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Quantum cryptography is a major ingredient of the future quantum internet that promises various secure communication tasks. Quantum conference key agreement (CKA) is an important cryptographic primitive of quantum cryptography, which provides the conference key among multiple users simultaneously. However, quantum CKA is currently far from practical application due to the low conference key rate. Here, we propose a quantum CKA protocol of three users with information-theoretic security. Our protocol only requires phase-randomized weak coherent sources and threshold single-photon detectors, and is anticipated to be experimentally demonstrated over 600 km under current technology. Our scheme can be widely implemented in the approaching large-scale quantum network., Comment: 6 pages, 3 figures, accepted by IEEE Access

With the development of computer technology and artificial intelligence (AI), service robots are widely used in our daily life. While the manufacturing cost of the robots is too expensive for most small technology companies. The biggest technical limitations are the design of the robot service and the resources sharing of the robot groups. As far as we know, there is no complete and open-source service robot cloud service platform. To solve the above problems, in this paper, a novel robot cloud platform called cloud robotics intelligent cloud platform (CRICP) is designed, which consists of gateway layer, an interface layer, service pool, and algorithm layer. Gateway layer mainly solves the problem of robot access control and service invocation requests scheduling. In addition, a standardized access method is proposed to overcome the problem that heterogeneous service robots cannot access the cloud platform. Interface layer is responsible for protocol injection, including motoring protocol, a management protocol, and other algorithms invocation protocol or service invocation interfaces protocol. Service Pool consists of different kinds of robot services which could scale based on the historical data analysis. In Algorithm layer, we can implement machine learning (ML) algorithm, deep learning (DL) algorithm, distributed algorithm, and so on. Finally, voice recognition service invocation experiment and cloud service dynamic scaling test are taken as an example to verify the availability and accuracy of our platform. Moreover, the compared results with a local framework and SOA also verifies the superiority of our platform.

Optoelectronic synaptic devices based on silicon nanomembrane (Si NM) and Poly(3-hexylthiophene) (P3HT) are fabricated. Synaptic functionalities such as excitatory postsynaptic current (EPSC), paired-pulse facilitation (PPF), and transition from short-term memory (STM) to long-term memory (LTM) are mimicked by using light to stimulate the Si NM/P3HT optoelectronic synaptic devices. The “learning-forgetting-relearning” behavior of a human brain may be simulated by using these devices.

Cooperative communications (CC) based on network coding (NC) can significantly increase the capacity of wireless networks. In this paper, we investigate how to apply NC in multi-hop wireless networks with multiple relay nodes and multiple sessions to achieve more practical and general CC based on NC. Based on NC, we consider to jointly optimize relay node selecting, scheduling and flow routing in CC in a multi-hop wireless network. We not only construct a mathematical model but also formulate a maximum-minimum (Max-Min) optimization problem for it. Then we reformulate and solve it with CPLEX. Through simulation, we validate that the achieved rate gain by NC can be greatly improved than the one by CC.

This paper presents an interval observer-based fault detection (IOFD) scheme in UAVs formation system. Firstly, for the formation system in healthy case, the interval observer is constructed based on the known boundary information of the disturbance term and relative output estimation error. Then, the residual errors that can be used for detecting the actuator faults are developed by the output estimation error. Different from the traditional FD schemes, it is not necessary to design the threshold generators in the IOFD scheme. At last, MATLAB proves the correctness and feasibility of the IOFD scheme.

Carrier motion in the perovskite thin films is directly visualized by the time-resolved EFISHG technique. Appropriate laser wavelength near the band edge enabled us to observe the electric field in the perovskite layer selectively. Carrier mobility has been estimated by analyzing the transient carrier motion as 0.02 cm2/Vs. EFISHG technique provides an effective way for studying the carrier motions in organic-inorganic perovskite thin film.

