Quantitative analysis of packet-processing applications regarding architectural guidelines for network-processing-engine development

This paper presents a simulation-based profile-driven quantitative analysis of packet-processing applications. In this domain, demands for increasing the performance and the ongoing development of network protocols both call for flexible and performance-optimized engines. Based on the achieved profiling results, we introduce platform-independent analysis that locates the performance bottlenecks and architectural challenges of a packet-processing engine. Finally based on these results, we extract helpful architectural guidelines for design of a flexible and high-performance embedded processor that is optimized for packet-processing operations in high-performance and cost-sensitive network embedded applications.     

Counting eosinophils in bronchoalveolar lavage fluid images with fuzzy methodology

This paper proposes a new fuzzy approach to count eosinophils, as a measure of inflammation, in bronchoalveolar lavage fluid images, provided by digital camera through microscope. We use fuzzy cluster analysis and fuzzy classification algorithm to determine the number of objects in an image. For this purpose, a fuzzy image processing procedure consisting of five main stages is presented. The first stage is pre-highlighting the objects in the images by using an image pre-processing method for enhancement, which is sharpening the image with the Laplaian high pass filter in order to have acceptable contrast in the image. The second stage is segmentation by clustering with fuzzy c-mean algorithm for portioning. In this stage the clustered data are the rough symbols of objects in the image containing noise. In the third step, first, a Gaussian low pass filter is used for noise reduction. Then, a contrast adoption in the image is done by modifying the membership functions in the image [H.R. Tizhoosh, G. Krell, B. Michaelis, Knowledge-based enhancement of megavoltage images in radiation therapy using a hybrid neuro-fuzzy system, Image and Vision Computing 19(July) (2000) 217–233]. Object recognition, the fourth stage, will be done by using fuzzy labeling for the objects in the image, using a fuzzy classification method. The number of labeled images shows the number of eosinophils in an image which is an index for diagnosing inflammation. The last stage is tuning parameters and verification of the system performance by using a feed forward Neural Network.     

A single-phase p-type ac–ac converter with reduced components count and high boost factor

This paper proposes a new single-phase direct step-up ac–ac converter by modifying the p-type impedance source. It provides a high boost factor as well as high efficiency, while only six parts are required to design it, involving just two bidirectional power switches. A safe commutation method has been applied to power switches to make the converter snubber-free and high efficient. Input and output harmonic filters are no longer required since input and output currents variate continuously with small ripple and low total harmonic distortion (THD). The proposed topology only modulates the output voltage amplitude, not the phase and frequency, so the output frequency is identical to the input frequency and constant. Thus, it can be utilized in step-up conversion applications, like inductive power transmission from low ac voltage sources. Input and output have the same ground, which is a good protective feature. In this paper, the operating principle of the converter is demonstrated. Experimental results have been represented to evaluate the performance of the converter. For this purpose, an experimental prototype has been fabricated. Results are investigated and compared with other previous step-up ac–ac converters. Results confirm the theory, operating principle, and performance of the converter.     

Investigating the effect of varying block size on power and energy consumption of GPU kernels

The Journal of Supercomputing - Power consumption is likely to remain a significant concern for exascale performance in the foreseeable future. In addition, graphics processing units (GPUs) have...     

Advanced Authentication Mechanisms for Identity and Access Management in Cloud Computing

Identity management is based on the creation and management of user identities for granting access to the cloud resources based on the user attributes. The cloud identity and access management (IAM) grants the authorization to the end-users to perform different actions on the specified cloud resources. The authorizations in the IAM are grouped into roles instead of granting them directly to the end-users. Due to the multiplicity of cloud locations where data resides and due to the lack of a centralized user authority for granting or denying cloud user requests, there must be several security strategies and models to overcome these issues. Another major concern in IAM services is the excessive or the lack of access level to different users with previously granted authorizations. This paper proposes a comprehensive review of security services and threats. Based on the presented services and threats, advanced frameworks for IAM that provide authentication mechanisms in public and private cloud platforms. A threat model has been applied to validate the proposed authentication frameworks with different security threats. The proposed models proved high efficiency in protecting cloud platforms from insider attacks, single sign-on failure, brute force attacks, denial of service, user privacy threats, and data privacy threats.     

