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Cooperative relationships and interactive decision behaviors between online stores and third-party logistics (TPL) have attracted increasing attention from academics as well as practitioners with the development of the online retailing industry. However, the decisions and performance of each member in a decentralized supply chain are not in line with the actual performance and decision behaviors of them, especially when taking individual altruism preference into account. Hence, without considering the truism of channel members will lead to unrealistic decisions and obtain anamorphic performance of firms and the entire system based on conventional self-interested models. This paper develops an evolutionary bilateral decision-making model to characterize the effects of all members’ altruism in an online shopping service supply chain (OSSSC). The model considers different altruism of each member in the supply chain and their changes at various intervals. The decision equilibrium and interactive rules of all members are deeply analyzed based on the evolutionary bilateral decision-model as the change of altruism of each party. Our results identify that: altruism preference impacts the decisions of all participants in the OSSSC system. When the TPL and the online store have high altruism and low altruism, respectively, both retail price and logistics service price tend toward low levels and all participants have high utilities. However, this situation is more favorable for the online store. In this case, changes in the altruism level of either party will adversely impact the utilities of all parties and the performance of the whole system; specially, when the online stores are self-interested while the TPL has altruism that fluctuates within a specific range, improving logistics service level will help to lower the retail price and increase market shares. Numerical experiments are conducted to examine and verify the results and some optimal managerial insights for online retailers and TPLs are provided.

For a multi-fingered robot hand, the individual control over single joints cannot guarantee their fine collaboration. For achieving a high-precision synchronization, a theory of synchronous control is introduced to multi-fingered robot hands. This paper introduced a new model-free and cross-coupling control strategy. It had been tested on the humanoid robot fingers and showed high positioning performance. For realizing the mutual influence between the control of all joints, we establish the synchronization error by the differential disposal of adjacent actuator errors, then position errors and synchronization errors are incorporated into a unified control frame. Meanwhile, considering the complex dynamic formulations of the dexterous hand and the characteristics of the control system, a model-free, cross-coupled trajectory tracking method is introduced and the explicit dynamic modeling parameters is not necessary. Finally, we tested our method on a multi-fingered hand platform HIT/DLR-II. The results prove that the new method has superior performance over traditional non-synchronous approaches.

A passenger-oriented method integrating perimeter control with bus dispatch is proposed for solving passenger dispersion problem under metro interruption. It’s essential to use perimeter control to prevent the neighborhood of the affected road network from congestion by postponing or transferring the surplus cars out of the protected area. For executing perimeter control, the theoretical tool of Macroscopic Fundamental Diagram (MFD) is used to interpret the relationship between private cars and buses which is required for transfer passengers from the targeted closed metro station. The framework based on MPC method is used to optimize the control parameters (e.g. the number of vehicles or dynamic split rates allowed to enter protected network). Furthermore, signal timing of the intersections on the boundary of protected network is studied considering the optimized split rates. Finally, the real road network around Zhujiang New Town station of Metro Line No. 5 in Guangzhou is modeled by Aimsun. A number of simulation experiments are conducted, and the efficiency of the proposed management strategy is verified by comparing with different existing strategies. To the best of our knowledge, it’s the first effort to solve passenger dispersion under subway interruption using the idea of perimeter control based on MFD.

The state-of-art dexterous prosthetic hand with multi-degree-of-freedom urgently requires a control method to match its dexterity. The purpose of this paper is to develop a method on rapid grasp control of prosthetic hand based on eye-tracking and verify its effectiveness by experiments. Firstly, an interactive experiment platform was established. Based on the platform, the operator can select the necessary grasping pattern from a graphic interface through eye movement and trigger the selected pattern by gazing the target for a short time (~300ms). The selected grasp pattern will be fed back to the operator during the hand prosthesis performing reach-and-grasp tasks. Finally, to verify the effectiveness of this method, experiments were conducted by an able-bodied participant wearing the prosthesis to grasp some daily-used objects. Our result shows that, by adopting the eye tracking technology in the human visual channel, the grasp control of the prosthesis can be supervised and regulated in real-time and thus an effective interaction between the dexterous prosthesis and the operator can be achieved.