Buildings can be viewed as small cities due to their size, users, and mixed complex activities. Similar to that in smart grid, Demand Side Management (DSM) in micro grid plays an important role in achieving effective and reliable energy management in buildings. In this paper, in order to reduce the Peak-to-Average Ratio of energy consumption and guarantee fairness between users, we investigate fair load scheduling for DSM based on Narrowband IoT (NB-IoT) technology in smart building. Firstly, the load scheduling model based on NB-IoT is constructed. Then, considering the constraints of energy consumption, energy storage and energy generation in buildings, a minimum-maximum fair energy load scheduling problem with PAR limit is formulated into Linear Programming (LP) and solved by commercial software CPLEX. Finally, simulation results validate our proposed optimization method to achieve fair load scheduling with DSM mechanism by comparing with the case without DSM mechanism in smart building.

With the rapid development of society and technology, home service robot is becoming cheaper and smarter. Facing with the difficulties of aging and shortage of labor, we can use home service robot (HSR) as a good companion and servant. However, the security and reliability problems have become bottlenecks in this field. It is meaningful to do researches on fault diagnosis of HSR. Due to its excellent performance in small sample learning, Support Vector Machine (SVM) is a powerful tool for many pattern recognition applications which include fault diagnosis. However, SVM suffers a lot from the high complexity of training time and memory space. This paper proposes a novel support vector selection (SVS) method which can accelerate the training speed of SVM. Experimental results using artificial data and fault samples of HSR are given to validate the effectiveness of the proposed method.

With the introduction of deep learning, a wave of artificial intelligence research has been set off again. Scientists focus on brain-inspired intelligence, namely, try to get inspiration from the brain nervous system and cognitive behavior mechanism, to develop intelligent computing models as well as algorithms with stronger information representation, processing and learning ability. So, the study of neurons and the connections between neurons of brain are needed. One major obstacle of reconstruction lies in segmenting and tracking neuronal processes. Electron microscopy is producing neurons images rapidly. In response, we propose an efficient method for neuronal tracking in electron microscopy images to help scientists reconstruct complex neurons. First, we track neurons by kernelized correlation filter to get candidate neuron; then we calculate overlap area and distance of the contours between two consecutive images to get final neuron. We evaluate the performance of our method on a public electron microscopy dataset. The method is superior in accuracy and efficiency.

This paper proposed an image deformation method based on outlines using modified Moving Least Squares. Firstly, we set some key points in the image to create control outlines as required and then move these points to generate new outlines. In order to warp these outlines to their new positions, we deform the image using modified Moving Least Squares. We provide a simple deformation formula and test the proposed method with cartoon image and realistic image. Experimental results show that the deformation is more realistic compared with the original Moving Least Squares method.

Single-image blind deconvolution is one of the most challenging fields in image processing which restores a sharp image from its blurred version. Nowadays blind deconvolution algorithms have made significant progress. However, the restoration of blurred images with little scale edges and periodic textures is still a hard work. To solve this problem, this paper proposes a new normalized sparse regularization blind deconvolution algorithm, which uses a gradient saliency map to prohibit the image small structures on image blurry kernel estimation. Firstly, salient detection is performed to select the important area which conforms with the human vision system and generates a binary mask to screen out useful gradients. Secondly, the normalized sparse regularization blind deconvolution method is applied to obtain accurate blur kernel and recover the sharp image. Finally, the experiment results show that the algorithm can effectively deblur the degraded image on different scenarios.

In recent years, service robot has become a hot topic in both the academic and industry research areas. However, the reliability and safety issues have become bottlenecks in this field. Fault diagnosis is a good way to improve the reliability of a service robot, but it is difficult to get a complete fault sample dataset because faults occur with strong sparseness. To overcome this problem, this paper proposes a software simulation platform for the fault diagnosis of service robot. The simulation platform can provide a 3D scene which makes it easy to use. Detailed design procedures are presented and discussed in the article. Besides, we carry out experiments on the simulation platform to demonstrate the feasibility and effectiveness of the proposed scheme using a SVM-based fault diagnosis method.

