Abstract: Harmonic functions are solutions to Laplace’s equation
that are known to have an advantage as a global approach in providing
the potential values for autonomous vehicle navigation. However,
the computation for obtaining harmonic functions is often too slow
particularly when it involves very large environment. This paper
presents a two-stage iterative method namely Modified Arithmetic
Mean (MAM) method for solving 2D Laplace’s equation. Once
the harmonic functions are obtained, the standard Gradient Descent
Search (GDS) is performed for path finding of an autonomous vehicle
from arbitrary initial position to the specified goal position. Details
of the MAM method are discussed. Several simulations of vehicle
navigation with path planning in a static known indoor environment
were conducted to verify the efficiency of the MAM method. The
generated paths obtained from the simulations are presented. The
performance of the MAM method in computing harmonic functions
in 2D environment to solve path planning problem for an autonomous
vehicle navigation is also provided.
Abstract: The efforts to understand the heat transfer behavior of supercritical water in supercritical water cooled reactor (SCWR) are ongoing worldwide to fulfill the future energy demand. The higher thermal efficiency of these reactors compared to a conventional nuclear reactor is one of the driving forces for attracting the attention of nuclear scientists. In this work, a solution procedure has been described for solving supercritical fluid flow problems in complex geometries. The solution procedure is based on non-staggered grid. All governing equations are discretized by finite volume method (FVM) in curvilinear coordinate system. Convective terms are discretized by first-order upwind scheme and central difference approximation has been used to discretize the diffusive parts. k-ε turbulence model with standard wall function has been employed. SIMPLE solution procedure has been implemented for the curvilinear coordinate system. Based on this solution method, 3-D Computational Fluid Dynamics (CFD) code has been developed. In order to demonstrate the capability of this CFD code in supercritical fluid flows, heat transfer to supercritical water in circular tubes has been considered as a test problem. Results obtained by code have been compared with experimental results reported in literature.
Abstract: The advancements in the field of Artificial Intelligence (AI) and technology has led to an evolution of an intelligent era. Neural networks, having the computational power and learning ability similar to the brain is one of the key AI technologies. Neuromorphic computing system (NCS) consists of the synaptic device, neuronal circuit, and neuromorphic architecture. Memristor are a promising candidate for neuromorphic computing systems, but when it comes to neuromorphic computing, the conductance behavior of the synaptic memristor or neuronal memristor needs to be studied thoroughly in order to fathom the neuroscience or computer science. Furthermore, there is a need of more simulation work for utilizing the existing device properties and providing guidance to the development of future devices for different performance requirements. Hence, development of NCS needs more simulation work to make use of existing device properties. This work aims to provide an insight to build neuronal circuits using memristors to achieve a Memristor based NCS. Here we throw a light on the research conducted in the field of memristors for building analog and digital circuits in order to motivate the research in the field of NCS by building memristor based neural circuits for advanced AI applications. This literature is a step in the direction where we describe the various Key findings about memristors and its analog and digital circuits implemented over the years which can be further utilized in implementing the neuronal circuits in the NCS. This work aims to help the electronic circuit designers to understand how the research progressed in memristors and how these findings can be used in implementing the neuronal circuits meant for the recent progress in the NCS.
Abstract: This paper deals with the steady and unsteady flow behavior on the separation bubble occurring on the rear portion of the suction side of T106A blade. The first phase was to implement the steady condition capturing the separation bubble. To accurately predict the separated region, the effects of three different turbulence models and computational grids were separately investigated. The results of Large Eddy Simulation (LES) model on the finest grid structure are acceptably in a good agreement with its relevant experimental results. The second phase is mainly to address the effects of wake entrance on bubble disappearance in unsteady situation. In the current simulations, from what was suggested in an experiment, simulating the flow unsteadiness, with concentrations on small scale disturbances instead of simulating a complete oncoming wake, is the key issue. Subsequently, the results from the current strategy to apply the effects of the wake and two other experimental work were compared to be in a good agreement. Between the two experiments, one of them deals with wake passing unsteady flow, and the other one implements experimentally the same approach as the current Computational Fluid Dynamics (CFD) simulation.