Recently, the Supernumerary Robotic Limbs (SRL) have emerged in the field of robotics for enhancing the user's ability without replacing natural limbs. Lots of researches have contributed to the mechanical design and control of SRL. However, building an artificial sensory nerve pathway of SRL has been largely ignored. In this paper, we built a multi-modal sensory feedback pathway for SRL. Three kinds of sensory pathway contained 1) fingertip pressure, 2) slippage and 3) proprioception information are built under the consideration of SRL platform through electrical stimulation. According to the experiment results of event-related potential (ERP) amplitude, establish the relationship between the physical parameters of the stimulus and the sensation. In addition, enhancement potentials of human sensation based on the brain-computer interface (BCI) is found in two aspects contained: 1) improvement of subjective perception resolution; 2) Shorten the time of sensory recognition. This paper can be used to objectively benchmark the human subjective and individualized sensation, and guide researchers to build the SRL sensory feedback pathways.

Due to poor robustness, instability, and the heavy burden of use, the traditional myoelectric control method is still powerless in the face of the control of the dexterous prosthetic hand. To solve this problem, a new method (CVEEI), that combines computer vision, eye tracking, electromyogram (EMG) and IMU was proposed in this paper. Firstly, through gazing (eye-tracking) in front of the screen, the grasping pattern of the objects can be fed back to the prosthetic hand controller; Then, the prosthetic hand can be controlled to transport the object to the position expected, on collaboration of both EMG and IMU. In this process, the grasping pattern of all objects can be recognized by computer vision in real-time. Importantly, through comparing the traditional EMG control method (co-contraction to switch) in the transport experiment of the objects, the superiority of this new method in operating the dexterous prosthetic hand was further verified (fast > 1s/single object) in this paper.

It is a question of great import for the dexterous prosthesis to realize its continuous, simultaneous and proportional control of multi-DOFs so that its rehabilitation function can be well achieved and its user acceptance rate can be improved. In this paper, we propose a new method, CNMF-HP, which integrates the constrained non-negative matrix factorization (NMF) and the Hadamard product, for estimating 2-DOF wrist movements (DOF-1, flexion/extension; DOF-2, adduction/abduction) from myoelectric signals. Based on this method, the simultaneous control of a multi-fingered prosthesis is verified in this paper. Through establishing the mapping relationship between the wrist movements and the finger movements of the dexterous prosthesis, two grasp control strategies (synchronous and asynchronous) are proposed and successfully applied in operating the dexterous prosthesis to grasp four kinds of objects of different grasping patterns (cylindrical, spherical, tripod and lateral). Then, the performance of different strategies (synchronous/asynchronous control) in the grasping process is compared in terms of the completion time and completion rate of the tasks, in this way the superiority of EMG control proposed in this paper is further verified.

Light composite material is applied more and more such as automobile, airplane, high speed train industry. The accuracy, efficiency and high reliability is required. One synchronized levelling system is developed, which included high performance cylinder with valve block, hydraulic power unit, de-centralized control system with synchronize algorithm. Hardware in loop system simulation method is applied. Finally, the performance is validated with real machine. This four-point levelling system improves the machine with high efficiency and good levelling effect, whose synchronization accuracy can reach less than 0.1 mm.

Hydrostatic transmission system has high power density and can realize continuously variable transmission, so it is widely used in the field of rail vehicle. Under background of "the belt and road", CRRC has developed a type of rail vehicle which is driven by hydraulic power. This paper presents the design concept and working principles of the vehicle. The transmission system mainly consists of an electric proportional control pump and two automatic high-pressure related control motors. Considering the application condition and safety requirement, the functions of twin drive, load limiting control, and anti-slipping are integrated in this system. And all the design is verified at customer side.

