Potential of ASAR/ENVISAT for the characterization of soil surface parameters over bare agricultural fields

The objective of this investigation is to analyze the sensitivity of ASAR (Advanced Synthetic Aperture Radar) data to soil surface parameters (surface roughness and soil moisture) over bare fields, at various polarizations (HH, HV, and VV) and incidence angles (20°-43°). The relationships between backscattering coefficients and soil parameters were examined by means of 16 ASAR images and several field campaigns. We have found that HH and HV polarizations are more sensitive than VV polarization to surface roughness. The results also show that the radar signal is more sensitive to surface roughness at high incidence angle (43°). However, the dynamics of the radar signal as a function of soil roughness are weak for root mean square (rms) surface heights between 0.5 cm and 3.56 cm (only 3 dB for HH polarization and 43° incidence angle). The estimation of soil moisture is optimal at low and medium incidence angles (20°-37°). The backscattering coefficient is more sensitive to volumetric soil moisture in HH polarization than in HV polarization. In fact, the results show that the depolarization ratio σ_HH⁰/σ_HV⁰ is weakly dependent on the roughness condition, whatever the radar incidence. On the other hand, we observe a linear relationship between the ratio σ_HH⁰/σ_HV⁰ and the soil moisture. The backscattering coefficient ratio between a low and a high incidence angle decreases with the rms surface height, and minimizes the effect of the soil moisture.     

The effects of modified zinc oxide nanoparticles on the mechanical/thermal properties of epoxy resin

Characterized by its strength, durability, and thermal properties, epoxy resin has been widely used as an adhesive, paint, and coating in many applications in the aerospace, civil and automotive industries. Despite this, the thermoset polymer resin has been known for its brittleness and low fracture resistance. This study focuses on the reinforcement of an epoxy resin system (diglycidyl ether of bisphenol A) with zinc oxide (ZnO) nanoparticles in their pristine form and a further modified form. The modification took place in two ways: coating with polydopamine (PDA) and covalently functionalizing them with (3-aminopropyl)triethoxysilane (APTES) and (3-glycidoxypropyl)trimethoxysilane (GPTMS). Therefore, four different types of nanoparticles were used: pristine ZnO, ZnO/PDA, ZnO/GPTMS, and ZnO/APTES aiming to improve the interfacial bonding between the polymeric matrix and the reinforcement. Thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy, and scanning electron microscopy characterization and imaging techniques were used to prove that the ZnO nanoparticles were successfully modified prior to manufacturing the epoxy composites. While tensile testing showed that using pristine ZnO increases the composite's strength by 32.14%, the fracture toughness of the resin was improved by 9.40% when reinforced with ZnO functionalized with APTES. TGA showed that the addition of functionalized nanoparticles increases the material's degradation temperature by at most 7.31 ± 4.9°C using ZnO/APTES. Differential scanning calorimetry and dynamic mechanical analysis testing proved that the addition of any type of nanoparticles increases the resin's glass transition temperature by as much as 7.83°C (ZnO/APTES).     

Study of the Soft and Hard X-Ray Emitted by APF Plasma Focus Device in Different Pressures

In this paper, an investigation on the X-rays emitted in different pressures by APF plasma focus devices using filtered PIN-diodes and fast plastic scintillation detector is reported. The highest X-ray emission was observed in the pressure of 1.6 torr and the behavior of X-ray intensities registered by different filters versus applied pressure were seemed to be similar. The X-ray angular distribution was bimodal, peaked approximately at ±18°. The intensity of X-rays decreased abruptly along the central axis of the device where the cylindrical plasma pinch was formed.     

