In order to solve the problem that the drivers can't find the optimal parking lot timely,a reservation based optimal parking lot recommendation model in Internet of Vehicle(IoV) environment is designed.Based on th...In order to solve the problem that the drivers can't find the optimal parking lot timely,a reservation based optimal parking lot recommendation model in Internet of Vehicle(IoV) environment is designed.Based on the users oriented parking information recommendation system,the model considers subjective demands of drivers comprehensively,makes a deeply analysis of the evaluation indicators.This recommendation model uses a phased selection method to calculate the optimal objective parking lot.The first stage is screening which based on the users' subjective parking demands;the second stage is processing the candidate parking lots through multiple attribute decision making.Simulation experiments show that this model can effectively solve the problems encountered in the process of finding optimal parking lot,save the driver's parking time and parking costs and also improve the overall utilization of parking facilities to ease the traffic congestion caused by vehicles parked patrol.展开更多
At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an experiment.The user load is therefore increased,and the learning efficiency of the stude...At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an experiment.The user load is therefore increased,and the learning efficiency of the students is decreased.To solve the problem of insufficient system interactivity and guidance,an experimental navigation system based on multi-mode fusion is proposed in this paper.The system first obtains user information by sensing the hardware devices,intelligently perceives the user intention and progress of the experiment according to the information acquired,and finally carries out a multi-modal intelligent navigation process for users.As an innovative aspect of this study,an intelligent multi-mode navigation system is used to guide users in conducting experiments,thereby reducing the user load and enabling the users to effectively complete their experiments.The results prove that this system can guide users in completing their experiments,and can effectively reduce the user load during the interaction process and improve the efficiency.展开更多
Background At present,the teaching of experiments in primary and secondary schools is affected by cost and security factors.Existing research on virtual experiment platforms has alleviated these problems.However,the l...Background At present,the teaching of experiments in primary and secondary schools is affected by cost and security factors.Existing research on virtual experiment platforms has alleviated these problems.However,the lack of real experimental equipment and use of a single channel to understand user intentions weaken these platforms operationally and degrade the naturalness of interactions.Methods To solve these problems,we propose an intelligent experimental container structure and a situational awareness algorithm,both of which are verified and applied to a chemical experiment involving virtual-real fusion.First,the acquired images are denoised in the visual channel using the maximum diffuse reflection chroma to remove overexposure.Second,container situational awareness is realized by segmenting the image liquid level and establishing a relation-fitting model.Then,strategies for constructing complete behaviors and making priority comparisons among behaviors are adopted for information complementarity and independence,respectively.A multichannel intentional understanding model and an inter-active paradigm that integrates vision,hearing,and touch are proposed.Results The experimental results show that the accuracy of the intelligent container situation awareness proposed in this paper reaches 99%,and the accuracy of the proposed intention understanding algorithm reaches 94.7%.The test shows that the intelligent experimental system based on the new interaction paradigm also has better performance and a more realistic sense of operation experience in terms of experimental efficiency.Conclusion The results indicate that the proposed experimental container and algorithm can achieve a natural level of human-computer interaction in a virtual chemical experiment platform,enhance the user′s sense of operation,and achieve high levels of user satisfaction.展开更多
Natural, efficient, intelligent, and barrier-free HCI （Human-Computer Interface） will be the main developing direction of the new intelligent HCI. Building an intelligent, natural, harmonious and humanistic HCI has ...Natural, efficient, intelligent, and barrier-free HCI （Human-Computer Interface） will be the main developing direction of the new intelligent HCI. Building an intelligent, natural, harmonious and humanistic HCI has been the primary developing tendency of the new HCI. ＂Select one from many＂ is one of the key questions in researching and designing HCI based on gestures. On the sin- gle channel interactive condition which is based on 3D gesture operation, we build a interactive model of＂Select one from many＂. Combining this model with ＂Token＂ technology and reciprocating movement feature, we present and realize a simple efficient ＂Se- lect one from many＂ algorithm, which is used in a concrete SOR （Selection-Operation-Release） system. In the SOR system, we real- ize a real-time selection, tracking and interaction of natural gestures.展开更多
Optoelectronic materials are essential for today's scientific and technological development,and machine learning provides new ideas and tools for their research.In this paper,we first summarize the development his...Optoelectronic materials are essential for today's scientific and technological development,and machine learning provides new ideas and tools for their research.In this paper,we first summarize the development history of optoelectronic materials and how materials informatics drives the innovation and progress of optoelectronic materials and devices.Then,we introduce the development of machine learning and its general process in optoelectronic materials and describe the specific implementation methods.We focus on the cases of machine learning in several application scenarios of optoelectronic materials and devices,including the methods related to crystal structure,properties(defects,electronic structure)research,materials and devices optimization,material characterization,and process optimization.In summarizing the algorithms and feature representations used in different studies,it is noted that prior knowledge can improve optoelectronic materials design,research,and decision-making processes.Finally,the prospect of machine learning applications in optoelectronic materials is discussed,along with current challenges and future directions.This paper comprehensively describes the application value of machine learning in optoelectronic materials research and aims to provide reference and guidance for the continuous development of this field.展开更多
