To linearize the multi.band PAs/transmitters, a serial of multi.band predistortion models based on multi.dimensional architecture have been proposed. However, most of these models work properly only for the signals wh...To linearize the multi.band PAs/transmitters, a serial of multi.band predistortion models based on multi.dimensional architecture have been proposed. However, most of these models work properly only for the signals whose harmonic and intermodulation products of carriers' non.overlap with the interested fundamental bands. In this paper, the non.overlapping conditions for dual.band and tri.band signals are derived and denoted in the form of closed.form expression. It can be used to verify whether a given dual.band/multi.band signals can be linearized properly by these multi.dimensional behavioral models. Also the conditions can be used to plan the frequency spacing and maximum bandwidth of a multi.band or non.continuous carrier aggregation signal. Several dual.band and triband signals were tested on the same PA, by employing 2.D DPD and 3.D DPD behavioral models. The measurement results show that the signals which don't satisfy the non.overlapping conditions cannot be linearized well by the multi.dimensional behavioral models which does not take the harmonic and intermodulation products of carriers' into account.展开更多
The pathophysiology of tinnitus is poorly understood and treatments are often unsuccessful. A number of animal models have been developed in order to gain a better understanding of tinnitus. A great deal has been lear...The pathophysiology of tinnitus is poorly understood and treatments are often unsuccessful. A number of animal models have been developed in order to gain a better understanding of tinnitus. A great deal has been learned from these models re- garding the electrophysiological and neuroanatomical correlates of tinnitus following exposure to noise or ototoxic drugs. Re- liable behavioral data is important for determining whether such electrophysiological or neuroanatomical changes are indeed related to tinnitus. Of the many documented tinnitus animal behavioral paradigms, the acoustic startle reflex had been pro- posed as a simple method to identify the presence or absence of tinnitus. Several behavioral models based on conditioned re- sponse suppression paradigms have also been developed. In addition to determining the presence or absence of tinnitus, some of the behavioral paradigms have provided signs of the onset, frequency, and intensity of tinnitus in animals. Although none of these behavioral models have been proved to be a perfect model, these studies provide useful information on understanding the neural mechanisms underlying tinnitus.展开更多
Today’s air combat has reached a high level of uncertainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets. With a set of membership functions, fuzzy logic is ...Today’s air combat has reached a high level of uncertainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets. With a set of membership functions, fuzzy logic is well-suited to tackle such complex states and actions. However, it is not necessary to fuzzify the variables that have definite discrete semantics.Hence, the aim of this study is to improve the level of model abstraction by proposing multiple levels of cascaded hierarchical structures from the perspective of function, namely, the functional decision tree. This method is developed to represent behavioral modeling of air combat systems, and its metamodel,execution mechanism, and code generation can provide a sound basis for function-based behavioral modeling. As a proof of concept, an air combat simulation is developed to validate this method and the results show that the fighter Alpha built using the proposed framework provides better performance than that using default scripts.展开更多
Objective Patients who experience knee osteoarthritis or chronic knee pain can alleviate their symptoms by performing self-knee massage.Understanding the readiness and types of determinants needed to facilitate self-k...Objective Patients who experience knee osteoarthritis or chronic knee pain can alleviate their symptoms by performing self-knee massage.Understanding the readiness and types of determinants needed to facilitate self-knee massage is needed to design effective,theory-informed interventions.The primary objective of this study was to apply the transtheoretical model of behavior change to identify how factors,which include the type of knee condition and pain level,predict an individual’s readiness to adopt self-knee massage.The secondary objective employed the capability,opportunity and motivation-behavior(COM-B)model to identify relevant determinants that are predictive of an individual’s readiness to undertake self-knee massage.Methods An observational study design was used to recruit individuals with knee osteoarthritis(n=270)and chronic knee pain(n=130).Participants completed an online survey that assessed the transtheoretical model of behavior change stages,COM-B determinants(capability,opportunity and motivation),along with self-administered massage behavior.Multivariate analysis of covariance and structural equation modeling were used to test the primary and secondary objective,respectively.Results Participants who had knee osteoarthritis scored higher on the action stage compared to those with chronic pain(P=0.003),and those who experienced greater level of pain scored higher in the contemplation(P<0.001)and action phases(P<0.001)of performing knee massage compared to those with milder pain.The COM-B structural equation model revealed self-administered knee massage to be predicted by capability(β=0.31,P=0.004)and motivation(β=0.29,P<0.001),but not opportunity(β=–0.10,P=0.39).Pain level predicted motivation(β=0.27,P<0.001),but not capability(β=0.09,P=0.07)or opportunity(β=0.01,P=0.83).Tests for mediating effects found that determinants of COM-B(motivation and capability)mediate between pain level and self-administered massage behavior(β=0.10,P=0.002).Conclusion Clinicians and researchers can expect that patients diagnosed with knee osteoarthritis or who have chronic knee pain are ready(action stage)or are considering the behavior(contemplation stage)of self-knee massage.Individuals who report having knee osteoarthritis or chronic knee pain should be coached to develop the skills to perform self-knee massage and helped to develop the motivation to carry out the therapy.展开更多
