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With the wide application of Unmanned Aerial Vehicle (UAV), more and more attention has been paid to UAV relay communication system. Due to the limited energy of airborne terminal of UAV, if the performance of the relay system need to further improved, the transmit powers between the transmitting node and the relay node should be allocated reasonably. This paper proposes two optimization criteria for UAV relay system, including capacity optimal and energy optimal. That is, the maximum transmission capacity or energy efficiency of the system is achieved through power distribution. The optimization models of the two optimization criteria are established and solved. Experiments show that the two optimization criteria can effectively improve the performance of UAV relay system.

Control-flow attacks cause powerful threats to the software integrity. Remote attestation for control flow is a crucial security service for ensuring the software integrity on embedded platforms. The fine-grained remote control-flow attestation with execution-profiling Control-Flow Graph (CFG) is applied to defend against control-flow attacks. It is a safe scheme but it may influence the runtime efficiency. In fact, we find out only the vulnerable parts of a program need being attested at costly fine-grained level to ensure the security, and the remaining normal parts just need a lightweight coarse-grained check to reduce the overhead. We propose Mutable Granularity Control-Flow Attestation (MGC-FA) scheme, which bases on a probabilistic model, to distinguish between the vulnerable and normal parts in the program and combine fine-grained and coarse-grained control-flow attestation schemes. MGC-FA employs the execution-profiling CFG to apply the remote control-flow attestation scheme on embedded devices. MGC-FA is implemented on Raspberry Pi with ARM TrustZone and the experimental results show its effect on balancing the relationship between runtime efficiency and control-flow security.

As a new mode of regional economic development, industrial cluster provides a natural platform for the cooperation, the integration of resources optimization and the enhancement of production flexibility between small and medium-sized enterprises. More and more scholars pay more attention to the research of complex supply chain network operation in industrial clusters. This paper makes a detailed comparison of production characteristics between process supply chain and discrete (assembly) supply chain in an industrial cluster. Relationships between the two supply chain conversions and the corresponding supply chain structure are pointed out. According to the collaboration among the participants in the cluster, six operation models of the process cluster supply chain are proposed. The characteristics of each operation mode are analyzed, which provides an important reference for the researchers of the operation and management of the process cluster supply chain.

A sleeping light was developed based on the experiments according to the preferred colour for bed room lighting, which was able to create cozy and relaxing atmosphere and jointly contributes to sound sleep at night. The goal of the present study was to conduct various tests to compare the performance between this light and a phase of daylight. Overall, the present results showed that the light outperformed a 5000K light to give a better sleeping quality.

In order to adapt to the complex and varying data process logic for the engineering training in the new manufacturing background, and achieve the management of RFID (Radio Frequency Identification) data in the shop floor. This paper proposes a complex event engine mechanism for the training data process based on cloud service. In the cloud, the training resource object is mapped into training cloud object with its atomic data operations. Then, the engine combines these atomic operations into the event execution to support the engineering training according to the service rules.

To improve the accuracy of analysis results is one of the hard challenges for static analysis. Especially, static analyzers generally analyze all paths of a program, including infeasible paths, which undoubtedly decreases the analysis accuracy. To mitigate the issue, we design and implement a static analyzer, called ABAZER-SE, which is based on the meta-compilation and the GCC abstract syntax tree. ABAZER-SE combines symbolic execution and static analysis techniques to detect bugs in the source code. In addition, it allows users to write a custom checker for a specific bug.

With the increasing development of information technology, engineering training system of the traditional colleges and universities has not completely satisfied the current practical tasks, for purpose of upgrading and innovation of teaching system in engineering training. An engineering training mobile service system based on the mobile internet of things is proposed in this paper. The system is developed based on the Android platform. Through the Android intelligent terminal and workshop wireless network system, it realizes mobile monitoring and management of the workshop production by the combination of pushing information. The implementation and operation of the system completely changed the traditional way of practice operation, greatly enhancing the real-time, timeliness and agility of information interaction between teacher and student in the practical operating process. It makes training more convenient, efficient and flexible.