Benefiting from the powerful learning capacity of deep learning (DP), a general model for predicting 3-DOF wrist movements could achieve good prediction accuracy for those subjects even not involved in the training. This paper tends to verify this assumption. Since the quantity of training dataset in DP largely influences the model's performance, a limited dataset collected from a number of subjects should be extended first through some data-augmentation approaches. In this paper, we first summarized the possible mistakes happen in the EMG data-collection procedures. Then, according to these mistakes, we designed six data-augmentation approaches to expend our EMG dataset. Through experiments, we found the prediction accuracy can be improved when some approaches are introduced during training. As well, the model robustness could also be improved when the same mistakes occur in the predicting process. With regards to those approaches, placing all electrodes in opposite direction and random switching two channels have significant positive effect on both accuracy and robustness. These two data-augmentation approaches are highly advocated in the pre-processing of the training data for DP-based prediction models.

This paper presents a new high precision binocular camera calibration method. In the classical calibration method, the camera parameters are usually obtained by the optimization calculation of the re-projection error. However, for the system used for three-dimensional optical measurement, this error does not represent the result of three-dimensional reconstruction. In this method, a specially designed calibration board is photographed at multiple angles. (there is no strict requirement in the calibration process.), the intrinsic parameters of the two cameras are obtained by the image. Then, the rotation matrix and translation matrix between the two cameras are computed by the centroid distance increment matrix method. Thus the degree of coupling between the parameters is reduced. At the same time, the space intersection method is used to reconstruct the 3D coordinates of calibration points. Finally, the reconstruction error is calculated and minimized to optimize the calibration parameters. This error directly reflects the efficiency of 3D reconstruction and is more suitable for the quality evaluation of binocular camera calibration. Experiments show that this method is simple, accurate and significantly improves the accuracy.

In order to overcome the performance degradation of long-term myoelectric pattern recognition, many studies introduced adaptive learning methods, which track the concept drift to reduce the potential misclassification risk (MR). Different from phenomenological analysis, for the first time, this paper intends to analytically model the learning process of adaptive learners with delayed and incomplete supervised information (noted as realistic adaptive learners, RAL). With theoretical analysis, we (1) proved that the MR upper bound of the RAL increases but converges to its limitation along with the time; (2) proved that for continuous concept drift, we can lower down the expected MR by improving the updating frequency; (3) predicted on what time the adaptive learner would exceed a given warning value of the expected risk; (4) designed a measure p, which determines the shape of the change curve and the limitation of the risk bound, to compare different adaptive learners. We also designed a method to estimate p without cumbersome long-term data. Based on realistic myoelectric data, we evaluated the performance of various learners with different p values and the inversely estimated results of p from the performance. The results showed the existence of the MR bound limitation of the RAL, as well as the great linearity (R-squared value of 0.941) of the estimation for p.

This paper exploited the single trial decoding of cortical-muscular activities (CMAs). The CMAs were measured by acquiring Electromyographic (EMG) signal, and Electroencephalographic (EEG) signal. We focused on CMAs related to sustained muscular contractions (SMC), and investigated on the classification performance of four types of CMAs with different combinations of three types of features. The four types of CMAs were relaxing, conducting precise hand operation without distractive mental task, conducting precise hand operation with distractive mental task, and conducting rough hand operation. The three types of features were combined root mean square (RMS) and wavelet packet decomposition (WPD) feature of EMG signals, common pattern spatial (CSP) filtered WPD feature of EEG signals, and cortical-muscular coherence (CMC) feature of EMG-EEG signals, which were noted as EMG features, EEG features, and CMC features respectively. In total of 5 subjects participated in the experiments. According to experimental results, we concluded that the classification performance of myoelectric controller can be significantly improved (p

How to design a robotic hand for reproducing the move characteristics of human hand joints is a big challenge in robotics. In this paper, we present an approach to determine the actuation configuration based on the statistical results of hand joint angle in different grasps. A relationship between the basic statistical metrics and actuation configuration strategies is built. In this case, a novel actuation configuration is proposed and the joints of four fingers are arranged into five actuation modules. For the mechanical implementation, the motion of human four finger joints is decomposed to proportion motion, differential motion and chain proportion motion, mechanically implemented by pulley, planetary gear differential module and gear transmission chain. Finally, the implemented mechanism is embedded in palm, and the mechanical implementation to the human hand move characteristics is verified by the measured joint angles of the robotic hand when actuators separately move along PC1 and PC2. Meanwhile, the robotic hand can grasp different objects with a versatile grasp function.

