Path Loss Models for Low-Height Mobiles in Forest and Urban

This paper presents path loss measurements at 2.1 GHz in forest and urban areas. Empirical path loss models have been presented for low-height dual-mobility channels. Three test scenarios are considered for the transmitter (Tx) and receiver (Rx) placed inside the test vehicle or on a test cart pushed at walking speed. Based on measurements, the in-leaf and single-slope path loss models are presented. The path loss exponents for the dual-mobility channels are found to be between 2.1 and 3.4 in urban and 8.0 in forest, with higher reference when antennas are placed inside the vehicle.     

Network Coding Based Converge-Cast Scheme in Wireless Sensor Networks

The converge-cast in wireless sensor networks (WSNs) is widely applied in many fields such as medical applications and the environmental monitoring. WSNs expect not only providing routing with high throughput but also achieving efficient energy saving. Network coding is one of the most promising techniques to reduce the energy consumption. By maximizing the encoding number, the message capacity per package can be extended to the most efficient condition. Thus, many researchers have focused their work on this field. Nevertheless, the packages sent by the outer nodes need to be temporary stored and delayed in order to maximize the encoding number. To find out the balance between inserting the delay time and maximizing the encoding number, a Converge-cast Scheme based on data collection rate prediction (CSRP) is proposed in this paper. To avoid producing the outdated information, a prediction method based on Modifying Index Curve Model is presented to deal with the dynamic data collection rate of every sensor in WSNs. Furthermore, a novel coding conditions based on CDS is proposed to increase the coding opportunity and to solve the collision problems. The corresponding analysis and experimental results indicate that the feasibility and efficiency of the CSRP is better than normal conditions without the prediction.     

Temporal Topic-Based Multi-Dimensional Social Influence Evaluation in Online Social Networks

Analytical applications in online social networks can be generalized as the influence evaluation problem, which targets at finding most influential users. Nowadays social influence evaluation is still an open and challenging issue. Most influence evaluation models focus on the single dimensional evaluation factor but fail to research on the multi-dimensional factors. In this paper, we propose a novel influence evaluation model: the temporal topic influence (TTI) evaluation model, which is a time-aware, content-aware and structure-aware evaluation model. For the aim of multi-dimensional evaluation, we incorporate multi-dimensional measure factors into our model, including the time factor, the topological information and the topic distribution information, etc. We propose a novel concept of user gravitational ability which is inspired by Newton’s law of universal gravitation. It can integrate multi-dimensional factors in an appropriate way. Our experiments are conducted on the Sina Weibo data set. Through the experimental analysis, we prove TTI model can calculate users’ influences effectively and efficiently. The TTI model can distinguish the value of users’ influences. And the TTI model identifies the top-k influential users with higher quality. We also validate the effect of time and topic measure factors in the influence evaluation process.     

WDTF: A Technique for Wireless Device Type Fingerprinting

In this Work, a technique for wireless device type fingerprinting has been introduced. The technique utilizes the information that revealed as a result of the homogeneity in devices of the same make and the heterogeneity in devices of a different make. The diversity in devices of different make is due to different device hardware compositions and the variations in their management capabilities. We apply the statistical technique on network traffic to create unique, reproducible device signatures. We demonstrate the efficacy of our technique on network traffic captured in different scenarios. We have used a total of 300 devices types representing a wide range of device classes. In the experiment, we have used more than 1.5 GB of filtered traffic for analysis and performance evaluation. We measure the performance of the technique by considering the accuracy of device type detection. The results obtained are promising with a higher detection rate than its counterparts.     

Thermoelectric and Magnetic Properties of Pt-Substituted $${BaFe_{4-{x}}Pt_{{x}}Sb_{12}}$$ Compounds