Many diseases can be detected via performing the electrocardiogram diagnosis. Although the electrocardiograms can be acquired in the public clinics, hospitals or even at homes by using the existing devices, these existing devices are not tiny enough to carry on the bodies. Hence, it is difficult to acquire the electrocardiograms all the time. In order to acquire the electrocardiograms all the time, this paper proposes a wearable electrocardiogram acquisition system. In particular, the R points of the electrocardiograms are detected by computing the regularities of the signals. If the regularity of a signal at a point v is about −1.5 and it is the minimum around its neighbor, then v is assumed to be the R point. Similarly, the Q points and the R points can be detected accordingly. Here, it is not required to compute the modulus maxima. Hence, the required computational power is very low. The simulation results show that the proposed algorithm outperforms the existing methods in terms of the required computational complexity.

This paper proposes a filter window bank structure. It consists of a bank of single input single output analysis linear time invariant filters, a bank of analysis periodic windows, a bank of single input single output synthesis linear time invariant filters and a bank of synthesis periodic windows. Since the joint downsampling functions and the upsampling functions in conventional uniform filter banks, conventional nonuniform filter banks, conventional uniform block filter banks and conventional nonuniform block filter banks are particular types of periodic window functions, these conventional filter banks are particular types of the proposed filter window banks. This paper derives the exact perfect reconstruction conditions for the proposed filter window banks with both the constant and the time varying synthesis periodic window functions. Finally, the filter window banks with both the constant synthesis periodic window functions and the time varying periodic window functions are compared to conventional nonuniform filter banks and conventional nonuniform block filter banks.

As there is a rapid development of the wearable camera embed glasses in this decade and these wearable camera embed glasses are portable for the consumer uses, many image recognition systems are developed based on these wearable camera embed glasses. To perform the image recognition, a deep learning based convolution neural network is employed. Instead of using the conventional back propagation approach for training the weight matrices in the convolution layer of the convolution neural network, this paper proposes an optimization approach for the design of these weight matrices. In particular, the error energy between the filtered input vectors and the desirable output vectors of the convolution layer as well as the L p norm of the weight matrices are minimized subject to the frequency selectivity specifications imposed on these weight matrices. This design problem is actually a nonconvex functional inequality constrained sparse problem. Our recently developed sparse optimization method and nonconvex functional inequality constrained optimization method are applied for finding the solution of the optimization problem.

In stand-alone brushless doubly fed generator (BDFG) based shaft power generation system, the output voltage of BDFG is strong influenced by the filter of load side converter (LSC) because of the coupling caused by the stator power winding leakage inductance. In order to eliminate the harmonic of the voltage, the LC-L filter based on the leakage inductance is put forward in this paper. The relationship between the filter parameters and performance, and the limitation of filter parameters for positive damping characteristic without extra active or passive damping has been analyzed. Then the design criterion and steps are presented and a filter based on a 64-kw BDFG shaft power generation system is designed. Finally, the validity of the filter design is verified by experiment.

More and more advanced persistent threat attacks has happened since 2009. This kind of attacks usually use more than one zero-day exploit to achieve its goal. Most of the times, the target computer will execute malicious program after the user open an infected compound document. The original detection method becomes inefficient as the attackers using a zero-day exploit to structure these compound documents. Inspired by the detection method based on structural entropy, we apply wavelet analysis to malicious document detection system. In our research, we use wavelet analysis to extract features from the raw data. These features will be used todetect whether the compound document was embed malicious code.

In the stand-alone brushless doubly fed generator (BDFG)-based shaft power generation system, the stator power winding leakage inductance leads to the strong coupling between load side converter (LSC) and BDFG. In this study, the leakage inductance was used as a part of LCL filter. The difference between LC-L and conventional LCL filter has been analyzed to reveal the damping characteristic that LC-L has in absence of extra damping method. Taking the effect of digital control into account, the relationship between the damping characteristic of LC-L and LC filter parameters has been deduced. The stability and robustness of the system in both situations have been studied Theoretical analysis is validated by simulation and experiment.