The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achievi...The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.展开更多
A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distri...A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.展开更多
A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the paramet...A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.展开更多
Intraspecific conflict induced by the innate aggressiveness is one of the main reasons for the extremely low survival rate in mud crab Scylla paramamosain aquaculture,which have impeded the sustainable culture of the ...Intraspecific conflict induced by the innate aggressiveness is one of the main reasons for the extremely low survival rate in mud crab Scylla paramamosain aquaculture,which have impeded the sustainable culture of the species.In this study,we first classified and quantified the aggressive behavior,and established a crab aggressive behavior model,laying the foundation for subsequent research on evaluating combat intensity.The contents of 5-hydroxytryptamine(5-HT),dopamine(DA),and cAMP in the hemolymph of the mud crabs before and after fighting were measured by high-performance liquid chromatography-mass spectrometry(HPLC-MS),and the mud crabs exhibited a significant increase of 5-HT(P<0.05),while the DA and cAMP decreased significantly(P<0.05).In addition,we applied EthoVision to examine the changes of the crab behavior after DA administration.After 0.5 h of injection,the movement speed,distance,duration of aggressive behavior,and intensity of aggression in the high concentration DA group were significantly higher than those in the saline injection group and the untreated control group(P<0.05).The results of real-time quantitative polymerase chain reaction(qRT PCR)analysis showed that the expression of DA 1 in the thoracic ganglia of the mud crabs was significantly down-regulated in the DA injection group,and the aggressive behavior was weakened.Conversely,DA1 expression was up-regulated when aggressive behavior was strengthened.Besides,there were significant differences in the expression levels of receptor expression genes including 5-HT1,5-HT2,and crustacean hyperglycemic hormone(CHH)in different tissues,indicating that the alteration of aggressive behavior of the mud crab after injection with different concentrations of DA could be regulated by changes in the expression levels of corresponding receptor genes.Our results contribute to a deeper analysis of the aggressive behavior mechanism of the mud crabs and provide a theoretical basis for reducing fighting-related mortalities in aquaculture.展开更多
This study focuses on the elderly population in Xueyuan Road Street of Haidian District in Beijing.Through KANO questionnaires and the theory of attractive quality,it investigates the demand levels and degrees for dif...This study focuses on the elderly population in Xueyuan Road Street of Haidian District in Beijing.Through KANO questionnaires and the theory of attractive quality,it investigates the demand levels and degrees for different community elderly care services.It introduces the Anderson behavioral model to analyze the influencing factors,categorizes different demographics,and examines the needs of elderly individuals with varying characteristics,proposing suggestions for the improvement of future community elderly care service facilities.展开更多
Introduction:Having a primary care usual source of care(USC)is associated with better population health outcomes.However,the percent of adults in the United States(US)with a usual primary care provider is declining.We...Introduction:Having a primary care usual source of care(USC)is associated with better population health outcomes.However,the percent of adults in the United States(US)with a usual primary care provider is declining.We sought to identify factors associated with establishing a USC at an urgent care clinic or emergency department as opposed to primary care.Methods:We analyzed data from 57,152 participants in the All of Us study who reported having a USC.We used the Andersen Behavioral Model of Health Services Use framework and multivariable logistic regression to examine associations among predisposing,enabling,and need factors,according to the source of usual care.Results:An urgent care clinic,minute clinic,or emergency department was the source of usual care for 6.3%of our sample.The odds of seeking care at this type of facility increased with younger age,lower educational attainment,and better health status.Black and Hispanic individuals,as well as those who reported experiencing discrimination in medical settings or that their provider was of a different race and ethnicity,were also less likely to have a primary care USC.Financial concerns,being anxious about seeing a provider,and the inability to take time off from work also increased the likelihood of having a non‐primary care USC.Conclusions:Improving the rates of having a primary care USC among younger and healthy adults may be achievable through policies that can improve access to convenient,affordable primary care.Efforts to improve diversity among primary care providers and reduce discrimination experienced by patients may also improve the USC rates for racial and ethnic minority groups.展开更多
Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of ...Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of TC4 tubes considering the couple effects of temperature,strain rate and strain is critical for understanding the deformation behavior of metals and optimizing the processing parameters in warm rotary draw bending of TC4 tubes. In this study, isothermal compression tests of TC4 tube alloy were performed from 573 to 873 K with an interval of 100 K and strain rates of 0.001, 0.010 and0.100 s^（-1）. The prediction of flow behavior was done using two constitutive models, namely modified Arrhenius model and artificial neural network（ANN） model. The predictions of these constitutive models were compared using statistical measures like correlation coefficient（R）, average absolute relative error（AARE） and its variation with the deformation parameters（temperature, strain rate and strain）. Analysis of statistical measures reveals that the two models show high predicted accuracy in terms of R and AARE. Comparatively speaking, the ANN model presents higher predicted accuracy than the modified Arrhenius model. In addition, the predicted accuracy of ANN model presents high stability at the whole deformation parameter ranges, whereas the predictability of the modified Arrhenius model has some fluctuation at different deformation conditions. It presents higher predicted accuracy at temperatures of 573-773 K, strain rates of 0.010-0.100 s^（-1）and strain of 0.04-0.32, while low accuracy at temperature of 873 K, strain rates of 0.001 s^（-1）and strain of 0.36-0.48.Thus, the application of modified Arrhenius model is limited by its relatively low predicted accuracy at some deformation conditions, while the ANN model presents very high predicted accuracy at all deformation conditions,which can be used to study the compression behavior of TC4 tube at the temperature range of 573-873 K and the strain rate of 0.001-0.100 s^（-1）. It can provide guideline for the design of processing parameters in warm rotary draw bending of LDTW TC4 tubes.展开更多