Background Robot grasping encompasses a wide range of research areas;however, most studies have been focused on the grasping of only stationary objects in a scene;only a few studies on how to grasp objects from a user...Background Robot grasping encompasses a wide range of research areas;however, most studies have been focused on the grasping of only stationary objects in a scene;only a few studies on how to grasp objects from a user's hand have been conducted. In this paper, a robot grasping algorithm based on deep reinforcement learning (RGRL) is proposed. Methods The RGRL takes the relative positions of the robot and the object in a user's hand as input and outputs the best action of the robot in the current state. Thus, the proposed algorithm realizes the functions of autonomous path planning and grasping objects safely from the hands of users. A new method for improving the safety of human-robot cooperation is explored. To solve the problems of a low utilization rate and slow convergence of reinforcement learning algorithms, the RGRL is first trained in a simulation scene, and then, the model para-meters are applied to a real scene. To reduce the difference between the simulated and real scenes, domain randomization is applied to randomly change the positions and angles of objects in the simulated scenes at regular intervals, thereby improving the diversity of the training samples and robustness of the algorithm. Results The RGRL's effectiveness and accuracy are verified by evaluating it on both simulated and real scenes, and the results show that the RGRL can achieve an accuracy of more than 80% in both cases. Conclusions RGRL is a robot grasping algorithm that employs domain randomization and deep reinforcement learning for effective grasping in simulated and real scenes. However, it lacks flexibility in adapting to different grasping poses, prompting future research in achieving safe grasping for diverse user postures.展开更多
This paper introduces the application of data mining technology in data service. Data mining is a new technology, but its application time is long, and the application effect is obvious. Data mining technology can be ...This paper introduces the application of data mining technology in data service. Data mining is a new technology, but its application time is long, and the application effect is obvious. Data mining technology can be used in enterprise customer service system, which can help enterprises to find potential customers, while retaining the most valuable customers. We pointed out the necessity of establishing data mining technology and service intelligence analysis system based on the combination of intelligence analysis and service characteristics and processes, the method of data mining, knowledge management ideas applied to intelligence analysis and service system.展开更多
In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and ca...In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.展开更多
Anonymity is a very important security objective in network communications.Recently,Pang et al.proposed a novel multirecipient signcryption scheme with complete anonymity and claimed that the new concrete scheme was s...Anonymity is a very important security objective in network communications.Recently,Pang et al.proposed a novel multirecipient signcryption scheme with complete anonymity and claimed that the new concrete scheme was strong existential unforgeability under selective multi-ID,chosen message attack.Unfortunately,by giving concrete attacks,named " inside attack" and " outside attack" respectively,we indicate that Pang et al.'s scheme is not secure in their security model.展开更多
Wearable sensors have been rapidly developed for application in various human monitoring systems.However,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics ...Wearable sensors have been rapidly developed for application in various human monitoring systems.However,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be stud-ied.Herein,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating effects.The multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber electrode.Due to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 kPa-1.Moreover,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the skin.During warming,this material yields a higher temperature than cotton.Furthermore,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on demand.The proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.展开更多
Background Augmented reality classrooms have become an interesting research topic in the field of education,but there are some limitations.Firstly,most researchers use cards to operate experiments,and a large number o...Background Augmented reality classrooms have become an interesting research topic in the field of education,but there are some limitations.Firstly,most researchers use cards to operate experiments,and a large number of cards cause difficulty and inconvenience for users.Secondly,most users conduct experiments only in the visual modal,and such single-modal interaction greatly reduces the users'real sense of interaction.In order to solve these problems,we propose the Multimodal Interaction Algorithm based on Augmented Reality(ARGEV),which is based on visual and tactile feedback in Augmented Reality.In addition,we design a Virtual and Real Fusion Interactive Tool Suite(VRFITS)with gesture recognition and intelligent equipment.Methods The ARGVE method fuses gesture,intelligent equipment,and virtual models.We use a gesture recognition model trained by a convolutional neural network to recognize the gestures in AR,and to trigger a vibration feedback after a recognizing a five finger grasp gesture.We establish a coordinate mapping relationship between real hands and the virtual model to achieve the fusion of gestures and the virtual model.Results The average accuracy rate of gesture recognition was 99.04%.We verify and apply VRFITS in the Augmented Reality Chemistry Lab(ARCL),and the overall operation load of ARCL is thus reduced by 29.42%,in comparison to traditional simulation virtual experiments.Conclusions We achieve real-time fusion of the gesture,virtual model,and intelligent equipment in ARCL.Compared with the NOBOOK virtual simulation experiment,ARCL improves the users'real sense of operation and interaction efficiency.展开更多