\({BaFe_{4-{x}}Pt_{{x}}Sb_{12}}\) (x = 0, 0.1, 0.2) compounds were prepared by melting and annealing, followed by a spark plasma sintering method. Low-temperature thermoelectric and magnetic properties were investigated based on Seebeck coefficient, electrical and thermal conductivity and magnetization measurements. The structural properties of \({BaFe_{4-{x}}Pt_{{x}}Sb_{12}}\) (x = 0, 0.1, 0.2) compounds were ascertained by powder x-ray diffraction analysis, confirming that all samples have a main phase of a skutterudite structure with the space group Im\({\mathrm {\bar{3}}}\). The lattice parameters obtained, 9.202(5), 9.199(5) and 9.202(1) Å for x = 0, 0.1 and 0.2, respectively, were found consistent with literature. The Seebeck coefficient sign shows that holes are dominant carriers in all compounds. The local maximum Seebeck coefficient was observed around 50 K which may be a trace of paramagnon-drag effect of charge carriers. Thermal conductivity and electrical resistivity measurements were carried out between 4.2 and 300 K. Temperature dependence of electrical resistivity reflects that all samples show semi-metallic behavior in our temperature range of 4.2–300 K. Samples for x = 0.1 and x = 0.2 show Kondo-like behavior. In magnetization measurement, we observe that there are two successive magnetic transitions in Pt-substituted compounds; however, there is only one (transition from a paramagnetic state to long-range magnetic ordering) in Pt-free compounds. In Pt-substituted compounds, the first transition appears at \( T _{ {\rm c}}\) = 48 K. In addition, the second transition is observed at \( T _{ {\rm irr}}\) = 30 K where an intermediate state is observed before the magnetic ordering transforms to an irreversible ferromagnetic state. We concluded that Pt substitution on the Fe side effectual on the thermoelectric and magnetic properties of \({BaFe_{4-{x}}Pt_{{x}}Sb_{12}}\) (x = 0, 0.1, 0.2) compounds.     

Fabrication and Electromagnetic Properties of Conjugated NH<Subscript>2</Subscript>-CuPc@Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>

Conjugated amino-phthalocyanine copper containing carboxyl groups/magnetite (NH₂-CuPc@Fe₃O₄) has been fabricated from FeCl₃·6H₂O and NH₂-CuPc via a simple solvothermal method and its electromagnetic properties investigated. Scanning electron microscopy and transmission electron microscopy revealed that the NH₂-CuPc@Fe₃O₄ was a waxberry-like nanomaterial with NH₂-CuPc molecules effectively embedded in the interior of Fe₃O₄ particles in the form of beads. Introduction of NH₂-CuPc effectively improved the complementarity between the dielectric and magnetic losses of the system, resulting in excellent electromagnetic performance. The minimum reflection loss of the as-prepared composite reached ?33.4 dB at 7.0 GHz for coating layer thickness of 4.0 mm and bandwidth below ?10.0 dB (90% absorption) of up to 3.8 GHz. These results indicate that introduction of NH₂-CuPc results in a composite with potential for use as an electromagnetic microwave absorption material.     

Indirect Measurement of Energy Density of Soft PZT Ceramic Utilizing Mechanical Stress

This paper reports on an indirect measurement of energy density of soft PZT ceramic utilizing mechanical stress. The method works analogous to the Olsen cycle and allows for a large amount of electro-mechanical energy conversion. A maximum energy density of 350 kJ/m³/cycle was found under 0–312 MPa and 1–20 kV/cm of applied mechanical stress and electric field, respectively. The obtained result is substantially higher than the results reported in previous studies of PZT materials utilizing a direct piezoelectric effect.     

Hybrid wavelet measurement matrices for improving compressive imaging

Compressive sensing principle claims that a compressible signal can be recovered from a small number of random linear measurements. However, the design of efficient measurement basis in compressive imaging remains as a challenging problem. In this paper, a new set of hybrid wavelet measurement matrices is proposed to improve the quality of the compressive imaging, increase the compression ratio and reduce the processing time. The performance of these hybrid wavelet matrices for image modeling and reconstruction is evaluated and compared with other traditional measurement matrices such as the random measurement matrices, Walsh and DCT matrices. The compressive imaging approach chosen in this study is the block compressive sensing with smoothed projected Landweber reconstruction technique. The simulation results indicate that the imaging performance of the proposed hybrid wavelet measurement matrices is approximately 2–3 dB better than that obtained using Gaussian matrix especially at higher compression ratios.     

Patch-based reconstruction of surfaces undergoing different types of deformations

We deal with the reconstruction of surfaces that deform under a variety of conditions. The deformation can range from no extension to a certain degree of extensibility. The deformed surface is reconstructed from a single image, given a 3D reference shape. This shape corresponds to the undeformed state of the surface and can be computed using any appropriate technique. In particular, we use homographies defined from two views of the surface. To proceed with the 3D reconstruction of the deformed surface, we assume that the deformations are locally homogeneous and that the overall surface deformation can be obtained by combining the local homogeneous deformations. For this purpose, the surface is split into small patches. For each patch, a mapping between the undeformed and the deformed shapes is computed. The mapping is specified by using the quadratic deformation model Fayad et al. (Proceedings of British Machine Vision Conference (BMVC), 2004). As a result, given the undeformed shape, we define an optimization procedure whose goal is to estimate the 3D positions of deformed points in each image. The optimization is performed on each patch, independently of the others. The experimental results show that this approach allows precise reconstruction of a wide class of real deformations.