Earticle

The law is the most powerful weapon to safeguard national stability and ensure flourishing of all causes as well as an instrument to protect the rights and interests of the masses, therefore, the just and accurate use of legal provisions is of crucial importance. With the increase of informatization level of the legal industry itself, more and more services in legal affairs are provided in information-based forms, and there is a large number of unstructured information in such business data. It’s a problem the legal industry needs to tackle in information management to rapidly acquire valuable content from the massive unstructured data and make use of such content. Based on analysis of problems arising in existing laws and regulations informatization system, this paper comes up with solution of a legal affairs information service platform based on cloud computing, UIMA, semantics, big data and Chinese word segmentation. This paper also proposes the four-layer technical framework solution on the basis of the design of integration and management method of unstructured data of heterology and isomerism, analyzing and processing method of unstructured data, semantics based unstructured information retrieval method and construction and maintenance method of ontology library. It also provides detailed introduction to the realization of the combination of big data and cloud computing and its application in this information platform by virtue of designing UFS - a distributed file system, MapReduce - a batch processing technology and BigTable - a distributed database. Data acquisition and expanded data analysis can be conducted by making use of the expandable UIMA framework and the sequential indexing of data content and analysis results can be materialized by means of applying Lucene indexing technology. With regard to information retrieval, the concept of ontology is introduced on the basis of traditional search model and a new search model based on domain ontology is proposed. IKAnalyzer 3.x is proposed to facilitate Chinese word segmentation. By taking advantage of such information service platform, legal affairs enterprises can effectively integrate structured and unstructured information resources and implement the storage, analysis, retrieval and decision-making applications of business data content.

Address assignment is a key challenge in ad hoc networks due to the lack of infrastructure. For autonomous addressing routing protocols require a distributed and self-managed mechanism to avoid address collisions in a dynamic network with fading channels and joining/leaving nodes. The propose and analyze a lightweight hybrid protocol that configures mobile ad hoc nodes based on a distributed address database stored in filters i.e. unreliable wireless links by utilizing the local path diversity that reduces the control load and makes the proposal robust to packet losses and network partitions. For evaluate the performance of our protocol, considering joining nodes and network initialization. Simulation results show that our protocol resolves all the address collisions and also reduces the control traffic when compared to previously proposed protocols. Hybrid routing protocol remarkably improves the packet delivery ratio, while maintaining high energy efficiency and low delivery latency.

Previously a novel chaos M-ary digital communication method based on spatiotemporal chaos Hamilton oscillator has been proposed. Without chaos synchronization circumstance, It has performance improvement in bandwidth efficiency, transmission efficiency and anti-white- noise performance compared with traditional communication method. In this paper, the formula for the design of the boundary of zone dividing demodulator in additive white Gaussian noise is derived, besides, the problem about how to determine the boundary of zone dividing demodulator in additive colored noise is deeply studied; Then a solution to construct anti-colored-noise chaos M-ary communication system is proposed, in which a pre-distortion filter is added after the chaos baseband modulator in the transmitter and whitening filter is added before zone dividing demodulator in the receiver. Finally, the chaos M-ary communication system based on Hamilton oscillator is constructed and simulated in different channel noise. The result shows that the proposed method in this paper can improve the anti-colored-noise performance of the whole communication system.

Such technical features of ANT as protocol stack structure, data frame format and channel configuration are first introduced in the paper, and then targeted at the groups that need real-time medical monitoring, an ANT protocol-based wireless network medical monitoring system is established to realize real-time acquisition of corresponding physiological data. This system adopts the chip NRF24AP2 compatible with ANT protocol as the core component of wireless network nodes of the medical monitoring system to conduct design of software and hardware. It is shown through power consumption analysis and communication reliability testing of the wireless network that this network features low power consumption under the premise of operating reliability, applicable to various applications giving priority to low power consumption.

Detection of forest fire is a complex and vital process. The system must be accurate and the response of the system must be fast. The main parameter to be measured in case of forest fire is temperature. Hence it is important to select appropriate temperature sensor considering the various parameters and real time scenario. In this paper selection of an appropriate temperature sensor for forest fire detection system is done based on real time experiment. Another important aspect of this system is the network for transmission of sensed data to base station for analysis. The network employed must be wireless and it must be secure, reliable, robust, easy to implement and cost effective. The loss of data or latency in the network can results in a disaster. AHP is used to select an appropriate network with higher throughput and lower latency.

ForCES is a new open programmable architecture, it separates control and forwarding, it also abstracts resources of Forwarding Elements (FE) into some Logical Function Blocks (LFB), Control Element (CE) can reconfigure the forwarding function of FEs by recomposing their LFB chains. Firstly, A SDN architecture based on ForCES is proposed. Then, based on the formalization of the concept of LFB and the traditional I/O matching algorithm, an LFB chain composition method is proposed. This method can combine a series of LFBs to an LFB chain according to special application request. Based on the LFB chain composition algorithm, an improved algorithm is proposed, which can improve the composition efficiency. At last, an example is provided to illustrate how this method works, and a simulation is given to compare the efficiency of the base algorithm and the improved algorithm.