It is known that the muscles actuate human hand joints with a coordinated manner and the hand postures can be reconstructed by a few (usually two) inputs through postural synergies, which has been applied in robotic hand design for reproducing the human versatile grasp function. As for the mechanical implementation, in terms of the joints implemented postural synergies, due to the excessive number of the output and the high contribution ratio of two inputs to one output, the mechanical implementation size is usually too bulky. In this paper, to make the implemented mechanism size smaller and possible to be integrated in the palm, we divided the joints of four fingers into five modules according to the statistical analysis results of each hand joint angle recorded from the human grasp experiment. In order to meet the three needs of prosthetic hand design: versatile grasp function, anthropomorphic physical property and easy-control, three different actuation configurations of postural synergies were evaluated. The actuation configuration of inter-module coordination shows an acceptable reconstruction error, a smaller implementation size and a keeping of the clear corresponding relation between principle components (PCs) and joints.

Due to the hand biomechanical constrains and coordinate manner of motor control, single one joint is difficult to move independently. The aim of this paper is to have an analysis on the joint independence of hand and wrist. At first, a grasp experiment under the tolerance grasping was completed, and the hand and wrist joint angles in different grasping postures were recorded for representing the functionality of human hand. Moreover, based on the recorded postures, the characteristics of each joint were analyzed from correlation and adaptability, for representing the joint inter-joint characteristic and self-characteristic, respectively. In this case, the joint independence was quantified through the joint independence-correlation and independence-adaptability. The quantified joint independence results show that the thumb, index finger and pinky had the highest independence from the view of finger, while from the joint view, the joint independence from high to low were: wrist, metacarpo-phalangeal (MCP), proximal interphalangeal (PIP) and abduction/adduction (ABD). Finally, based on the quantified joint independence, a preliminary actuation configuration was proposed.

Emergency service decision makers are facing the following problems: where to locate the ambulance facility and how many ambulance vehicles should allocate to the station in order to meet the patient needs effectively. In this paper, we study the problem of joint planning of emergency medical services management, which typically consist of emergency location planning and patients assignment to hospitals. Due to ambulance station response time and the shortest traveling time for correct hospital means life to the patient, especially for the patients with various severity of injuries. We have formulated a mixed integer program for the problem at hand, which tries to minimize the total cost for construction of ambulance facility location, ambulance vehicles, and the traveling time cost including the ambulance from station to patient point and from demand point to hospital. The problem is solved using some real-world data sets which have been collected through the Songjiang EMS system at Shanghai General Hospital. Finally, we compare the performance of the obtained results which corresponding to a series of location and allocation hospital with the existing emergency system in Songjiang district, the optimal ambulance station and vehicles allocation plan can cut down the government expenditures at least 3,100,000 RMB.

In order to improve the prosthetic hand's design and usability, this paper presents a synthetic framework for evaluating the current prosthetic hands' anthropomorphic features with 12 quantified prosthetic hand anthropomorphism evaluation indexes (QPHAEIs). Our primary results show that a global anthropomorphic score (GAS) of the current commercial prosthetic hands is only 45.2%. The compliance, coupling speed ratio and configuration of the degrees of freedom (DOF) are found to be the lowest three anthropomorphism evaluation indexes in all QPHAEIs. Besides these significant findings, a consideration priority order in prosthetic hand's anthropomorphic index design is also proposed. Further correlation analysis indicates that evaluation methods using rotation axis distribution, rather than experimental grasp gesture, are more reliable to measure a prosthetic hand's GAS.

In this paper, we study the event-triggered consensus problem for multi-agent systems with general linear dynamics under a general directed graph. We propose a decentralized event-triggered consensus controller (ETCC) for each agent to achieve consensus, without requiring continuous communication among agents. Each agent only needs to monitor its own state continuously to determine when to trigger an event and broadcast its state to its out-neighbors. The agent updates its controller when it broadcasts its state to its out-neighbors or receives new information from its in-neighbors. The ETCC can be implemented in multiple steps. We prove that under the proposed ETCC there is no Zeno behavior exhibited. To relax the requirement of continuous monitoring of each agent's own state, we further propose a self-triggered consensus controller (STCC). Simulation results are given to illustrate the theoretical analysis and show the advantages of the event-triggered and self-triggered controllers in this paper.

