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In recent years, malware has experienced explosive growth and has become one of the most severe security threats. However, feature engineering easily restricts the traditional machine learning methods-based malware classification and is hard to deal with massive malware. At the same time, the dynamic analysis methods have the problems of complex operation and high cost, which are not suitable for efficiently classifying large quantities of malware. Therefore, we propose a novel static malware detection method based on this study’s AlexNet convolutional neural network (CNN). Unlike existing solutions, we convert all malware bytes into color images, propose an improved AlexNet architecture, and solve the unbalanced datasets with the data enhancement method. Extensive experiments are performed using the Microsoft malware dataset and the Google Code Jam (GCJ) dataset. The experimental results show that the accuracy of the Microsoft malware dataset reaches 99.99%, and the GCJ dataset reaches 99.38%. We also verify that our method can better extract the texture features of malware and improve the accuracy and detection efficiency.

Hydraulic flushing drilling technology can not only improve the efficiency of high-pressure and low-permeability geological reservoir coalbed methane drainage but also effectively reduce the probability of coal and gas outburst disasters through pressure relief. The main mechanism of this technology is to expand the borehole diameter through hydraulic flushing measures, increase the strain of the coal around the borehole, and increase the development of cracked pores, to improve the permeability of the coal seam and realize the dual reduction of ground and gas pressure. However, in the actual application process, the interaction mechanism among the stress field, the structure field, and the seepage field is still not clear, and there is no clear method to accurately determine the pressure relief range based on the pressure relief mechanism in order to carry out reasonable drilling arrangements. Therefore, this article comprehensively uses laboratory experiments, numerical simulations, and field practices to fully explain the hydraulic flushing pressure relief mechanism and proposes a method to accurately determine the pressure relief range based on the radial line strain law. The results based on radial line strain showed that the effective relief radius expands to 0.86 m once adopting the Φ579 mm hydraulic flushing borehole compared to Φ160 mm; the borehole’s equivalent diameter of drilling field #11 is 2 to 3 times than that of #10 and 1.2 times the average CBM extraction amount. Therefore, as the borehole diameter increases, the permeability and radial line strain of the coal around the borehole increase significantly, but the tendency of the increase in permeability decreases with increasing vertical stress. The findings of this study can help for a better understanding of the pressure relief and permeability enhancement mechanism of hydraulic flushing, and the method of determining the pressure relief range based on radial strain can also provide a new way for other mines to practice ideas.

Due to the complicated coalbed methane (CBM) occurrence conditions and the diverse geological structures in China, the promotion and application of the coal and gas simultaneous extraction technology have been seriously restricted. In view of this, this paper chooses Qingdong Coal Mine protection layer mining and CBM extraction field practice as the research background. Firstly, based on the similar material simulation experiment that simulates coal mining, the dynamic changing pattern of a mining field’s overburdened strata and corresponding stress are obtained, the relationship between gas desorption and stress can then be clarified. Further, with the help of the fractal theory and box counting method, the fracture development characteristics of the overlying strata are quantitatively described on the basis of experimental images. Finally, by building a model for calculating the penetrability coefficient of coal seam based on fractal dimension of mining fissure and analyzing the relationship between fissure development and fractal dimension, the gas migration law and the fissure development areas of #7 and #8 overburden strata where CBM concentrates can be revealed and determined. According to the orientation of the area mentioned above, the location of the CBM pumping field in relation to the coal seam roof and the arrangement of CBM extraction boreholes can be optimized, which make CBM extraction efficient. Meanwhile, the risk of coal and gas outburst is significantly reduced when the CBM concentration is controlled within 0.2% to 0.6% outside the corner of the working face and 0.1% to 0.35% in return flow, which is lower than 0.8%, the threshold of CBM concentration.

A time delay estimation algorithm based on three-order cumulant with the different symmetry of modulation signal between training sequence and information sequence of AIS (Automatic Identification System) is presented, which aims to overcome the large time delay and strong noise in the receiver side of AIS. Theoretical analysis and simulation results show that this algorithm successfully suppresses the influence of Gaussian noise. Moreover, under non-Gaussian and correlative noise, it can also obtain a fine estimated performance. Simulation results show that this algorithm is superior to the correlative and data-aided time delay estimation ones.