The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specifi...The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specific data converter simulation environment has been developed which allows designers to perform time-domain behavioral simulations of pipelined analog to digital converters （ADCs）. All the necessary blocks of this specific simulation environment have been implemented using the popular Matlab simulink environment. The purpose of this paper is to present the behavioral models of these blocks taking into account most of the pipelined ADC non-idealities, such as sampling jitter, noise, and operational amplifier parameters （white noise, finite DC gain, finite bandwidth, slew rate, and saturation voltages）. Simulations, using a 10-bit pipelined ADC as a design example, show that in addition to the limits analysis and the electrical features extraction, designers can determine the specifications of the basic blocks in order to meet the given data converter requirements.展开更多
Checking if the implementations conform to the requirement models is challenging. Most existing techniques for consistency checking either focus on requirement models（e.g., requirements consistency checking）, or on ...Checking if the implementations conform to the requirement models is challenging. Most existing techniques for consistency checking either focus on requirement models（e.g., requirements consistency checking）, or on the implementations（e.g., code-based testing） only. In this paper we propose an approach to checking behavioral consistency of implementations against requirement models directly to overcome these limitations. Our approach extracts two behavioral models represented by Labelled Transition Systems（LTS） from requirement models and implementations respectively, and checks the behavioral consistency between these two models based on behavioral simulation relation of LTS. The checking results of our approach provide evidence for behavioral inconsistency as well as inconsistent localization. A research prototype called BCCH and a case study are presented to give initial validation of this approach.展开更多
An envelope domain multislice behavioral modeling is introduced. The tradition AM-AM and AM- PM characteristics of power amplifiers axe extended to envelope domain and base-band filter is applied to distortion complex...An envelope domain multislice behavioral modeling is introduced. The tradition AM-AM and AM- PM characteristics of power amplifiers axe extended to envelope domain and base-band filter is applied to distortion complex envelope signal for description of the envelope memory effect. Using traditional one and two-tone tests, the coefficients of nonlinear model and the FIR filter can be extracted. At last the model has been applied to a 10 W WCDMA Power amplifier to predict its output signal. And simulation results show that the model output conforms very well to the traditional transistor level simulation results.展开更多
Voherra series behavioral model for radio frequency （RF） power amplifier （PA） has been widely used in system-level simulation, however, high computational complexity makes this kind of model limited to ＂weak＂ no...Voherra series behavioral model for radio frequency （RF） power amplifier （PA） has been widely used in system-level simulation, however, high computational complexity makes this kind of model limited to ＂weak＂ nonlinearity. In order to reduce the computational complexity and the number of coefficients of Volterra series kernels, a Volterra series improved behavioral model based on Laguerre orthogonal polynomials function, namely Voherra-Laguerre behavioral model, is proposed. Mathematical expressions of Volterra-Laguerre behavioral model is derived, and accuracy of the model is verified through comparison of measured and simulation output data from a freescale PA using MRF21030 transistor. Mathematical analysis and simulation results show that Voherra-Laguerre behavioral model has a simple structure, much less coefficients and better modeling performance than general Volterra series model. The model can be used more correctly for system-level simulation of RF PA with wideband signal.展开更多
With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recogn...With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets.展开更多
Atomic switches can be used in future nanodevices and to realize conceptually novel electronics in new types of computer architecture because of their simple structure, ease of operation, stability, and reliability. T...Atomic switches can be used in future nanodevices and to realize conceptually novel electronics in new types of computer architecture because of their simple structure, ease of operation, stability, and reliability. The atomic switch is a single solid-state switch with inherent learning abilities that exhibits various nonlinear behaviors with network devices. However, previous studies focused on experiments and nonvolatile memory applications, and studies on the application of the physical properties of the atomic switch in computing were nonexistent. Therefore, we present a simple behavioral model of a molecular gap-type atomic switch that can be included in a simulator. The model was described by three simple equations that reproduced the bistability using a double-well potential and was able to easily be transferred to a simulator using arbitrary numerical values and be integrated into HSPICE. Simulations using the experimental parameters of the proposed atomic switch agreed with the experimental results. This model will allow circuit designers to explore new architectures, contributing to the development of new computing methods.展开更多