Investigation of Nitrogen HXR with Neon Admixture on the APF Plasma Focus

An investigation on the HXR emitted from APF plasma focus device operated with different volumetric ratios of nitrogen-neon (N₂:Ne) admixture working gas at different voltage-pressure limits is presented. The optimum pressures obtained at the applied voltages of 12, and 13 kV were 3.5 torr for percentage of (50:50) of (N₂:Ne) admixture and 3 torr for percentages of (75:25) and (90:10) in admixture and also for pure N₂, while at the voltage of 11 kV, the optimum pressures were 3 torr for percentage of (50:50) and 2.5 torr for percentages of (75:25), (90:10), and pure N₂. At each applied voltages of 11, 12, and 13 kV, with increasing percentage of N₂ in the (N₂:Ne) admixture, the intensity of HXR was found to increase where the low intensity was for percentage of (50:50) of (N₂:Ne) and the higher intensity was for pure N₂. The results illustrate that the voltage and the composition of working gas are effective parameters in the HXR emission from a plasma focus device.     

A business model for deploying Web services:A data-centric approach based on factual dependencies

The standards XML, SOAP, WSDL and UDDI allow (i) services to be accessed and executed via the Web; and (ii) a loose coupling of these services. Thanks to these standards, Web services technology is becoming not only a de facto integration standard, but also a de facto Internet standard instance of the SOA architecture. However, the deployment of such a technology is still hindered by some technical as well as methodological issues. This paper proposes a business model with multiple interfaced abstraction levels as a framework to methodologically deploy Web services technology with respect to SOA architecture. The attributes describing the business objects and coordination artifacts as described in the highest abstraction level of the business model, i.e. the universe of discourse, are aggregated according to a time/space constraint called factual dependency. Each aggregation of factually dependent attributes is validated with regard to an actual business event. The aggregation is then interfaced to lead to a well-specified Web service. The resulting comprehensive set of consistent Web services are then registered in a public or a private UDDI to be discovered and invoked by any business process. The proposed Web services generation process aims at unlocking and turning informational assets into actions. It differs from the current IT perspective approaches that generate Web services directly from redundant and inconsistent elements in the enterprise information systems.     

Template-based finite-element mesh generation from medical images

The finite-element (FE) method is commonly used in biomedical engineering to simulate the behaviour of biological structures because of its ability to model complex shapes in a subject-specific manner. However, generating FE meshes from medical images remains a bottleneck. We present a template-based technique for semi-automatically generating FE meshes which is applicable to prospective studies of individual patients in which FE meshes must be generated from scans of the same structure taken at different points in time to study the effects of disease progression/regression. In this "template-based" meshing approach, the baseline FE (tetrahedral) volume mesh is first manually aligned with the follow-up images. The triangulated surface of the mesh is then automatically deformed to fit the imaged organ boundary. The deformed surface nodes are then smoothed using a Laplacian smoothing algorithm to correct triangle (surface nodes) distortion and thus preserve triangle quality. Finally, the internal mesh nodes are smoothed to correct distorted tetrahedral elements and thus preserve tetrahedral element quality. This template-based approach is shown to be as accurate and precise as the previous technique used by our group, while preserving element quality and volume.     

Quantum Artificial Intelligence Based Node Localization Technique for Wireless Networks

Artificial intelligence (AI) techniques have received significant attention among research communities in the field of networking, image processing, natural language processing, robotics, etc. At the same time, a major problem in wireless sensor networks (WSN) is node localization, which aims to identify the exact position of the sensor nodes (SN) using the known position of several anchor nodes. WSN comprises a massive number of SNs and records the position of the nodes, which becomes a tedious process. Besides, the SNs might be subjected to node mobility and the position alters with time. So, a precise node localization (NL) manner is required for determining the location of the SNs. In this view, this paper presents a new quantum bird migration optimizer-based NL (QBMA-NL) technique for WSN. The goal of the QBMA-NL approach is for determining the position of unknown nodes in the network by the use of anchor nodes. The QBMA-NL technique is mainly based on the mating behavior of bird species at the time of mating season. In addition, an objective function is derived based on the received signal strength indicator (RSSI) and Euclidean distance from the known to unknown SNs. For demonstrating the improved performance of the QBMA-NL technique, a wide range of simulations take place and the results reported the supreme performance over the recent NL techniques.