Search results for: Compressed sensing

Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle

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The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.

Keywords: Complex-valued signal processing, synthetic aperture radar (SAR), 2-D radar imaging, compressive sensing, Sparse Bayesian learning.

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Authors: Hae Young Lee, Tae Ho Cho

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In many sensor network applications, sensor nodes are deployed in open environments, and hence are vulnerable to physical attacks, potentially compromising the node's cryptographic keys. False sensing report can be injected through compromised nodes, which can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. Ye et al. proposed a statistical en-route filtering scheme (SEF) to detect such false reports during the forwarding process. In this scheme, the choice of a security threshold value is important since it trades off detection power and overhead. In this paper, we propose a fuzzy logic for determining a security threshold value in the SEF based sensor networks. The fuzzy logic determines a security threshold by considering the number of partitions in a global key pool, the number of compromised partitions, and the energy level of nodes. The fuzzy based threshold value can conserve energy, while it provides sufficient detection power.

Keywords: Fuzzy logic, security, sensor network.

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Authors: Naser Ahmadi Sani, Karim Solaimani, Lida Razaghnia, Jalal Zandi

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In recent decades, rapid and incorrect changes in land-use have been associated with consequences such as natural resources degradation and environmental pollution. Detecting changes in land-use is one of the tools for natural resource management and assessment of changes in ecosystems. The target of this research is studying the land-use changes in Haraz basin with an area of 677000 hectares in a 15 years period (1996 to 2011) using LANDSAT data. Therefore, the quality of the images was first evaluated. Various enhancement methods for creating synthetic bonds were used in the analysis. Separate training sites were selected for each image. Then the images of each period were classified in 9 classes using supervised classification method and the maximum likelihood algorithm. Finally, the changes were extracted in GIS environment. The results showed that these changes are an alarm for the HARAZ basin status in future. The reason is that 27% of the area has been changed, which is related to changing the range lands to bare land and dry farming and also changing the dense forest to sparse forest, horticulture, farming land and residential area.

Keywords: HARAZ Basin, Change Detection, Land-use, Satellite Data.

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Authors: P. Kumsawat, N. Pimpru, K. Attakitmongcol, A.Srikaew

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In this paper, we proposed an efficient data compression strategy exploiting the multi-resolution characteristic of the wavelet transform. We have developed a sensor node called “Smart Sensor Node; SSN". The main goals of the SSN design are lightweight, minimal power consumption, modular design and robust circuitry. The SSN is made up of four basic components which are a sensing unit, a processing unit, a transceiver unit and a power unit. FiOStd evaluation board is chosen as the main controller of the SSN for its low costs and high performance. The software coding of the implementation was done using Simulink model and MATLAB programming language. The experimental results show that the proposed data compression technique yields recover signal with good quality. This technique can be applied to compress the collected data to reduce the data communication as well as the energy consumption of the sensor and so the lifetime of sensor node can be extended.

Keywords: Wireless sensor network, wavelet transform, data compression, ZigBee, skipped high-pass sub-band.

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Authors: S. Mohamed Rabeek, Mi Kyoung Park, M. Annamalai Arasu

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This paper presents a design of a wireless read out system for tracking the frequency shift of the polymer coated piezoelectric micro electromechanical resonator due to gas absorption. The measure of this frequency shift indicates the percentage of a particular gas the sensor is exposed to. It is measured using an oscillator and an FPGA based frequency counter by employing the resonator as a frequency determining element in the oscillator. This system consists of a Gas Sensing Wireless Readout (GSWR) and an USB Wireless Transceiver (UWT). GSWR consists of an oscillator based on a trans-impedance sustaining amplifier, an FPGA based frequency readout, a sub 1GHz wireless transceiver and a micro controller. UWT can be plugged into the computer via USB port and function as a wireless module to transfer gas sensor data from GSWR to the computer through its USB port. GUI program running on the computer periodically polls for sensor data through UWT - GSWR wireless link, the response from GSWR is logged in a file for post processing as well as displayed on screen.

Keywords: Gas sensor, GSWR, micro-mechanical system, UWT, volatile emissions.