Lithological facies classification is a pivotal task in petroleum geology, underpinning reservoir characterization and influencing decision-making in exploration and production operations. Traditional classification m...Lithological facies classification is a pivotal task in petroleum geology, underpinning reservoir characterization and influencing decision-making in exploration and production operations. Traditional classification methods, such as support vector machines and Gaussian process classifiers, often struggle with the complexity and nonlinearity of geological data, leading to suboptimal performance. Moreover, numerous prevalent approaches fail to adequately consider the inherent dependencies in the sequence of measurements from adjacent depths in a well. A novel approach leveraging an attention-based gated recurrent unit (AGRU) model is introduced in this paper to address these challenges. The AGRU model excels by exploiting the sequential nature of well-log data and capturing long-range dependencies through an attention mechanism. This model enables a flexible and context-dependent weighting of different parts of the sequence, enhancing the discernment of key features for classification. The proposed method was validated on two publicly available datasets. Results demonstrate a considerably improvement over traditional methods. Specifically, the AGRU model achieved superior performance metrics considering precision, recall, and F1-score.展开更多
Bulky external power supplies largely limit the continuous long-term application and miniaturization development of smart sensing devices.Here,we fabricate a flexible and wearable integrated sensing system on an elect...Bulky external power supplies largely limit the continuous long-term application and miniaturization development of smart sensing devices.Here,we fabricate a flexible and wearable integrated sensing system on an electrospun all-nanofiber platform.The three parts of the sensing system are all obtained by a facile ink-based direct writing method.The resistive pressure sensor is realized by decorating MXene sheets on TPU nanofiber.And,the resistive temperature sensor is prepared by compositing MXene sheets into poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS).The thin-film zinc–air battery(ZAB)includes an interdigital zinc–air electrode that is bonded with a gel polymer electrolyte.It can supply a high open-circuit voltage of 1.39 V and a large areal capacity of 18.2 mAh cm^(-2) for stable and reliable power-supplying sensing parts operation.Thanks to the hydrophobic nature of TPU and open-ended micropores in the TPU nanofiber,the sensing system is waterproof,self-cleaning,and air and moisture permeable.For application,the above-mentioned functional components are seamlessly integrated into an intelligent electronic wristband,which is comfortably worn on a human wrist to monitor pulse and body temperature in real time with continuous operation of up to 4 h.By the novel design and remarkable performance,the proposed integrated all-nanofiber sensing system presents a promising solution for developing advanced multifunctional wearable electronics.展开更多
Tungsten oxide(WO_(3))-based memristors show promising applications in neuromorphic computing.However,single-layer WO_(3) memristors suffer from issues such as weak memory performance and nonlinear conductance variati...Tungsten oxide(WO_(3))-based memristors show promising applications in neuromorphic computing.However,single-layer WO_(3) memristors suffer from issues such as weak memory performance and nonlinear conductance variations.In this work,a functional layer based on the hybrids of WO_(3−x) and TiO_(2) is proposed for constructing flexible memristors featuring outstanding synaptic characteristics.Applying diverse electrical stimulations to the memristor enables a range of synaptic functions,elucidating its conduction mechanism through the conductive filament model.The incorporation of TiO_(2) not only enhances the memristor’s memory characteristics but makes its conductance more linear,symmetrical and uniform during the long-term changes.Furthermore,in view of the enhanced device performance by TiO_(2) doping,the potential of this device for simple behavioral simulation and processing of complex computing problems is explored.The“learning-forgetting-relearning”characteristics and device integrability are visually demonstrated.Applying the device to a convolutional neural network,the recognition accuracy of MNIST handwritten digits reaches 98.7%.展开更多
An ultrathin angle-insensitive color filter enabling high color saturation and a wide color gamut is proposed by relying on magnesium hydride-hydrogenated amorphous silicon[MgH2-a-Si:H]lossy dielectric layer.Based on ...An ultrathin angle-insensitive color filter enabling high color saturation and a wide color gamut is proposed by relying on magnesium hydride-hydrogenated amorphous silicon[MgH2-a-Si:H]lossy dielectric layer.Based on effective medium theory,the MgH2-a-Si:H layer with an ultrathin thickness can be equivalent to a quasi-homogeneous dielectric layer wit an effective complex refractive index,which can be tuned by altering the thickness of MgH2to obtain the targeted value o the imaginary part,corresponding to the realization of high color saturation.It is verified that the proposed color filte offers highly enhanced color saturation in conjunction with a wide color gamut by introducing a few-nanometer thic MgH2layer.As the MgH2-a-Si:H layer retains the advantages of high refractive index and tiny thickness,the proposed colo filter exhibits large angular tolerance up to±60°.In addition,MgH2with an unstable property can interconvert with Mg unde a dehydrogenation/hydrogenation reaction,which empowers the proposed color filter with dynamically tunable outpu color.The proposed scheme shows great promise in color printing and ultracompact display devices with high color sat uration,wide gamut,large angular tolerance,and dynamic tunability.展开更多
Flexible pressure sensors capable of monitoring diverse physiological signals and body movements have garnered tremendous attention in wearable electronic devices.Thereinto,high constant sensitivity over a wide pressu...Flexible pressure sensors capable of monitoring diverse physiological signals and body movements have garnered tremendous attention in wearable electronic devices.Thereinto,high constant sensitivity over a wide pressure range combined with breathability,biocompatibility,biodegradability is pivotal for manufacturing of reliable pressure sensors in practical sensing applications.In this work,inspired by the multilayered structure of skin epidermis,we propose and demonstrate a multi-attribute wearable piezoresistive pressure sensor consisting of multilayered gradient conductive poly(ε-caprolactone)nanofiber membranes composites.In response to externally applied pressure,a layer-by-layer current path is activated inside the multilayered membranes composites,leading to the most salient sensing performance of high constant sensitivity of 33.955 kPa^(−1) within the pressure range of 0–80 kPa.The proposed pressure sensor also exhibits a fast response–relaxation time,a low detection limit,excellent stability,which can be successfully used to measure human physiological signals.Lastly,an integrated sensor array system that can locate objects’positions is constructed and applied to simulate sitting posture monitoring.These results indicate that the proposed pressure sensor holds great potential in health monitoring and wearable electronic devices.展开更多