The human factors and their interaction with other factors play an important role in the flight safety of transport aircraft.In this paper,a paradigm of risk assessment for transport aircraft interacting with piloting...The human factors and their interaction with other factors play an important role in the flight safety of transport aircraft.In this paper,a paradigm of risk assessment for transport aircraft interacting with piloting behaviors is proposed,with focus on landing which is the most accident-prone flight stage in aviation safety statistics.Model-based flight simulation serves as our data source for landing risk analysis under uncertainties.A digital pilot in the loop that reflects the human piloting behaviors is employed to facilitate simulation efficiency.Eight types of unsafe events in landing are identified from statistics.On this basis,the landing safety boundary is extracted via stochastic simulation to divide safety and hazardous flight status domains,which con-tributes to flight status management and risk warning.The simulation results indicate that appro-priate piloting behavior,which is active response and fast target acquisition with minimum overshoot and fluctuation,shows benefit to landing safety.The subset simulation technique is employed to further refine the boundary with less computational workload.Furthermore,the effect of airspeed,windspeed,and other factors on landing risk is also discussed.The proposed risk assess-ment method would help optimize operation procedure and develop targeted pilot training program.展开更多
Anticipating others’actions is innate and essential in order for humans to navigate and interact well with others in dense crowds.This ability is urgently required for unmanned systems such as service robots and self...Anticipating others’actions is innate and essential in order for humans to navigate and interact well with others in dense crowds.This ability is urgently required for unmanned systems such as service robots and self-driving cars.However,existing solutions struggle to predict pedestrian anticipation accurately,because the influence of group-related social behaviors has not been well considered.While group relationships and group interactions are ubiquitous and significantly influence pedestrian anticipation,their influence is diverse and subtle,making it difficult to explicitly quantify.Here,we propose the group interaction field(GIF),a novel group-aware representation that quantifies pedestrian anticipation into a probability field of pedestrians’future locations and attention orientations.An end-to-end neural network,GIFNet,is tailored to estimate the GIF from explicit multidimensional observations.GIFNet quantifies the influence of group behaviors by formulating a group interaction graph with propagation and graph attention that is adaptive to the group size and dynamic interaction states.The experimental results show that the GIF effectively represents the change in pedestrians’anticipation under the prominent impact of group behaviors and accurately predicts pedestrians’future states.Moreover,the GIF contributes to explaining various predictions of pedestrians’behavior in different social states.The proposed GIF will eventually be able to allow unmanned systems to work in a human-like manner and comply with social norms,thereby promoting harmonious human-machine relationships.展开更多
Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Mean...Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.展开更多
基金supported by National Key Basic Research Program of China (973 Program) (No.2014CB339900)the National High Technology Research and Development Program of China (863 Program) (No. 2015AA016801)National Natural Science Foundations of China (No.61327806)
文摘To linearize the multi.band PAs/transmitters, a serial of multi.band predistortion models based on multi.dimensional architecture have been proposed. However, most of these models work properly only for the signals whose harmonic and intermodulation products of carriers' non.overlap with the interested fundamental bands. In this paper, the non.overlapping conditions for dual.band and tri.band signals are derived and denoted in the form of closed.form expression. It can be used to verify whether a given dual.band/multi.band signals can be linearized properly by these multi.dimensional behavioral models. Also the conditions can be used to plan the frequency spacing and maximum bandwidth of a multi.band or non.continuous carrier aggregation signal. Several dual.band and triband signals were tested on the same PA, by employing 2.D DPD and 3.D DPD behavioral models. The measurement results show that the signals which don't satisfy the non.overlapping conditions cannot be linearized well by the multi.dimensional behavioral models which does not take the harmonic and intermodulation products of carriers' into account.
基金supported by the grants of the National Key Basic Research Program of China,No.2014CB943001the National Natural Science Foundation of China,Major Project,No.81120108009
文摘The pathophysiology of tinnitus is poorly understood and treatments are often unsuccessful. A number of animal models have been developed in order to gain a better understanding of tinnitus. A great deal has been learned from these models re- garding the electrophysiological and neuroanatomical correlates of tinnitus following exposure to noise or ototoxic drugs. Re- liable behavioral data is important for determining whether such electrophysiological or neuroanatomical changes are indeed related to tinnitus. Of the many documented tinnitus animal behavioral paradigms, the acoustic startle reflex had been pro- posed as a simple method to identify the presence or absence of tinnitus. Several behavioral models based on conditioned re- sponse suppression paradigms have also been developed. In addition to determining the presence or absence of tinnitus, some of the behavioral paradigms have provided signs of the onset, frequency, and intensity of tinnitus in animals. Although none of these behavioral models have been proved to be a perfect model, these studies provide useful information on understanding the neural mechanisms underlying tinnitus.