The RFID technology has attracted considerable attention in recent years, and brings convenience to supply chain management. In this paper, we concentrate on designing path-checking protocols to check the valid paths in supply chains. By entering a valid path, the check reader can distinguish whether the tags have gone through the path or not. Based on modified schnorr signature scheme, we provide a path-checking method to achieve multi-signatures and final verification. In the end, we conduct security and privacy analysis to the scheme.

This paper proposes a novel method of killing birds and applying vaccines for suppressing the spread of avian influenza via a nonlinear switching control approach. The switching strategy is based on the population of the susceptible birds and the population of the susceptible humans. There are four switching cases. For the first three switching cases, the elimination control force and the quarantine control force are equal to either zero or one. For the last switching case, they are equal to one minus a scalar divided by the population of the susceptible birds and one minus another scalar divided by the population of the susceptible humans, respectively. The system state vectors of the avian influenza model are guaranteed to reach the desirable equilibrium point. Also, the positivity requirements on the system states as well as the constraints on both the lower bounds and the upper bounds of both the elimination control force and the quarantine control force are guaranteed to be satisfied. Computer numerical simulation results show that the proposed control strategy is very effective and efficient.

A kind of ant colony optimization algorithm based on Petri nets has been proposed to solve the problem of hybrid flow shop scheduling. First put forward the scheduling model of manufacturing system based on Petri net, then improve the traditional algorithm of ant scheduling algorithm. Finally this algorithm is used in a company which produces automotive glass and has the features of hybrid flow shop. Test results prove the feasibility and the effectiveness of this algorithm.

In this paper, we propose a new angle quantization index modulation (AQIM) method, called the difference AQIM (DAQIM) method. The proposed method aims to improve the watermarking performance against gain attacks. Unlike the original AQIM method [1], the DAQIM method quantizes the difference of the two angles instead of the angles themselves. The experimental results demonstrate that our proposed method outperforms both the AQIM and the gradient direction watermarking (GDWM) [2] methods in terms of document-to-watermark ratio (DWR).

To solve the inherent non-adaptive problem existed in the expected patch Log likelihood (EPLL), an updating process of the Gaussian mixture model introduced into the EPLL and an improved EPLL scheme via adaptive Gaussian mixture prior is proposed in this paper. Experimental results show that the proposed method outperforms the existing image denoising algorithms.

Pharmaceutical manufacturing is legally bound and supervised by government. Paper-based and manual pharmaceutical manufacturing systems are time-consuming, manpower-wasting, high-quality-cost and error-prone. This paper presents a Manufacturing Execution System (MES) to control production process on the shop floor. Some new advanced technologies, such as RFID, wireless manufacturing, real-time data collecting, real-time work-in-process (WIP) tracking and tracing methodology, are integrated in the MES. A wireless device named IDT (Intelligent Data Terminal) by utilizing 433MHz communication mode is deployed on the shop floor, which enables MES to perform real-time production control. Based on this real-time MES, real-time supervision can be adopted and adapted for FDA (Food and Drug Administration). This paper also provides a Web-Access monitoring on workshops and a Data-Transmission supervision on products. A case study is depicted to show the effectiveness of MES for pharmaceutical manufacturing as well as the advantages of real-time supervision for FDA.

RFID technology was used in this system presented by the paper to open up a new mode of management .The system integrated teaching management, equipment management, materials management, personnel management, and other information effectively to achieve real-time collection of various basis data so as to conduct statistics for dynamic statements, real-time queries, tracking and analysis. New mode of management could guarantee the unified management, deployment of the experimenters and laboratory equipment, the opening rate and utilization of laboratories effectively. In addition, a scientific evaluation mechanism for experimental teaching could be established by the real-time information, in order to evaluate the experimental skills, practical abilities and innovation abilities of students, ,then the quality guarantee system of experimental teaching was further improved.