Abstract: Telemedicine services use a large amount of data, most of which are diagnostic images in Digital Imaging and Communications in Medicine (DICOM) and Health Level Seven (HL7) formats. Metadata is generated from each related image to support their identification. This study presents the use of decision trees for the optimization of information search processes for diagnostic images, hosted on the cloud server. To analyze the performance in the server, the following quality of service (QoS) metrics are evaluated: delay, bandwidth, jitter, latency and throughput in five test scenarios for a total of 26 experiments during the loading and downloading of DICOM images, hosted by the telemedicine group server of the Universidad Militar Nueva Granada, Bogotá, Colombia. By applying decision trees as a data mining technique and comparing it with the sequential search, it was possible to evaluate the search times of diagnostic images in the server. The results show that by using the metadata in decision trees, the search times are substantially improved, the computational resources are optimized and the request management of the telemedicine image service is improved. Based on the experiments carried out, search efficiency increased by 45% in relation to the sequential search, given that, when downloading a diagnostic image, false positives are avoided in management and acquisition processes of said information. It is concluded that, for the diagnostic images services in telemedicine, the technique of decision trees guarantees the accessibility and robustness in the acquisition and manipulation of medical images, in improvement of the diagnoses and medical procedures in patients.
Abstract: Nowadays flight simulators offer tremendous possibilities for safe and cost-effective pilot training, by utilization of powerful, computational tools. Due to technology outpacing methodology, vast majority of training related work is done by human instructors. It makes assessment not efficient, and vulnerable to instructors’ subjectivity. The research presents an Objective Assessment Tool (gOAT) developed at the Warsaw University of Technology, and tested on SW-4 helicopter flight simulator. The tool uses database of the predefined manoeuvres, defined and integrated to the virtual environment. These were implemented, basing on Aeronautical Design Standard Performance Specification Handling Qualities Requirements for Military Rotorcraft (ADS-33), with predefined Mission-Task-Elements (MTEs). The core element of the gOAT enhanced algorithm that provides instructor a new set of information. In details, a set of objective flight parameters fused with report about psychophysical state of the pilot. While the pilot performs the task, the gOAT system automatically calculates performance using the embedded algorithms, data registered by the simulator software (position, orientation, velocity, etc.), as well as measurements of physiological changes of pilot’s psychophysiological state (temperature, sweating, heart rate). Complete set of measurements is presented on-line to instructor’s station and shown in dedicated graphical interface. The presented tool is based on open source solutions, and flexible for editing. Additional manoeuvres can be easily added using guide developed by authors, and MTEs can be changed by instructor even during an exercise. Algorithm and measurements used allow not only to implement basic stress level measurements, but also to reduce instructor’s workload significantly. Tool developed can be used for training purpose, as well as periodical checks of the aircrew. Flexibility and ease of modifications allow the further development to be wide ranged, and the tool to be customized. Depending on simulation purpose, gOAT can be adjusted to support simulator of aircraft, helicopter, or unmanned aerial vehicle (UAV).
Abstract: The objective of the present study is to numerically investigate the effect of CO2 replacement of N2 in air stream on the flame characteristics of the CH4 turbulent diffusion flame. The Open source Field Operation and Manipulation (OpenFOAM) has been used as the computational tool. In this regard, laminar flamelet and modified k-ε models have been utilized as combustion and turbulence models, respectively. Results reveal that the presence of CO2 in air stream changes the flame shape and maximum flame temperature. Also, CO2 dilution causes an increment in CO mass fraction.
Abstract: Internet of things is a new concept that its emergence has caused ubiquity of sensors in human life, so that at any time, all data are collected, processed and transmitted by these sensors. In order to establish a secure connection, the first challenge is authentication between sensors. However, this challenge also requires some features so that the authentication is done properly. Anonymity, untraceability, and being lightweight are among the issues that need to be considered. In this paper, we have evaluated the authentication protocols and have analyzed the security vulnerabilities found in them. Then an improved light weight authentication protocol for sensor-to-sensor communications is presented which uses the hash function and logical operators. The analysis of protocol shows that security requirements have been met and the protocol is resistant against various attacks. In the end, by decreasing the number of computational cost functions, it is argued that the protocol is lighter than before.
Abstract: The propagation of microwave is affected by rain and dust particles causing signal attenuation and de-polarization. Computations of these effects require knowledge of the propagation characteristics of microwave and millimeter wave energy in the climate conditions of the studied region. This paper presents effect of wind and humidity on wireless communication such as microwave links in the North West region of Libya (Al-Khoms). The experimental procedure is done on three selected antennae towers (Nagaza station, Al-Khoms center station, Al-Khoms gateway station) for determining the attenuation loss per unit length and cross-polarization discrimination (XPD) change. Dust particles are collected along the region of the study, to measure the particle size distribution (PSD), calculate the concentration, and chemically analyze the contents, then the dielectric constant can be calculated. The results show that humidity and dust, antenna height and the visibility affect both attenuation and phase shift; in which, a few considerations must be taken into account in the communication power budget.