Two-phase flow instability may occur in nuclear reactor systems, which is often accompanied by periodic fluctuation in fluid flow rate. In this study, bubble rising and coalescence characteristics under inlet flow pulsation condition are analyzed based on the MPS-MAFL method. To begin with, the single bubble rising behavior under flow pulsation condition was simulated. The simulation results show that the bubble shape and rising velocity fluctuate periodically as same as the inlet flow rate. Additionally, the bubble pairs’ coalescence behavior under flow pulsation condition was simulated and compared with static condition results. It is found that the coalescence time of bubble pairs slightly increased under the pulsation condition, and then the bubbles will continue to pulsate with almost the same period as the inlet flow rate after coalescence. In view of these facts, this study could offer theory support and method basis to a better understanding of the two-phase flow configuration under flow pulsation condition.

How to verify the integrity of outsourced data is an important problem in cloud storage. Most of previous work focuses on three aspects, which are providing data dynamics, public verifiability, and privacy against verifiers with the help of a third party auditor. In this paper, we propose an identity-based data storage and integrity verification protocol on untrusted cloud. And the proposed protocol can guarantee fair results without any third verifying auditor. The theoretical analysis and simulation results show that our protocols are secure and efficient.

Due to the input time-delay existing in most thrust systems of the ships, the robustH∞controller is designed for the ship dynamic positioning (DP) system with time-delay. The input delay system is turned to a neutral time-delay system by a state-derivative control law. The less conservative result is derived for the neutral system with state-derivative feedback by the delay-decomposition approach and linear matrix inequality (LMI). Finally, the numerical simulations demonstrate the asymptotic stability and robustness of the controller and verify that the designed DP controller is effective in the varying environment disturbances of wind, waves, and ocean currents.

Mobile phones and personal digital assistants are becoming increasingly important in our daily life since they enable us to access a large variety of ubiquitous services. Mobile networks, formed by the connection of mobile devices following some relationships among mobile users, provide good platforms for mobile virus spread. Quick and efficient security patch dissemination strategy is necessary for the update of antivirus software so that it can detect mobile virus, especially the new virus under the wireless mobile network environment with limited bandwidth which is also large scale, decentralized, dynamically evolving, and of unknown network topology. In this paper, we propose an efficient semi autonomy-oriented computing (SAOC) based patch dissemination strategy to restrain the mobile virus. In this strategy, some entities are deployed in a mobile network to search for mobile devices according to some specific rules and with the assistance of a center. Through experiments involving both real-world networks and dynamically evolving networks, we demonstrate that the proposed strategy can effectively send security patches to as many mobile devices as possible at a considerable speed and lower cost in the mobile network. It is a reasonable, effective, and secure method to reduce the damages mobile viruses may cause.

Considering the problem of dynamic positioning systems for the slowly varying disturbances, a parametrically adaptive observer is presented. The peak frequency of observer is adjusted on-line by autoregressive (AR) spectral estimation; other parameters of observer are optimized using particle swarm optimization (PSO). The peak frequency can be calculated by spectral analysis of the pitch, roll, and heave measurements. In the spectral estimation, Levinson-Durbin algorithm is used to solve the Yule-Walker equations. Finally, the computer simulation is given to demonstrate the effectiveness of the proposed method.

Summary Since sensitivity analysis provides information on changes of the system dynamics with respect to changes of system parameters, it has been long recognized as an important tool for power system small-signal stability analysis and controller designs. Sensitivity analysis is now much more important due to all the anticipated changes of future power systems, so more efficient and feasible methods are needed. The current sensitivity analysis methods are either simulation based or eigenvalue based. The eigenvalues and/or the time domain trajectories of the investigated system are solved for scenarios both before and after the parameter changes to evaluate the impacts of these changes on the system dynamics. However, both methods are actually numerically based, so often insufficient in fully revealing system physical characteristics. This paper analyzes the drawbacks of the available methods for analyzing the dynamic impacts of parameter changes in a power system and then develops a feedback-based model for sensitivity analysis. The model is easier to identify the dynamic interactions of components; meanwhile, it also offers a new perspective on sensitivity analysis from the frequency domain. Case studies of increasing complexity demonstrate fully that the application of the proposed method reveals new insights on power system dynamics that conventional methods could not do.