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Multi- and hyperspectral imaging modalities encompass a growing number of spectral techniques that find many applications in geospatial, biomedical and machine vision fields. The rapidly increasing number of applications requires a convenient easy-to-navigate software that can be used by new and experienced users to analyze data, develop, apply, and deploy novel algorithms. Herein, we present our platform, IDCube that performs essential operations in hyperspectral data analysis to realize the full potential of spectral imaging. The strength of the software lies in its interactive features that enable the users to optimize parameters and obtain visual input for the user. The entire software can be operated without any prior programming skills allowing interactive sessions of raw and processed data. IDCube Lite, a free version of the software described in the paper, has many benefits compared to existing packages and offers structural flexibility to discover new hidden features.

A new framework for advanced machine learning-based analysis of hyperspectral datasets HSKL was built using the well-known package scikit-learn. In this paper, we describe HSKL’s structure and basic usage. We also showcase the diversity of models supported by the package by applying 17 classification algorithms and measure their baseline performance in segmenting objects with highly similar spectral properties.

Based on the Cubature Kalman filter algorithm (CKF) algorithm, we present a new particle filtering algorithm. To construct the importance density of samples, the importance density function is generated by a new framework, in which the state of each particle is predicted according to the concept of CKF. In this way, the new proposed method can take into account the most recent measurements, resulting in an accurate approximation to the nonlinear non-Gaussian system. Thus, we can get a great improvement in the estimation performance of the system. Finally, the effectiveness of the proposed model is validated through simulation.

Since its establishment, Luckin Coffee has attracted much attention because of its “subversive new retail model”. After the exposure of financial fraud, its business model has caused more extensive disputes. This paper analyzes the deep motivation of financial fraud through qualitative analysis and case empirical research, combined with fraud triangle theory and rationalization factors, and tries to seek capital market capital The current reasons provide enlightenment for the reform path of market supervision in China.

In order to overcome the problem of low matching accuracy in traditional electric vehicle powertrain parameter matching method, a parameter matching method of Electric Vehicle Powertrain Based on genetic algorithm is proposed. In this method, genetic algorithm is used to construct the objective function of vehicle energy consumption optimization and the objective function of power performance. By solving the objective function, the transmission ratio of power system is optimized. After the above optimization, the parameters matching of electric vehicle power system is realized from three aspects: motor parameter matching, transmission ratio parameter matching and battery parameter matching. The experimental results show that the proposed parameter matching method can accurately match the speed and gradient of electric vehicles, and the matching results are basically consistent with the actual results.

In order to shorten the visualization fusion time of unstructured data and improve the fusion effect, a visualization fusion method of unstructured data based on improved clustering is proposed. The basic situation of unstructured data of power grid is analyzed, and the data acquisition architecture is designed. Based on the collected data, multiple sensors are used to measure the same object. The influence factors are obtained by calculating historical data, historical data fusion results and observation values. The visual fusion objective function is designed, and the influence factor is used to modify the objective function, and the modified unstructured data fusion results are output. The experimental results show that the fusion effect of this method is good, the fusion time is short, and the practical application effect is good.

In order to solve the problems of low data detection accuracy and unbalanced scheduling in traditional multi-channel communication scheduling methods of distribution network, an intelligent multi-channel communication scheduling method based on isolated forest algorithm is proposed. In this method, the isolated forest algorithm is used to calculate the growth path length of isolated tree nodes, and the abnormal scores are denoised to accurately detect the communication data of intelligent distribution network. According to the detection results of communication data, priority division and communication channel load calculation are completed, and multi-channel communication scheduling of intelligent distribution network is realized. Experimental results show that, compared with the traditional multi-channel scheduling method, the proposed method has higher accuracy of communication data detection, and can achieve balanced channel scheduling, which has higher practical application.