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Authors: Othman Belgassim, Krzysztof Jemielniak

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The analysis of Acoustic Emission (AE) signal generated from metal cutting processes has often approached statistically. This is due to the stochastic nature of the emission signal as a result of factors effecting the signal from its generation through transmission and sensing. Different techniques are applied in this manner, each of which is suitable for certain processes. In metal cutting where the emission generated by the deformation process is rather continuous, an appropriate method for analysing the AE signal based on the root mean square (RMS) of the signal is often used and is suitable for use with the conventional signal processing systems. The aim of this paper is to set a strategy in tool failure detection in turning processes via the statistic analysis of the AE generated from the cutting zone. The strategy is based on the investigation of the distribution moments of the AE signal at predetermined sampling. The skews and kurtosis of these distributions are the key elements in the detection. A normal (Gaussian) distribution has first been suggested then this was eliminated due to insufficiency. The so called Beta distribution was then considered, this has been used with an assumed β density function and has given promising results with regard to chipping and tool breakage detection.

Keywords: AE signal, skew, kurtosis, tool failure

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Authors: Roozbeh Keshmiri, Alireza Mohamad Shahri

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Fuzzy controllers are potential candidates for the control of nonlinear, time variant and also complicated systems. Anti lock brake system (ABS) which is a nonlinear system, may not be easily controlled by classical control methods. An intelligent Fuzzy control method is very useful for this kind of nonlinear system. A typical antilock brake system (ABS) by sensing the wheel lockup, releases the brakes for a short period of time, and then reapplies again the brakes when the wheel spins up. In this paper, an intelligent fuzzy ABS controller is designed to adjust slipping performance for variety of roads. There are tow major sections in the proposing control system. First section consists of tow Fuzzy-Logic Controllers (FLC) providing optimal brake torque for both front and rear wheels. Second section which is also a FLC provides required amount of slip and torque references properties for different kind of roads. Simulation results of our proposed intelligent ABS for three different kinds of road show more reliable and better performance in compare with two other break systems.

Keywords: Fuzzy Logic Control, ABS, Anti lock BrakingSystem.

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Authors: Christine O. Wangia, Jennifer A. Orwa, Francis W. Muregi, Patrick G. Kareru, Kipyegon Cheruiyot, Eric Guantai

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Ruellia (syn. Dipteracanthus) species are wild perennial creepers belonging to the Acanthaceae family. These species are reported to possess anti-inflammatory, analgesic, antioxidant, gastroprotective, anticancer, and immuno-stimulant properties. Phytochemical screening of both aqueous and methanolic extracts of Ruellia species revealed the presence of saponins. Saponins have been reported to possess anti-inflammatory, antioxidant, immuno-stimulant, antihepatotoxic, antibacterial, anticarcinogenic, and antiulcerogenic activities. The objective of this study was to quantify and analyze the Fourier transform infrared (FTIR) spectra of saponins in crude extracts of three Kenyan Ruellia species namely Ruellia prostrata (RPM), Ruellia lineari-bracteolata (RLB) and Ruellia bignoniiflora (RBK). Sequential organic extraction of the ground whole plant material was done using petroleum ether (PE), chloroform, ethyl acetate (EtOAc), and absolute methanol by cold maceration, while aqueous extraction was by hot maceration. The plant powders and extracts were mixed with spectroscopic grade KBr and compressed into a pellet. The infrared spectra were recorded using a Shimadzu FTIR spectrophotometer of 8000 series in the range of 3500 cm^-1 - 500 cm^-1. Quantitative determination of the saponins was done using standard procedures. Quantitative analysis of saponins showed that RPM had the highest quantity of crude saponins (2.05% ± 0.03), followed by RLB (1.4% ± 0.15) and RBK (1.25% ± 0.11), respectively. FTIR spectra revealed the spectral peaks characteristic for saponins in RPM, RLB, and RBK plant powders, aqueous and methanol extracts; O-H absorption (3265 - 3393 cm^-1), C-H absorption ranging from 2851 to 2924 cm^-1, C=C absorbance (1628 - 1655 cm^-1), oligosaccharide linkage (C-O-C) absorption due to sapogenins (1036 - 1042 cm^-1). The crude saponins from RPM, RLB and RBK showed similar peaks to their respective extracts. The presence of the saponins in extracts of RPM, RLB and RBK may be responsible for some of the biological activities reported in the Ruellia species.1

Keywords: Ruellia bignoniiflora, Ruellia lineari-bracteolata, Ruellia prostrata, Saponins.