In regularized kernel methods, the solution of a learning problem is found by minimizing a functional consisting of a empirical risk and a regularization term. In this paper, we study the existence of optimal solution...In regularized kernel methods, the solution of a learning problem is found by minimizing a functional consisting of a empirical risk and a regularization term. In this paper, we study the existence of optimal solution of multi-kernel regularization learning. First, we ameliorate a previous conclusion about this problem given by Micchelli and Pontil, and prove that the optimal solution exists whenever the kernel set is a compact set. Second, we consider this problem for Gaussian kernels with variance σ∈（0,∞）, and give some conditions under which the optimal solution exists.展开更多
Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic systems.To address these critical bottlenecks,we propose an optoelect...Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic systems.To address these critical bottlenecks,we propose an optoelectronic memristor based on zinc oxide-indium tin oxide/tungsten oxide(ZnO-ITO/WO_(3-x))heterojunctions as a promising solution.Through applying different types of electrical and optical signals,the device successfully emulates diverse synaptic functions including short-term/long-term synaptic plasticity,alongside short-term and long-term memory.Introducing the ZnO-ITO functional layer enhances the photoresponse of the WO_(3-x)-based memristor and demonstrates“learning-forgetting-relearning”behavior under optical modulation.Furthermore,based on the photoelectric cooperative memristor array,a convolutional neural network for vehicle type recognition is constructed,which solves the problem of zero weight and negative weight complexity.In regard to energy efficiency,the neural network built with this device operates at a power level of only 10^(-3)W,representing a reduction of more than 4 orders of magnitude compared with a standard central processor.Hence,the photoelectric memristor proposed in this work provides a new idea for neuromorphic computing and is expected to promote the development of energy-efficient brain-like computing.展开更多
By using the numerical simulation for the temperature field in the metal organic vapor deposition （MOCVD） reactor by induction heating, it is found that the temperature distribution in the conventional cylinder-shap...By using the numerical simulation for the temperature field in the metal organic vapor deposition （MOCVD） reactor by induction heating, it is found that the temperature distribution in the conventional cylinder-shaped susceptor is nonuniform due to the skin effect of the induced current, which makes the temperature distribution of the wafer nonuniform. Therefore, a novel susceptor with a A-shaped slot is proposed. This slot changes the mode and the rate of the heat transfer in the susceptor, which improves the uniformity of the temperature distribution in the wafer. By using the finite element method （FEM）, the susceptor with this structure for heating a wafer of four inches in diameter is optimized. It is observed that the optimized susceptor with the A-shaped slot makes the uniformity of the temperature distribution in the wafer improve by more than 85%, and a good uniformity of temperature distributions is kept under different wafer temperatures, which may be beneficial to the film growth.展开更多
Prevalent use of motion capture(MoCap)produces large volumes of data and MoCap data retrieval becomes crucial for efficient data reuse.MoCap clips may not be neatly segmented and labeled,increasing the difficulty of r...Prevalent use of motion capture(MoCap)produces large volumes of data and MoCap data retrieval becomes crucial for efficient data reuse.MoCap clips may not be neatly segmented and labeled,increasing the difficulty of retrieval.In order to effectively retrieve such data,we propose an elastic content-based retrieval scheme via unsupervised posture encoding and strided temporal alignment(PESTA)in this work.It retrieves similarities at the sub-sequence level,achieves robustness against singular frames and enables control of tradeoff between precision and efficiency.It firstly learns a dictionary of encoded postures utilizing unsupervised adversarial autoencoder techniques and,based on which,compactly symbolizes any MoCap sequence.Secondly,it conducts strided temporal alignment to align a query sequence to repository sequences to retrieve the best-matching sub-sequences from the repository.Further,it extends to find matches for multiple sub-queries in a long query at sharply promoted efficiency and minutely sacrificed precision.Outstanding performance of the proposed scheme is well demonstrated by experiments on two public MoCap datasets and one MoCap dataset captured by ourselves.展开更多
基金partially supported by the National Natural Science Foundation of China under Grants No.60903176the Provincial Natural Science Foundation of Shandong under Grants No.ZR2012FM010,No.ZR2010FQ028+1 种基金the Program for Youth science and technology starfund of Jinan No.TNK1108the Sub-Project of the National Key Technology R&D Program No.2012BAF12B07-3
文摘In order to solve the problem that the drivers can't find the optimal parking lot timely,a reservation based optimal parking lot recommendation model in Internet of Vehicle(IoV) environment is designed.Based on the users oriented parking information recommendation system,the model considers subjective demands of drivers comprehensively,makes a deeply analysis of the evaluation indicators.This recommendation model uses a phased selection method to calculate the optimal objective parking lot.The first stage is screening which based on the users' subjective parking demands;the second stage is processing the candidate parking lots through multiple attribute decision making.Simulation experiments show that this model can effectively solve the problems encountered in the process of finding optimal parking lot,save the driver's parking time and parking costs and also improve the overall utilization of parking facilities to ease the traffic congestion caused by vehicles parked patrol.
基金the the National Key R&D Program of China(No.2018YFB1004901)the Independent Innovation Team Project of Jinan City(No.2019GXRC013).