Image recognition is widely used in the field of computer vision today. As a kind of image recognition, digit recognition is widely used. Today, the online recognition technology in digit recognition is relatively mature while the offline recognition technology is not. This paper mainly introduces an offline recognition system for handwritten digits based on convolutional neural networks. The system uses the MINST dataset as a training sample and pre-processes the picture with the Opencv toolkit. Then it uses LeNet-5 in the convolutional neural network to extract the handwritten digit image features, repeatedly convolution pooling, and pull the result into a one-dimensional vector. And finally find the highest probability point to determine the result to achieve handwritten digit recognition with the Softmax regression model. The application of this system can greatly reduce labor costs and improve work efficiency, which is of great significance in many fields.

This paper investigates the distributed finite-time consensus problem of double integrator systems with time varying disturbances in absence of velocity information. Based on the continuous homogeneous finite time consensus protocol for the nominal multi-agent systems (MAS), both the discontinuous and continuous integral sliding mode (ISM) protocols are developed respectively by using only the position information of local and neighboring agents. Simulation results validate the effectiveness of the proposed scheme.

Most existing control algorithms for mobile robots are rather complicated yet seldom considering ground sliding nor actuation failures. This paper presents an adaptive tracking control algorithm for mobile robots operating over the slip-ping/skidding surface and at the same fine possibly suffering from actuator faults. The proposed control bears the simple structure of proportion-integrals-differential (PID) in which the PID gains are adaptively self-tuned, completely avoiding time-consuming manual “trial and error” tuning process as usually involved in most traditional PID control methods. The salient features of the proposed control lie in not only its simplicity in design and implementation, but also its ability to cope with modeling uncertainties and actuation faults as well as the sliding impacts. Simulations on butterfly trajectory tracking demonstrate and confirm the superior performance of the developed adaptive PID control as compared with traditional one.

This paper presents a structurally simple and computationally inexpensive PD tracking control scheme for UAVs in the presence of nonparametric uncertainties and actuation faults. Both stability and transient performance are ensured with the proposed method. Furthermore, the resultant PD control is adaptive, robust and fault-tolerant, in which the PD gains are automatically tuned online. Both systematic theoretical analysis and numerical simulation demonstrate the effectiveness of the proposed control design.

The popularity of smartphone makes mobile phone security even more important. We proposed Intelligent Walking Authentication (IWA), a lightweight, non-disturbing and automatically update smartphone authentication scheme. By collecting phone acceleration sensor data and calculate statistical features while walking, gait feature vector is generated in real time and compared with gait feature vector template to complete the authentication. The authentication has low computational complexity and not require large amounts of tagged data as previous work. A success rate of 93.63% is achieved on a 30person walking data set. A 91.00% authentication success rate is achieved on a data set of 11 people real-life simulated scenarios. The experimental results show that IWA can effectively resist the attack behavior in the authentication process and perform well in different locations while only increasing the power by 78.22mW.

Speed up Robust Features (SURF) algorithm is an effective feature point extraction algorithm and its high efficiency and high stability are superior to similar algorithms, so it is widely used in image feature point extraction. However, due to the shortcomings of the SURF algorithm itself, it is easy to produce a mismatch phenomenon when performing feature point matching. When the image to be matched and the template image are quite different, the mismatch phenomenon is particularly obvious. In order to eliminate the mismatch, this paper improves the SURF algorithm by adding the RANSAC algorithm that eliminates the mismatched points. Experimental results show that the improved SURF algorithm can effectively eliminate false matching points.

This work is focused on synthesis of molybdenum oxide (MoO3) by Plasma Enhanced Atomic layer deposition (PEALD) using molybdenum hexacarbonyl (Mo(CO)6) is selected as precursor for Mo and O2 is adopted as precursor for plasma. Ex-situ growth characterizations were carried out by X-ray reflectivity (XRR), scanning electron microscope (SEM), X-ray diffraction (XRD) and X-ray photoelectron spectroscopy (XPS). XRR result indicates the linear growth of the thin films. While amorphous as-deposited film was observed by XRD. XPS and SEM was applied to further analyze the quality of the film. The growth of MoO3 can be layer controllable and have good film continuity. There merits are helpful in further synthesis of MoS2 by sulfurization.

