological data.Using a standardized workflow,we extracted 21 rheological descriptors and established 12 indicators to evaluate structural continuity and geometric fidelity.Interpretable machine learning models revealed that direction-dependent defects are governed by the synergistic interplay among ink yield stress,support bath zero shear viscosity,flow behavior index,and time constant.To enable the prediction of printability in a generalizable manner,we further developed a cascaded neural network,which achieved mean relative prediction errors below 15%across all indicators.Experimental validation using three-dimensional(3 D)-printed constructs and micro-computed tomography(μCT)reconstructions confirmed a strong correlation between predicted and actual fidelity.This work establishes a physics-informed,data-driven paradigm for decoding and optimizing embedded printing,offering broad applicability and providing a robust tool for the rapid pairing of suitable printable ink-support bath combinations.
基金funded by Princess Nourah bint Abdulrahman University Researchers Supporting Project number(PNURSP2026R234)Princess Nourah bint Abdulrahman University,Riyadh,Saudi Arabia.
文摘Spam emails remain one of the most persistent threats to digital communication,necessitating effective detection solutions that safeguard both individuals and organisations.We propose a spam email classification frame-work that uses Bidirectional Encoder Representations from Transformers(BERT)for contextual feature extraction and a multiple-window Convolutional Neural Network(CNN)for classification.To identify semantic nuances in email content,BERT embeddings are used,and CNN filters extract discriminative n-gram patterns at various levels of detail,enabling accurate spam identification.The proposed model outperformed Word2Vec-based baselines on a sample of 5728 labelled emails,achieving an accuracy of 98.69%,AUC of 0.9981,F1 Score of 0.9724,and MCC of 0.9639.With a medium kernel size of(6,9)and compact multi-window CNN architectures,it improves performance.Cross-validation illustrates stability and generalization across folds.By balancing high recall with minimal false positives,our method provides a reliable and scalable solution for current spam detection in advanced deep learning.By combining contextual embedding and a neural architecture,this study develops a security analysis method.
文摘Message structure reconstruction is a critical task in protocol reverse engineering,aiming to recover protocol field structures without access to source code.It enables important applications in network security,including malware analysis and protocol fuzzing.However,existing methods suffer from inaccurate field boundary delineation and lack hierarchical relationship recovery,resulting in imprecise and incomplete reconstructions.In this paper,we propose ProRE,a novel method for reconstructing protocol field structures based on program execution slice embedding.ProRE extracts code slices from protocol parsing at runtime,converts them into embedding vectors using a data flow-sensitive assembly language model,and performs hierarchical clustering to recover complete protocol field structures.Evaluation on two datasets containing 12 protocols shows that ProRE achieves an average F1 score of 0.85 and a cophenetic correlation coefficient of 0.189,improving by 19%and 0.126%respectively over state-of-the-art methods(including BinPRE,Tupni,Netlifter,and QwQ-32B-preview),demonstrating significant superiority in both accuracy and completeness of field structure recovery.Case studies further validate the effectiveness of ProRE in practical malware analysis scenarios.
基金funded by the Deanship of Graduate Studies and Scientific Research at Jouf University under grant No.(DGSSR-2024-02-01176).
文摘In recent years,ransomware attacks have become one of the most common and destructive types of cyberattacks.Their impact is significant on the operations,finances and reputation of affected companies.Despite the efforts of researchers and security experts to protect information systems from these attacks,the threat persists and the proposed solutions are not able to significantly stop the spread of ransomware attacks.The latest remarkable achievements of large language models(LLMs)in NLP tasks have caught the attention of cybersecurity researchers to integrate thesemodels into security threat detection.Thesemodels offer high embedding capabilities,able to extract rich semantic representations and paving theway formore accurate and adaptive solutions.In this context,we propose a new approach for ransomware detection based on an ensemblemethod that leverages three distinctLLMembeddingmodels.This ensemble strategy takes advantage of the variety of embedding methods and the strengths of each model.In the proposed solution,each embedding model is associated with an independently trainedMLP classifier.The predictions obtained are then merged using a weighted voting technique,assigning each model an influence proportional to its performance.This approach makes it possible to exploit the complementarity of representations,improve detection accuracy and robustness,and offer a more reliable solution in the face of the growing diversity and complexity of modern ransomware.