Abstract: In this paper, effectiveness of a machine design process is evaluated on the basis of the specific output calculus. Concretely, a screw-worm gear mechanical transmission is designed by using the classical and the 3D-CAD methods. Strength analysis and drawing of the designed parts is substantially aided by employing the SolidWorks software. Quality of the design process is assessed by manufacturing (printing) the parts, and by computing the efficiency, specific load, as well as the specific output (work) of the mechanical transmission. Influence of the stroke, travelling velocity and load on the mechanical output, is emphasized. Optimal design of the mechanical transmission becomes possible by the appropriate usage of the acquired results.
Abstract: This paper presents a general approach to implement
efficient queries’ interpreters in a functional programming language.
Indeed, most of the standard tools actually available use an imperative
and/or object-oriented language for the implementation (e.g. Java for
Jena-Fuseki) but other paradigms are possible with, maybe, better
performances. To proceed, the paper first explains how to model
data structures and queries in a functional point of view. Then, it
proposes a general methodology to get performances (i.e. number of
computation steps to answer a query) then it explains how to integrate
some optimization techniques (short-cut fusion and, more important,
data transformations). It then compares the functional server proposed
to a standard tool (Fuseki) demonstrating that the first one can be
twice to ten times faster to answer queries.
Abstract: Urban flooding resulting from a sudden release of
water due to dam-break or excessive rainfall is a serious threatening
environment hazard, which causes loss of human life and large
economic losses. Anticipating floods before they occur could
minimize human and economic losses through the implementation
of appropriate protection, provision, and rescue plans. This work
reports on the numerical modelling of flash flood propagation
in urban areas after an excessive rainfall event or dam-break.
A two-dimensional (2D) depth-averaged shallow water model is
used with a refined unstructured grid of triangles for representing
the urban area topography. The 2D shallow water equations are
solved using a second-order well-balanced discontinuous Galerkin
scheme. Theoretical test case and three flood events are described
to demonstrate the potential benefits of the scheme: (i) wetting and
drying in a parabolic basin (ii) flash flood over a physical model of
the urbanized Toce River valley in Italy; (iii) wave propagation on
the Reyran river valley in consequence of the Malpasset dam-break
in 1959 (France); and (iv) dam-break flood in October 1982 at the
town of Sumacarcel (Spain). The capability of the scheme is also
verified against alternative models. Computational results compare
well with recorded data and show that the scheme is at least as
efficient as comparable second-order finite volume schemes, with
notable efficiency speedup due to parallelization.
Abstract: Sentiment analysis is a recent field of study that computationally assesses the emotional nature of a body of text. To assess its test-validity, sentiment analysis was carried out on the emotional corpus of text from a personal 15-day mood diary. Self-reported mood scores varied more or less accurately with daily mood evaluation score given by the software. On further assessment, it was found that while sentiment analysis was good at assessing ‘global’ mood, it was not able to ‘locally’ identify and differentially score synonyms of various emotional words. It is further critiqued for treating the intensity of an emotion as universal across cultures. Finally, the software is shown not to account for emotional complexity in sentences by treating emotions as strictly positive or negative. Hence, it is posited that a better output could be two (positive and negative) affect scores for the same body of text.
Abstract: Recent researches has focused on nucleic acids as a
substrate for designing biomolecular circuits for in situ monitoring
and control. A common approach is to express them by a set of
idealised abstract chemical reaction networks (ACRNs). Here, we
present new results on how abstract chemical reactions, viz., catalysis,
annihilation and degradation, can be used to implement circuit
that accurately computes logarithm function using the method of
Arithmetic-Geometric Mean (AGM), which has not been previously
used in conjunction with ACRNs.
