Search results for: precise time domain expanding algorithm

Authors: Ahmed Ali Asadi, Julio R. Martinez-Alvarado, Claudia V. Camacho-Guevara, J. Jesus Cabrales-Ruvalcaba, Julieta Y. Islas-Limon, Bertha M. Viñas-Velazquez

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The transformation of education in Mexico incorporates human sexuality subjects in its study plans for elementary education level, leaving aside the training of teachers to educate on such topics. The objective of this study was to evaluate the curricular content domain related to human sexuality subjects of public elementary school teachers in Mexico. For this, a transversal descriptive-prospective study with a quantitative focus has been conducted. The population for this study consisted of 109 fifth and sixth-grade teachers from a school zone of the State Education System. It was found in the results that fifth-grade teachers got a low achievement level, sixth-grade teachers got a medium achievement level, while teachers who give classes on both grades obtained a high achievement level on domain of curricular subjects related to sexuality. Likewise, a relation of different variables with the participant’s achievement level is exposed.

Keywords: curricular content, evaluation, sexual education, teacher

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Authors: Michael R. Phangtriastu, Herriyandi Herriyandi, Diaz D. Santika

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This paper presents a comparison of the implementation of metaheuristic algorithms to train the antecedent parameters and consequence parameters in the adaptive network-based fuzzy inference system (ANFIS). The algorithms compared are genetic algorithm (GA), particle swarm optimization (PSO), and artificial bee colony (ABC). The objective of this paper is to benchmark well-known metaheuristic algorithms. The algorithms are applied to several data set with different nature. The combinations of the algorithms' parameters are tested. In all algorithms, a different number of populations are tested. In PSO, combinations of velocity are tested. In ABC, a different number of limit abandonment are tested. Experiments find out that ABC is more reliable than other algorithms, ABC manages to get better mean square error (MSE) than other algorithms in all data set.

Keywords: ANFIS, artificial bee colony, genetic algorithm, metaheuristic algorithm, particle swarm optimization

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Authors: David Kriebel, Jan Edgar Mehner

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The paper introduces a method to efficiently simulate nonlinear changing electrostatic fields occurring in micro-electromechanical systems (MEMS). Large deflections of the capacitor electrodes usually introduce nonlinear electromechanical forces on the mechanical system. Traditional finite element methods require a time-consuming remeshing process to capture exact results for this physical domain interaction. In order to accelerate the simulation process and eliminate the remeshing process, a formulation of a strongly coupled electromechanical transducer element will be introduced, which uses a combination of finite-element with an advanced mesh morphing technique using radial basis functions (RBF). The RBF allows large geometrical changes of the electric field domain while retaining the high element quality of the deformed mesh. Coupling effects between mechanical and electrical domains are directly included within the element formulation. Fringing field effects are described accurately by using traditional arbitrary shape functions.

Keywords: electromechanical, electric field, transducer, simulation, modeling, finite-element, mesh morphing, radial basis function

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Authors: Reham Khalaf-Nazzal, Imad Dweikat, Paula Gimenez, Iker Oyenarte, Alfonso Martinez-Cruz, Domonik Muller

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Metal cation transport mediator (CNNM) gene family comprises 4 isoforms that are expressed in various human tissues. Structurally, CNNMs are complex proteins that contain an extracellular N-terminal domain preceding a DUF21 transmembrane domain, a ‘Bateman module’ and a C-terminal cNMP-binding domain. Mutations in CNNM2 cause familial dominant hypomagnesaemia. Growing evidence highlights the role of CNNM2 in neurodevelopment. Mutations in CNNM2 have been implicated in epilepsy, intellectual disability, schizophrenia, and others. In the present study, we aim to elucidate the function of CNNM2 in the developing brain. Thus, we present the genetic origin of symptoms in two family cohorts. In the first family, three siblings of a consanguineous Palestinian family in which parents are first cousins, and consanguinity ran over several generations, presented a varying degree of intellectual disability, cone-rod dystrophy, and autism spectrum disorder. Exome sequencing and segregation analysis revealed the presence of homozygous pathogenic mutation in the CNNM2 gene, the parents were heterozygous for that gene mutation. Magnesium blood levels were normal in the three children and their parents in several measurements. They had no symptoms of hypomagnesemia. The CNNM2 mutation in this family was found to locate in the CBS1 domain of the CNNM2 protein. The crystal structure of the mutated CNNM2 protein was not significantly different from the wild-type protein, and the binding of AMP or MgATP was not dramatically affected. This suggests that the CBS1 domain could be involved in pure neurodevelopmental functions independent of its magnesium-handling role, and this mutation could have affected a protein partner binding or other functions in this protein. In the second family, another autosomal dominant CNNM2 mutation was found to run in a large family with multiple individuals over three generations. All affected family members had hypomagnesemia and hypermagnesuria. Oral supplementation of magnesium did not increase the levels of magnesium in serum significantly. Some affected members of this family have defects in fine motor skills such as dyslexia and dyslalia. The detected mutation is located in the N-terminal part, which contains a signal peptide thought to be involved in the sorting and routing of the protein. In this project, we describe heterogenous clinical phenotypes related to CNNM2 mutations and protein functions. In the first family, and up to the authors’ knowledge, we report for the first time the involvement of CNNM2 in retinal photoreceptor development and function. In addition, we report the presence of a neurophenotype independent of magnesium status related to the CNNM2 protein mutation. Taking into account the different modes of inheritance and the different positions of the mutations within CNNM2 and its different structural and functional domains, it is likely that CNNM2 might be involved in a wide spectrum of neuropsychiatric comorbidities with considerable varying phenotypes.

