Lithium-ion batteries are the main power supply equipment in many fields due to their advantages of no memory, high energy density, long cycle life and no pollution to the environment. Accurate prediction for the remaining useful life (RUL) of lithium-ion batteries can avoid serious economic and safety problems such as spontaneous combustion. At present, most of the RUL prediction studies ignore the lithium-ion battery capacity recovery phenomenon caused by the rest time between the charge and discharge cycles. In this paper, a fusion method based on wasserstein generative adversarial network (GAN) is proposed. This method achieves a more reliable and accurate RUL prediction of lithium-ion batteries by combining the artificial neural network (ANN) model which takes the rest time between battery charging cycles into account and the empirical degradation models which provide the correct degradation trend. The weight of each model is calculated by the discriminator in the wasserstein GAN model. Four data sets of lithium-ion battery provided by the NASA Ames Research Center are used to prove the feasibility and accuracy of the proposed method.

In the traditional method, the software quality is measured by various metrics of the software, such as decoupling level (DL), which can be used to predict software defect. However, DL, which treats all the ?les equally, has not taken file importance into consideration. Therefore, a novel software quality metric, named as improved decoupling level (IDL), based on the importance of documents was proposed. First, the PageRank algorithm was used to calculate the importance of ?les to obtain the weights of the dependencies, and then defect prediction models was established by combining the software scale, dependencies, scores and software defects to assess the software quality. Compared to most existing module-based software quality evaluation methods, IDL has similar or even superior performance in the prediction of software quality. The results indicate that IDL measures the importance of each ?le in the software more accurately by combining the PageRank algorithm in DL, which indirectly re?ects the quality of software by predicting the bug information in software and improves the accuracy of prediction result of software bug information.

The concept of dense small cell has been recently emerged as a promising architecture that can signi?cantly improve spectrum efficiency and system capacity. However, it brings frequent handover for user equipment (UE). Furthermore, this will bring a great deal of signaling overhead to the core network. Virtual technology has been received widespread attention for solving this problem. Its essence is to form virtual cells by clustering various terminals properly. The local mobility management proposed recently is based on the virtual technology. Therefore, the formation process of virtual cells is the basis for the research in local mobility management. So clustering scheme for dense small cell network has been studied in this paper, and a maximum benefit merging algorithm based on undirected weighted graph has been proposed. There are X2 interfaces between the cluster head and each of cluster members within the same cluster. The cluster heads manage the handover among cluster members acting as the local anchors. The proposed clustering scheme is useful for local mobility management. The simulation results show that the proposed clustering algorithm can decrease the signaling overhead more than 70% and 20% compared with the non-clustering algorithm and other clustering algorithms respectively.

Opportunistic routing (OR) could adapt to dynamic wireless sensor networks (WSNs) because of its inherent broadcast nature. Most of the existing OR protocols focus on the variations of propagation environment which are caused by channel fading. However, a few works deal with the dynamic scenario with mobile nodes. In this paper, a mobile node (MN) aware OR (MN-OR) is proposed and applied to a WSN in the high-speed railway scenario where the destination node is deployed inside a high speed moving train, and the MN-OR not only considers the mobility of node but also utilizes the candidate waiting time induced by the timer-based coordination scheme. Specifically, to reduce the number of duplicate transmissions and mitigate the delay of information transmission, a new selection strategy of the candidate forwarders is presented. In addition, two priority assignment methods of the candidate forwarders are proposed for the general relay nodes (GRNs) and the rail-side nodes (RSNs) according to their different routing requirements. Extensive simulation results demonstrate that the proposed MN-OR protocol can achieve better network performances compared with some existing routing schemes such as the well-known Ad-hoc on-demand distance vector routing (AODV) and the extremely opportunistic routing (ExOR) protocols.