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Authors: Dean J. Callaghan, Mark M. McGrath

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Sensorized instruments that accurately measure the interaction forces (between biological tissue and instrument endeffector) during surgical procedures offer surgeons a greater sense of immersion during minimally invasive robotic surgery. Although there is ongoing research into force measurement involving surgical graspers little corresponding effort has been carried out on the measurement of forces between scissor blades and tissue. This paper presents the design and development of a force measurement test apparatus, which will serve as a sensor characterization and evaluation platform. The primary aim of the experiments is to ascertain whether the system can differentiate between tissue samples with differing mechanical properties in a reliable, repeatable manner. Force-angular displacement curves highlight trends in the cutting process as well the forces generated along the blade during a cutting procedure. Future applications of the test equipment will involve the assessment of new direct force sensing technologies for telerobotic surgery.

Keywords: Force measurement, minimally invasive surgery, scissor blades, tissue cutting.

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Authors: Mukesh Singh Boori, Vít Voženílek

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Olomouc is a unique and complex landmark with widespread forestation and land use. This research work was conducted to assess important and complex land use change trajectories in Olomouc region. Multi-temporal satellite data from 1991, 2001 and 2013 were used to extract land use/cover types by object oriented classification method. To achieve the objectives, three different aspects were used: (1) Calculate the quantity of each transition; (2) Allocate location based landscape pattern (3) Compare land use/cover evaluation procedure. Land cover change trajectories shows that 16.69% agriculture, 54.33% forest and 21.98% other areas (settlement, pasture and water-body) were stable in all three decade. Approximately 30% of the study area maintained as a same land cove type from 1991 to 2013. Here broad scale of political and socioeconomic factors was also affect the rate and direction of landscape changes. Distance from the settlements was the most important predictor of land cover change trajectories. This showed that most of landscape trajectories were caused by socio-economic activities and mainly led to virtuous change on the ecological environment.

Keywords: Remote Sensing, land use/cover, Change trajectories, Image classification.

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Authors: Satyavati Shukla, Lakhan V. Rathod, Mohan V. Khire

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Rapid urbanization changes the land use/land cover pattern of a developing region. Due to these land surface changes, stream flow of the rivers also changes. It is important to investigate the factors affecting hydrological characteristics of the river basin for better river basin management planning. This study is aimed to understand the effect of Land Use/Land Cover (LU/LC) changes on stream flow of Upper Bhima River basin which is highly stressed in terms of water resources. In this study, Upper Bhima River basin is divided into two adjacent sub-watersheds: Mula-Mutha (urbanized) sub-watershed and Bhima (non-urbanized) sub-watershed. First of all, LU/LC changes were estimated over 1980, 2002, and 2009 for both Mula-Mutha and Bhima sub-watersheds. Further, stream flow simulations were done using Soil and Water Assessment Tool (SWAT) for the streams draining both watersheds. Results revealed that stream flow was relatively higher for urbanized sub-watershed. Through Sensitivity Analysis it was observed that out of all the parameters used, base flow was the most sensitive parameter towards LU/LC changes.

Keywords: Land Use/Land Cover, remote sensing, stream flow, urbanization.

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Authors: M. Geetha Priya, D. Krishnaveni

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Snow depth estimation and monitoring studies have been carried out for decades using empirical relationship or extrapolation of point measurements carried out in field. With the development of advanced satellite based remote sensing techniques, a modified approach is proposed in the present study to estimate the winter accumulated snow depth at basin scale. Assessment of snow depth by differencing Digital Elevation Model (DEM) generated at the beginning and end of winter season can be experimented for the region of interest (Himalayan and polar regions) accounting for winter accumulation (solid precipitation). The proposed approach is based on existing geodetic method that is being used for glacier mass balance estimation. Considering the satellite datasets purely acquired during beginning and end of winter season, it is possible to estimate the change in depth or thickness for the snow that is accumulated during the winter as it takes one year for the snow to get transformed into firn (snow that has survived one summer or one-year old snow).

Keywords: Digital elevation model, snow depth, geodetic method, snow cover.

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Authors: Tae Kyung Kim, Hee Suk Seo

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Recent advances in wireless sensor networks have led to many routing methods designed for energy-efficiency in wireless sensor networks. Despite that many routing methods have been proposed in USN, a single routing method cannot be energy-efficient if the environment of the ubiquitous sensor network varies. We present the controlling network access to various hosts and the services they offer, rather than on securing them one by one with a network security model. When ubiquitous sensor networks are deployed in hostile environments, an adversary may compromise some sensor nodes and use them to inject false sensing reports. False reports can lead to not only false alarms but also the depletion of limited energy resource in battery powered networks. The interleaved hop-by-hop authentication scheme detects such false reports through interleaved authentication. This paper presents a LMDD (Low energy method for data delivery) algorithm that provides energy-efficiency by dynamically changing protocols installed at the sensor nodes. The algorithm changes protocols based on the output of the fuzzy logic which is the fitness level of the protocols for the environment.

