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International audience; Motivated by an application of vibration analysis to gearbox fault surveillance, a new demodulation approach for gearbox vibration signals has recently been developed. Within this approach, the demodulation problem yields the study of a rank factorization problem for centrohermitian matrices. In this paper, using the properties of centrohermitian matrices, we first show that the rank factorization problem for centrohermitian matrices can be transformed into a rank factorization problem for real matrices. Based on previous works, we then show how to parametrize a class of centrohermitian solutions of the rank factorization problem that is important in practice.

Secure multiparty protocols are useful tools for parties wishing to jointly compute a function while keeping their input data secret. The millionaires' problem is the first secure two-party computation problem, where the goal is to securely compare two private numbers without a trusted third-party. There have been several solutions to the problem; however, these solutions are either insecure in the malicious model or cannot verify the validity of inputs. In this paper, we introduce Variance, a privacy-preserving two-party protocol for solving Yao's millionaires' problem in a Bitcoin setting, in which each party controls several Bitcoin accounts (single and multi signature addresses) and they want to find out who owns more bitcoins without revealing (1) how many accounts they own or the addresses associated with their accounts, (2) the balance of any of their accounts, and (3) their total wealth of bitcoins while assuring the other party that they are not claiming more bitcoin than they possess. We utilize zero knowledge proofs to provide a solution to the problem, and subsequently prove that Variance is secure against active adversaries in the malicious model.

This paper presents an elaboration of thin films dedicated to photovoltaic systems. Zinc oxide (ZnO) on fluorine tin oxide (FTO) coated glass substrates are one of the best semiconductors oriented to solar cell preparations. In this study, the ZnO solution is performed with some sol concentration (0.1 M to 0.5 M) to verify its effect on thin-film samples. On the other hand, samples prepared are analyzed and characterized in structural and the optical properties using different techniques as ultraviolet-visible (UV-vis) spectrometry, Fourier transform infrared spectroscopy (FT-IR) and X-ray diffraction (XRD). This work showed the variation of the energy gap (Eg) values. The Eg values allow us to ensure good solar cells. In this study, the thin films prepared showed that the energy gap values are ranged between 3.29 eV and 3.4 eV. These results led us to confirm the possibility of having an easy passage of the electrical current. In addition, the transmittance spectra of the ZnO/FTO thin films showed an average of ∼75% in the visible region and presented sharp absorption edges at 375 nm. The experimental preparation ensures a good decision about electrical energy production which based on the photovoltaic systems.

The Rothstein code is a binary vector representation of the slope of a line or scaling factor that was originally introduced for the scalar transformation of images. The methodology has built-in interpolation with each operation. The technique is underutilized for data operations and its use is amenable for the practical and real-world management of data from different sources, different data sampling methods, and discordant outputs from related processes. This work proposes and demonstrates the use of the code for assimilating data sets with discordant sizes for simple matrix operations. Examples presented are for the calculation of a matrix determinant, adding matrices, and matrix multiplication where the matrix sizes are untenable. The emphasis is on understanding the technique and its potential using simple examples, 2-dimensional matrices, and integer arithmetic.

This paper presents the first experimental results of a new MEMS microphone with in-vacuum capacitive transduction. The device is divided into a pressure-harvesting rigid piston in air, linked to a capacitive transducer enclosed in a vacuum cavity. In theory, this separation should lead to very low acoustical and mechanical noises, thereby increasing the overall microphone performance (estimated SNR>75 dB(A)). First wafer-level tests give a clear proof-of-concept of this new microphone design, with a resonance frequency of 19kHz and a measured sensitivity of $6\pm 0.5 \mathrm{fF}/\mathrm{Pa}$ .

Consensus protocols are mechanisms that enable a group of entities to reach an agreement on a specific subject. In blockchain systems, consensus protocols are the cornerstone of achieving security and scalability. They not only enable nodes in the network to agree on the valid information that can be added to the ledger while keeping all nodes synchronized, they also establish the sequence of order in which blocks (and consequently transactions) are affixed. In this paper, we provide a comprehensive review of the working principles of the most commonly used consensus protocols in blockchain-based cryptocurrencies. We categorize them based on their permission requirements and perform a thorough comparative evaluation. More specifically, we identify computational difficulty, barrier for entry, platform utilization, and weaknesses in terms of scalability and fairness.