Aiming to realize fast and accurate fault diagnosis in complex network environment, this article proposes a set of anomaly detection algorithm and intelligent fault diagnosis model. Firstly, a novel anomaly detection algorithm based on time series analysis is put forward to improve the generalized likelihood ratio (GLR) test, and thus, detection accuracy is enhanced and the algorithm complexity is reduced. Secondly, the intelligent fault diagnosis model is established by introducing neural network technology, and thereby, the anomaly information of each node in end-to-end network is integrated and processed in parallel to intelligently diagnose the fault cause. Finally, server backup solution in enterprise information network is taken as the simulation scenario. The results demonstrate that the proposed method can not only detect fault occurrence in time, but can also implement online diagnosis for fault cause, and thus, real-time and intelligent fault management process is achieved.

NAND flash chips have been innovated from two-dimension (2D) design which is based on planar NAND cells to three-dimension (3D) design which is based on vertical NAND cells. Two types of NAND flash technologies–charge-trap (CT) and floating-gate (FG) are presented in this paper to introduce NAND flash designs in detail. The physical characteristics of CT-based and FG-based 3D NAND flashes are analyzed. Moreover, the advantages and disadvantages of these two technologies in architecture, manufacture, interference and reliability are studied and compared.

Vehicular Ad-hoc networks (VANETs) are kinds of mobile Ad-hoc networks (MANETs), which consist of mobile vehicles with on-board units (OBUs) and roadside units (RSUs). With the rapid development of computation and communication technologies, peripheral or incremental changes in VANETs evolve into a revolution in process. Cloud computing as a solution has been deployed to satisfy vehicles in VANETs which are expected to require resources (such as computing, storage and networking). Recently, with special requirements of mobility, location awareness, and low latency, there has been growing interest in research into the role of fog computing in VANETs. The merging of fog computing with VANETs opens an area of possibilities for applications and services on the edge of the cloud computing. Fog computing deploys highly virtualized computing and communication facilities at the proximity of mobile vehicles in VANET. Mobile vehicles in VANET can also demand services of low-latency and short-distance local connections via fog computing. This paper presents the current state of the research and future perspectives of fog computing in VANETs. Moreover, we discuss the characteristics of fog computing and services based on fog computing platform provided for VANETs. In this paper, some opportunities for challenges and issues are mentioned, related techniques that need to be considered have been discussed in the context of fog computing in VANETs. Finally, we discuss about research directions of potential future work for fog computing in VANETs. Within this article, readers can have a more thorough understanding of fog computing for VANETs and the trends in this domain.

Increased adoption of smartphones leads to the explosive growth of mobile network traffic. Understanding the traffic characteristics of mobile network is important for Internet Service Providers (ISPs) to optimize network resources. In this paper, we conduct a detailed measurement study on the HTTP traffic characteristics of cellular network among different operating systems (OSs) as well as different device-types. Firstly, we propose a probability-based method to identify the installed OS of each smartphone. Then we analyze the traffic characteristics of these smartphones in terms of OS and device-type based on a dataset across 31 days (a billing cycle). Finally, we identify the installed apps of each smartphone and compare the usage of apps on the dimensions of OS and device-type. Our measurement study provides insights for network operators to strategize pricing and resource allocation for their cellular data networks.

The authentication codes with arbitration are able to solve dispute between the sender and the receiver. The authentication codes with trusted arbitration are called , the authentication codes with distrust arbitration are called . As an expansion of , an is an authentication system which is closer to the reality environment. Therefore, have more extensive application value. In this paper, we construct a class of based on polynomials over finite fields, give the parameters of the constructed codes, and calculate a variety of cheating attacks the maximum probabilities of success. Especially, in a special case, the constructed are perfect. Compared with a known type of codes, they have almost the same security level, however, our codes need less storage requirements. Therefore, our codes have more advantages.