基金supported by the National Natural Science Foundation of China under Grant No.72293575.
文摘Temporal knowledge graph completion(TKGC),which merges temporal information into traditional static knowledge graph completion(SKGC),has garnered increasing attention recently.Among numerous emerging approaches,translation-based embedding models constitute a prominent approach in TKGC research.However,existing translation-based methods typically incorporate timestamps into entities or relations,rather than utilizing them independently.This practice fails to fully exploit the rich semantics inherent in temporal information,thereby weakening the expressive capability of models.To address this limitation,we propose embedding timestamps,like entities and relations,in one or more dedicated semantic spaces.After projecting all embeddings into a shared space,we use the relation-timestamp pair instead of the conventional relation embedding as the translation vector between head and tail entities.Our method elevates timestamps to the same representational significance as entities and relations.Based on this strategy,we introduce two novel translation-based embedding models:TE-TransR and TE-TransT.With the independent representation of timestamps,our method not only enhances capabilities in link prediction but also facilitates a relatively underexplored task,namely time prediction.To further bolster the precision and reliability of time prediction,we introduce a granular,time unit-based timestamp setting and a relation-specific evaluation protocol.Extensive experiments demonstrate that our models achieve strong performance on link prediction benchmarks,with TE-TransR outperforming existing baselines in the time prediction task.
基金Supported by Key Project of Jiangsu Education Science Planning"Research on the Structural Adjustment of Higher Education in Jiangsu in the Context of High-Quality Economic Development"(B/2021/01/67).
文摘In the context of the coordinated pursuit of"carbon peak and neutrality"objectives,alongside the strategy to establish a robust agricultural nation,the economic and social development of rural areas is undergoing a profound paradigm shift.The traditional rural division of labor pattern,which depends on tangible factors such as land,labor,and capital,has increasingly encountered developmental challenges characterized by diminishing marginal returns and a detrimental cycle of internal competition.The new quality productive force,centered on data,algorithms,green technologies,bioengineering,and clean energy,offers a potential pathway for the rural division of labor system to overcome the"low-level equilibrium".This force is characterized by attributes such as non-exclusivity,replicability,network collaboration,and ecological compatibility.This paper develops a three-dimensional collaborative analytical framework encompassing"technology,institution,and culture".It systematically elucidates the internal logic by which new quality productive forces drive the transformation of the rural division of labor from"quantitative factor matching"to"qualitative structural reorganization"through three principal mechanisms:technology embedding,institutional reconstruction,and cultural coupling.Furthermore,the study proposes corresponding policy recommendations,thereby offering theoretical insights to support the modernization of China s agriculture and rural areas,as well as the development of a strong agricultural country.
基金supported by the key technology project of China Southern Power Grid Corporation(GZKJXM20220041)partly by the National Key Research and Development Plan(2022YFE0205300).
文摘This paper presents an optimal operation method for embedded DC interconnections based on low-voltage AC/DC distribution areas(EDC-LVDA)under three-phase unbalanced compensation conditions.It can optimally determine the transmission power of the DC and AC paths to simultaneously improve voltage quality and reduce losses.First,considering the embedded interconnected,unbalanced power structure of the distribution area,a power flow calculation method for EDC-LVDA that accounts for three-phase unbalanced compensation is introduced.This method accurately describes the power flow distribution characteristics under both AC and DC power allocation scenarios.Second,an optimization scheduling model for EDC-LVDA under three-phase unbalanced conditions is developed,incorporating network losses,voltage quality,DC link losses,and unbalance levels.The proposed model employs an improved particle swarm optimization(IPSO)two-layer algorithm to autonomously select different power allocation coefficients for the DC link and AC section under various operating conditions.This enables embedded economic optimization scheduling while maintaining compensation for unbalanced conditions.Finally,a case study based on the IEEE 13-node system for EDC-LVDA is conducted and tested.The results show that the proposed optimal operation method achieves a 100%voltage compliance rate and reduces network losses by 13.8%,while ensuring three-phase power balance compensation.This provides a practical solution for the modernization and upgrading of low-voltage power grids.