基金This work was supported by the National Natural Science Foundation of China(62003359).
文摘Today’s air combat has reached a high level of uncertainty where continuous or discrete variables with crisp values cannot be properly represented using fuzzy sets. With a set of membership functions, fuzzy logic is well-suited to tackle such complex states and actions. However, it is not necessary to fuzzify the variables that have definite discrete semantics.Hence, the aim of this study is to improve the level of model abstraction by proposing multiple levels of cascaded hierarchical structures from the perspective of function, namely, the functional decision tree. This method is developed to represent behavioral modeling of air combat systems, and its metamodel,execution mechanism, and code generation can provide a sound basis for function-based behavioral modeling. As a proof of concept, an air combat simulation is developed to validate this method and the results show that the fighter Alpha built using the proposed framework provides better performance than that using default scripts.
基金supported by Dr.Navin Kaushal's lab start-up funding from the School of Health and Human Sciences at Indiana University,Indianapolis.
文摘Objective Patients who experience knee osteoarthritis or chronic knee pain can alleviate their symptoms by performing self-knee massage.Understanding the readiness and types of determinants needed to facilitate self-knee massage is needed to design effective,theory-informed interventions.The primary objective of this study was to apply the transtheoretical model of behavior change to identify how factors,which include the type of knee condition and pain level,predict an individual’s readiness to adopt self-knee massage.The secondary objective employed the capability,opportunity and motivation-behavior(COM-B)model to identify relevant determinants that are predictive of an individual’s readiness to undertake self-knee massage.Methods An observational study design was used to recruit individuals with knee osteoarthritis(n=270)and chronic knee pain(n=130).Participants completed an online survey that assessed the transtheoretical model of behavior change stages,COM-B determinants(capability,opportunity and motivation),along with self-administered massage behavior.Multivariate analysis of covariance and structural equation modeling were used to test the primary and secondary objective,respectively.Results Participants who had knee osteoarthritis scored higher on the action stage compared to those with chronic pain(P=0.003),and those who experienced greater level of pain scored higher in the contemplation(P<0.001)and action phases(P<0.001)of performing knee massage compared to those with milder pain.The COM-B structural equation model revealed self-administered knee massage to be predicted by capability(β=0.31,P=0.004)and motivation(β=0.29,P<0.001),but not opportunity(β=–0.10,P=0.39).Pain level predicted motivation(β=0.27,P<0.001),but not capability(β=0.09,P=0.07)or opportunity(β=0.01,P=0.83).Tests for mediating effects found that determinants of COM-B(motivation and capability)mediate between pain level and self-administered massage behavior(β=0.10,P=0.002).Conclusion Clinicians and researchers can expect that patients diagnosed with knee osteoarthritis or who have chronic knee pain are ready(action stage)or are considering the behavior(contemplation stage)of self-knee massage.Individuals who report having knee osteoarthritis or chronic knee pain should be coached to develop the skills to perform self-knee massage and helped to develop the motivation to carry out the therapy.
文摘The rapid advent in artificial intelligence and big data has revolutionized the dynamic requirement in the demands of the computing resource for executing specific tasks in the cloud environment.The process of achieving autonomic resource management is identified to be a herculean task due to its huge distributed and heterogeneous environment.Moreover,the cloud network needs to provide autonomic resource management and deliver potential services to the clients by complying with the requirements of Quality-of-Service(QoS)without impacting the Service Level Agreements(SLAs).However,the existing autonomic cloud resource managing frameworks are not capable in handling the resources of the cloud with its dynamic requirements.In this paper,Coot Bird Behavior Model-based Workload Aware Autonomic Resource Management Scheme(CBBM-WARMS)is proposed for handling the dynamic requirements of cloud resources through the estimation of workload that need to be policed by the cloud environment.This CBBM-WARMS initially adopted the algorithm of adaptive density peak clustering for workloads clustering of the cloud.Then,it utilized the fuzzy logic during the process of workload scheduling for achieving the determining the availability of cloud resources.It further used CBBM for potential Virtual Machine(VM)deployment that attributes towards the provision of optimal resources.It is proposed with the capability of achieving optimal QoS with minimized time,energy consumption,SLA cost and SLA violation.The experimental validation of the proposed CBBMWARMS confirms minimized SLA cost of 19.21%and reduced SLA violation rate of 18.74%,better than the compared autonomic cloud resource managing frameworks.