The error vector magnitude (EVM) is extensively applied as a metric for digital transmitter signal quality compliance in modern communication systems. This article is focused on the effects of local oscillator (LO) phase noise and nonlinear distortion of power amplifier on EVM. This article contributes to below aspects. First, the relationships between EVM and two effects, LO phase noise and nonlinear distortion of power amplifier, are derived and expressed. Second, to simplify the expression, the third-order intermodulation distortion (IMD3) is used to calculate the EVM. Then, an expression for the EVM is derived based on the digital transmitter model that considers local oscillator phase noise and nonlinear distortion of power amplifier. Finally, the math formula of bit error rate (BER) versus EVM is given which can be easier and more useful to predict BER, according to analysis of the relationship between EVM and signal to noise rate (SNR), inspired by the works of Rishad, Md. Shahriar and AHM, 2006. Simulations are carried out to display the performance of EVM based on these relationships.

It is of great value and significance to model the interests of microblog user in terms of business and sociology. This paper presents a framework for mining and analyzing personal interests from microblog text with a new algorithm which integrates term frequency-inverse document frequency (TF-IDF) with TextRank. Firstly, we build a three-tier category system of user interest based on Wikipedia. In order to obtain the keywords of interest, we preprocess the posts, comments and reposts in different categories to select the keywords which appear both in the category system and microblogs. We then assign weight to each category and calculate the weight of keyword to get TF-IDF factors. Finally we score the ranking of each keyword by the TextRank algorithm with TF-IDF factors. Experiments on real Sina microblog data demonstrate that the precision of our approach significantly outperforms other existing methods.

To understand website complexity deeply, a web page complexity measurement system is developed. The system measures the complexity of a web page at two levels: transport-level and content-level, using a packet trace-based approach rather than server or client logs. Packet traces surpass others in the amount of information contained. Quantitative analyses show that different categories of web pages have different complexity characteristics. Experimental results show that a news web page usually loads much more elements at more accessing levels from much more web servers within diverse administrative domains over much more concurrent transmission control protocol (TCP) flows. About more than half of education pages each only involve a few logical servers, where most of elements of a web page are fetched only from one or two logical servers. The number of content types for web game traffic after login is usually least. The system can help web page designers to design more efficient web pages, and help researchers or Internet users to know communication details.

Information hiding techniques adopted in secret communication should meet the requirements of high hiding capacity, real-time and high robustness. For the purpose of real-time speech secure communication, an information hiding algorithm based on the analysis-by-synthesis (ABS) speech coding scheme is presented in this article. This algorithm substitutes secret speech data bits for linear predictive coefficients (LPCs) in linear predictive coding (LPC). Statistics show that the change of voiced signal track is slow and the codebook for LPCs vector is large in ABS coding scheme. Therefore, a new concept, filter similarity, is proposed to determine the LPC parameters for substituting with secret speech information, and to generate multi-codebook for saving storage space to store secret speech information. To achieve the best effects of information hiding, a dynamic threshold is built to make an optimal trade-off among hiding-capacity, security, robustness, transparence and real time. Experiments show that the proposed approach meets the requirements of information hiding and secret communication speech quality. The test results indicate that this approach reaches high hiding capacity with an excellent speech quality and complicating speakers’ recognition.

Along with the increasing number of vehicles, parking space becomes narrow gradually, safety parking puts forward higher requirements on the driver’s driving technology. How to safely, quickly and accurately park the vehiclo to parking space right? This paper presents an automatic parking scheme based on trajectory planning, which analyzing the mechanical model of the vehicle, establishing vehicle steering model and parking model, coming to the conclusion that it is the turning radius is independent of the vehicle speed at low speed. The Matlab simulation environment verifies the correctness and effectiveness of the proposed algorithm for parking. A class of the automatic parking problem of intelligent vehicles is solved.

From the perspective of compressed sensing (CS) theory, the channel estimation problem in large-scale multiple input multiple output (MIMO)-orthogonal frequency division multiplexing (OFDM) system is investigated. According to the theory, the smaller mutual coherence the reconstruction matrix has, the higher success probability the estimation can obtain. Aiming to design a pilot that can make the system reconstruction matrix having the smallest mutual coherence, this paper proposes a low complexity joint algorithm and obtains a kind of non-orthogonal pilot pattern. Simulation results show that compared with the conventional orthogonal pilot pattern, applying the proposed pattern in the CS channel estimation can obtain the better normalized mean square error performance. Moreover, the bit error rate performance of the large-scale MIMO-OFDM system is also improved.