基金Supported by the Naional Natural Science Fund Project of China:81072883,81173342
文摘Objective To systematically evaluate the effect of acupoint catgut embedding therapy （ACET） for simple obesity. Methods Computer retrieval was used for randomized controlled trials on the treatment effect of simple obesity with ACET in databases of the China National Knowledge Infrastructure （CNKI）, Wanfang Data system, and the China Biology Medicine disc （CBMDisc）. The Jadad Quality Scale was used in the evaluation of included studies. The outcome indicators were analyzed with the Review Manage 5.1 software. Results A total of 16 randomized controlled trials were included finally. The meta-analysis result showed that compared with the control group, there was statistically significance on the total efficiency of using ACET for simple obesity [OR=2.51, 95% confidence interval （1.74, 3.63）, Z=4.91, P〈0.000 01]. The analysis on the literature quality showed that there was only 2 article marked as 3 points. The other 25 articles marked ≤2 points. The quality of published articles was generally low. There were publication biases and the blinding method was seldom used, the losses of follow-up / drop oup / withdraw were reported with less. There were 27 acupoints used in the treatment, which mainly included Tianshu （天枢ST 25）, Zhongwan （中脘 CV 12）, Fenglong （丰隆 ST 40）, Shufen （水分 CV 9）, Qihai （气海 CV 6）, Sanyinjiao （三阴交 SP 6）, Zusnli （足三里 ST 36）, Ashi point, Daheng （大横 SP 25）. The five kinds of catgut embedding needle were injection needles ＋ acupuncture needle, specialized catgut embedding needle, spinal needle, triangular needle, and skin suture needle. Conclusion There is definite efficiency of using ACET in the treatment of simple obesity. However, the clinical efficiency still lacks of sufficient evidences. Therefore, further clinical research should be conducted in the providing of reliable evidences in the clinical decision-making in the future.
文摘The embedded data acquistition technology in vehicle electronic system was discussed. This technology adopts the parallel working mode, gets vehicle electronic system data by communication. This technology can provide us a lot of information on the electronic control unit, is very useful for the development of the vehicle electronic system, and can be used in diagnosis. The key points to this technology are the timer interrupt, A/D interrupt, communication interrupt and real time operation. This technology has been validated by the application in the electronic control mechanism transmission shifting system of the tank.
文摘Objective This review aimed to systematically evaluate the evidence on the effects of acupoint catgut embedding （ACE） therapy for patients with polycystic ovary syndrome （PCOS）. Methods Five databases （CBM, CNKI, Wanfang Database, VlP Database, and PubMed） were searched to identify relevant studies published before June 2027. The outcomes were resumption of menstruation and serum levels of testosterone （T）. The methodological quality of the included studies was judged using the Cochrane risk of bias tool. The overall level of evidence was judged by the Grading of Recommendations Assessment, Development, and Evaluation （GRADE） criteria. Results Twenty- five randomized controlled trials were included. ACE therapy significantly lowered serum T levels, and patients receiving ACE treatment reported resumption of menstruation. However, these results should be interpreted with caution due to a high risk of randomization and blinding bias, and likely publication bias. The level of evidence for resumption of menstruation and serum T levels was assessed as ＂low＂ and ＂low＂, respectively, using GRADE. Conclusion The current evidence on ACE therapy for PCOS is insufficient to draw firm conclusions due to the poor methodological quality. Future well- designed trials are needed to validate the therapeutic efficacy, safety, and mechanisms of ACE in patients with PCOS.