文摘A wavelet collocation method with nonlinear auto companding is proposed for behavioral modeling of switched current circuits.The companding function is automatically constructed according to the initial error distribution obtained through approximating the input output function of the SI circuit by conventional wavelet collocation method.In practical applications,the proposed method is a general purpose approach,by which both the small signal effect and the large signal effect are modeled in a unified formulation to ease the process of modeling and simulation.Compared with the published modeling approaches,the proposed nonlinear auto companding method works more efficiently not only in controlling the error distribution but also in reducing the modeling errors.To demonstrate the promising features of the proposed method,several SI circuits are employed as examples to be modeled and simulated.
基金The National Natural Science Foundation of China(No.60621002)the National High Technology Research and Development Pro-gram of China(863 Program)(No.2007AA01Z2B4).
文摘A novel behavioral model using three-layer time-delay feed-forward neural networks （TDFFNN）is adopted to model radio frequency （RF）power amplifiers exhibiting memory nonlinearities. In order to extract the parameters, the back- propagation algorithm is applied to train the proposed neural networks. The proposed model is verified by the typical odd- order-only memory polynomial model in simulation, and the performance is compared with different numbers of taped delay lines（TDLs） and perceptrons of the hidden layer. For validating the TDFFNN model by experiments, a digital test bench is set up to collect input and output data of power amplifiers at a 60 × 10^6 sample/s sampling rate. The 3.75 MHz 16-QAM signal generated in the vector signal generator（VSG） is chosen as the input signal, when measuring the dynamic AM/AM and AM/PM characteristics of power amplifiers. By comparisons and analyses, the presented model provides a good performance in convergence, accuracy and efficiency, which is approved by simulation results and experimental results in the time domain and frequency domain.
基金Supported by the National Key R&D Program of China(No.2023YFD2401005)the Key R&D Program of Ningbo(No.2022Z059)the K.C.Wong Magna Fund of Ningbo University。
文摘Intraspecific conflict induced by the innate aggressiveness is one of the main reasons for the extremely low survival rate in mud crab Scylla paramamosain aquaculture,which have impeded the sustainable culture of the species.In this study,we first classified and quantified the aggressive behavior,and established a crab aggressive behavior model,laying the foundation for subsequent research on evaluating combat intensity.The contents of 5-hydroxytryptamine(5-HT),dopamine(DA),and cAMP in the hemolymph of the mud crabs before and after fighting were measured by high-performance liquid chromatography-mass spectrometry(HPLC-MS),and the mud crabs exhibited a significant increase of 5-HT(P<0.05),while the DA and cAMP decreased significantly(P<0.05).In addition,we applied EthoVision to examine the changes of the crab behavior after DA administration.After 0.5 h of injection,the movement speed,distance,duration of aggressive behavior,and intensity of aggression in the high concentration DA group were significantly higher than those in the saline injection group and the untreated control group(P<0.05).The results of real-time quantitative polymerase chain reaction(qRT PCR)analysis showed that the expression of DA 1 in the thoracic ganglia of the mud crabs was significantly down-regulated in the DA injection group,and the aggressive behavior was weakened.Conversely,DA1 expression was up-regulated when aggressive behavior was strengthened.Besides,there were significant differences in the expression levels of receptor expression genes including 5-HT1,5-HT2,and crustacean hyperglycemic hormone(CHH)in different tissues,indicating that the alteration of aggressive behavior of the mud crab after injection with different concentrations of DA could be regulated by changes in the expression levels of corresponding receptor genes.Our results contribute to a deeper analysis of the aggressive behavior mechanism of the mud crabs and provide a theoretical basis for reducing fighting-related mortalities in aquaculture.
文摘This study focuses on the elderly population in Xueyuan Road Street of Haidian District in Beijing.Through KANO questionnaires and the theory of attractive quality,it investigates the demand levels and degrees for different community elderly care services.It introduces the Anderson behavioral model to analyze the influencing factors,categorizes different demographics,and examines the needs of elderly individuals with varying characteristics,proposing suggestions for the improvement of future community elderly care service facilities.
文摘Introduction:Having a primary care usual source of care(USC)is associated with better population health outcomes.However,the percent of adults in the United States(US)with a usual primary care provider is declining.We sought to identify factors associated with establishing a USC at an urgent care clinic or emergency department as opposed to primary care.Methods:We analyzed data from 57,152 participants in the All of Us study who reported having a USC.We used the Andersen Behavioral Model of Health Services Use framework and multivariable logistic regression to examine associations among predisposing,enabling,and need factors,according to the source of usual care.Results:An urgent care clinic,minute clinic,or emergency department was the source of usual care for 6.3%of our sample.The odds of seeking care at this type of facility increased with younger age,lower educational attainment,and better health status.Black and Hispanic individuals,as well as those who reported experiencing discrimination in medical settings or that their provider was of a different race and ethnicity,were also less likely to have a primary care USC.Financial concerns,being anxious about seeing a provider,and the inability to take time off from work also increased the likelihood of having a non‐primary care USC.Conclusions:Improving the rates of having a primary care USC among younger and healthy adults may be achievable through policies that can improve access to convenient,affordable primary care.Efforts to improve diversity among primary care providers and reduce discrimination experienced by patients may also improve the USC rates for racial and ethnic minority groups.