In cognitive radio networks, spectrum sensing is used to detect the spectral state of authorized users. In particular, upon detecting primary users (PUs) appearances, Secondary User (SU) vacates the channel and performs the spectrum handoff. In order to protect the PUs, interference constrains and reserved channel are considered. If the SU can’t find any idle channel after the whole spectrum sensing, it carries out spectrum handoff to the reserved channel. In addition, spectrum handoff delay is derived. The nonlinear constrained optimization problem for the presented approach is formulated. In special, the goal is to minimize the SU’s handoff delay while protecting the PU from the interference. Numerical results discuss the impact factors on the handoff delay. Lower interference constrains can not only protect the PUs, but also can provide the lower handoff delay for SUs.

The paper proposes a vertical handoff algorithm based on differential pre-decision and improved utility-function method. This algorithm is relied on utility function to improve its two parameters, which are received signal strength and bandwidth, by using their normalized values to determine the target network. Then, it enters judgment stage of vertical handoff, where introduce differential prediction algorithm that has good accuracy to further constraint the switching decision through taking a prediction of the RSS into account. The purpose is to reduce the impact of ping-pong effect and to obtain accurate handoff. The paper applies MATLAB software to gain the simulated analysis based on this algorithm, And compares the performance of this switching algorithm with utility function algorithm to demonstrate its priority. Simulation results shows that the proposed algorithm can significantly reduce the impact of the ping-pong effect and improve the switching efficiency and the system performance as well in heterogeneous network environments.

This abstract demonstrates simple, low cost and high gain microstrip array antennas with suitable feeding technique and suitable dielectric substrate for applications in the GHz frequency range. The objective of this paper is to design, and fabricate a 16 element rectangular microstrip patch array antenna. Therefore, a novel particle swarm optimization method based on IE3D was used to design an inset feed linearly polarized rectangular microstrip patch antenna array with sixteen elements. .Initially we set our antenna as a single patch and after evaluating the outcomes of antenna features; operation frequency, radiation patterns, reflected loss, efficiency and antenna gain, we transformed it to a 2x1 array. Finally, we analyzed the 2×2 array, then 4×2 array and finally 4 × 4 array to increase directivity, gain, efficiency and have better radiation patterns. The simulation has been performed by Zeland software version 14.0 and the desired antenna provides a return loss of -42.154dB at 2.45 GHz by using RT Duroid dielectric substrate with Єr= 2.45 and height , h= 1.58mm. The gain of the antenna is found to be 19.455 dBi and the side lobe is maintained lower than the main lobe. Since the resonant frequency of these antenna is around 2- 4 GHz, so these are suitable for S – band applications and can be used in WLAN communication systems.

Due to the question about the distribution of the randomness, mobility and mutual interference between nodes in the wireless networks may be difficult to achieve power control accurately. Therefore, propose a power control algorithm based on minimizing interrupt probability. The algorithm which be based on random geometric network model, under ensuring receiving in the receiver by getting the SIR value, adjusts transmit power. Simulation results show that the algorithm not only can solve the problem of the distribution of the nodes in a wireless net- work, can also according to the channel decline, transmitter was adjusted dynamically in real time. Deduce approximate expression of Interrupt probability transmission capacity. Under meet minimum interrupt probability and maximum transmission capacity, deduce power control expression. By this algorithm, the outage probability decreased by 14.8%, the transmission capacity is increased by 15.6%.

The increase in demand for high data transmission rates and channel capacity has led to the evolution of Free Space Optical (FSO) communication links. In this paper, performance analysis of a high-speed free space optical communication link has been observed. The performance of 10 Gbps FSO link has been evaluated on the basis of Q Factor, SNR ratio, and total power of the received signal for a link distance ranging from 800 m to 2000 m at different power levels of data transmission and different levels of atmospheric attenuation. It has been seen from the results that the value of SNR of received signal lies in the range from 45 dB to 14 dB and 48 dB to 10 dB for the transmission power of 6 dBm and attenuation of 25 dB respectively. Also, the value of the total power of received signal lies in the range of -52 dBm to -73 dBm and -30 dBm to -60 dBm for the transmission power of 6 dBm and attenuation of 25 dB respectively.

This paper presents design and analysis of a novel S-shaped left-handed material based on the equivalent circuit theory. The effective permittivity and effective permeability of the novel S-shaped left-handed material are both negative in the range from 5GHz to 7GHz. A conventional microstrip antenna is designed following the empirical formula, and a high gain microstrip antenna is designed with use of the novel S-shaped left- handed materials. The performances of the conventional antenna and the modified antenna are simulated by HFSS software. The simulation results show that the gain of the antenna increased by 3.94dB, and the half power beam width decreased by 38.9°. Therefore, it is concluded that the performance of microstrip antenna can be improved by using left-handed materials.

