Simplified gateway selection scheme for multihop relay in vehicular ad hoc network

Integrating vehicular ad hoc network (VANET) and universal mobile telecommunication system (UMTS) could be a promising architecture for future machine‐to‐machine applications. This integration can help vehicles have steady Internet connection through the UMTS network and in communicating with other vehicles. However, dead spot areas and unsuccessful handoff processes caused by the high speed of vehicles can disrupt the implementation of this kind of architecture. In this paper, a new simplified gateway selection (SGS) scheme for multihop relay in a VANET‐UMTS integration network is proposed. The proposed scheme extends the coverage or/and calming of the frequent handoff process and allows vehicles to continue to be connected to the UMTS infrastructure network. An integrated simulation environment that combines VanetMobiSim and NS2 is used to simulate and evaluate the proposed scheme. The simulation results show that the SGS scheme performed better when it was implemented with ad hoc on a demand distance vector routing and destination‐sequenced distance vector routing protocols. Furthermore, the SGS scheme is compared with other cluster‐based gateway selections used in the previous works. The results show that our SGS scheme outperforms other cluster‐based gateway selections scheme in terms of selection delay, control packet overhead, packet delivery ratio, and overall throughput. Copyright © 2013 John Wiley & Sons, Ltd.     

Social media in marketing: A review and analysis of the existing literature

People worldwide are largely engaged and attached with the web 2.0 technology and Social media platforms. By the same token, businesses start looking at such technologies as effective mechanisms to interact more with their customers. Equally, the related issues of social media marketing have been also the focus of attention for academics and researchers to expand the current understanding about such phenomena over the marketing area. Accordingly, the main aim of this study is to systematically examine and review the current studies that have conducted over the related area of social media and marketing. By reviewing approximately 144 articles, the researchers were able to provide an overview of the main themes and trends covered by the relevant literature such as the role of social media on advertising, the electronic word of mouth, customers’ relationship management, and firms’ brands and performance. In this review, it has also studied the most common research approaches adopted to examine the related issues of social media marketing. Further discussion is also introduced followed by an explanation of the current review limitations and recommended directions to be examined by future studies.     

Correction to: Enhanced TOA Estimation Using OFDM over Wide-Band Transmission Based on a Simulated Model

Wireless Personal Communications -     

Scalable perceptual audio representation with an adaptive three time-scale sinusoidal signal model

This work is concerned with the development and optimization of a signal model for scalable perceptual audio coding at low bit rates. A complementary two-part signal model consisting of Sines plus Noise (SN) is described. The paper presents essentially a fundamental enhancement to the sinusoidal modeling component. The enhancement involves an audio signal scheme based on carrying out overlap-add sinusoidal modeling at three successive time scales, large, medium, and small. The sinusoidal modeling is done in an analysis-by-synthesis overlapadd manner across the three scales by using a psychoacoustically weighted matching pursuits. The sinusoidal modeling residual at the first scale is passed to the smaller scales to allow for the modeling of various signal features at appropriate resolutions. This approach greatly helps to correct the pre-echo inherent in the sinusoidal model. This improves the perceptual audio quality upon our previous work of sinusoidal modeling while using the same number of sinusoids. The most obvious application for the SN model is in scalable, high fidelity audio coding and signal modification.     

A WLAN band‐notched compact four element UWB MIMO antenna

A compact four‐element multiple‐input‐multiple‐output (MIMO) antenna for ultra‐wideband (UWB) applications with WLAN band‐notched characteristics is proposed here. The proposed antenna has been designed to operate from 2 to 12 GHz while reject the frequencies between 4.9 to 6.4 GHz. The four antenna elements are placed orthogonal to attain the polarization diversity and high isolation. A thin stub connected to the ground plane is deployed as a LC notch filter to accomplish the rejected WLAN band in each antenna element. The mutual coupling between the adjacent elements is at least 17 dB while it has low indoor and outdoor envelop correlation (<0.45) and high gain with compact size of two boards, each measuring 50 × 25 mm². To validate the concept, the prototype antenna is manufactured and measured. The comparison of the simulation results showed good agreement with the measured results. The low‐profile design and compact size of the proposed MIMO antenna make it a good candidate for diversity applications desired in portable devices operating in the UWB region.     

The effectiveness of software metrics in identifying error-prone classes in post-release software evolution process

Many empirical studies have found that software metrics can predict class error proneness and the prediction can be used to accurately group error-prone classes. Recent empirical studies have used open source systems. These studies, however, focused on the relationship between software metrics and class error proneness during the development phase of software projects. Whether software metrics can still predict class error proneness in a system’s post-release evolution is still a question to be answered. This study examined three releases of the Eclipse project and found that although some metrics can still predict class error proneness in three error-severity categories, the accuracy of the prediction decreased from release to release. Furthermore, we found that the prediction cannot be used to build a metrics model to identify error-prone classes with acceptable accuracy. These findings suggest that as a system evolves, the use of some commonly used metrics to identify which classes are more prone to errors becomes increasingly difficult and we should seek alternative methods (to the metric-prediction models) to locate error-prone classes if we want high accuracy.     

Designing genetic regulatory networks using fuzzy Petri nets approach

In this paper, we have successfully presented a fuzzy Petri net (FPN) model to design the genetic regulatory network. Based on the FPN model, an efficient algorithm is proposed to automatically reason about imprecise and fuzzy information. By using the reasoning algorithm for the FPN, we present an alternative approach that is more promising than the fuzzy logic. The proposed FPN approach offers more flexible reasoning capability because it is able to obtain results with fuzzy intervals rather than point values. In this paper, a novel model with a new concept of hidden fuzzy transition (HFT) to design the genetic regulatory network is developed. We have built the FPN model and classified the input data in terms of time point and obtained the output data, so the system can be viewed as the two-input and one output system. This method eliminates possible false predictions from the classical fuzzy model thereby allowing a wider search space for inferring regulatory relationship. The experimental results show the proposed approach is feasible and acceptable to design the genetic regulatory network and investigate the dynamical behaviors of gene network.     

Malware classification approaches utilizing binary and text encoding of permissions

International Journal of Information Security - With the advancement of smartphone technology, the development of mobile applications is rapidly growing. These apps are designed to help mobile...     

Speech compression exploiting linear prediction coefficients codebook and hamming correction code algorithm

In this paper, a replacement algorithm for Linear Prediction Coefficients (LPC) along with Hamming Correction Code based Compressor (HCDC) algorithms are investigated for speech compression. We started with an CELP system with order 12 and with Discrete Cosine Transform (DCT) based residual excitation. Forty coefficients with transmission rate of 5.14 kbps were first used. For each frame of the testing signals we applied a multistage HCDC, we tested the compression performance for parities from 2 to 7, we were able to achieve compression only at parity 4. This rate reduction was made with no compromise in the original CELP signal quality since compression is lossless. The compression approach is based on constructing dynamic reflection coefficients codebook, this codebook is constructed and used simultaneously using a certain store/retrieve threshold. The initial linear prediction codec we used is excited by a discrete cosine transform (DCT) residual, the results were tested using the MOS and SSNR, we had acceptable ranges for the MOS (average 3.6), and small variations of the SSNR (±5 db).