Keywords: Data delivery, routing, simulation.

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Authors: Yohei Saika, Hiroki Sakaematsu, Shota Akiyama

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We investigated statistical performance of Bayesian inference using maximum entropy and MAP estimation for several models which approximated wave-fronts in remote sensing using SAR interferometry. Using Monte Carlo simulation for a set of wave-fronts generated by assumed true prior, we found that the method of maximum entropy realized the optimal performance around the Bayes-optimal conditions by using model of the true prior and the likelihood representing optical measurement due to the interferometer. Also, we found that the MAP estimation regarded as a deterministic limit of maximum entropy almost achieved the same performance as the Bayes-optimal solution for the set of wave-fronts. Then, we clarified that the MAP estimation perfectly carried out phase unwrapping without using prior information, and also that the MAP estimation realized accurate phase unwrapping using conjugate gradient (CG) method, if we assumed the model of the true prior appropriately.

Keywords: Bayesian inference using maximum entropy, MAP estimation using conjugate gradient method, SAR interferometry.

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Authors: Seung You Na, Joo Hyun Jung, Jin Young Kim, Mohammad AhangarKiasari

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There are various kinds of medical equipment which requires relatively accurate positional adjustments for successful treatment. However, patients tend to move without notice during a certain span of operations. Therefore, it is common practice that accompanying operators adjust the focus of the equipment. In this paper, tracking controllers for medical equipment are suggested to replace the operators. The tracking controllers use AHRS sensor information to recognize the movements of patients. Sensor fusion is applied to reducing the error magnitudes through linear Kalman filters. The image processing of optical markers is included to adjust the accumulation errors of gyroscope sensor data especially for yaw angles. The tracking controller reduces the positional errors between the current focus of a device and the target position on the body of a patient. Since the sensing frequencies of AHRS sensors are very high compared to the physical movements, the control performance is satisfactory. The typical applications are, for example, ESWT or rTMS, which have the error ranges of a few centimeters.

Keywords: AHRS, Sensor fusion, Tracking control, Position and posture.

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Authors: F.Alilat, S.Loumi, H.Merrad, B.Sansal

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In this article a modification of the algorithm of the fuzzy ART network, aiming at returning it supervised is carried out. It consists of the search for the comparison, training and vigilance parameters giving the minimum quadratic distances between the output of the training base and those obtained by the network. The same process is applied for the determination of the parameters of the fuzzy ARTMAP giving the most powerful network. The modification consist in making learn the fuzzy ARTMAP a base of examples not only once as it is of use, but as many time as its architecture is in evolution or than the objective error is not reached . In this way, we don-t worry about the values to impose on the eight (08) parameters of the network. To evaluate each one of these three networks modified, a comparison of their performances is carried out. As application we carried out a classification of the image of Algiers-s bay taken by SPOT XS. We use as criterion of evaluation the training duration, the mean square error (MSE) in step control and the rate of good classification per class. The results of this study presented as curves, tables and images show that modified fuzzy ARTMAP presents the best compromise quality/computing time.

Keywords: Neural Networks, fuzzy ART, fuzzy ARTMAP, Remote sensing, multispectral Classification.

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Authors: Sher Muhammad, Mirza Muhammad Waqar

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It is necessary to monitor and identify mangroves types and spatial extent near coastal areas because it plays an important role in coastal ecosystem and environmental protection. This research aims at identifying and mapping mangroves types along Karachi coast ranging from 24.79⁰ to 24.85⁰ in latitude and 66.91⁰ to 66.97⁰ in longitude using hyperspectral remote sensing data and techniques. Image acquired during February, 2012 through Hyperion sensor have been used for this research. Image pre processing includes geometric and radiometric correction followed by Minimum Noise Fraction (MNF) and Pixel Purity Index (PPI). The output of MNF and PPI has been analyzed by visualizing it in n-dimensions for end member extraction. Well distributed clusters on the n-dimensional scatter plot have been selected with the region of interest (ROI) tool as end members. These end members have been used as an input for classification techniques applied to identify and map mangroves species including Spectral Angle Mapper (SAM), Spectral Feature Fitting (SFF) and Spectral Information Diversion (SID). Only two types of mangroves namely Avicennia Marina (White Mangroves) and Avicennia germinans (Black Mangroves) have been observed throughout the study area.