This paper addresses the frequency regulation problem in paralleled inverter-based microgrid. A fully distributed adaptive control scheme is presented without the need for the central computer. With this method the frequency is regulated to its nominal value, while the power sharing of generators is maintained at the same time. By estimating the parameters on power lines adaptively, the distributed generators do not need prior knowledge of the microgrid system. The adaptive nature of the proposed controller yields a stable performance of the paralleled inverter system. Simulation examples illustrate the effectiveness of the proposed control method.

Benefit from the good etching and patterning possibilities and its electrical properties, platinum silicide attracts renewed attention as a suitable candidate for next generation CMOS technologies recently. This work focuses on the effects of the trimethylaluminum (TMA) pretreatment on the PEALD growth of Pt film on Si substrate by using MeCpPtMe3 and ammonia plasma as precursors. The incubation period of ALD Pt was shortened by TMA pretreatment, and the saturation growth rate reached 0.2iA/cycle. X-ray diffraction showed that as-deposited films are strongly preferred orientation of the (iii) plane. The findings are important for obtaining well defined silicide films which would be used in the advanced CMOS source and drain technology.

The Map Matching Problem (MMP) aims to find a real optimal region from a map repository, which is the most similar map to the ideal sample. Though there is a significant difference between MMP and the general Image Matching Problem. The former prefers approximate match and ignores details of edge. Both of them must solve variances of scale, translation and rotation. However, the Scale Invariant Feature Transform (SIFT) is not perfect to match the rotated maps because the number of feature points selected by SIFT is really variant while the image is rotated. This paper presents a simple novel Rotational Invariant Map Matching (RIMM) model that is really invariant to scale, translation and rotation. The RIMM model achieves these invariance abilities based on the inherent, stable, and unique attributes of a map, which are mass center and Primary Gradient Direction. Because these two features are irrelevant to translation, rotation and scale. Our test results show that the RIMM model accurately eliminates variance of translation and rotation. Moreover, The RIMM model can quantitatively evaluate the matched maps by the cosine similarity so that the candidate maps can be ranked and compared objectively.

In this paper, we consider a multi-source single-relay wireless network, where the relay facilitates transmissions of the sources' signals to the destination. We study the relay power allocation among the sources, and use the bargaining theory to model the negotiation among the sources on fair allocation of the relay power. By assigning a bargaining power to each source to indicate its transmission priority, we propose an asymmetric Nash bargaining solution (NBS)-based relay power allocation scheme. The impact of the bargaining powers on the relay power allocation and network performance is analyzed. We show that the proposed scheme addresses the tradeoff between the sum-rate of the network and the fairness among the sources, and can be adapted to meet different requirements in different applications by proper selection of the bargaining powers.

One of the most important topics in software industry is how to utilize the OpenMP 3.0 programming model to improve the execution of irregular and unstructured applications. In this paper, we present an original task scheduling strategy-Hybrid strategy, which is suited to the execution of OpenMP programs on Cell heterogeneous multicore. Hybrid scheduling strategy creates tasks in breadth-first order while executes tasks in work-first fashion during application execution. The former is capable of creating enough tasks, which prevents the worker threads from idling. While the latter guarantees task dependence is freed quickly and consequently, the overhead with respect to task searching is significant decreased. The evaluation, with a variety of Barcelona OpenMP Task Suite, is conducted on a PS3 heterogeneous multicore. And the experimental results indicate that Hybrid policy outperforms the existing work-first and breadth-first scheduling strategies for most irregular and unstructured benchmarks, with speedups from 1.5 to 4.6 when 6 SPEs are used.

This paper considers a multi-user single-relay wireless network, where the relay gets paid for helping the users forward signals, and the users pay to receive the relay service. We study the relay power allocation and pricing problem, and model the interaction between the users and the relay as a two-level Stackelberg game. In this game, the relay, modeled as the service provider and the leader of the game, sets the relay price to maximize its revenue; while the users are modeled as customers and the follower who buy power from the relay. For the relay power allocation among users, we use a bargaining game model to achieve a fair allocation. Based on the proposed fair relay power allocation rule, we then analyze the optimal relay power price that maximizes the relay's revenue, and derive the analytical solution. Simulation shows that the proposed power allocation scheme achieves a higher network sum-rate than the even power allocation, and is fairer than the sum-rate-optimal allocation. We also show that the proposed pricing and power allocation solution is consistent with the laws of supply and demand.