文摘At present,most experimental teaching systems lack guidance of an operator,and thus users often do not know what to do during an experiment.The user load is therefore increased,and the learning efficiency of the students is decreased.To solve the problem of insufficient system interactivity and guidance,an experimental navigation system based on multi-mode fusion is proposed in this paper.The system first obtains user information by sensing the hardware devices,intelligently perceives the user intention and progress of the experiment according to the information acquired,and finally carries out a multi-modal intelligent navigation process for users.As an innovative aspect of this study,an intelligent multi-mode navigation system is used to guide users in conducting experiments,thereby reducing the user load and enabling the users to effectively complete their experiments.The results prove that this system can guide users in completing their experiments,and can effectively reduce the user load during the interaction process and improve the efficiency.
文摘Background At present,the teaching of experiments in primary and secondary schools is affected by cost and security factors.Existing research on virtual experiment platforms has alleviated these problems.However,the lack of real experimental equipment and use of a single channel to understand user intentions weaken these platforms operationally and degrade the naturalness of interactions.Methods To solve these problems,we propose an intelligent experimental container structure and a situational awareness algorithm,both of which are verified and applied to a chemical experiment involving virtual-real fusion.First,the acquired images are denoised in the visual channel using the maximum diffuse reflection chroma to remove overexposure.Second,container situational awareness is realized by segmenting the image liquid level and establishing a relation-fitting model.Then,strategies for constructing complete behaviors and making priority comparisons among behaviors are adopted for information complementarity and independence,respectively.A multichannel intentional understanding model and an inter-active paradigm that integrates vision,hearing,and touch are proposed.Results The experimental results show that the accuracy of the intelligent container situation awareness proposed in this paper reaches 99%,and the accuracy of the proposed intention understanding algorithm reaches 94.7%.The test shows that the intelligent experimental system based on the new interaction paradigm also has better performance and a more realistic sense of operation experience in terms of experimental efficiency.Conclusion The results indicate that the proposed experimental container and algorithm can achieve a natural level of human-computer interaction in a virtual chemical experiment platform,enhance the user′s sense of operation,and achieve high levels of user satisfaction.
基金Supported by the National Natural Science Foundation of China(No.61173079,No.60973093,No.60873089)the Key Project of Natural Science Foundation of Shandong Province(ZR2011FZ003)
文摘Natural, efficient, intelligent, and barrier-free HCI （Human-Computer Interface） will be the main developing direction of the new intelligent HCI. Building an intelligent, natural, harmonious and humanistic HCI has been the primary developing tendency of the new HCI. ＂Select one from many＂ is one of the key questions in researching and designing HCI based on gestures. On the sin- gle channel interactive condition which is based on 3D gesture operation, we build a interactive model of＂Select one from many＂. Combining this model with ＂Token＂ technology and reciprocating movement feature, we present and realize a simple efficient ＂Se- lect one from many＂ algorithm, which is used in a concrete SOR （Selection-Operation-Release） system. In the SOR system, we real- ize a real-time selection, tracking and interaction of natural gestures.
基金Project supported by the National Natural Science Foundation of China (Grant No.61601198)the University of Jinan PhD Foundation (Grant No.XBS1714)。
文摘Optoelectronic materials are essential for today's scientific and technological development,and machine learning provides new ideas and tools for their research.In this paper,we first summarize the development history of optoelectronic materials and how materials informatics drives the innovation and progress of optoelectronic materials and devices.Then,we introduce the development of machine learning and its general process in optoelectronic materials and describe the specific implementation methods.We focus on the cases of machine learning in several application scenarios of optoelectronic materials and devices,including the methods related to crystal structure,properties(defects,electronic structure)research,materials and devices optimization,material characterization,and process optimization.In summarizing the algorithms and feature representations used in different studies,it is noted that prior knowledge can improve optoelectronic materials design,research,and decision-making processes.Finally,the prospect of machine learning applications in optoelectronic materials is discussed,along with current challenges and future directions.This paper comprehensively describes the application value of machine learning in optoelectronic materials research and aims to provide reference and guidance for the continuous development of this field.
文摘Background Robot grasping encompasses a wide range of research areas;however, most studies have been focused on the grasping of only stationary objects in a scene;only a few studies on how to grasp objects from a user's hand have been conducted. In this paper, a robot grasping algorithm based on deep reinforcement learning (RGRL) is proposed. Methods The RGRL takes the relative positions of the robot and the object in a user's hand as input and outputs the best action of the robot in the current state. Thus, the proposed algorithm realizes the functions of autonomous path planning and grasping objects safely from the hands of users. A new method for improving the safety of human-robot cooperation is explored. To solve the problems of a low utilization rate and slow convergence of reinforcement learning algorithms, the RGRL is first trained in a simulation scene, and then, the model para-meters are applied to a real scene. To reduce the difference between the simulated and real scenes, domain randomization is applied to randomly change the positions and angles of objects in the simulated scenes at regular intervals, thereby improving the diversity of the training samples and robustness of the algorithm. Results The RGRL's effectiveness and accuracy are verified by evaluating it on both simulated and real scenes, and the results show that the RGRL can achieve an accuracy of more than 80% in both cases. Conclusions RGRL is a robot grasping algorithm that employs domain randomization and deep reinforcement learning for effective grasping in simulated and real scenes. However, it lacks flexibility in adapting to different grasping poses, prompting future research in achieving safe grasping for diverse user postures.
