A privacy-preserving distributed transfer learning in activity recognition

Telecommunication Systems - Along with the widespread use of smartphones, activity recognition using embedded inertial sensors has intrigued researchers. The learning and employing activity...     

Hydrothermal synthesis of different colors and morphologies of ZnO nanostructures and comparison of their photocatalytic properties

Various zinc oxide nanostructures were synthesized using thermal decomposition of zinc acetate dihydrate in a single process. The characterization of samples using powder X-ray diffraction, scanning electron microscope and FT-IR measurements revealed that the pure phase of different morphologies such as nanoparticles, nanowires and nanodisks had been synthesized successfully. Surprisingly some synthesized ZnO nanostructures were dark gray. The results showed that the reason may have been related to the oxygen deficiency and strong asymmetric stretching mode of wurtzite ZnO nanostructure. Using such samples, the photodegradation of Methylene blue was performed by UV–vis absorption measurement and the effect of morphology on the photocatalytic properties of different ZnO nanostructures was examined. The results showed that the nanodisks had the best photocatalytic performance among the other morphologies. The reason was attributed to the presence of specific crystal planes such as (0001) facets in nanodisks which can improve their photocatalytic performance.     

An evolutionary decoding method for HMM-based continuous speech recognition systems using particle swarm optimization

The main recognition procedure in modern HMM-based continuous speech recognition systems is Viterbi algorithm. Viterbi algorithm finds out the best acoustic sequence according to input speech in the search space using dynamic programming. In this paper, dynamic programming is replaced by a search method which is based on particle swarm optimization. The major idea is focused on generating initial population of particles as the speech segmentation vectors. The particles try to achieve the best segmentation by an updating method during iterations. In this paper, a new method of particles representation and recognition process is introduced which is consistent with the nature of continuous speech recognition. The idea was tested on bi-phone recognition and continuous speech recognition workbenches and the results show that the proposed search method reaches the performance of the Viterbi segmentation algorithm ; however, there is a slight degradation in the accuracy rate.     

An analytical solution for nonlinear dynamics of a viscoelastic beam-heavy mass system

The aim of this study is to develop an approximate analytic solution for nonlinear dynamic response of a simply-supported Kelvin-Voigt viscoelastic beam with an attached heavy intra-span mass. A geometric nonlinearity due to midplane stretching is considered and Newton’s second law of motion along with Kelvin-Voigt rheological model, which is a two-parameter energy dissipation model, are employed to derive the nonlinear equations of motion. The method of multiple timescales is applied directly to the governing equations of motion, and nonlinear natural frequencies and vibration responses of the system are obtained analytically. Regarding the resonance case, the limit-cycle of the response is formulated analytically. A parametric study is conducted in order to highlight the influences of the system parameters. The main objective is to examine how the vibration response of a plain (i.e. without additional adornment) beam is modified by the presence of a heavy mass, attached somewhere along the beam length.     

Quantum Entanglement and Cryptography for Automation and Control of Dynamic Systems

This paper addresses the application of quantum entanglement and cryptography for automation and control of dynamic systems.A dynamic system is a system where t...     

Decision fusion of horizontal and vertical trajectories for recognition of online Farsi subwords

Online handwriting is formed by a combination of horizontal and vertical trajectories. If these trajectories are treated separately, new recognition methods are emerged. In contrast, one classifier is often used to recognize handwriting. In this work, some features for x(t) and y(t) signals were proposed and used to make two separate classifiers. After initial recognition by these classifiers, their results were fused for final recognition. Using HMM classifiers and simple product rule for decision fusion, the recognition results of 42 classes of Farsi subwords showed promising achievements.     

Energy Metabolites as Biomarkers in Ischemic and Dilated Cardiomyopathy

With more than 25 million people affected, heart failure (HF) is a global threat. As energy production pathways are known to play a pivotal role in HF, we sought here to identify key metabolic changes in ischemic- and non-ischemic HF by using a multi-OMICS approach. Serum metabolites and mRNAseq and epigenetic DNA methylation profiles were analyzed from blood and left ventricular heart biopsy specimens of the same individuals. In total we collected serum from n = 82 patients with Dilated Cardiomyopathy (DCM) and n = 51 controls in the screening stage. We identified several metabolites involved in glycolysis and citric acid cycle to be elevated up to 5.7-fold in DCM (p = 1.7 × 10⁻⁶). Interestingly, cardiac mRNA and epigenetic changes of genes encoding rate-limiting enzymes of these pathways could also be found and validated in our second stage of metabolite assessment in n = 52 DCM, n = 39 ischemic HF and n = 57 controls. In conclusion, we identified a new set of metabolomic biomarkers for HF. We were able to identify underlying biological cascades that potentially represent suitable intervention targets.     

天气雷达低噪声放大器的仿真设计

The intersection of Quantum Technologies and Robotics Autonomy is explored in the present paper. The two areas are brought together in establishing an interdisciplinary interface that contributes to advancing the field of system autonomy, and pushes the engineering boundaries beyond the existing techniques. The present research adopts the experimental aspects of quantum entanglement and quantum cryptography, and integrates these established quantum capabilities into distributed robotic platforms, to explore the possibility of achieving increased autonomy for the control of multi-agent robotic systems engaged in cooperative tasks. Experimental quantum capabilities are realized by producing single photons (using spontaneous parametric down-conversion process), polarization of photons, detecting vertical and horizontal polarizations, and single photon detecting/counting. Specifically, such quantum aspects are implemented on network of classical agents, i.e., classical aerial and ground robots/unmanned systems. With respect to classical systems for robotic applications, leveraging quantum technology is expected to lead to guaranteed security, very fast control and communication, and unparalleled quantum capabilities such as entanglement and quantum superposition that will enable novel applications.     

Bistable Piezoelectric Flutter Energy Harvesting with Uncertainty

The analytical formulation of piezoelectric flutter energy harvesting using a bistable material, while considering uncertainties in the model is presented in this paper. Bistable laminates provide the advantage of large deflection due to the nonlinear snap-through characteristics when exposed to external loading, and can therefore provide a suitable base for piezoelectric material in energy harvesting applications. A piezoelectric material that is bounded on the surface of bistable laminates, subjected to external loading, generates large strains and hence relatively higher electrical output energy, in comparison with the case where piezoelectric material is bonded on a regular surface, with analogous loading conditions. Although information regarding the external loading, material characteristics of the bistable laminate and the piezoelectric material, boundary conditions, and overall electrical circuit efficiency can be defined for analytical purposes, the exact model of the system is not readily accessible. The unavoidable uncertainties in the material, loading, and efficiency of a complex system call for a probabilistic approach. Hence, this paper provides a formulation that considers uncertainty bounds in obtaining a realistic model. Optimal Uncertainty Quantification (OUQ) is used in this paper, which takes into account uncertainty measures with optimal bounds and incomplete information about the system, as a well-defined optimization problem according to maximum probabilities, subjected to the imposed constraints. The OUQ allows the inspection of the solution for a span of uncertain input parameters, as a reliable and realistic model.