This paper presents a corner matching method based on feature optical flow estimation and weighted Hausdorff distance. First of all, the feature corners are extracted. In order to make the corners distribute evenly, image partitioning and neighboring corner being eliminated are adopted. Secondly, judging from the improved approach of feature optical flow estimation, the local optical flow estimation on the corners can be calculated, rough optical flow vectors are gained and approximate matching of the corners is achieved. At the last, through the introduction of the corner response function, a weighted Hausdorff distance method is proposed. In this way, the corners of the two images can be accurately matched. The experimental results show that the presented method can reduce the computational complexity and raise matching precision, and then the precise moving object tracking is realized.

In this paper, we investigate the relation between eigenvalues of quadratic characteristic matrix and its companion matrix, and some bounds for the quadratic eigenvalues are firstly obtained. Secondly, we transforms quadratic eigenvalue problem (QEP) into an optimization problem, and figure out its eigenvalues was adopted based on a unified particle swarm optimization (UPSO) with dynamic updating. Numerical examples indicated UPSO method has a faster convergence rate, strong adaptability, higher accuracy and so on, which is a better algorithm for solving QEP.

Quantitative study of the characteristics of plants plays an important role in the plants' growth and development research, and non-destructive measurement of the height of plants based on machine vision technology is one of the difficulties. In this paper, a new algorithm which combined three-dimensional computer vision techniques and image processing method, is proposed to solve this problem. We acquired cotton images using one single camera in the non-destructive monitoring system for cotton growth first. Through the pre-processing of the cotton image, the height of cotton is represented by coordinates of two key points on the image. Based on the parameters of the camera and some constraints of the two key points, we can obtain plant height in the world coordinate system. Experimental results show that plant height measurement error range can be controlled in less than 5mm.

Problems as low speed or inaccurate results in the process of line detection with Hough Transform and Improved Hough Transform remain unsatisfactorily solved. This paper puts forward a new algorithm which is based on Improved Hough Transform to speed up the image processing and keep the highest precision. This algorithm transforms the slopes between the suspected points and the known point to angles, then detections single line or multi-lines. The results of experimentation show that, compared with standard Hough transform, this algorithm easier, faster, and real-time. The precise of this algorithm can meet the need of the examination.

Sparse matrix-vector multiplication is a kernel which is widely used in scientific applications. The sparse-data is usually stored in the compressed row storage format, which introduces the irregular reference pattern. It's a problem for the software cache on Cell architecture because the software cache line is always set to a specific size in traditional software cache strategies, which limits cache utilization and increases memory bandwidth overhead. In this paper, we propose an adaptive cache line strategy which continuously adjusts cache line size during SpMV multiplication execution. Therefore, the transferred data size and the execution time are significantly decreased. Moreover, a prefetching scheme is proposed to further improve performance. The evaluation indicates that our adaptive cache line scheme achieves a speedup factor from 2.11 to 3.57 compared to the traditional software cache approach. And the prefetching approach translates into speedup factor up to 3.2 for the SpMV multiplications.

Great volumes of shallow-buried (< 2000m) natural gases have been found in Mesozoic-Cenozoic sedimentary basins in China, which mainly consist of biogases and low-maturity gases. As the two kinds of gases are frequently accumulated in one structure or one horizon, therefore, identification of genetic types of the gases is important for their exploration and development in the basins. Investigation on the gas geochemistry and distribution in different basins, the authors classify the gases into two genetic types, one is biogenetic gas, and the other one is low-maturity gas. The biogenetic gases are subdivided further into two subtypes for their sources, the source rock-derived biogenetic gas and oil derived biogenetic gas. Consideration on burial history of the source rocks, the source rock-derived biogases are divided into primary-buried and secondary-buried biogases, the former is generated from the source rocks in primary burial history, and the latter is from the source rocks in up-rise or secondary burial history. The primary-buried biogases generated from source rocks are mostly distributed in Quaternary basins or modern delta deposits, their accumulations are controlled by reservoir and seal-rock assemblages. The secondary-buried biogas occurs in a basin with down-up-down burial history. The biogas biodegraded from oil is distributed closely with heavy oil pools, and the more the oil biodegraded, the more biogas is accumulated. The low-maturity gases are widely distributed in shallow-buried reservoirs in Meso-Cenozoic basins. Keyword: primary-buried biogas; secondary-buried biogas; oil-degraded biogas; low-maturity gas; gas identification; gas accumulation.