基金Pre-Research Project of the National Natural Science Foundation of China supported by Southeast University ( NoXJ0605227)
文摘A system of number recognition with a graphic user interface （GUI） is implemented on the embedded development platform by using the fuzzy pattern recognition method. An application interface （API） of uC/ OS-Ⅱ is used to implement the features of multi-task concurrency and the communications among tasks. Handwriting function is implemented by the improvement of the interface provided by the platform. Fuzzy pattern recognition technology based on fuzzy theory is used to analyze the input of handwriting. A primary system for testing is implemented. It can receive and analyze user inputs from both keyboard and touch-screen. The experimental results show that the embedded fuzzy recognition system which uses the technology which integrates two ways of fuzzy recognition can retain a high recognition rate and reduce hardware requirements.
基金Supported by National Administration of Traditional Chinese Medicine Project:Innovation Team and Talents Cultivation Program of National Administration of Traditional Chinese Medicine (No. ZYYCXTD-C-202006)。
文摘OBJECTIVE: To evaluate the clinical effectiveness and safety of acupoint catgut embedding and acupuncture on simple obesity by Meta-analysis. METHODS: Studies on clinical randomized controlled trials of acupoint catgut embedding for simple obesity which were published from January 2015 to November 2020 were searched in Cochrane Central Register of Control Trials(Central), Pub Med, China Science and Technology Journal Database, China National Knowledge Infrastructure Database and Wanfang databases. And those that met the inclusion criteria were screened. Rev Man5.3 was used for Meta-analysis. The “Risk of Bias” tool was used to evaluate the quality of included studies. R studio software was used for the measurement of publication bias. RESULTS: A total of 33 studies were included for Metaanalysis, including 2685 patients with simple obesity. Meta-analysis results showed the comparison of effectiveness rate was relative risk(RR) = 1.12, 95%CI(1.08, 1.16), body mass index(BMI) was mean difference(MD) =-1.12, 95%CI(-2.09,-0.14), waist circumference was MD =-2.14, 95%CI(-4.22,-0.06), and body mass was MD =-2.36, 95%CI(-3.99,-0.73). On the basis of diet and exercise intervention, the effectiveness rate [RR = 1.12, 95%CI(1.05, 1.19)], BMI [MD =-0.88, 95%CI(-1.35,-0.40)], waist circumference [MD =-1.10, 95%CI(-4.27, 2.07)], and body mass [MD =-0.68, 95%CI(-2.90, 1.54)]. The risk of bias of included literatures was low. CONCLUSIONS: Acupoint catgut embedding therapy was slightly better than acupuncture therapy in most of the outcomes. Moreover, the treatment frequency of acupoint catgut embedding is less with larger stimulation intensity, which is more conducive to clinical promotion.
基金supported by National Natural Science Foundation of China(Grant No.50875090,Grant No.50905063)National Hi-tech Research and Development Program of China(863 Program,Grant No.2009AA4Z111)China Postdoctoral Science Foundation (Grant No.20090460769)
文摘The software-based computer numerical control（CNC） system includes three types of tasks： periodic real-time tasks, aperiodic real-time tasks, and non-real-time tasks. The tasks are characterized by concurrency, hybridization, and correlation, which make system implementation difficult. The conventional scheduling algorithm can not meet the demands of system implementation in the software-based CNC system completely. The uncertainty factors when running real-time tasks affect control performance by degrading manufacturing accuracy as a result of system resource and processor use restrictions. To address the technical difficulty of embedded system implementation, a novel fuzzy feedback scheduling algorithm based on output jitter of key real-time tasks for a software-based CNC system is proposed. Time characteristics, such as sampling jitter, input-output jitter, and non-schedulability are discussed, followed by quantification through simulations of the impact of time characteristics on manufacturing accuracy. On the basis of this research, the scheduler architecture is designed, and then the algorithm table is calculated. When the system resource changes, the key periodic real-time tasks meet their deadlines by means of dynamically adjusting the task period. The simulated results show that the machining precision rises by an order of magnitude for the proposed scheduler in resource-constrained software-based CNC systems. Moreover, unlike conventional feedback scheduling methods, the algorithm in this paper does not rely on the availability of task execution times and is easy to implement while incurring only a small overhead.