For achieving a closed-loop, bidirectional control over myoelectric prosthetic hands, adopting the electrical stimulation in the sensory feedback channel for providing electrotactile substitution is currently a big trend. However, the electrical pulses used for stimulation may spread to the EMG collection sites which significantly interferes the controlling stability. In this paper, a novel noise cancellation method is proposed to suppress the interference between the electrotactile feedback subsystem and the electromyographic collection subsystem. Based on the propagation model of the stimulation noise, this method integrates the optimization of the stimulation waveform, the special design of the stimulation electrode and the advanced technique of digital signal processing. Experiments on healthy subjects are conducted to verify the feasibility of the proposed method. Primary results show that, through the method, the signal to noise rate (SNR) of the EMG signals reaches to 43dB, without frequency or time multiplexing.

In this paper, the distributed cooperative attitude tracking control law based on a new modified fast terminal sliding mode is presented for multiple spacecraft formation flying in the presence of model uncertainty and external disturbance. Firstly, to speed the convergence rate and avoid the singularity problem, a new modified fast terminal sliding mode manifold is proposed. Then, based on the proposed terminal sliding mode manifold, the distributed cooperative attitude tracking controller is designed for the spacecraft formation flying(SFF) in the presence of model uncertainty and external disturbance, Meanwhile, the finite time stability of SFF system can be also guaranteed. Finally, numerical simulation is given to verify the validity of the proposed control algorithm.

This paper considers the decentralized event-triggered consensus problem for discrete-time linear multi-agent systems. The communication topology among agents is assumed to be a general directed graph containing a spanning tree. We propose an event-based consensus control algorithm rendering the states of agents reach consensus. The triggering condition is decentralized only based on the agent's own information. Compared to the traditional consensus control law which needs communication at every iteration, the proposed event-triggered consensus algorithm in this paper can reduce the communication load greatly. Simulation is given to illustrate the theoretical results.

A common source for controlling hand prosthesis is the myoelectric signal (MES, also termed electromyography, EMG) that are collected from human body. For a pattern recognition-based EMG control scheme, research has found that the classification accuracy obtained offline may deteriorate owing to signal instinct or changed environment, which results in a reduced system stability. Based on support vector machine (SVM), this paper proposed an adaptive learning procedure intending to keep the classification accuracy. The general idea was to rearrange the training samples of the classifier in real-time by measuring their Kuhn-Tucker (KT) conditions. To regulating the learning effectiveness and system complexity, a forgetting factor was applied to each EMG sample considering its life period. The proposed learning algorithm was validated on a multi-session MES dataset collected from a series of control scenarios, within which the myoelectric signals were collected from two healthy subjects while performing a large variety of finger motions. The experimental results showed that the accuracy of the classifiers could be effectively maintained. In addition, the introduced forgetting factor can effectively confine the classifier's complexity in the long run.

This paper considers the distributed attitude synchronization problem for multiple spacecraft with external disturbances. Distributed discontinuous adaptive controller is designed based on the relative attitudes and angular velocities of neighboring spacecraft and attitude synchronization can be reached for any communication graph containing a directed spanning tree. To tackle the chattering effect caused by the discontinuous controller, a continuous controller is further proposed, under which both the synchronization errors and the adaptive gains are ultimately bounded. Extensions to the case with a leader-follower communication graph with the leader as the spanning tree's root are further studied.

Objective: Investigate the effects of TSA on MCF-7 cell growth in vitro and the expressions of fragile HiT (Fhit) and Survivin gene in human breast cancer cell strain MCF-7. Methods: Cultured cells were divided into control group and TSA groups, and treated with DMSO and different concentration of TSA (50, 100, 200, 500nmol/L) respectively. Then the cell activity was observed by try pan blue stain assay and the transcription level of Fhit and Survivin were analyzed by using real-time PCR. The change of Fhit protein was analyzed by western bolt. Results: The proliferation of breast cancer cell MCF-7 was inhibited significantly after culture with TSA. TSA inhibited the breast cancer cell growth in dose-dependent and time-dependent manners. The expression of Fhit mRNA and protein were all increased significantly (3.12 vs 1, P

