Characterizations of friction welding joint interface for AISI 316

Because of heat amount is different from peripheral to central of friction welding interface, which is leaded to vary the characterizations along that interface. Current study, respectively, focused on the effect of different friction pressure on micro-structural and mechanical properties of that friction welding joint interface. Presently, these friction pressures are 110, 130, 150 and 170 MPa while kept all other conditions constant. The effects of different friction pressure on welding interface characterization were investigated by EDX, SEM, tensile, compression, impact and hardness tests. The tensile tests carried out on the standardized test piece with diameter 6 mm and 8 mm, thus, compression tests were extracted from the positions of 0°, 45° 90° with test specimen of 4 mm diameter and 6.5 mm length at weld center. Whereas, the impact test pieces were picked up in two positions, the first one is symmetrical, which it obtained to the respect of the rotation axis and the interface, on the other hand, the second one is non-symmetrical with the axis of rotation and symmetrical to the interface, for making the notch head coincide with the center of the welded joint, The obtained results showed that with reducing of friction pressure will present lack of bonding increasing from peripheral toward the welding center, which will responsible on reducing of the mechanical properties such as tensile, compression and impact strength.     

Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines

Magnetic resonance imaging (MRI) is increasingly used in the diagnosis of Alzheimer's disease (AD) in order to identify abnormalities in the brain. Indeed, cortical atrophy, a powerful biomarker for AD, can be detected using structural MRI (sMRI), but it cannot detect impairment in the integrity of the white matter (WM) preceding cortical atrophy. The early detection of these changes is made possible by the novel MRI modality known as diffusion tensor imaging (DTI). In this study, we integrate DTI and sMRI as complementary imaging modalities for the early detection of AD in order to create an effective computer-assisted diagnosis tool. The fused Bag-of-Features (BoF) with Speeded-Up Robust Features (SURF) and modified AlexNet convolutional neural network (CNN) are utilized to extract local and deep features. This is applied to DTI scalar metrics (fractional anisotropy and diffusivity metric) and segmented gray matter images from T1-weighted MRI images. Then, the classification of local unimodal and deep multimodal features is first performed using support vector machine (SVM) classifiers. Then, the majority voting technique is adopted to predict the final decision from the ensemble SVMs. The study is directed toward the classification of AD versus mild cognitive impairment (MCI) versus cognitively normal (CN) subjects. Our proposed method achieved an accuracy of 98.42% and demonstrated the robustness of multimodality imaging fusion.     

Fuzzy based multi-criteria vertical handover decision modeling in heterogeneous wireless networks

Vertical handover gain significant importance due to the enhancements in mobility models by the Fourth Generation (4G) technologies. However, these enhancements are limited to specific scenarios and hence do not provide support for generic mobility. Similarly, various schemes are proposed based on these mobility models but most of them are suffered from the high packet loss, frequent handovers, too early and late handovers, inappropriate network selection, etc. To address these challenges, a generic vertical handover management scheme for heterogeneous wireless networks is proposed in this article. The proposed scheme works in three phases. In the first phase, a handover triggering approach is designed to identify the appropriate place for initiating handover based on the estimated coverage area of a WLAN access point or cellular base station. In the second phase, fuzzy rule based system is designed to eliminate the inappropriate networks before deciding an optimal network for handover. In the third phase, a network selection scheme is developed based on the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) decision mechanism. Various parameters such as delay, jitter, Bit Error Rate (BER), packet loss, communication cost, response time, and network load are considered for selecting an optimal network. The proposed scheme is tested in a mobility scenario with different speeds of a mobile node ranging from very low to very high. The simulation results are compared with the existing decision models used for network selection and handover triggering approaches. The proposed scheme outperforms these schemes in terms of energy consumption, handover delay and time, packet loss, good put, etc.     

Analysis of whispering-gallery superconducting dielectric resonator modes

The whispering-gallery (WG) modes of a superconducting dielectric resonator (SDR) based on a sapphire cylindrical dielectric resonator and a YBa₂Cu₃O_{7 –} shielding cylinder have been studied. A method for the determination of the resonant frequencies and the maximum quality factor of such modes is presented. Calculations have shown that most of the mode energy could be confined between the caustic surface of the WG modes provided the dimensions of the SDR are properly selected, and a magnitude of 10⁹ forQ of the SDR could be estimated. A phenomenal explanation is given to account for such outstanding microwave behavior.     

A novel deep learning neural network for fast-food image classification and prediction using modified loss function

Multimedia Tools and Applications - Accurate food image classification is often critical to accurately monitor the dietary assessment to reduce the risk of different heart-related diseases,...     

Identification of microstructural mechanisms during densification of a TiAl alloy by spark plasma sintering

This work aims at identifying, by coupled scanning and transmission electron microscopy (SEM and TEM) observations, the densification mechanisms occurring when an atomized Ti-47Al-1W-1Re-0.2Si powder is densified by spark plasma sintering (SPS). For this purpose, interruptions of the SPS cycle have been performed to follow the evolution of the microstructure step by step. The powder particles exhibit a classical dendritic microstructure containing a large amount of out-of-equilibrium α phase. During heating-up, the microstructure undergoes successive transformations. At T = 525-875 °C the α phase transforms into γ. The γ phase formed is supersaturated in W and Re. It de-saturates for T above 875 °C by discontinuous precipitation of W and Re-rich B2 phase. Densification takes place for T between 900 °C and 1150 °C by plastic deformation of the powder particles. TEM observations show that the repartition of the plastic deformation is correlated to the dendritic microstructure, and that dynamic recrystallization mechanisms occur. Microstructural phenomena directly resulting from the high currents involved in the SPS process have not been observed.     

Exact analytic solitary wave solutions for the RKL model

Interest in finding exact solitary wave solutions of nonlinear evolution equations by means of different methods has grown steadily in recent years. These exact solutions are important to understand the mechanism of the complicated nonlinear physical phenomena. By use of the Jacobi elliptic function method, we find the exact analytic solitary wave solutions for the RKL model with cubic-quintic non-Kerr terms, describing the propagation of extremely short pulses in optical fibers. These new solutions may be useful for describing the propagation of optical pulses in non-Kerr media.     

Resilience and survivability in communication networks: Strategies,principles, and survey of disciplines

The Internet has become essential to all aspects of modern life, and thus the consequences of network disruption have become increasingly severe. It is widely recognised that the Internet is not sufficiently resilient, survivable, and dependable, and that significant research, development, and engineering is necessary to improve the situation. This paper provides an architectural framework for resilience and survivability in communication networks and provides a survey of the disciplines that resilience encompasses, along with significant past failures of the network infrastructure. A resilience strategy is presented to defend against, detect, and remediate challenges, a set of principles for designing resilient networks is presented, and techniques are described to analyse network resilience.     

On the verification of the effect of water depth on the performance of basin type solar stills

Many experimental and numerical studies have been done on different configurations of solar stills to optimize the design by examining the effect of climatic, operational and design parameters on its performance. The majority of the investigators presented their results in scatter diagrams rather than correlations. One of the most important of the operational parameters that has received a considerable attention in the literature is the brine depth. A good number of the investigations on the effect of brine depth are cited in this study. For each of these studies, a correlation was developed from the data reported by each study. A concluding correlation from all brine depth data was developed. The correlation showed a decreasing trend in the productivity with the increase in the brine depth. An experimental study was subsequently conducted to verify this trend by an experimental investigation on a solar still that was constructed and tested with five different brine depths, namely 1, 4, 6, 8 and 10 cm. The present study validated the decreasing trend in productivity with the increase of brine depth and showed that the still productivity could be influenced by the brine depth by up to 48%.