Keywords: Mangrove, Hyperspectral, SAM, SFF, SID.

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Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: Ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph.

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Authors: B. G. Sheeparamatti, J. S. Kadadevarmath

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Microcantilevers are the basic MEMS devices, which can be used as sensors, actuators and electronics can be easily built into them. The detection principle of microcantilever sensors is based on the measurement of change in cantilever deflection or change in its resonance frequency. The objective of this work is to explore the analogies between mechanical and electrical equivalent of microcantilever beams. Normally scientists and engineers working in MEMS use expensive software like CoventorWare, IntelliSuite, ANSYS/Multiphysics etc. This paper indicates the need of developing electrical equivalent of the MEMS structure and with that, one can have a better insight on important parameters, and their interrelation of the MEMS structure. In this work, considering the mechanical model of microcantilever, equivalent electrical circuit is drawn and using force-voltage analogy, it is analyzed with circuit simulation software. By doing so, one can gain access to powerful set of intellectual tools that have been developed for understanding electrical circuits Later the analysis is performed using ANSYS/Multiphysics - software based on finite element method (FEM). It is observed that both mechanical and electrical domain results for a rectangular microcantlevers are in agreement with each other.

Keywords: Electrical equivalent circuit analogy, FEM analysis, micro cantilevers, micro sensors.

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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Speaker recognition is performed in high Additive White Gaussian Noise (AWGN) environments using principals of Computational Auditory Scene Analysis (CASA). CASA methods often classify sounds from images in the time-frequency (T-F) plane using spectrograms or cochleargrams as the image. In this paper atomic decomposition implemented by matching pursuit performs a transform from time series speech signals to the T-F plane. The atomic decomposition creates a sparsely populated T-F vector in “weight space” where each populated T-F position contains an amplitude weight. The weight space vector along with the atomic dictionary represents a denoised, compressed version of the original signal. The arraignment or of the atomic indices in the T-F vector are used for classification. Unsupervised feature learning implemented by a sparse autoencoder learns a single dictionary of basis features from a collection of envelope samples from all speakers. The approach is demonstrated using pairs of speakers from the TIMIT data set. Pairs of speakers are selected randomly from a single district. Each speak has 10 sentences. Two are used for training and 8 for testing. Atomic index probabilities are created for each training sentence and also for each test sentence. Classification is performed by finding the lowest Euclidean distance between then probabilities from the training sentences and the test sentences. Training is done at a 30dB Signal-to-Noise Ratio (SNR). Testing is performed at SNR’s of 0 dB, 5 dB, 10 dB and 30dB. The algorithm has a baseline classification accuracy of ~93% averaged over 10 pairs of speakers from the TIMIT data set. The baseline accuracy is attributable to short sequences of training and test data as well as the overall simplicity of the classification algorithm. The accuracy is not affected by AWGN and produces ~93% accuracy at 0dB SNR.

Keywords: Time-frequency plane, atomic decomposition, envelope sampling, Gabor atoms, matching pursuit, sparse dictionary learning, sparse autoencoder.

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Authors: Vladimir Veremey

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The paper describes the design and simulation of dual-polarization antennas that use the resonance and radiating properties of the H₀₀ mode of metal open waveguides. The proposed antennas are formed by two orthogonal slots in a finite conducting ground plane. The slots are backed by metal screens connected to the ground plane forming open waveguides. It has been shown that the antenna designs can be efficiently used in mm-wave bands. The antenna single mode operational bandwidth is higher than 10%. The antenna designs are very simple and low-cost. They allow flush installation and can be efficiently used in various communication and remote sensing devices on fast moving carriers. Mutual coupling between antennas of the proposed design is very low. Thus, multiple antenna structures with proposed antennas can be efficiently employed in multi-band and in multiple-input-multiple-output (MIMO) systems.

Keywords: Antenna, antenna arrays, multiple-input-multiple-output, MIMO, millimeter wave bands, slot antenna, flush installation, directivity, open waveguide, conformal antennas.