Abstract: Link adaptation is an important strategy for achieving robust wireless multimedia communications based on quality of service (QoS) demand. Scheme switching in multiple-input multiple-output (MIMO) systems is an aspect of link adaptation, and it involves selecting among different MIMO transmission schemes or modes so as to adapt to the varying radio channel conditions for the purpose of achieving QoS delivery. However, finding the most appropriate switching method in MIMO links is still a challenge as existing methods are either computationally complex or not always accurate. This paper presents an intelligent switching method for the MIMO system consisting of two schemes - transmit diversity (TD) and spatial multiplexing (SM) - using fuzzy logic technique. In this method, two channel quality indicators (CQI) namely average received signal-to-noise ratio (RSNR) and received signal strength indicator (RSSI) are measured and are passed as inputs to the fuzzy logic system which then gives a decision – an inference. The switching decision of the fuzzy logic system is fed back to the transmitter to switch between the TD and SM schemes. Simulation results show that the proposed fuzzy logic – based switching technique outperforms conventional static switching technique in terms of bit error rate and spectral efficiency.
Abstract: In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.
Abstract: The quantum communication technology is an evolving
design which connects multiple quantum enabled devices to internet
for secret communication or sensitive information exchange. In
future, the number of these compact quantum enabled devices
will increase immensely making them an integral part of present
communication systems. Therefore, safety and security of such
devices is also a major concern for us. To ensure the customer
sensitive information will not be eavesdropped or deciphered, we
need a strong authentications and encryption mechanism. In this
paper, we propose a mutual authentication scheme between these
smart quantum devices and server based on the secure exchange of
information through quantum channel which gives better solutions
for symmetric key exchange issues. An important part of this
work is to propose a secure mutual authentication protocol over
the quantum channel. We show that our approach offers robust
authentication protocol and further our solution is lightweight,
scalable, cost-effective with optimized computational processing
overheads.
Abstract: This paper presents a prediction performance of
feedforward Multilayer Perceptron (MLP) and Echo State Networks
(ESN) trained with extended Kalman filter. Feedforward neural
networks and ESN are powerful neural networks which can track and
predict nonlinear signals. However, their tracking performance
depends on the specific signals or data sets, having the risk of
instability accompanied by large error. In this study we explore this
process by applying different network size and leaking rate for
prediction of nonlinear or chaotic signals in MLP neural networks.
Major problems of ESN training such as the problem of initialization
of the network and improvement in the prediction performance are
tackled. The influence of coefficient of activation function in the
hidden layer and other key parameters are investigated by simulation
results. Extended Kalman filter is employed in order to improve the
sequential and regulation learning rate of the feedforward neural
networks. This training approach has vital features in the training of
the network when signals have chaotic or non-stationary sequential
pattern. Minimization of the variance in each step of the computation
and hence smoothing of tracking were obtained by examining the
results, indicating satisfactory tracking characteristics for certain
conditions. In addition, simulation results confirmed satisfactory
performance of both of the two neural networks with modified
parameterization in tracking of the nonlinear signals.
Abstract: This paper presents state estimation with Phasor Measurement Unit (PMU) allocation to obtain complete observability of network. A matrix is designed with modeling of zero injection constraints to minimize PMU allocations. State estimation algorithm is developed with optimal allocation of PMUs to find accurate states of network. The incorporation of PMU into traditional state estimation process improves accuracy and computational performance for large power systems. The nonlinearity integrated with zero injection (ZI) constraints is remodeled to linear frame to optimize number of PMUs. The problem of optimal PMU allocation is regarded with modeling of ZI constraints, PMU loss or line outage, cost factor and redundant measurements. The proposed state estimation with optimal PMU allocation has been compared with traditional state estimation process to show its importance. MATLAB programming on IEEE 14, 30, 57, and 118 bus networks is implemented out by Binary Integer Programming (BIP) method and compared with other methods to show its effectiveness.
Abstract: The representative volume element (RVE) plays a central role in the mechanics of random heterogeneous materials with a view to predicting their effective properties. In this paper, a computational homogenization methodology, developed to determine effective linear elastic properties of composite materials, is extended to predict the effective nonlinear elastoplastic response of long fiber reinforced composite. Finite element simulations of volumes of different sizes and fiber volume fractures are performed for calculation of the overall response RVE. The dependencies of the overall stress-strain curves on the number of fibers inside the RVE are studied in the 2D cases. Volume averaged stress-strain responses are generated from RVEs and compared with the finite element calculations available in the literature at moderate and high fiber volume fractions. For these materials, the existence of an RVE is demonstrated for the sizes of RVE corresponding to 10–100 times the diameter of the fibers. In addition, the response of small size RVE is found anisotropic, whereas the average of all large ones leads to recover the isotropic material properties.