Recent advancements in MEMSs technology, VLSI and Wireless Private Area Networks have contributed in developing enormous interest in wireless sensor networks by both academia and research community.WSN is formed by large number of small, cheap and low energy sensors that work together in monitoring regions. WSN find its application in many areas such as object tracking, disaster relief and smart environments. Most of these applications need location awareness of sensor nodes to estimate the origin of events. Localization has remained a challenge in successful implementation of WSN and so, it is a hotspot of research. Range free localization techniques are given lot of importance in recent research works because they suit well for low cost, low energy and less infrastructure requirements of WSN and also involve lesser computation complexity. DV-HOP is one of the range free techniques that have attracted researchers’ interest. In this paper, DV-HOP algorithm is implemented by deploying anchor nodes in a structured way at various radio ranges. Structured deployment of anchors give more accurate location estimates than random deployment that was followed in basic DV-HOP, which has been demonstrated in a detailed manner by the simulation results.

The vibration signal is nonstationary and it is difficult to acquire the sample with typical fault. An improved ACO algorithm based on adaptive control parameters is introduced into SVM model to propose a new fault diagnosis (IMASFD) method in this paper. In the IMASFD method, the EMD method is used to decompose fault vibration signal into IMF components, the energy of IMF components is selected to construct the fault feature vectors. Then the adaptive controlling pheromone strategy, adaptive controlling stochastic selection threshold strategy and dynamic evaporation rate strategy are used to improve the basic ACO algorithm. The improved ACO algorithm is used to optimize the parameters of SVM model in order to obtain the optimal values of parameter combination in the SVM model. And a new fault diagnosis (IMASFD) method is proposed. Finally, the proposed IMASFD method is applied to the test data from bearing data center of CWRU. The experimental results show that the proposed method can accurately and effectively realize high precision fault diagnosis of rolling bearing, and has strong robustness and generalization ability, provides an effective method for realizing fault diagnosis of rolling bearing.

The tradeoff between energy efficiency (EE) and spectral efficiency (SE) under the smart grid with joint energy harvesting and grid power supply is considered. The price factor in economics is used to propose the economic EE and SE. Then a new EE-SE tradeoff metric called the EE-SE adaptive tradeoff (ESAT) is built under the fluctuating harvesting energy. Furthermore, the offline optimization problem is put forward and the solution is discussed. The offline solutions based on the branch-and-bound algorithm and the Lagrange dual decomposition method are discussed to analyze the influence of renewable energy quantity on the proposed structure. Numerical results indicate that the proposed ESAT framework is efficient to the tradeoff between EE and SE.

Compressive Data Gathering (CDG) has recently emerged to provide energy efficient data aggregation in wireless sensor networks (WSNs). Existing CDG is done by forming a span-tree from all sensors to the data sink, which leads to a lot of energy consumption in maintain this tree. In this paper, we present a clustering based CDG scheme for large-scale WSNs. This scheme reduces traditional network communication cost by introducing in-network compression and recovers sensory data accurately by using compress sensing theory. With extensive simulation, we demonstrate that our scheme prolongs nearly 45% network’s lifetime compared with the Hybrid compressive data gathering schemes.

The advent multimedia real time application demands large volume of data to execute the required quality of service (QoS). Existing centralized approach lacks support its suitability in terms of dynamic mobility, scalability, reliability, seamless connectivity, etc. This motivates host based dynamic and distributed mobility management (DMM) solution for MIPv6 protocol to execute an intelligent mobility operation at an access network level rather centralized. The presented fully DMM architecture (FDMM) is implemented for integrated WLAN and WiMAX networks, where the entire mobility functions are distributed at access level in order to achieve a fast exchange of signaling information during handover operation. In addition, IEEE 802.21 media independent handover (MIH) standard is also adopted in the proposed work to execute seamless handover procedures across a heterogeneous background. The performance analysis of MIH-FDMM is compared with existing centralized mobility management (CMM) scheme in terms of handover delay, throughput, packet loss, etc. for real time traffic classes (constant and variable bit rate (CVBR)). Simulation result proves that the combined MIH-FDMM significantly minimize the handover delay, packet loss ratio and thus accomplishes seamless service for both real time and non-real time QoS efficiency.

