Advanced Materials Research Vols. 756-759

Abstract: Due to the android platform is open source, more and more developers and manufacturers to use it. At the same time its security attracts more and more challenges, it is vulnerable to mobile phone virus attacks. In order to solve these problems, we should detect the files in the phone. Because the Boyer-Moore algorithms efficiency is higher than others, so we use it in android application intrusion detection. First we should set up a virus signature library, and store these signatures in the SQLite Database. Then scanning system of documents carries on the analysis and extraction corresponding feature codes, and use the BM algorithm to match them with virus signature, and we can find the viruses. What is new and original in this paper is that the efficiency of intrusion detection is higher.

Abstract: Among preemptive real-time uniprocessor scheduling algorithms, many researches, such as optimal and heuristic algorithms, considers only one task attribute and neglects also the variation of attributes. To understand the relations between task attributes and scheduling success ratio, we first define the sensitivity of scheduling success ratio to task attributes. Sensitivity means the intensity of variation of scheduling success ratio as task attributes varies. The paper analyzes the sensitivities of scheduling success ratio to arrival time, execution time, deadline and laxity respectively, which have close relations with scheduling. Based on the definition of sensitivity, we also define attributes influence on scheduling success ratio, which is that the greater the influence, the higher the ratio. The essence of dynamic scheduling is a scheduling based on priority, with each dynamic algorithm matching a priority table, and vice versa. It is also much easier to infer the algorithm from the priority table, which can consider several task attributes. As priority table has various designs, it can correspond to a lot of algorithms, among which, many are inefficient. In order to deal with this kind of problem, we propose a new priority table design PTBM combining deadline and laxity based on the analysis of sensitivity and influence, which makes that a task with small deadline and large laxity has higher priority. We compare PTBM with EDF, LLF and PTD through simulation. The results verify the analysis of sensitivity and influence, and it also shows that PTBM outperforms on scheduling success ratio. It needs further exploration to design more efficient priority table by analyzing more task attributes influence on scheduling success ratio, which includes criticalness, task type and so on.

Abstract: Antenna sidelobe cancellation is effective method to repress radar sidelobe jamming. This paper analysed the function and characteristics completely based on the principle of sidelobe cancellation, and look for jamming method more effective according to the weakness and technique crux. The results indicate that the adaptive side lobe cancellation technique can effectively antagonize the active jamming.

Abstract: The definition of the cold chain logistics and the problem of the agricultural cold chain logistics are introduced. According to the characteristics of cold chain logistics, exploring the cold chain logistics distribution path optimization method. Based on the model of the agricultural products cold chain logistics distribution routing optimization, particle swarm optimization algorithm is constructed to solve the optimization problem. Taking an example, the results have been conducted finally to demonstrate the effectiveness of the algorithm for agricultural products cold chain logistics distribution routing optimization problem.

Abstract: Accurate estimation of the received signal strength indicator (RSSI) from a set of sequentially measured ones is essential for a number of practical applications including link quality evaluation for sensor network routing, indoor wireless localization and more recently, handover in health monitoring systems. This paper develops a simple and robust RSSI estimation algorithm that can effectively mitigate the magnitude variation in the RSSI measurements due to the combined effects of fast fading and non-line-of-sight (NLOS) signal propagation. The new method is based on the robust M-estimator and we propose a simple approach that requires bisection search only to obtain the robust RSSI estimate. Computer simulations corroborate the validity of the theoretical developments and demonstrate the superior performance of the proposed technique over commonly adopted RSSI estimation methods including the simple moving average, the discrete Kalman filter and the exponential smoothing.

Abstract: The switch is applied into topology discovery areas has become a hot research topic in network management technology. Through summarizing many defects of the SNMP (simple network) for the link layer discovery protocol, this paper presents a new topology discovery algorithm based on self-learning switch MAC. Research on the algorithm is about assumptions, definitions, principles and process. Through compare advantages and disadvantages in SNMP and MACs self-learning, the theoretical support will be provided for other scholars in the field of network management.

Abstract: Digital Signal Processing technology is an important tool for modern signal processing. The speedy development ARM embedded processor has powerful computed capability for digital signal processing algorithms. The paper provides a common hardware platform in recent years. In this paper, used assemble language to realize the algorithms and FIR Filter based on ARM-Linux embedded environment. The results shown that the ARM can quickly and efficiently complete a series of digital signal processing algorithms. Digital signal processing algorithm on ARM embedded system provides an effective way.

Abstract: Process of face detection and face feature location on sequence images is analyzed in this paper. Firstly, designer image is captured. Secondly, color threshold method is used to detect whether the image containing human face. thirdly, after above detection, if a human face existing, the Adaboost algorithm based on improved weight update is used to locate facial feature parts. Location on facial feature parts is premise of designing facial image and foundation for realization of intelligent character design system.

Abstract: Linear value function approximation with binary features is important in the research of Reinforcement Learning (RL). When updating the value function, it is necessary to generate a feature vector which contains the features that should be updated. In high dimensional domains, the generation process will take lot more time, which reduces the performance of algorithm a lot. Hence, this paper introduces Optional Feature Vector Generation (OFVG) algorithm as an improved method to generate feature vectors that can be combined with any online, value-based RL method that uses and expands binary features. This paper shows empirically that OFVG performs well in high dimensional domains.

Abstract: Based on traditional LMS algorithm, variable step LMS algorithm and the analysis for improved algorithm, a new variable step adaptive algorithm based on computational verb theory is put forward. A kind of sectorial linear functional relationship is established between step parameters and the error. The simulation results show that the algorithm has the advantage of slow change which is closely to zero. And overcome the defects of some variable step size LMS algorithm in adaptive steady state value is too large.