A method to resample and scale data to arbitrary length with built-in interpolation was adapted from the scalar image transformation methods based on the Rothstein binary code for the slope of a line. Unlike other transformation methods, binary code transformations have built in interpolation. The theoretical validity of the method is based on human vision reception. An application to resample simulated signal to data lengths of powers of 2 for a Fast Fourier Transform (FFT) was presented as an example. A demonstration of validity was that FFT points from data of arbitrary N scaled to a power of two using the method matched the FFT from the original data series limited to powers of 2. A simple comparison to the methods of zero-padding and an averaging interpolation was also demonstrated. The computational advantage of the method may enhance or supplement standard signal processing techniques.

In this paper, we present the design, fabrication and first experimental results of a microscale hinge mechanism allowing the mechanical transfer of a force between two atmospheres. When applied to the design of a capacitive MEMS microphone, this mechanism allows the division of the device into two separate parts: a pressure harvesting membrane in air, linked to a capacitive transducer sitting in vacuum. Theoretically, this separation should result in very low acoustical and mechanical noises, thereby increasing overall microphone performance (estimated SNR>75dB(A)), while maintaining a small device footprint (

Over the years, email has evolved into one of the most widely used communication channels for both individuals and organizations. However, despite near ubiquitous use in much of the world, current information technology standards do not place emphasis on email security. Not until recently, webmail services such as Yahoo's mail and Google's gmail started to encrypt emails for privacy protection. However, the encrypted emails will be decrypted and stored in the service provider's servers. If the servers are malicious or compromised, all the stored emails can be read, copied and altered. Thus, there is a strong need for end-to-end (E2E) email encryption to protect email user's privacy. In this paper, we present a certificateless one-way group key agreement protocol with the following features, which are suitable to implement E2E email encryption: (1) certificateless and thus there is no key escrow problem and no public key certificate infrastructure is required; (2) one-way group key agreement and thus no back-and-forth message exchange is required; and (3) n-party group key agreement (not just 2- or 3-party). This paper also provides a security proof for the proposed protocol using "proof by simulation". Finally, efficiency analysis of the protocol is presented at the end of the paper.

in this paper, a cognitive system based on a nonlinear neural controller and an intelligent algorithm is used to guide an autonomous mobile robot during continuous path-tracking. The controller will navigate over solid obstacles with avoidance. The goal of the proposed structure is to plan and track the reference path equation for the autonomous mobile robot in the mining environment in order to avoid the obstacles and reach to the target position by using intelligent optimization algorithms. Particle Swarm Optimization and Artificial Bee Colony algorithms are used for finding the solutions of the mobile robot navigation problems in the mine by searching the optimal paths. The algorithms are used for finding the reference path equation of the optimal path, as well as finding and tuning the neural control gains values online for the nonlinear neural controller. The goal is to obtain the best torques actions of the wheels for the mining autonomous mobile robot. Simulation results are done by using MATLAB which showed that the proposed cognitive system is more accurate in terms of planning a reference path to avoid obstacles, online finding, and tuning parameters of the controller which generates smooth control actions without saturation for tracking the reference path equation, as well as minimizing the mobile robot tracking pose error.

Water-based and kerosene-based magnetic nanofluids are prepared, and used to study the photo-thermal conversion efficiency of a solar collector under solar simulator. Iron oxide coated with silica (Fe 3 O 4 @SiO 2 ) nanoparticles (NPs) were synthesized and dispersed in two types of base fluids (i.e., water and kerosene) as the absorbing medium. The temperature rise characteristics of the nanofluids are investigated at different heights of the solar collector, for a duration of 300 minutes, under solar intensities of 1000 W/m2 and 2000 W/m2. The experimental results show that Fe 3 O 4 @SiO 2 nanofluids improve the photo-thermal conversion efficiency compared with the base fluids, since the NPs enhance the light absorption effectiveness. The collector filled with Fe 3 O 4 @SiO 2 /kerosene nanofluid has more temperature intensification than the collector with Fe 3 O 4 @SiO 2 /H 2 O nanofluid. However, the last one has a higher photo-thermal conversion efficiency, for the reason that H 2 O has much higher specific heat capacity than kerosene. The overall performance characterization of the nanofluids demonstrated the utility of using nanofluids based on Fe 3 O 4 @SiO 2 NPs in direct absorption solar collectors.

The rapid development of cyber threats and intelligence challenges the traditional design of static cyber defense platforms. This paper discusses the need for an agile structure to inform the development of cybersecurity solutions that are not only widely adaptable to unknown threats, specific business practices, and technical requirements, but are also efficiently translatable to products. It employs a systems engineering approach in the evaluation of several Reference Architectures for cyber defense that were gathered from the both the public and private sector. The Northrop Grumman Cyber Defense Reference Architecture is introduced in this paper to go beyond basic cyber hygiene by focusing on cognitive tasks through functional implementations of advanced analytics and automation. The limitations of frameworks, design patterns, and security control checklists in comparison to reference architectures are also discussed.

