Non-linear Shunting of Piezo-actuators for Vibration Suppression

Vibrations at a resonant frequency lead to catastrophic failure or at the very least, shorten the life span of the structure due to fatigue. These problems force engineers to implement damping techniques. Smart materials have been used over two decades to reduced vibration amplitudes. Recently, there has been much research and development on smart materials and structures. This work introduces an innovative approach for vibration suppression using passively shunted piezolectric materials. Initially linear circuit elements such as resistors, capacitors, and inductances, or building a non-linear circuit with different impedance designs were used. Instead of such elements, a switched electromechanical shunt has been proposed as a method to suppress vibrations of mechanical structures. In this state switching technique, bonded piezoelectric elements are switched from open circuit to closed circuit depending on the voltage produced from the piezoelectric patch. This new shunt circuit utilizes diodes. Diodes are nonlinear circuit elements and vibration amplitude is reduced due to introduction of nonlinearity into the system. A physics-based electro-mechanical model is developed and validated against experimental results. The smart plate consists of a rectangular aluminum plate modeled in cantilever configuration with surface bonded piezoelectric patches. Basic equations for piezoelectric sensors and actuators are presented. The equation of motion for the plate structure with bonded piezoelectric patch is depicted. The implementation of the circuit is demonstrated analytically and experimentally. The concept is demonstrated on two different modes and vibration peaks are lowered using the above mentioned circuit. Then a numerical model of the plate with the piezoelectric patch and the circuit is built in Simulink after designing a finite element model in ABAQUS. The data shows the effect of damping in Frequency Response Functions (FRFs) and in the response plots. A state-space model is also developed. Simulations of the model are compared to the experimental results. The results indicate the feasibility of the smart damping materials for many industrial applications where reducing noise and vibrations are desired. It is clear that the maximum suppression that can be obtained with this method is dependent on the voltage drop across the piezoelectric element

Image enhancement in embedded devices for internet of things

This paper proposes a new color interpolation method which can be used in embedded devices for IoT system. In this work, we use regression approach for generating and designing filters to restore color image. The filters are designed with four sizes, 5x5 training filter, 7x7 training filter, 9x9 training filter, and 11x11 training filter. The obtained filters are tested in 25 LC dataset to assess the performance. Experimental results inform that the proposed filters provide outstanding performance when they are compared with conventional methods. As compared with the other methods, the proposed filters produce the best average interpolation performance both objectively and visually

Rectification of Random Walkers Induced by Energy Flow at Boundaries

We explore rectification phenomena in a system where two-dimensional random walkers interact with a funnel-shaped ratchet under two distinct classes of reflection rules. The two classes include the angle of reflection exceeding the angle of incidence ($\theta_{reflect} > \theta_{incident}$), or vice versa ($\theta_{reflect} < \theta_{incident}$). These generalized boundary reflection rules are indicative of non-equilibrium conditions due to the introduction of energy flows at the boundary. Our findings reveal that the nature of such particle-wall interactions dictates the system's behavior: the funnel either acts as a pump, directing flow, or as a collector, demonstrating a ratchet reversal. Importantly, we provide a geometric proof elucidating the underlying mechanism of rectification, thereby offering insights into why certain interactions lead to directed motion, while others do not.Comment: 5 pages, 6 figure

Towards Certification of Machine Learning-Based Distributed Systems

Machine Learning (ML) is increasingly used to drive the operation of complex distributed systems deployed on the cloud-edge continuum enabled by 5G. Correspondingly, distributed systems' behavior is becoming more non-deterministic in nature. This evolution of distributed systems requires the definition of new assurance approaches for the verification of non-functional properties. Certification, the most popular assurance technique for system and software verification, is not immediately applicable to systems whose behavior is determined by Machine Learning-based inference. However, there is an increasing push from policy makers, regulators, and industrial stakeholders towards the definition of techniques for the certification of non-functional properties (e.g., fairness, robustness, privacy) of ML. This article analyzes the challenges and deficiencies of current certification schemes, discusses open research issues and proposes a first certification scheme for ML-based distributed systems.Comment: 5 pages, 1 figure, 1 tabl

Emergent learning in physical systems as feedback-based aging in a glassy landscape

