Energy-efficient,fast-settling,modified nested-current-mirror,single-stage-amplifier for high-resolution LCDs in 90-nm CMOS

The Internet of Things (IoT) presents opportunities to address a variety of systemic, metabolic healthcare issues. Cardiovascular disease and diabetes are among the greatest contributors to premature death worldwide. Wireless wearable continuous monitoring systems such as ECG sensors connected to the IoT can greatly decrease the risk of death related to cardiac issues by providing valuable long-term information to physicians, as well as immediate contact with emergency services in the event of a heart attack or stroke. In this report we discuss the fabrication, characterization and validation of composite fabric ECG sensors made from Nylon^® coated with reduced graphene oxide (rGO_x) as part of a self-powered wearable IoT sensor. We utilize an electronic probing station to measure electrical properties, take live ECG data to measure signal reliability, and provide detailed surface characterization through scanning electron microscopy. Finally, bonding between the layers of the composite and between composite and the Nylon^® is analyzed by Fourier transform Infrared spectroscopy. Furthermore, a low power analog front end circuit designed in 65 nm CMOS process is presented to interface the sensor with a system on chip used in a wearable IoT healthcare device.     

A Model-Based Reinforcement Learning Protocol for Routing in Vehicular Ad hoc Network

Todays by equipping vehicles with wireless technologies, Vehicular Ad Hoc Network (VANET) has been emerged. This type of network can be utilized in many fields such as emergency, safety or entertainment. It is also considered as a main component of intelligent transportation system. However, due to the nodes velocity (vehicles velocity), varying density, obstacles and lack of fixed infrastructure, finding and maintaining a route between nodes are always challenging in VANET. Any routing protocol can be effective only if the nodes can learn and adapt themselves with such a dynamic environment. One way to achieve this adaptation is using machine learning techniques. In this paper we try to reach this goal by applying Multi-Agent Reinforcement Learning (MARL) that enables agents to solve routing optimization problems in a distributed way. Although model-free Reinforcement Learning (RL) schemes are introduced for this purpose, such techniques learn using a trial and error scheme in a real environment so they cannot reach an optimal policy in a short time. To deal with such a problem, we have proposed a mode-based RL based routing scheme. We have also developed a Fuzzy Logic (FL) system to evaluate the quality of links between neighbor nodes based on parameters such as velocity and connection quality. Outputs of this fuzzy system have been used to form the state transition model, needed in MARL. Results of evaluations have shown that our approach can improve some routing metrics like delivery ratio, end-to-end delay and traffic overhead.

     

Multi-objective algorithms for the application mapping problem in heterogeneous multiprocessor embedded system design

The Journal of Supercomputing - Design at the Electronic System-Level tackles the increasing complexity of embedded systems by raising the level of abstraction in system specification and modeling....     

Flow separation control in open-channel bends

The investigation of fluid flow in sharp open-channel bends is key to controlling undesired sedimentation in natural river reaches. The difficulties are associated with controlling the flow separation in meanderings. Flow separation decreases the width of the flow, and consequently, the conveyance capacity while increasing erosion and mixing. This study proposes a novel approach to reduce the flow separation at the inner banks of sharp open-channel bends. Three-dimensional numerical experiments were conducted. To find the most reliable procedure, five turbulence models were examined. The employed numerical approach is formulated within the framework of the finite volume method and the volume of fluid (VOF) technique to solve the Navier–Stokes equations. Water levels and velocity profiles are obtained in different sections of the channel and are compared to experimental studies of a 90° sharp open-channel bend. A close agreement is observed using the RSM (Reynolds stress model) turbulence model. Moreover, the evaluation of acquired velocity profiles demonstrates that in a regular bend, the lowest velocity occurs near the inner bank, where it has a flow separation tendency. The same numerical procedure is employed to simulate water flow through a sharp converging open-channel bend. The measurements of velocity profiles and velocity vectors in the curved sections support the idea that decreasing the channel width considerably reduces the overall velocity variations in cross-sectional areas of the test case and is effective to control flow separation.     