This paper presents the measured results of two circuits fabricated with a millimeter wave 100 nm Gallium Nitride on Silicon (GaN/Si) process. The first circuit is a 27-34 GHz power amplifier, presenting 6 W of output power in pulsed operation and 5.6 W in CW operation. The second circuit, using exactly the same process, is a 8-12 GHz Low Noise Amplifier presenting 1.3 dB noise figure from 11 to 13 GHz.

The objective of this paper is to discuss different scenarios for Principal Component Analysis classifier implemented for email filtering process (Ham vs. spam emails). The study highlights on the variation of the accuracy of these classifiers with respect to the variation in feature preprocessing. Four scenarios were considered: Scenario 1: Ham and Spam classes are represented with different features. Scenario 2: Ham and Spam classes are represented with same features. Scenario 3: Ham and Spam classes are represented with common terms. Scenario 4: Ham and Spam classes are represented with common Features and Characteristic terms. Different experiments were done using a public corpus extracted from the University of California-Irvine Machine Learning Repository. Different training and test sets were used. A comparison with Support Vector Machine and Bayes detector was done to prove its superior behavior.

In the last decade, several approaches concerning private data release for data mining have been proposed. Data mashup, on the other hand, has recently emerged as a mechanism for integrating data from several data providers. Fusing both techniques to generate mashup data in a distributed environment while providing privacy and utility guarantees on the output involves several challenges. That is, how to ensure that no unnecessary information is leaked to the other parties during the mashup process, how to ensure the mashup data is protected against certain privacy threats, and how to handle the high-dimensional nature of the mashup data while guaranteeing high data utility. In this paper, we present Fusion, a privacy-preserving multi-party protocol for data mashup with guaranteed LKC-privacy for the purpose of data mining. Experiments on real-life data demonstrate that the anonymous mashup data provide better data utility, the approach can handle high dimensional data, and it is scalable with respect to the data size.

Kernel fuzzy clustering has been applied to data with nonlinear relationships. Two approaches were used: clustering with a single kernel and clustering with multiple kernels. While clustering with a single kernel doesn't work well with “multiple-density” clusters, Multiple Kernel Fuzzy clustering tries to find an optimal linear weighted combination of kernels with initial fixed (not necessarily the best) parameters. Our algorithm tries to find the optimal parameters of each kernel in each cluster. It is a generalization of the single Kernel Fuzzy c-means and the Multiple Kernel Fuzzy clustering algorithms. In our algorithm, there is no need to give “good” parameters of each kernel and no need to give an initial “good” number of kernels. Every cluster will be characterized by a Gaussian Kernel with optimal parameters. Using different databases and different clustering validity measures, it is compared to other similar clustering algorithms showing its effective clustering performance.

In this paper, we focus on the node localization problem in the context of wireless sensor networks (WSN). By adopting a cross-layer approach, we propose a novel single-anchor localization system that is able of intercepting its neighboring communications and simultaneously identifying (MAC layer) and localizing (Physical layer) the current transmitting node on the channel. The particularity of our proposal is that it does not have any impact on the nodes. The anchor is equipped with an antenna array with large aperture (compared to the wavelength), which allows both traffic analysis and localization of any transmitting node in the covered localization area. The spatial performance of the proposal is evaluated by simulation in all the localization area (ZL) as a function of the signal-to-noise ratio (SNR). Simulation results show good localization performance, especially near the anchor.

© 2014 IEEE. This paper presents an in-depth study of designing, implementing and executing unit test cases using the xUnit.net testing tool in general and in the context of the TeleMedicine Cluster System project within the ICT Design subject delivered at UTS, Australia. The case studies are based on the utilisation of the tool in Visual Basic 2012 using the.NET framework for C#. The paper elucidates on how and why the xUnit framework can be applied in the context of the TMC system, and how it can be tailored to meet the testing ad integration needs of the delivery of TMC system.

Data-as-a-Service (DaaS) mashup enables data providers to dynamically integrate their data on demand depending on consumers' requests. Utilizing DaaS mashup, however, involves some challenges. Mashing up data from multiple sources to answer a consumer's request might reveal sensitive information and thereby compromise the privacy of individuals. Moreover, data integration of arbitrary DaaS providers might not always be sufficient to answer incoming requests. In this paper, we provide a cloud-based framework for privacy-preserving DaaS mashup that enables secure collaboration between DaaS providers for the purpose of generating an anonymous dataset to support data mining. Experiments on real-life data demonstrate that our DaaS mashup framework is scalable and can efficiently and effectively satisfy the data privacy and data mining requirements specified by the DaaS providers and the data consumers.