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Authors: M. Maleki, M. Latifi, M. Amani-Tehran

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Nano fibers produced by electrospinning are of industrial and scientific attention due to their special characteristics such as long length, small diameter and high surface area. Applications of electrospun structures in nanotechnology are included tissue scaffolds, fibers for drug delivery, composite reinforcement, chemical sensing, enzyme immobilization, membrane-based filtration, protective clothing, catalysis, solar cells, electronic devices and others. Many polymer and ceramic precursor nano fibers have been successfully electrospun with diameters in the range from 1 nm to several microns. The process is complex so that fiber diameter is influenced by various material, design and operating parameters. The objective of this work is to apply genetic algorithm on the parameters of electrospinning which have the most significant effect on the nano fiber diameter to determine the optimum parameter values before doing experimental set up. Effective factors including initial polymer concentration, initial jet radius, electrical potential, relaxation time, initial elongation, viscosity and distance between nozzle and collector are considered to determine finest diameter which is selected by user.

Keywords: Electrospinning, genetic algorithm, nano fiber diameter, optimization.

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic Resonance Imaging (MRI) is a lengthy medical scan that stems from a long acquisition time. Its length is mainly due to the traditional sampling theorem, which defines a lower boundary for sampling. However, it is still possible to accelerate the scan by using a different approach such as Compress Sensing (CS) or Parallel Imaging (PI). These two complementary methods can be combined to achieve a faster scan with high-fidelity imaging. To achieve that, two conditions must be satisfied: i) the signal must be sparse under a known transform domain, and ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm must be applied to recover the signal. While the rapid advances in Deep Learning (DL) have had tremendous successes in various computer vision tasks, the field of MRI reconstruction is still in its early stages. In this paper, we present an end-to-end method for MRI reconstruction from k-space to image. Our method contains two parts. The first is sensitivity map estimation (SME), which is a small yet effective network that can easily be extended to a variable number of coils. The second is reconstruction, which is a top-down architecture with lateral connections developed for building high-level refinement at all scales. Our method holds the state-of-art fastMRI benchmark, which is the largest, most diverse benchmark for MRI reconstruction.

Keywords: Accelerate MRI scans, image reconstruction, pyramid network, deep learning.

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Authors: M. Nirmala

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Power quality in terms of power factor, THD and precisely regulated output voltage are the major key factors for efficient operation of power electronic converters. This paper presents an easy and effective active wave shaping control scheme for the pulsed input current drawn by the uncontrolled diode bridge rectifier thereby achieving power factor nearer to unity and also satisfying the THD specifications. It also regulates the output DC-bus voltage. CCM boost power factor correction with constant frequency operation features smaller inductor current ripple resulting in low RMS currents on inductor and switch thus leading to low electromagnetic interference. The objective of this work is to develop an active PFC control circuit using CCM boost converter implementing variable duty cycle control. The proposed scheme eliminates inductor current sensing requirements yet offering good performance and satisfactory results for maintaining the power quality. Simulation results have been presented which covers load changes also.

Keywords: CCM Boost converter, Power factor Correction, Total harmonic distortion, Variable Duty Cycle.

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Authors: Yi-Cheng Huang, Yan-Chen Shin

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This paper proposes method of diagnosing ball screw preload loss through the Hilbert-Huang Transform （HHT） and Multiscale entropy （MSE） process. The proposed method can diagnose ball screw preload loss through vibration signals when the machine tool is in operation. Maximum dynamic preload of 2 %, 4 %, and 6 % ball screws were predesigned, manufactured, and tested experimentally. Signal patterns are discussed and revealed using Empirical Mode Decomposition（EMD）with the Hilbert Spectrum. Different preload features are extracted and discriminated using HHT. The irregularity development of a ball screw with preload loss is determined and abstracted using MSE based on complexity perception. Experiment results show that the proposed method can predict the status of ball screw preload loss. Smart sensing for the health of the ball screw is also possible based on a comparative evaluation of MSE by the signal processing and pattern matching of EMD/HHT. This diagnosis method realizes the purposes of prognostic effectiveness on knowing the preload loss and utilizing convenience.