文摘This paper introduces the application of data mining technology in data service. Data mining is a new technology, but its application time is long, and the application effect is obvious. Data mining technology can be used in enterprise customer service system, which can help enterprises to find potential customers, while retaining the most valuable customers. We pointed out the necessity of establishing data mining technology and service intelligence analysis system based on the combination of intelligence analysis and service characteristics and processes, the method of data mining, knowledge management ideas applied to intelligence analysis and service system.
文摘In this paper, we conduct research on the high robustness JavaEE enterprise development mode based on Hadoop and cloud servers. The current virtual machine real-time migration can only achieve manual migration, and cannot achieve full-automatic migration. In other words, when the server overload requires the administrator to artificially select a low-load host, and then hit migration command to implement the migration. In recent years, the Hadoop is becoming popular, and the read performance of the data is measured in terms of the time overhead for reading the required data. The key to reducing read time is to optimize that Hadoop cloud data read time and the RDBMS data query time. This paper integrates the mentioned techniques to construct the novel JavaEE enterprise development pattern that will promote the further development of the related techniques.
基金Shandong Provincial Natural Science Foundation,China(No.ZR2014FL011)Higher Educational Science and Technology Program of Shandong Province,China(No.J13LN21)
文摘Anonymity is a very important security objective in network communications.Recently,Pang et al.proposed a novel multirecipient signcryption scheme with complete anonymity and claimed that the new concrete scheme was strong existential unforgeability under selective multi-ID,chosen message attack.Unfortunately,by giving concrete attacks,named " inside attack" and " outside attack" respectively,we indicate that Pang et al.'s scheme is not secure in their security model.
基金supported by the National Natural Science Foundation of China under Grant(62311540155,62174068)Jinan City-University Integrated Development Strategy Project under Grant(JNSX2023017)+4 种基金Taishan Scholars Project Special Funds(tsqn202312035)the Tianjin Science and Technology Plan Project(22JCZDJC00630)the Higher Education Institution Science and Technology Research Project of Hebei Province(JZX2024024)the China National Key Research and Development Program(2022YFC3601400)the Natural Science Foundation of Shandong Province China(ZR2020ME120).
文摘Wearable sensors have been rapidly developed for application in various human monitoring systems.However,the wearing comfort and thermal properties of these devices have been largely ignored,and these characteristics urgently need to be stud-ied.Herein,we develop a wearable and breathable nanofiber-based sensor with excellent thermal management functionality based on passive heat preservation and active Joule heating effects.The multifunctional device consists of a micropatterned carbon nanotube(CNT)/thermoplastic polyurethane(TPU)nanofiber electrode,a microporous ionic aerogel electrolyte and a microstructured Ag/TPU nanofiber electrode.Due to the presence of a supercapacitive sensing mechanism and the appli-cation of microstructuration,the sensor shows excellent sensing performance,with a sensitivity of 24.62 kPa-1.Moreover,due to the overall porous structure and hydrophobicity of TPU,the sensor shows good breathability(62 mm/s)and water repellency,with a water contact angle of 151.2°.In addition,effective passive heat preservation is achieved by combining CNTs with high solar absorption rates(85%)as the top layer facing the outside,aerogel with a low thermal conductivity(0.063 W m-1 k-1)as the middle layer for thermal insulation,and Ag with a high infrared reflectance rate as the bottom layer facing the skin.During warming,this material yields a higher temperature than cotton.Furthermore,the active Joule heat-ing effect is realized by applying current through the bottom resistive electrode,which can quickly increase the temperature to supply controlled warming on demand.The proposed wearable and breathable sensor with tunable thermal properties is promising for monitoring and heat therapy applications in cold environments.
基金the National Key R&D Program of China(2018YFB1004901)the Independent Innovation Team Project of Jinan City(2019GXRC013).
文摘Background Augmented reality classrooms have become an interesting research topic in the field of education,but there are some limitations.Firstly,most researchers use cards to operate experiments,and a large number of cards cause difficulty and inconvenience for users.Secondly,most users conduct experiments only in the visual modal,and such single-modal interaction greatly reduces the users'real sense of interaction.In order to solve these problems,we propose the Multimodal Interaction Algorithm based on Augmented Reality(ARGEV),which is based on visual and tactile feedback in Augmented Reality.In addition,we design a Virtual and Real Fusion Interactive Tool Suite(VRFITS)with gesture recognition and intelligent equipment.Methods The ARGVE method fuses gesture,intelligent equipment,and virtual models.We use a gesture recognition model trained by a convolutional neural network to recognize the gestures in AR,and to trigger a vibration feedback after a recognizing a five finger grasp gesture.We establish a coordinate mapping relationship between real hands and the virtual model to achieve the fusion of gestures and the virtual model.Results The average accuracy rate of gesture recognition was 99.04%.We verify and apply VRFITS in the Augmented Reality Chemistry Lab(ARCL),and the overall operation load of ARCL is thus reduced by 29.42%,in comparison to traditional simulation virtual experiments.Conclusions We achieve real-time fusion of the gesture,virtual model,and intelligent equipment in ARCL.Compared with the NOBOOK virtual simulation experiment,ARCL improves the users'real sense of operation and interaction efficiency.