Design and fabrication of a new high gain multilayer negative refractive index metamaterial antenna for X‐band applications

This article presents the design of a planar high gain and wideband antenna using a negative refractive index multilayer superstrate in the X‐band. This meta‐antenna is composed of a four‐layer superstrate placed on a conventional patch antenna. The structure resonates at a frequency of 9.4 GHz. Each layer of the metamaterial superstrate consists of a 7 × 7 array of electric‐field‐coupled resonators, with a negative refractive index of 8.66 to 11.83 GHz. The number of layers and the separation of superstrate layers are simulated and optimized. This metamaterial lens has significantly increased the gain of the patch antenna to 17.1 dBi. Measurements and simulation results proved about 10 dB improvement of the gain.     

Application of Swarm Intelligence and Evolutionary Computation Algorithms for Optimal Reservoir Operation

Water Resources Management - Real-world problems often contain complex structures and various variables, and classical optimization techniques may face difficulties finding optimal solutions....     

Deployment optimization of software objects by design-level delay estimation

The quantitative performance evaluation of different deployments of distributed software objects over computational nodes is one of the main activities during the early stages of the design phase and should be supported by automated tools. The important design decision is to finding the optimal placement of objects, from the performance viewpoint, for different input workloads. Each deployment of objects may impose two kinds of delay on the overall performance of the software: first, the communicational delay due to the remote invocations among distributed objects and second, the computational delay due to the resource sharing by two or more concurrently executing object invocations. The object deployment problem can be formulated as an optimization problem to find the optimal deployment for which the total delay is minimal. In this paper an analytical model for delay prediction of object deployments considering the input workload of the software is presented. This model applies the object-oriented load metrics such as object population and object utilization to estimate the total amount of delay corresponding to a given object deployment. To achieve this, a novel method, called delay propagation, is proposed to compute the amount of delay corresponding to each method invocation which affects the overall response time of the software. In order to verify the proposed analytical delay predictor model, a statistical regression-based method is used. Moreover, by comparing the proposed method with the existing deployment optimization methods, which apply the Layered Queueing Networks to evaluate the performance of each deployment in the search space, a significant improvement in efficiency is observed due to the fast evaluation of each deployment instance in the search space.     

Evaluating banana ripening status from measuring dielectric properties

Electrical properties of banana fruit were studied in order to develop a rapid and non-destructive assessment method and to control its ripening treatment. A 5 V sine wave AC power supply and a rectangular parallel plate capacitor sample were used to span the difference in capacitance caused by the introduction of a banana fruit between the plates. To remove the effect of air gap between the plates, an equivalent capacitor was derived. The correlation between dielectric constant and quality parameters of banana fruit was investigated. The dielectric constant of banana fruit decreased as a result of the ripening treatment. Experiments indicated that the best frequency of sine wave that can predict the level of ripeness was 100 kHz. The coefficient of determination (R²) of ripeness level prediction was obtained 0.94 at this frequency. This method can confidently predict the ripeness level of banana fruit.     

Enhanced Hilbert–Huang transform and its application to modal identification

The well‐known Hilbert–Huang transform (HHT) consists of empirical mode decomposition to extract intrinsic mode functions (IMFs) and Hilbert spectral analysis to obtain time–frequency characteristics of IMFs through the Hilbert transform. There are two mathematical requirements that limit application of the Hilbert transform. Moreover, noise effects caused by the empirical mode decomposition procedure add a scatter to derivative‐based instantaneous frequency determined by the Hilbert transform. In this paper, a new enhanced HHT is proposed in which by avoiding mathematical limitations of the Hilbert spectral analysis, an additional parameter is employed to reduce the noise effects on the instantaneous frequencies of IMFs. To demonstrate the efficacy of the proposed method, two case studies associated with structural modal identification are selected. In the first case, through identification of a typical 3‐DOF structural model subjected to a random excitation, accuracy of the enhanced method is verified. In the second case, ambient response data recorded from a real 15‐story building are analyzed, and nine modal frequencies of the building are identified. The case studies indicate that the enhanced HHT provides more accurate and physically meaningful results than HHT and is capable to be an efficient tool in structural engineering applications. Copyright © 2012 John Wiley & Sons, Ltd.