Instance of hidden instability traps in intermittent transition of moving masses along a flexible beam

The problem of an elastic beam under the periodic loading of successive moving masses is investigated as a pragmatic case for studying dynamic stability of linear time-varying systems. This model serves to highlight the odds of multi-solutions coexistence, a form of hidden instability which reveals dangerous as it may be precipitated by the slightest disturbance or variation in the model. Since no engineering model perfectly represents a physical system, such situations for which Floquet theory naively predicts stability are potentially inevitable. The harmonic balancing method is used in order to thoroughly explore the stability diagrams for detecting these instability gaps. Although this phenomenon has also been described in other physical systems, it has not been addressed for beam–moving mass systems. This result may find particular importance in applications involving self-induced vibrations of elastic structures and hence also appears of practical relevance.     

Verformungsverhalten nanostrukturierter HPPMS‐Hartstoffschichten

Elastic‐Plastic Deformation Behavior of Nanostructured HPPMS Hard Coatings Nitride hard coatings deposited via HPPMS (High Power Pulsed Magnetron Sputtering) or HiPIMS (High Power Impulse Magnetron Sputtering) are widely used in tribological applications due to their promising wear and corrosion resistance. During the application, the coated tools or components may be exposed to significant mechanical loads. Therefore, investigations on deformation behavior of the coatings under mechanical loading are of great importance. The objective of the present study was a comprehensive investigation on deformation behavior of nitride hard coatings from the coating system M‐Al‐O‐N (M = Cr, V) using nanoindentation und nanoscratch tests. In this regard, both nanoscale multilayer (nanolaminate) and monolayer coatings were investigated. All the coatings were deposited using HPPMS technology. Contrary to the expectations regarding a brittle behavior of ceramic‐like coatings, the results depict a considerable plastic deformation of the investigated hard coatings. Furthermore, in addition to a high strength, the applied coatings show a high crack resistance under mechanical loading.     

Catalytic reduction of 2,4‐dinitrophenylhydrazine by cuttlebone supported Pd NPs prepared using Conium maculatum leaf extract

A facile and green process to synthesise cuttlebone supported palladium nanoparticles (Pd NPs/cuttlebone) is reported using Conium maculatum leaf extract and in the absence of chemical solvents and hazardous materials. The antioxidant content of the C. maculatum leaf extract played a significant role in converting Pd²⁺ ions to Pd NPs. Various techniques were used for the characterisation of the Pd NPs/cuttlebone such as field‐emission scanning electron microscopy, X‐ray diffraction, energy dispersive X‐ray spectroscopy, Fourier transform infrared and ultraviolet–visible spectroscopy. This Pd NPs/cuttlebone showed excellent catalytic activity in the reduction of 2,4‐dinitrophenylhydrazine to 2,4‐diaminophenylhydrazine by sodium borohydride as the source of hydrogen at ambient condition. The catalyst could be separated and recycled up to five cycles with no loss of its activity.Inspec keywords: catalysis, catalysts, chemical engineering, palladium, nanoparticles, field emission electron microscopy, scanning electron microscopy, X‐ray diffraction, X‐ray chemical analysis, sodium compounds, ultraviolet spectroscopy, visible spectroscopyOther keywords: catalytic reduction, 2,4‐dinitrophenylhydrazine, cuttlebone, Conium maculatum leaf extract, green process, palladium nanoparticles, antioxidant content, field‐emission scanning electron microscopy, X‐ray diffraction, energy dispersive X‐ray spectroscopy, Fourier transform infrared, ultraviolet–visible spectroscopy, 2,4‐diaminophenylhydrazine, sodium borohydride     

Multi expression programming: a new approach to formulation of soil classification

This paper presents an alternative approach to formulation of soil classification by means of a promising variant of genetic programming (GP), namely multi expression programming (MEP). Properties of soil, namely plastic limit, liquid limit, color of soil, percentages of gravel, sand, and fine-grained particles are used as input variables to predict the classification of soils. The models are developed using a reliable database obtained from the previously published literature. The results demonstrate that the MEP-based formulas are able to predict the target values to high degree of accuracy. The MEP-based formulation results are found to be more accurate compared with numerical and analytical results obtained by other researchers.