A five-fingered, multi-sensory biomechatronic hand with sEMG interface is presented. The cambered palm is specially designed to enhance the stability while grasping. The location of the thumb is designed by maximizing interaction area between the thumb and other fingers. The opposite thumb could grasp along a cone surface, while maintaining its function. By taken the advantage of coupling linkage mechanism, each finger with three phalanges could fulfill flexion-extension movement independently. Besides, each finger is equipped with torque and position sensors. Thus, the cosmetics and dexterity are improved remarkably compared to conventional prosthesis. The hardware architecture is divided into control system and EMG signal processing system. Moreover, a novel two-stage decision strategy combing the position-based impedance control scheme is implemented to realize the real-time sEMG control of the hand. According to the grasp experiment results, the hand can accomplish several grasp modes stably; the success rate of 10 modes is up to 90%.

The development of a biomechatronic hand with multi-FSRs (Force Sensitive Resistor) interface is presented. The cambered palm is specially designed to enhance the stability while grasping. The opposite thumb could grasp along a cone surface, while maintaining its function. By taken the advantage of coupling linkage mechanism, each finger with three phalanges could fulfill flexion and extension independently. Besides, each finger is equipped with torque and position sensors. Thus, the cosmetics and dexterity are improved remarkably compared to commercial prosthesis. The hardware architecture is hierarchically organized as control system and human-machine interaction system. To evaluate the performances of the hand, the pattern reorganization experiment based on support vector machine (SVM) was conducted. The results show that FSR sensing technology is suitable for muscle activity detection; Compared to nearest neighborhood classifier, SVM method improves the predict success rate. Moreover, it also demonstrates that the hand is dexterous and manipulates like human.

Firstly, to minimize the ripples of the electric magnetic torque and flux linkage produced in the conventional direct torque control (DTC) system for permanent magnet synchronous motors (PMSM); this paper proposes a expected space vector modulation (ESVM) strategy of DTC. The expected voltage was produced by SVM. PI controller was used in flux and torque controller, instead of hysteresis comparator and switching table in conventional direct torque control. Secondly, to chattering reduction and advance state-dynamic performance of PMSM servo system, a dynamic sliding mode controller was designed. By constructing new switching function with integral term, the first order or high order derivative of control output were introduced in switching function. Dynamic sliding mode control laws with time continuum essentially was obtained. The experimental results show that the steady state and dynamic performance of the proposed DTC based on DSMC are improved dramatically, compared with system of the basic DTC or general SMC.

Instantaneous phase currents are required for successful operation of three-phase current controllers. The technique for reconstructing motor phase currents using information from a single current sensor in the dc-link of an inverter has been applied to reduce the cost, weight and volume of system. However, the duration of an active switching state may be so short that the dc-link current cannot be measured reliably. This paper presents an improved PWM modulation strategy named switching state axial translation (SSAT) to overcome this problem. The new SSAT method modifies the PWM voltage vectors by moving the switching state waveforms along the axis when the phase currents cannot be measured. A combination of analytical and experimental results shows that this method offers an attractive phase current reconstruction performance.

In the force control of multi-functional prosthetic hands, it is important to extract grasp force information besides mode specifications directly from the myoelectric signals. In this paper, a force sensor is adopted to record the hand's enveloping force when the hand is performing several grasp modes, synchronously with 6 channels surface electromyography (EMG) which are extracting from the subject's forearm. Three pattern regression methods, locally weighted projection regression (LWPR), artificial neural network (ANN) and support vector machine (SVM) are used to find the best representative relationship of these two kinds of signals. Experimental results show that the SVM method is better than LWPR and ANN, especially in the case of cross-session validation. Also, the force regression performance is better when grasping within several specific modes than grasping randomly. Based on these results, an efficient online prediction of the hand grasp force is present finally, with an accuracy of around 0.9 in squared correlation coefficient (SCC) and 5~10N error over a range of 60N. It can be utilized for the prosthetic hand's control to provide a reasonable exerting force reference.