文摘Aimed at the deficiencies of resources based time Petri nets （RBTPN） in doing scheduling analysis for distributed real-time embedded systems, the assemblage condition of complex scheduling sequences is presented to easily compute scheduling length and simplify scheduling analysis. Based on this, a new hierarchical RBTPN model is proposed. The model introduces the definition of transition border set, and represents it as an abstract transition. The abstract transition possesses all resources of the set, and has the highest priority of each resource; the cxecution time of abstract transition is the longest time of all possible scheduling sequences. According to the characteristics and assemblage condition of RBTPN, the refinement conditions of transition border set are given, and the conditions ensure the correction of scheduling analysis. As a result, it is easy for us to understand the scheduling model and perform scheduling analysis.
基金the Korea Institute of Oriental Medicine(Grant No.KSN1823211 and KSN20234115)。
文摘OBJECTIVE:To assess the efficacy of acupoint catgut embedding(ACE)for simple obesity in preclinical animal experiments.METHODS:We searched the following 14 electronic databases:PubM ed,Cochrane Library,EMBASE,Oriental Medicine Advanced Searching Integrated System,KoreaMed,Korean Studies Information Service System,Science-on,Research Information Sharing Service,Korea Citation Index,Korea Traditional Knowledge Portal,China Network Knowledge Infrastructure Database,Wanfang Database,Chinese Science and Technology Journal Database,and Chinese Biology Medicine Database,from inception to November 2021 without language limitation.The assessment was performed according to the guidelines of Animal Research:Reporting of in vivo experiments;and Metaanalysis was performed using Reviewer Manager 5.4.1 software.RESULTS:Twenty-four studies involving 813 animals were selected.Meta-analysis showed that ACE was beneficial for weight control[n=40,MD=-50.63,95%CI(-57.59,-43.67),P<0.00001,I 2=0%]and reduced the Lee index[n=40,MD=-18.79,95%CI(-20.01,-17.57),P<0.00001,I 2=0%].However,when efficacy of ACE was compared with that of manual acupuncture,electroacupuncture,or oilistat therapy,statistical difference was not observed between the two groups.CONCLUSIONS:This systematic review suggests that ACE may be efficacious in treating obesity.Moreover,the analyses highlighted the necessity to perform welldesigned,higher-quality experiments.
文摘Optical fiber acceleration seismometer as an important instrument can offer high sensitivity, anti-jamming and non-touched advantage which has an extensive application field. Its signal processing ability will decide whole system’s performance to some extent because it will affect directly the factors such as resolving power, precision and dynamic range. The signal processing is usually realized by analog circuits which was more inferior in stability, flexibility and anti-jamming to digital processing system. A digital processing system of optical fiber acceleration seismometer has been designed based on the embedded system design scheme. Synthetic-heterodyne demodulation has been studied, and signal processing has been realized. The double processors of ARM and DSP are employed to implement respectively the system control and signal processing, and to provide the output interfaces such as LCD, DAC and Ethernet interface. This system can vary with the measured signal in real time and linearly, and its work frequency bandwidth is between 10Hz and 1kHz. The system has better anti-jamming ability and can work normally when the SNR is 40dB.
基金Supported by the National Natural Science Foundation of China(61671193)Science and Technology Program of Zhejiang Province(2018C04012,2017C33049)Science and Technology Platform Construction Project of Fujian Science and Technology Department(2015Y2001)
文摘In stroke rehabilitation,rehabilitation equipments can help with the training.But traditional equipments are not convenient to carry,which limits patients to use related rehabilitation techniques.To solve this kind of problem,a new embedded rehabilitation system based on brain computer interface(BCI)is proposed in this paper.The system is based on motor imagery(MI)therapy,in which electroencephalogram(EEG)is evoked by grasping motor imageries of left and right hands,then collected by a wearable device.The EEG is transmitted to a Raspberry Pie processing unit through Bluetooth and decoded as the instructions to control the equipment extension.Users experience the limb movement through the visual feedback so as to achieve active rehabilitation.A pilot study shows that the user can control the movement of the rehabilitation equipment through his mind,and the equipment is convenient to carry.The study provides a new way to stroke rehabilitation.