基金financially supported by the National Natural Science Foundation of China(Nos.51275415 and50905144)the Natural Science Basic Research Plan in Shanxi Province(No.2011JQ6004)the Program of the Ministry of Education of China for Introducing Talents of Discipline to Universities(No.B08040)
文摘Warm rotary draw bending provides a feasible method to form the large-diameter thin-walled（LDTW）TC4 bent tubes, which are widely used in the pneumatic system of aircrafts. An accurate prediction of flow behavior of TC4 tubes considering the couple effects of temperature,strain rate and strain is critical for understanding the deformation behavior of metals and optimizing the processing parameters in warm rotary draw bending of TC4 tubes. In this study, isothermal compression tests of TC4 tube alloy were performed from 573 to 873 K with an interval of 100 K and strain rates of 0.001, 0.010 and0.100 s^（-1）. The prediction of flow behavior was done using two constitutive models, namely modified Arrhenius model and artificial neural network（ANN） model. The predictions of these constitutive models were compared using statistical measures like correlation coefficient（R）, average absolute relative error（AARE） and its variation with the deformation parameters（temperature, strain rate and strain）. Analysis of statistical measures reveals that the two models show high predicted accuracy in terms of R and AARE. Comparatively speaking, the ANN model presents higher predicted accuracy than the modified Arrhenius model. In addition, the predicted accuracy of ANN model presents high stability at the whole deformation parameter ranges, whereas the predictability of the modified Arrhenius model has some fluctuation at different deformation conditions. It presents higher predicted accuracy at temperatures of 573-773 K, strain rates of 0.010-0.100 s^（-1）and strain of 0.04-0.32, while low accuracy at temperature of 873 K, strain rates of 0.001 s^（-1）and strain of 0.36-0.48.Thus, the application of modified Arrhenius model is limited by its relatively low predicted accuracy at some deformation conditions, while the ANN model presents very high predicted accuracy at all deformation conditions,which can be used to study the compression behavior of TC4 tube at the temperature range of 573-873 K and the strain rate of 0.001-0.100 s^（-1）. It can provide guideline for the design of processing parameters in warm rotary draw bending of LDTW TC4 tubes.
文摘The increasing architecture complexity of data converters makes it necessary to use behavioral models to simulate their electrical performance and to determine their relevant data features. For this purpose, a specific data converter simulation environment has been developed which allows designers to perform time-domain behavioral simulations of pipelined analog to digital converters （ADCs）. All the necessary blocks of this specific simulation environment have been implemented using the popular Matlab simulink environment. The purpose of this paper is to present the behavioral models of these blocks taking into account most of the pipelined ADC non-idealities, such as sampling jitter, noise, and operational amplifier parameters （white noise, finite DC gain, finite bandwidth, slew rate, and saturation voltages）. Simulations, using a 10-bit pipelined ADC as a design example, show that in addition to the limits analysis and the electrical features extraction, designers can determine the specifications of the basic blocks in order to meet the given data converter requirements.
基金Supported by the National Natural Science Foundation of China(91118003,61003071)the Fundamental Research Funds for the Central Universities(3101046,201121102020006)the Special Funds for Shenzhen Strategic New Industry Development(JCYJ20120616135936123)
文摘Checking if the implementations conform to the requirement models is challenging. Most existing techniques for consistency checking either focus on requirement models（e.g., requirements consistency checking）, or on the implementations（e.g., code-based testing） only. In this paper we propose an approach to checking behavioral consistency of implementations against requirement models directly to overcome these limitations. Our approach extracts two behavioral models represented by Labelled Transition Systems（LTS） from requirement models and implementations respectively, and checks the behavioral consistency between these two models based on behavioral simulation relation of LTS. The checking results of our approach provide evidence for behavioral inconsistency as well as inconsistent localization. A research prototype called BCCH and a case study are presented to give initial validation of this approach.
文摘An envelope domain multislice behavioral modeling is introduced. The tradition AM-AM and AM- PM characteristics of power amplifiers axe extended to envelope domain and base-band filter is applied to distortion complex envelope signal for description of the envelope memory effect. Using traditional one and two-tone tests, the coefficients of nonlinear model and the FIR filter can be extracted. At last the model has been applied to a 10 W WCDMA Power amplifier to predict its output signal. And simulation results show that the model output conforms very well to the traditional transistor level simulation results.
基金Supported by the National Natural Science Foundation of China （No. 60573111 ）
文摘Voherra series behavioral model for radio frequency （RF） power amplifier （PA） has been widely used in system-level simulation, however, high computational complexity makes this kind of model limited to ＂weak＂ nonlinearity. In order to reduce the computational complexity and the number of coefficients of Volterra series kernels, a Volterra series improved behavioral model based on Laguerre orthogonal polynomials function, namely Voherra-Laguerre behavioral model, is proposed. Mathematical expressions of Volterra-Laguerre behavioral model is derived, and accuracy of the model is verified through comparison of measured and simulation output data from a freescale PA using MRF21030 transistor. Mathematical analysis and simulation results show that Voherra-Laguerre behavioral model has a simple structure, much less coefficients and better modeling performance than general Volterra series model. The model can be used more correctly for system-level simulation of RF PA with wideband signal.