In this paper, we propose a throughput-maximum resource provision scheme in the OFDMA-based Wireless Virtual Network (WVN). The proposed scheme takes the dynamics of both traffic arrivals and wireless channels into consideration. Furthermore, we consider a more flexible service contract where average resource provision is guaranteed for each slice. As it is practically impossible to know future traffic arrival and channel information, we employ the Lyapunov Optimization to develop an online resource provision algorithm. The proposed online algorithm performs joint subcarrier and power allocation to each slice based on the traffic information, wireless channel state as well as historical resource provision. Theoretic analysis implies that the proposed algorithm can arbitrarily get close to the theoretic optimal throughput with degradations in delay, and the two performances can be balanced on demand. Extensive simulation results show that our proposed scheme can significantly improve the average throughput, while reducing the average delay and achieving an excellent isolation performance.

This paper studies the way to the invasion of smart grid networked systems - replay attacks, which can result in the invasion of the smart grid, while not being detected by normal anomaly detection mechanisms. To be able to resist the replay attack, the paper designs a new strategy that can effectively improve the chances of repeat attacks detection for the system controller, but it also will sacrifice some level of performance as the price.

Compressive sensing (CS) MRI have been developed to speed up data acquisition without significantly degrading image quality. This paper proposes a novel compressed sensing reconstruction method exploiting temporally complementary morphological characteristics. This method relies on some well-developed signal processing techniques: morphological component analysis (MCA) and sparse derivatives. It also relies on well-developed MRI reconstruction techniques: incoherent undersampling schemes and parallel imaging. Other MRI schemes were simulated to make comparsion with our MCA-based CS method. CS and parallel imaging has been merged together to highly increase acceleration rate. This work simulates this framework also. Performance of applying different temporal regularizations individually and hybrid signal models based on MCA with and without auxilary spatial regularization are all analyzed in this paper. Nonlinear conjugate gradient algorithm is applied to gain all signal components simultaneously.

Nowadays, data centers consume substantial power, which takes up a considerable portion of local power supply (e.g., smart grid). In this paper, we leverage data center workload scheduling for the coordination between data centers and the smart grid, aiming to reduce the electricity cost of data centers and smooth the load variation of the smart grid simultaneously. We first build cost models of workload scheduling at data centers and the power generation and variation at the smart grid. We formulate the objective function as a weighted sum of the cost of the smart grid and the penalty caused by workload scheduling. Using the dual decomposition method, we then derive the optimal offline solution. To facilitate online implementation, we finally propose a Receding Horizon Control (RHC) based algorithm to obtain the suboptimal solution using limited predicted information. Extensive simulation results show that our proposed scheme can significantly reduce the cost of the smart grid, by up to 20%, while smoothing the load variation simultaneously.

Virtual Network Embedding (VNE) is a key step towards network virtualization. In this paper, we first introduce a new link interference metric for each link to quantify the interference caused by its bandwidth scarcity to accept VN requests, and then an Interference-based VNE (I-VNE) algorithm is proposed. Benefited from the new metric, I-VNE can jointly consider the temporal and spatial topology information of networks, and tries to embed each virtual network request with low interference to avoid rejecting the future requests. Our simulations show that, I-VNE can significantly improve performance in terms of time-average revenue, acceptance ratio and average node utilization with more unbalanced average link utilization, compared with the three existing VNE algorithms with only the global resource information in the spatial dimension.

This abstract address the problem of removing step artifacts from a predominantly low-pass signal. In particular, we consider the case where the step artifacts have an appreciable rise time rather than exhibiting instantaneous step discontinuities. The problem arises in certain physiological measurements, such as near infrared spectroscopic (NIRS) time-series imaging. NIRS is an attractive non-invasive cortical imaging technique [1]. However, this kind of step artifact, caused by detection approach, is one of the difficulties in breast NIRS data analysis.