Objective video quality assessment methods often evaluate all the frames regardless of their importance. For wireless distorted videos, not every frame has the same contribution to the final overall quality due to the channel fading and interference, which may lead to the capacity variation in temporal. Besides, with the content similarity and error propagation pattern in temporal domain, it is possible to evaluate the overall quality with only part of the frames. In this paper, a demonstration is performed to show that the video quality can be evaluated with reduced frames set (RFS), and a state transition model is proposed to extract the RFS. At last, a video quality assessment (VQA) method is carried out based on RFS. Compared with several state-of-the-art methods, our method can achieve a suitable accuracy with less frames to be processed.

Considering the shortcomings of the existing vehicle-to-vehicle (V2V) communication antennas, this paper proposes a regular hexagon broadband microstrip antenna. By loading shorting pins and etching V-shape slots with different size at each angle of the regular hexagon patch, it realizes impedance matching and obtains better impedance bandwidth. The simulated results show that the relative bandwidth of this antenna reaches 35.55%, covers the frequency band of 4.74 GHz to 6.79 GHz. The antenna acquires an omni-directional radiation pattern in the horizontal plane whose out of roundness is less than 0.5 dB. In addition, the antenna is manufactured and tested, whose tested results are basically consistent with simulated results. Because the height of antenna is 3 mm, it is easy to be hidden on roof of a vehicle for V2V communication.

As an effective solution for indoor coverage and service offloading from the conventional cellular networks, femtocells have attracted a lot of attention in recent years. This study investigates the resource block (RB) and power allocation in heterogeneous network. Specifically, the concern here is to maximize the signal-to-interference-plus- noise-ratio (SINR) of macrocell and energy efficiency of femtocell while providing the finite interference. In this paper, the network model is divided into two layers, in which the macro base station and clusters constitute the first layer network; femtocells inside cluster make up the second layer. Because of the different model structure, different game theory is used in each layer. Stackelberg Game is used in the first layer, and non-cooperation game is used in the second layer. Meanwhile RB and power levels stand for the actions that are associated with each player in the game. The problem of resource allocation algorithm is formulated as a mixed integer programming problem. In order to minimize the complexity of the proposed algorithm, the resource allocation task is decomposed into two sub problems: a RB allocation and a power allocation. The simulation results are compared with the traditional methods, the analysis illustrates the proposed algorithm has a better performance regarding SINR and energy efficiency of the heterogeneous network.

Reliability-based hybrid automatic repeat request (ARQ) (RB-HARQ) is a recently introduced approach to incremental-redundancy ARQ. In RB-HARQ scheme, the bits that are to be retransmitted are adaptively selected at the receiver based on the estimated bit reliability. It could result in significant performance gain but requires huge overhead in the feedback channel. In this study, an improved RB-HARQ scheme (IRB-HARQ) for structured low-density parity-check codes is proposed, which simplifies the comparison operations needed to search the bits to be retransmitted and outperforms the RB-HARQ scheme in consideration of the bit transmission power for the requesting messages on the feedback link. Simulation results show that the IRB-HARQ scheme is more efficient and practical than the RB-HARQ scheme.

To enhance the detection accuracy and deduce false positive rate of distributed denial of service (DDoS) attack detection, a new machine learning method was proposed. With the analysis of support vector machine (SVM) and the wavelet kernel function theory, an admissive support vector kernel, which is a wavelet kernel constructed in this article, implements the combination of the wavelet technique with SVM. Then, wavelet support vector machine (WSVM) is applied to DDoS attack detections and as a classifying means to test the validity of the wavelet kernel function. Simulation experiments show that under the same conditions, the predictive ability of WSVM is improved and the computation burden is alleviated. The detection accuracy of WSVM is higher than the traditional SVM by about 4%, while its false positive is lower than the traditional SVM. Thus, for DDoS detections, WSVM shows better detection performance and is more adaptive to the changing network environment.