Keywords: Empirical Mode Decomposition, Hilbert-Huang Transform, Multi-scale Entropy, Preload Loss, Single-nut Ball Screw

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Authors: Yung-Ting Chang, Chung-You Tsai, Yu-Chuan Li

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Nosocomial (i.e., hospital-acquired) infections (NI) is a major cause of morbidity and mortality in hospitals. NI rate is higher in intensive care units (ICU) than in the general ward due to patients with severe symptoms, poor immunity, and accepted many invasive therapies. Contact behaviors between health caregivers and patients is one of the infect factors. It is difficult to obtain complete contact records by traditional method of retrospective analysis of medical records. This paper establishes a contact history inferential model (CHIM) intended to extend the use of Proximity Sensing of rapid frequency identification (RFID) technology to transferring all proximity events between health caregivers and patients into clinical events (close-in events, contact events and invasive events).The results of the study indicated that the CHIM can infer proximity care activities into close-in events and contact events. The infection control team could redesign and build optimal workflow in the ICU according to the patient-specific contact history which provided by our automatic tracing system.

Keywords: Active Radio Frequency Identification, Intensive Care Unit, Nosocomial Infections

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Authors: Ki-Sung Park, Dae-Hee Lee, Dae-Ho Won, Yeon-Mo Yang

Abstract:

Solar power plants(SPPs) have shown a lot of good outcomes in providing a various functions depending on industrial expectations by deploying ad-hoc networking with helps of light loaded and battery powered sensor nodes. In particular, it is strongly requested to develop an algorithm to deriver the sensing data from the end node of solar power plants to the sink node on time. In this paper, based on the above observation we have proposed an IEEE802.15.4 based self routing scheme for solar power plants. The proposed beacon based priority routing Algorithm (BPRA) scheme utilizes beacon periods in sending message with embedding the high priority data and thus provides high quality of service(QoS) in the given criteria. The performance measures are the packet Throughput, delivery, latency, total energy consumption. Simulation results under TinyOS Simulator(TOSSIM) have shown the proposed scheme outcome the conventional Ad hoc On-Demand Distance Vector(AODV) Routing in solar power plants.

Keywords: Solar Power Plants(SPPs), Self routing, Quality of Service(QoS), WPANs, WSNs, TinyOS, TOSSIM, IEEE802.15.4

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Authors: K. Indra Gandhi

Abstract:

Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: Model-driven development, wireless sensor networks, data acquisition, separation of concern, layered design.

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Authors: I Made Darmayuda, Zhou Jun, Krishna Mainali, Simon Ng Sheung Yan, Saisundar S, Eran Ofek

Abstract:

Personnel protection devices are cardinal in safety hazard applications. They are widely used in home, office and in industry environments to reduce the risk of lethal shock to human being and equipment safety. This paper briefly reviews various personnel protection devices also describes the basic working principle of conventional ground fault circuit interrupter (GFCI) or ground fault isolator (GFI), its disadvantages and ways to overcome the disadvantages with solid-state relay (SSR) based GFI with ultrafast response up on fault implemented in printed circuit board. This solid state GFI comprises discrete MOSFET based alternating current (AC) switches, linear optical amplifier, photovoltaic isolator and sense resistor. In conventional GFI, current transformer is employed as a sensing element to detect the difference in current flow between live and neutral conductor. If there is no fault in equipment powered through GFI, due to insulation failure of internal wires and windings of motors, both live and neutral currents will be equal in magnitude and opposite in phase.

Keywords: current transformer, electrocution, GFCI, GFI

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Authors: Mohammad Reza Zamani Kouhpanji

Abstract:

This paper presents a MEMS/NEMS device for fatigue and fracture characterization of nanomaterials. This device can apply static loads, cyclic loads, and their combinations in nanomechanical experiments. It is based on the electromagnetic force induced between paired parallel wires carrying electrical currents. Using this concept, the actuator and sensor parts of the device were designed and analyzed while considering the practical limitations. Since the PWCC device only uses two wires for actuation part and sensing part, its fabrication process is extremely easier than the available MEMS/NEMS devices. The total gain and phase shift of the MEMS/NEMS device were calculated and investigated. Furthermore, the maximum gain and sensitivity of the MEMS/NEMS device were studied to demonstrate the capability and usability of the device for wide range of nanomaterials samples. This device can be readily integrated into SEM/TEM instruments to provide real time study of the mechanical behaviors of nanomaterials as well as their fatigue and fracture properties, softening or hardening behaviors, and initiation and propagation of nanocracks.

Keywords: Sensors and actuators, MEMS/NEMS devices, fatigue and fracture nanomechanical testing device, static and cyclic nanomechanical testing device.

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