文摘With the rapid growth of complexity and functionality of modern electronic systems, creating precise behavioral models of nonlinear circuits has become an attractive topic. Deep neural networks (DNNs) have been recognized as a powerful tool for nonlinear system modeling. To characterize the behavior of nonlinear circuits, a DNN based modeling approach is proposed in this paper. The procedure is illustrated by modeling a power amplifier (PA), which is a typical nonlinear circuit in electronic systems. The PA model is constructed based on a feedforward neural network with three hidden layers, and then Multisim circuit simulator is applied to generating the raw training data. Training and validation are carried out in Tensorflow deep learning framework. Compared with the commonly used polynomial model, the proposed DNN model exhibits a faster convergence rate and improves the mean squared error by 13 dB. The results demonstrate that the proposed DNN model can accurately depict the input-output characteristics of nonlinear circuits in both training and validation data sets.
文摘Atomic switches can be used in future nanodevices and to realize conceptually novel electronics in new types of computer architecture because of their simple structure, ease of operation, stability, and reliability. The atomic switch is a single solid-state switch with inherent learning abilities that exhibits various nonlinear behaviors with network devices. However, previous studies focused on experiments and nonvolatile memory applications, and studies on the application of the physical properties of the atomic switch in computing were nonexistent. Therefore, we present a simple behavioral model of a molecular gap-type atomic switch that can be included in a simulator. The model was described by three simple equations that reproduced the bistability using a double-well potential and was able to easily be transferred to a simulator using arbitrary numerical values and be integrated into HSPICE. Simulations using the experimental parameters of the proposed atomic switch agreed with the experimental results. This model will allow circuit designers to explore new architectures, contributing to the development of new computing methods.
基金supported by the Airworthiness Technology Research Center of Beihang University,China.
文摘The human factors and their interaction with other factors play an important role in the flight safety of transport aircraft.In this paper,a paradigm of risk assessment for transport aircraft interacting with piloting behaviors is proposed,with focus on landing which is the most accident-prone flight stage in aviation safety statistics.Model-based flight simulation serves as our data source for landing risk analysis under uncertainties.A digital pilot in the loop that reflects the human piloting behaviors is employed to facilitate simulation efficiency.Eight types of unsafe events in landing are identified from statistics.On this basis,the landing safety boundary is extracted via stochastic simulation to divide safety and hazardous flight status domains,which con-tributes to flight status management and risk warning.The simulation results indicate that appro-priate piloting behavior,which is active response and fast target acquisition with minimum overshoot and fluctuation,shows benefit to landing safety.The subset simulation technique is employed to further refine the boundary with less computational workload.Furthermore,the effect of airspeed,windspeed,and other factors on landing risk is also discussed.The proposed risk assess-ment method would help optimize operation procedure and develop targeted pilot training program.
基金supported in part by the National Natural Science Foundation of China (NSFC,62125106,61860206003,and 62088102)in part by the Ministry of Science and Technology of China (2021ZD0109901)in part by the Provincial Key Research and Development Program of Zhejiang (2021C01016).
文摘Anticipating others’actions is innate and essential in order for humans to navigate and interact well with others in dense crowds.This ability is urgently required for unmanned systems such as service robots and self-driving cars.However,existing solutions struggle to predict pedestrian anticipation accurately,because the influence of group-related social behaviors has not been well considered.While group relationships and group interactions are ubiquitous and significantly influence pedestrian anticipation,their influence is diverse and subtle,making it difficult to explicitly quantify.Here,we propose the group interaction field(GIF),a novel group-aware representation that quantifies pedestrian anticipation into a probability field of pedestrians’future locations and attention orientations.An end-to-end neural network,GIFNet,is tailored to estimate the GIF from explicit multidimensional observations.GIFNet quantifies the influence of group behaviors by formulating a group interaction graph with propagation and graph attention that is adaptive to the group size and dynamic interaction states.The experimental results show that the GIF effectively represents the change in pedestrians’anticipation under the prominent impact of group behaviors and accurately predicts pedestrians’future states.Moreover,the GIF contributes to explaining various predictions of pedestrians’behavior in different social states.The proposed GIF will eventually be able to allow unmanned systems to work in a human-like manner and comply with social norms,thereby promoting harmonious human-machine relationships.
文摘Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic control.However,existing research ignores the impact of users’irrationality on decision-making in the epidemic.Meanwhile,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual situation.To address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic dynamics.According to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is high.Then,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of disease.Simulations and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.