As the digital divide, e-government are in the process of Normanization construction in our country should pay attention to the research subject. E-government is essentially Normanization in the administrative areas of application, and solve the problem of the digital divide is the basic premise of this application. Based on dialectical materialism as a guide, considering the management, social informatics, politics and economics and other disciplines, and use the research methods such as the theory discussion and empirical analysis and preliminary analyses the e-government construction in our country, the appearance of the digital divide related problems: for example, the digital divide, forming reason, and its influence on the electronic government affairs, and draw lessons from the developed countries such as the United States, Singapore, the Netherlands and Norway some successful experiences in solving problems of the digital divide, the growing digital divide into digital opportunity, the backwardness advantage, how to bridge the digital divide in China put forward the corresponding countermeasures.

It is known that Motor Imagery (MI) improves neurorehabilitation in stroke patients while action observation (AO) has the potential to facilitate MI. However, little is known about how to use AO effectively in MI practice. The aim of our study is to compare the effectiveness of synchronous and asynchronous AO in facilitating MI for neurorehabilitation of stroke patients. The participants with hand motor dysfunction following stroke were asked to imagine a specific object insertion and removal task guided by synchronous or asynchronous AO during MI practice. The event-related power decrease (ERD) or event-related power increase (ERS) in sensorimotor rhythms (SMR) of electroencephalographic (EEG) was calculated to evaluate the cortex excitation during MI. The Nine Hole Peg Test (NHPT) and Pinch Strength Test (PST) were used to score functional recovery of the paralyzed hand. The effectiveness of MI was evaluated according to the cortex excitation and the scores of hand functional recovery. The results of ERD in EEG SMR indicate that synchronous AO increases cortex excitation more effectively than asynchronous AO in MI. Meanwhile, higher NHPT and PST scores were achieved after MI training guided by synchronous AO. This reflects that the hand motor function is also improved more significantly by MI practice guided by synchronous AO. Therefore, compared to asynchronous AO, synchronous AO significantly facilitates MI practice and leads to more effective neurorehabilitation of stroke patients.

ICT based e-commerce in the course of development of its applied technology to mature, tend to improve facilities, scope of application continue to promote, not only for the social and economic development has added new vitality, but also greatly enriched the social and economic Form. With progress in information network technology is another 3G (third-generation communication technology) appears, once again for the information network technology platform based on e-commerce development of a new historic opportunity. This paper to address the use of 3G technology in the emerging e-commerce issues and counter measures to start on.

This article aims at designing and implementing a cloud testing platform based on virtualization technology. This platform is capable of providing an enormous amount of testing resources, and these resources are assigned dynamically on demand, which reduces the cost of developing and testing. On the platform, users could immediately get the resources they want as they ask for them, without any complicated process for preparation. The proposed testing platform is to enhance the management of testing, and improve the accuracy and efficiency as well through several experiments.

This paper presents an approach to train junior Windows software programmers for making software more appealing to students. This approach proposes to separate the software development technologies into three layers, which are the language layer, the application layer and the project layer. For each layer, based on the idea of PBL, this paper gives 20,12 and 1 projects to make the course interesting and easy to understand. Each student must finish a project named as LMS at the end of the course which contains many main technologies of Windows programming. According to the academic results and student surveys, most of the students can finish this course successfully and make a progress in software programming.

The implementation of automatically fitting the theoretical model of spatial variogram has always been a problem in the realm of geostatistics. Considering that the genetic algorithm has sufficient robustness and it has the virtue of searching the global optimum while solving the nonlinear problems, so this paper takes the method of genetic algorithm to automatically fit the theoretical model of spatial variogram. However, the traditional genetic algorithm has the deficiency of slow convergence rate and gets premature convergence easily, according to which this paper proposes a kind of new improved genetic algorithm: comprehensively considering the optimal preservation, self-adaptive regulated probability of intercross and of mutation, introducing the simulated annealing algorithm to revise the fitness function and the survival mechanism. The validation of typical cases and application in fitting the spatial variogram show that this improved algorithm converges quickly and is globally convergent. It is worthy to say that the improved genetic algorithm is a simple and effective method of fitting spatial variogram and other nonlinear problems.