By training linear physical networks to learn linear transformations, we discern how their physical properties evolve due to weight update rules. Our findings highlight a striking similarity between the learning behaviors of such networks and the processes of aging and memory formation in disordered and glassy systems. We show that the learning dynamics resembles an aging process, where the system relaxes in response to repeated application of the feedback boundary forces in presence of an input force, thus encoding a memory of the input-output relationship. With this relaxation comes an increase in the correlation length, which is indicated by the two-point correlation function for the components of the network. We also observe that the square root of the mean-squared error as a function of epoch takes on a non-exponential form, which is a typical feature of glassy systems. This physical interpretation suggests that by encoding more detailed information into input and feedback boundary forces, the process of emergent learning can be rather ubiquitous and, thus, serve as a very early physical mechanism, from an evolutionary standpoint, for learning in biological systems.Comment: 11 pages, 7 figure

Phytochemical investigation and cytotoxic activity of hydro alcoholic fraction of Trianthema decandra

193-203The objective of our study was to perform phytochemical analysis and evaluate for cytotoxic activity of hydro alcoholic fraction (H1) of Trianthema decandra L. (Aizoaceae) against breast, liver and cervical cancers. Hydro alcoholic fraction was separated from methanolic extract, which was prepared by maceration method from aerial parts of T. decandra The GC-MS analysis confirms the presence of seventeen bioactive compounds which belongs to carbohydrates, terpenoids, alkaloids, cardiac glycosides, fatty acids and their esters or alcohols, and their presence were supported with Fourier Transform Infrared Spectroscopy (FT-IR) and preliminary phytochemical analysis. Most of the compounds are biologically active and are known to exhibit antimicrobial and cancer preventive properties. Hydro alcoholic fraction was subjected to morphological evaluation and MTT cell viability assay. It has exhibited significant cytotoxic activity and their IC50 values were determined as 165.22 + 1.53 mg/ml, 175.28 + 1.7 mg/ml and 201.93 + 1.33 mg/ml against MCF-7, HeLa and HepG2 cancer cells, respectively. This bioactive fraction has exhibited cytotoxicity relatively more against breast cancer than cervical and liver cancers

Reliability and capability based computation offloading strategy for vehicular ad hoc clouds

In the Internet of Vehicles (IoV), with the increasing demand for intelligent technologies such as driverless driving, more and more in-vehicle applications have been put into autonomous driving. For the computationally intensive task, the vehicle self-organizing network uses other high-performance nodes in the vehicle driving environment to hand over tasks to these nodes for execution. In this way, the computational load of the cloud alleviated. However, due to the unreliability of the communication link and the dynamic changes of the vehicle environment, lengthy task completion time may lead to the increase of task failure rate. Although the flooding algorithm can improve the success rate of task completion, the offloading expend will be large. Aiming at this problem, we design the partial flooding algorithm, which is a comprehensive evaluation method based on system reliability in the vehicle computing environment without infrastructure. Using V2V link to select some nodes with better performance for partial flooding offloading to reduce the task complete time, improve system reliability and cut down the impact of vehicle mobility on offloading. The results show that the proposed offloading strategy can not only improve the utilization of computing resources, but also promote the offloading performance of the system

Towards Transparent and Trustworthy Cloud

Despite its immense benefits in terms of flexibility, resource consumption, and simplified management, cloud computing raises several concerns due to lack of trust and transparency. Like all computing paradigms based on outsourcing, the use of cloud computing is largely a matter of trust. There is an increasing pressure by cloud customers for solutions that would increase their confidence that a cloud service/application is behaving in a secure and correct manner. Cloud assurance techniques, developed to assess the trustworthiness of cloud services, can play a major role in building trust. In this paper, we start from the assumption that an opaque cloud does not fit security, and present a reliable evidence collection process and infrastructure extending existing assurance techniques towards the definition of a trustworthy cloud. The proposed process and infrastructure are applied to a case study on cloud certification showing their utility

Defining and matching test-based certificates in Open SOA

Following the Service-Oriented Architecture (SOA) and the Cloud paradigms, an increasing number of organizations implement their business processes and applications via runtime composition of services made available on the cloud by single suppliers. This scenario however introduces new security risks and threats, as the service providers may not provide the level of assurance required by their customers. There is therefore the need of a new certification scheme for services that provides trusted evidence that a service has some security properties, and a matching infrastructure to compare service certificates with users' certification preferences. In this paper, we propose a first solution to the definition of a test-based certification process for SOA