In this paper, we conduct research on the wireless sensor network management methods based on the runtime model. With the deepening of the research, scalability and maintainability of wireless sensor network has become an important target of its application promotion. Consider that the nodes randomly distributed monitoring area, looking for a complete coverage of this area several disjoint nodes which uses genetic algorithm to optimize the network survival time nodes and corresponding coverage. From the point of view of software engineering, most of the specific software system knowledge hidden in the program and document, the model as the main content of the document and procedures of high-level abstractions. The management of the network is urgently needed. As the additional research, we also conduct theoretical analysis on the wireless sensor network security enhancement methodology with the tradition game theory and mathematical optimization approaches which will be meaningful. Game theory is on the interaction between much of decision-making behavior has, according to the different subjects in the control information and the cognition of their own capabilities which will be a novel method for the analysis. The numerical simulation shows that our method performed better compared with other related approaches. In the future, more research will be conducted to polish the current method.

With the development of sensor technology, network technology, embedded control technology and wireless communication technology, the application of wireless sensor networks (WSN) has become more and more widely. Wireless sensor networks have been named the most influential and important technology of the world in twenty-first Century. In wireless sensor networks, data fusion is an important research branch. In this paper, a data prediction model of wireless sensor network based on weight improved particle swarm optimization neural network algorithm is proposed. In view of the deficiency of the traditional BP neural network model, this paper combines with the characteristics of the data prediction model, and the BP neural network model is improved and integrated. After that, we train the neural network's sample set, and add the momentum item to correct the weight, so that the neural network can be predicted more quickly and accurately. The main idea of this paper is to predict the future data based on the historical data which are collected by sensor nodes, so as to achieve the purpose of reducing the amount of data transmission in the network and saving the energy of nodes. Finally, the experimental results show that the improved particle swarm optimization algorithm based on weight improved particle swarm optimization neural network algorithm has higher accuracy than the multiple regression method and the grey prediction method. In addition, the method can be used to effectively save energy in wireless sensor data transmission.

Infrastructure as a Service (IaaS) is one of the three important fundamental service models provided by cloud computing. It provides users with computing resource and storage resource in terms of virtual machine instances. Because of the rapid development of cloud computing, more and more application systems have been deployed on the IaaS cloud computing platforms. Therefore, once anomalies incur in the IaaS cloud computing platforms, all the application systems cannot work normally. In order to enhance the dependability of IaaS cloud computing platform, a virtual machine instance anomaly detection system is proposed for IaaS cloud computing platform to detect virtual machine instances that exhibit abnormal behaviors. The proposed virtual machine instance system consists of four modules that are the data collection, the data transmission, the data storage, and the anomaly detection. In order to reduce the computing complexity and improve the detection precision, the anomaly detection module introduces the principal components analysis to reprocess the collected data and then adopts the Bayesian decision theory to detect the abnormal data. Experimental results show that the proposed virtual machine instance anomaly detection system is effective.

Long Term Evolution (LTE) is an advanced standard of the mobile communication systems. LTE is a fourth generation technology which is expected to provide mobile broadband platform for services in innovation in the foreseeable future. It is a next generation standard by 3rd Generation Partnership Project (3GPPP). In this paper the analysis of physical layer (PHY) of LTE transceiver in downlink and uplink transmissions is done. Simulations of the physical layer of LTE transceiver are obtained using Mathworks LTE System Toolbox. To show the performance of LTE transceivers in Physical Downlink Shared Channel (PDSCH) and Physical Uplink Shared Channel (PUSCH) simulation results are being presented. Measurements of Bit Error Rate (BER) and throughput are respectively obtained for different simulation configurations.

In order to discuss different types of network anonymity and the correlations among them, this paper separates network anonymity into two variables on the basis of subject object dichotomy. One is network technical anonymity, referring to the amount of information concealed that lead to difficulties in identifying the subject; the other is perceptive anonymity, which means how anonymous one perceive him/herself has been. Then the author explores how to measure these variables and set up a test model to see if there is any causal relation between them. The data was collected from Sina Weibo, and it is intended for empirical test. This thesis proved that there is an obvious causal relation between the two types of anonymity.

In this paper, the performance of the single-estimation and multiple-estimation is investigated in multiple-input multiple-output (MIMO) Rician flat fading channels using the traditional least squares estimator and the Bayesian minimum mean square error estimator. In high-speed mobile environment, relatively severe channel conditions change, at this point, the sender is difficult to obtain more accurate of the instantaneous channel state information, for the implementation of adaptive MIMO transmission under this scenario. The MIMO techniques can be combined with space-time coding technique for coding diversity gain and also can use a simple multiplexing transmission in order to improve the transmission rate. The pseudo random sequence is certain, but it has many properties similar to that of the random binary data. Such as any two pseudo random sequence of cross correlation is small. In the research, we combine the basic theory of the state-of-the algorithm to propose our method. In the experimental part, we compare our method with other related state-of-the-art algorithms. The result proves the effectiveness and feasibility of the proposed method. In the near future, we plan to conduct more literature review and theoretical analysis to modify and optimize our current method.