This paper from new institutional economic angle demonstrate that supervision management introduced into engineering project management is an exchange way of reduce transactions costs, then the author give an expectation of information engineering construction supervision management.

The embedded multi-media terminal was designed and developed, which using SAMSUNG Corporation's S3C2410 chip as core processor. Firstly, an embedded Linux operating platform has been built in the UP-NETARM2410-S target machine according to system requirements, which includes boot-loader, kernel, file system, and related device drivers. Then the upper computer equipped Qt/Embedded as SDK(Software Development Kits) to call FFMPEG library to realize picture browser, audio and video player, calendar clock and other GUI interface. Finally, the object code after being cross compiled was embedded into the target machine to run. The experiment results demonstrated that the embedded multi-media terminal constructed by the solution had a proper design, run stably, and achieved the prospective design aim.

In delay tolerant networks (DTNs), all the networking functions rely on the contribution of the participants to fulfill the store-and-forward fashion. Since wireless nodes are buffer and energy constrained, it may not be in the best interest of a node to always accept relay request. In recent years, incentive mechanisms have been proposed to stimulate nodes to cooperate in packet forwarding. However, the lack of end-to-end paths, high variation and long feedback delay in DTNs imply that existing solutions for mobile ad-hoc networks do not apply to DTNs. In this paper, we address the problem assuming that nodes are rational to optimize self interest. We propose a model, named Pay-for-Gain (PFG), based on game theory and loan-credit theory, to investigate equilibrium point that maximizes their own interest. For comparison, the strategy tit-for-tat (TFT) and PFG are tested in existing routing protocols in DTNs.

A tri-stages security requirements engineering development model, which includes early-stage security requirements modeling, security policy and late-stage security requirements modeling, is proposed to improve the traditional security requirements modeling method. An extended framework, which defines new security flaw node, threat means node and elimination link, is proposed to identify the security objectives correctly and describe early-stage security requirements entirely. A method of defining security strategy formally is proposed to express security environment, avoid the conflicts and reduce the complexities of security rules. A kind of requirements modeling language CC-UML, which constructed by Conservative Extension of UML Metamodel, is proposed to integrate the CC functional requirements and late-stage security requirements seamlessly.

Delay Tolerant Networks (DTNs) are characterized by intermittent connectivity, high delay and without end-to-end path from the source to the destination. The fundamental way of message routing in DTNs is store-and-forward. Thus, the mal-behaving nodes in the networks, which are uncooperative to relay messages, will significantly undermine the routing performance. In this paper, we propose a novel congestion control solution for DTNs with mal-behaving nodes named Incentive Multi-paths Routing with Alternative Storage (IMRASFC). IMRASFC firstly initializes multi-paths routing to mitigate link load, then it establishes rules to bestir mal-behaving nodes to store and forward messages, at last it selects alternative nodes with available storage to store data which would otherwise be dropped given buffer exhaustion. Simulation results show that IMRASFC improves the performance of routing algorithms significantly, especially when the number of copies in the network is large.

Delay Tolerant Networks are with intermittent connectivity, high latency and without end-to-end paths from the source to the destination. Message delivering in these networks is characterized by store-and-forward. So the sequence of message delivering and discarding is important to the performance of routing algorithms. However, there is little effort concentrating on buffer management optimization, which can effectively utilize the limited resource. In this paper, we employ optimal theory to propose a novel buffer management strategy named Optimal Buffer Management (OBM) to optimize the sequence of message forwarding and message discarding. In OBM strategy, globe optimization considering delivery ratio, delay, and overhead is adopt to improve the overall performance of routing algorithms. The simulation results also show that the OBM policy is much better than the existing ones in delivery ratio, delay, and overhead.