Information fusion technology is applied to blood pressure measurement in this paper. By this means, the dynamic blood pressure can be tested, which is based on pulse transit time. Human ECG, pulse, body temperature and blood pressure information are the subjects investigated, and then the research of the blood pressure measurement is done with Synergetic Theory applied to information fusion. The experimental results show that this method can reduce measurement errors caused by all kinds of factors involved in blood pressure, have achieved the initial target of blood pressure judgment, and provide effective evidences for the correct disease diagnosis and immediate treatment.

In this paper, by employing bivariate cubic C-1 B-splines, a bivariate B-spline finite element method is presented to solve bending problems of rectangular plates. In comparison with analytical solutions, it is found that, for various boundary conditions and different loading conditions, the accuracy of the present numerical method is very satisfactory.

Based on three-layer structural model (ERP/MES/PCS) of process industrial integrated automation, it provides a brief introduction to the manufacturing execution system. The conception and main content of UML is introduced. Combined with quality management system in cement enterprises and modeling tool Visio, modeling process and typical UML views are given.

The stretching dynamics of a semiflexible chain by introducing time-independent tension is presented in this paper. Dissipative particle dynamics is used as the leading method to simulate the stretching behaviors of polymer by introducing the bead-rod or bead-spring type particles. The numerical results show us that in the low tension regime the flexibility can play an important role during the stretching process. It is also can be found that the larger tension leads to the increase of the fraction extension in the intermediate tension regime. And in the high tension regime, the fast equilibrium can be obtained.

The present state of cement industry information system construction and the cement production process feature are briefly exposited and analyzed. On the basis of absorbing advanced thought and technologies such as Industrial IT, ERP and MES, it comes up with cement enterprise information system architecture, being more easier to be put into effect, based on three-layer structure (ERP/MES/PCS) and its functions. Ultimately, it gives an information system solution suitable for Chinese cement enterprises. The feasibility and validity of the solution has been testified in engineering practice.

Cement production process and its administration feature are exposed and analyzed. On the basis of that, it brings forward cement enterprise manufacturing execution system (MES) architecture that centers on real-time database. The design approach of RTDB, design practice and method of cement enterprise MES information integration are significantly researched. Finally a successful realization case is given.

Manufacture execution system is the bridge connecting enterprise resource planning (ERP) and process control system (PCS), the key of integrated automation system of process industry based on ERP/MES/PCS. Reviewing briefly the status of automation and process flow in China's cement businesses, the paper presents architecture of MES for cement industry and describes function of all modules. Meanwhile, information integration and production optimization function of MES are also discussed.

Solder joints experience repeated reverse thermal stress in service, caused by the mismatch in the coefficient of thermal expansion (CTE) between solder and Cu substrate. Lead-free composite solder was fabricated by mechanically mixing Sn-3.5Ag solder paste with Cu reinforcement particles to improve service capability of the base solder alloy. Thermomechanical fatigue (TMF) tests were carried out in environmental chambers. Two temperature profiles, with the same extreme temperature of -40 degC to 125 degC and a 10-minute dwell time at temperature extremes, were applied in the tests. One was a 5-minute ramp time and another was a 20-minute ramp time. Microstructural characteristics and residual mechanical strengths of the solder joints were investigated after 0, 100, 250 and 500 TMF cycles. Composite solder joints showed better TMF performance than the Sn-3.5Ag eutectic solder joints. The results proved that ramp rate was one of the key issues for the damages in solder joints