基金supported by National Natural Science Fundation(General Program)of China(Grant:61972211).
文摘Lithological facies classification is a pivotal task in petroleum geology, underpinning reservoir characterization and influencing decision-making in exploration and production operations. Traditional classification methods, such as support vector machines and Gaussian process classifiers, often struggle with the complexity and nonlinearity of geological data, leading to suboptimal performance. Moreover, numerous prevalent approaches fail to adequately consider the inherent dependencies in the sequence of measurements from adjacent depths in a well. A novel approach leveraging an attention-based gated recurrent unit (AGRU) model is introduced in this paper to address these challenges. The AGRU model excels by exploiting the sequential nature of well-log data and capturing long-range dependencies through an attention mechanism. This model enables a flexible and context-dependent weighting of different parts of the sequence, enhancing the discernment of key features for classification. The proposed method was validated on two publicly available datasets. Results demonstrate a considerably improvement over traditional methods. Specifically, the AGRU model achieved superior performance metrics considering precision, recall, and F1-score.
基金supported by the National Natural Science Foundation of China under Grant(62174068)the Tianjin Science and Technology Plan Project(22JCZDJC00630)+2 种基金the Higher Education Institution Science and Technology Research Project of Hebei Province(JZX2024024)the China National Key Research and Development Program(2022YFC3601400)the Natural Science Foundation of Shandong Province China,(ZR2020ME120).
文摘Bulky external power supplies largely limit the continuous long-term application and miniaturization development of smart sensing devices.Here,we fabricate a flexible and wearable integrated sensing system on an electrospun all-nanofiber platform.The three parts of the sensing system are all obtained by a facile ink-based direct writing method.The resistive pressure sensor is realized by decorating MXene sheets on TPU nanofiber.And,the resistive temperature sensor is prepared by compositing MXene sheets into poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate)(PEDOT:PSS).The thin-film zinc–air battery(ZAB)includes an interdigital zinc–air electrode that is bonded with a gel polymer electrolyte.It can supply a high open-circuit voltage of 1.39 V and a large areal capacity of 18.2 mAh cm^(-2) for stable and reliable power-supplying sensing parts operation.Thanks to the hydrophobic nature of TPU and open-ended micropores in the TPU nanofiber,the sensing system is waterproof,self-cleaning,and air and moisture permeable.For application,the above-mentioned functional components are seamlessly integrated into an intelligent electronic wristband,which is comfortably worn on a human wrist to monitor pulse and body temperature in real time with continuous operation of up to 4 h.By the novel design and remarkable performance,the proposed integrated all-nanofiber sensing system presents a promising solution for developing advanced multifunctional wearable electronics.
基金supported by the National Natural Science Foundation of China under Grant(62104080,62204170)Natural Science Foundation of Shandong Province under Grant(ZR2023ZD03)+1 种基金Jinan City-University Integrated Development Strategy Project under Grant(JNSX2023017)Taishan Scholars Project Special Funds(tsqn202312035).
文摘Tungsten oxide(WO_(3))-based memristors show promising applications in neuromorphic computing.However,single-layer WO_(3) memristors suffer from issues such as weak memory performance and nonlinear conductance variations.In this work,a functional layer based on the hybrids of WO_(3−x) and TiO_(2) is proposed for constructing flexible memristors featuring outstanding synaptic characteristics.Applying diverse electrical stimulations to the memristor enables a range of synaptic functions,elucidating its conduction mechanism through the conductive filament model.The incorporation of TiO_(2) not only enhances the memristor’s memory characteristics but makes its conductance more linear,symmetrical and uniform during the long-term changes.Furthermore,in view of the enhanced device performance by TiO_(2) doping,the potential of this device for simple behavioral simulation and processing of complex computing problems is explored.The“learning-forgetting-relearning”characteristics and device integrability are visually demonstrated.Applying the device to a convolutional neural network,the recognition accuracy of MNIST handwritten digits reaches 98.7%.
基金supported by the Natural Science Foundation of Shandong Province(No.ZR2019BF013)the National Natural Science Foundation of China(Nos.62005095 and 61905091)。
文摘An ultrathin angle-insensitive color filter enabling high color saturation and a wide color gamut is proposed by relying on magnesium hydride-hydrogenated amorphous silicon[MgH2-a-Si:H]lossy dielectric layer.Based on effective medium theory,the MgH2-a-Si:H layer with an ultrathin thickness can be equivalent to a quasi-homogeneous dielectric layer wit an effective complex refractive index,which can be tuned by altering the thickness of MgH2to obtain the targeted value o the imaginary part,corresponding to the realization of high color saturation.It is verified that the proposed color filte offers highly enhanced color saturation in conjunction with a wide color gamut by introducing a few-nanometer thic MgH2layer.As the MgH2-a-Si:H layer retains the advantages of high refractive index and tiny thickness,the proposed colo filter exhibits large angular tolerance up to±60°.In addition,MgH2with an unstable property can interconvert with Mg unde a dehydrogenation/hydrogenation reaction,which empowers the proposed color filter with dynamically tunable outpu color.The proposed scheme shows great promise in color printing and ultracompact display devices with high color sat uration,wide gamut,large angular tolerance,and dynamic tunability.
基金the National Natural Science Foundation of China(Nos.62174068 and 61888102)Rizhao City Key Research and Development Program(No.2021ZDYF010102).