Currently, there are two main kinds of routing strategies in delay tolerant networks, including single-copy forward routing and multi-copies replication routing. In this paper, we present a novel routing scheme called Single-Copy Replication routing (SCR) which has higher delivery ratio than single-copy forward scheme as well as lower overhead than multicopies replication strategy. SCR only duplicates bundles to the node selected as next hop. Based on the idea of SCR routing strategy, Time Interval Protocol (TIP) is designed to select the next hop according to the time interval between the sender and the destination. Also, we build mathematic model Dominos to analyze the properties of SCR scheme. In the end, the ONE simulator is applied to verify SCR. The theoretical analysis and simulation results both demonstrate that SCR can get higher delivery ratio and lower overhead comparing with other classic routing algorithms.

The main character of Delay Tolerant Networks (DTNs) is that there is not an end-to-end path from the source node to the destinations due to the intermittent connections and mobility of nodes. In this paper, we construct the mathematic model based on queue with vacation theory to analyze the impact of buffer management strategy on DTN multicast routing, and then compute the minimal delay and maximal delay from the source to the destinations according to this model; at last, we do simulation with On-demand Routing, Dynamic Tree Routing and Static Tree Routing algorithms, and the results show that our theory runs well.

Delay/Disruption Tolerant Networks (DNTs) enables nodes to communicate by means of asynchronous sending messages without the need for an end-to-end path. In this paper, we study the problem of multicasting in DTNs. Several schemes have been proposed for multicast routing assuming the group of message receivers is known by sender, and the group members do not change during the process of message delivery. In this paper, we propose a Flexible Multicast Routing scheme, without any prior knowledge about the networks, which can handle multicast group members changing problem. Simulation results show that our routing strategies can achieve higher message delivery ratios and lower delivery latency than existing approaches.

The creative ability index is quite important for enterprises. This paper proposes an evaluation method for enterprise innovation ability based on rough set theory. Firstly, an index reduction which effects the enterprises based on the rough set theory is carried out, then the major indexes of enterprise development ability is extracted. Secondly, the standardized processing of all kinds of index values based on the membership function makes them have a unified dimension thus possessing comparability. Thirdly, a comprehensive evaluation of enterprise creative ability via the principal component analysis is performed. Finally, we obtain the creative ability level of that enterprise compared with other ones by using its concrete statistical data to prove its effectiveness.

Delay-tolerant networks (DTN) have the capacity to interconnect devices in roomy regions unlike traditional networks. Based on common sense, the more similar the mobility pattern of nodes, the more stable their relative positions, which results in a connection between them with a longer duration In this paper, a novel routing scheme using the similarity degree of mobility pattern is proposed to optimize routing performance. In addition, a comprehensive metric called similarity degree is applied to scale the degree of similarity of the mobility pattern which includes deviation of the intermediate node’s speed direction from that of the destination, and distance from the intermediate node to the destination. A message is forwarded to the next hop node with the largest similarity degree.

Delay-tolerant networks (DTNs) have the capacity to interconnect the devices in roomy regions unlike today’s networks. In this paper, we propose a routing scheme named Time Interval Routing (TIR) to increase deliver ratio and decrease deliver latency in DTNs. TIR, only using limited and local information as well as simple algorithm, chooses the node in transmission range with the least time interval among neighbors as the next hop. Due to the limited time duration of connections, in this paper, we propose Bundle-Transfer strategies (BTS) mechanisms to ensure that TIR sends the bundle to the destination with the highest possibility. Through comprehensive simulation, TIR displays its advantage over other classic routing schemes in DTNs.

This paper describes the design considerations of microcontroller based process control for washing machine. In this paper, AT89S51 microcontroller is used to control the process of washing cycle and to drive the external output devices such as water inlet valve, wash motor, water drain valve. The control strategy program for AT89S51 microcontroller is implemented by using assembly language. The objectives of this development are to design a simple control system using low cost microcontroller, to construct the functions of system using simple control system. The main abstraction of this research is to improve control and software systems of microcontroller based process simple control system in Electronics.