文摘Flexible pressure sensors capable of monitoring diverse physiological signals and body movements have garnered tremendous attention in wearable electronic devices.Thereinto,high constant sensitivity over a wide pressure range combined with breathability,biocompatibility,biodegradability is pivotal for manufacturing of reliable pressure sensors in practical sensing applications.In this work,inspired by the multilayered structure of skin epidermis,we propose and demonstrate a multi-attribute wearable piezoresistive pressure sensor consisting of multilayered gradient conductive poly(ε-caprolactone)nanofiber membranes composites.In response to externally applied pressure,a layer-by-layer current path is activated inside the multilayered membranes composites,leading to the most salient sensing performance of high constant sensitivity of 33.955 kPa^(−1) within the pressure range of 0–80 kPa.The proposed pressure sensor also exhibits a fast response–relaxation time,a low detection limit,excellent stability,which can be successfully used to measure human physiological signals.Lastly,an integrated sensor array system that can locate objects’positions is constructed and applied to simulate sitting posture monitoring.These results indicate that the proposed pressure sensor holds great potential in health monitoring and wearable electronic devices.
基金Supported by National Natural Science Foundation of China (Grant No.11071276)
文摘In regularized kernel methods, the solution of a learning problem is found by minimizing a functional consisting of a empirical risk and a regularization term. In this paper, we study the existence of optimal solution of multi-kernel regularization learning. First, we ameliorate a previous conclusion about this problem given by Micchelli and Pontil, and prove that the optimal solution exists whenever the kernel set is a compact set. Second, we consider this problem for Gaussian kernels with variance σ∈（0,∞）, and give some conditions under which the optimal solution exists.
基金supported by the National Natural Science Foundation of China(62174068,62311540155,62174068,and 61804063)Jinan City-University Integrated Development Strategy Project(JNSX2023017)+2 种基金Taishan Scholars Project Special Funds(tsqn202312035)the National Key Research and Development Program of China(2019YFA0705900)funded by MOSTthe Natural Science Foundation of Jilin Province(20220201070GX)。
文摘Traditional transistors confront severe challenges of insufficient computing capability and excessive power consumption in large-scale neuromorphic systems.To address these critical bottlenecks,we propose an optoelectronic memristor based on zinc oxide-indium tin oxide/tungsten oxide(ZnO-ITO/WO_(3-x))heterojunctions as a promising solution.Through applying different types of electrical and optical signals,the device successfully emulates diverse synaptic functions including short-term/long-term synaptic plasticity,alongside short-term and long-term memory.Introducing the ZnO-ITO functional layer enhances the photoresponse of the WO_(3-x)-based memristor and demonstrates“learning-forgetting-relearning”behavior under optical modulation.Furthermore,based on the photoelectric cooperative memristor array,a convolutional neural network for vehicle type recognition is constructed,which solves the problem of zero weight and negative weight complexity.In regard to energy efficiency,the neural network built with this device operates at a power level of only 10^(-3)W,representing a reduction of more than 4 orders of magnitude compared with a standard central processor.Hence,the photoelectric memristor proposed in this work provides a new idea for neuromorphic computing and is expected to promote the development of energy-efficient brain-like computing.
基金Project supported by the Foundation of Hunan Province(No.2012GK3103)the Scientific Research Fund of Hunan Provincial Education Department(No.12C0108)the National Natural Science Foundation of China(No.61376076)
文摘By using the numerical simulation for the temperature field in the metal organic vapor deposition （MOCVD） reactor by induction heating, it is found that the temperature distribution in the conventional cylinder-shaped susceptor is nonuniform due to the skin effect of the induced current, which makes the temperature distribution of the wafer nonuniform. Therefore, a novel susceptor with a A-shaped slot is proposed. This slot changes the mode and the rate of the heat transfer in the susceptor, which improves the uniformity of the temperature distribution in the wafer. By using the finite element method （FEM）, the susceptor with this structure for heating a wafer of four inches in diameter is optimized. It is observed that the optimized susceptor with the A-shaped slot makes the uniformity of the temperature distribution in the wafer improve by more than 85%, and a good uniformity of temperature distributions is kept under different wafer temperatures, which may be beneficial to the film growth.
基金supported by Shandong Provincial Natural Science Foundation of China under Grant No.ZR2022MF294.
文摘Prevalent use of motion capture(MoCap)produces large volumes of data and MoCap data retrieval becomes crucial for efficient data reuse.MoCap clips may not be neatly segmented and labeled,increasing the difficulty of retrieval.In order to effectively retrieve such data,we propose an elastic content-based retrieval scheme via unsupervised posture encoding and strided temporal alignment(PESTA)in this work.It retrieves similarities at the sub-sequence level,achieves robustness against singular frames and enables control of tradeoff between precision and efficiency.It firstly learns a dictionary of encoded postures utilizing unsupervised adversarial autoencoder techniques and,based on which,compactly symbolizes any MoCap sequence.Secondly,it conducts strided temporal alignment to align a query sequence to repository sequences to retrieve the best-matching sub-sequences from the repository.Further,it extends to find matches for multiple sub-queries in a long query at sharply promoted efficiency and minutely sacrificed precision.Outstanding performance of the proposed scheme is well demonstrated by experiments on two public MoCap datasets and one MoCap dataset captured by ourselves.