Keywords: magnesium transport, autosomal recessive, autism, neurodevelopment, CBS domain

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Authors: Ali Allahverdi, Harun Aydilek, Asiye Aydilek

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Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution.

Keywords: single machine scheduling, number of tardy jobs, heuristi, lower and upper bounds

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Authors: Hamdy M. Youssef, Eman A. Al-Lehaibi

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This paper presents an iteration method for the numerical solutions of a one-dimensional problem of generalized thermoelasticity with one relaxation time under given initial and boundary conditions. The thermoelastic material with variable properties as a power functional graded has been considered. Adomian’s decomposition techniques have been applied to the governing equations. The numerical results have been calculated by using the iterations method with a certain algorithm. The numerical results have been represented in figures, and the figures affirm that Adomian’s decomposition method is a successful method for modeling thermoelastic problems. Moreover, the empirical parameter of the functional graded, and the lattice design parameter have significant effects on the temperature increment, the strain, the stress, the displacement.

Keywords: Adomian, decomposition method, generalized thermoelasticity, algorithm

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Authors: N. Reichbach, A. Kuperman

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The paper describes a design of a monitoring system for super capacitor packs in propulsion systems, allowing determining the instantaneous energy capacity under power loading. The system contains real-time recursive-least-squares identification mechanism, estimating the values of pack capacitance and equivalent series resistance. These values are required for accurate calculation of the state-of-energy.

Keywords: real-time monitoring, RLS identification algorithm, state-of-energy, super capacitor

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Authors: Tudor Barbu

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An automatic moment-based texture segmentation approach is proposed in this paper. First, we describe the related work in this computer vision domain. Our texture feature extraction, the first part of the texture recognition process, produces a set of moment-based feature vectors. For each image pixel, a texture feature vector is computed as a sequence of area moments. Second, an automatic pixel classification approach is proposed. The feature vectors are clustered using some unsupervised classification algorithm, the optimal number of clusters being determined using a measure based on validation indexes. From the resulted pixel classes one determines easily the desired texture regions of the image.

Keywords: image segmentation, moment-based, texture analysis, automatic classification, validation indexes

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Authors: Sirus Mohammadi, Rohala Moghimi

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The main advantages of microgrids are high energy efficiency through the application of Combined Heat and Power (CHP), high quality and reliability of the delivered electric energy and environmental and economic advantages. This study presents an energy management system (EMS) to optimize the operation of the microgrid (MG). In this paper an Adaptive Modified Firefly Algorithm (AMFA) is presented for optimal operation of a typical MG with renewable energy sources (RESs) accompanied by a back-up Micro-Turbine/Fuel Cell/Battery hybrid power source to level the power mismatch or to store the energy surplus when it’s needed. The problem is formulated as a nonlinear constraint problem to minimize the total operating cost. The management of Energy storage system (ESS), economic load dispatch and operation optimization of distributed generation (DG) are simplified into a single-object optimization problem in the EMS. The proposed algorithm is tested on a typical grid-connected MG including WT/PV/Micro Turbine/Fuel Cell and Energy Storage Devices (ESDs) then its superior performance is compared with those from other evolutionary algorithms such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Fuzzy Self Adaptive PSO (FSAPSO), Chaotic Particle PSO (CPSO), Adaptive Modified PSO (AMPSO), and Firefly Algorithm (FA).

Keywords: microgrid, operation management, optimization, firefly algorithm (AMFA)

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Authors: R. P. Hewawasam, A. F. Dulhunty

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The ryanodine receptor (RyR) is an intracellular ion channel that releases Ca2+ from the sarcoplasmic reticulum and is essential for the excitation-contraction coupling and contraction in striated muscle. Human muscle specific glutathione transferase M2-2 (GSTM2-2) is a highly specific inhibitor of cardiac ryanodine receptor (RyR2) activity. Single channel-lipid bilayer studies and Ca2+ release assays performed using the C-terminal half of the GSTM2-2 and its mutants F157A and Y160A confirmed the ability of the C terminal domain of GSTM2-2 to specifically inhibit the cardiac ryanodine receptor activity. Objective of the present study is to determine the effect of C terminal domain of GSTM2-2 (GSTM2-2C) and the mutants, F157A and Y160A on the Ca2+ transients of neonatal ventricular cardiomyocytes. Primary cardiomyocytes were cultured from neonatal rats. They were treated with GSTM2-2C and the two mutants F157A and Y160A at 15µM and incubated for 2 hours. Then the cells were led with Fluo-4AM, fluorescent Ca2+ indicator, and the field stimulated (1 Hz, 3V and 2ms) cells were excited using the 488 nm argon laser. Contractility of the cells were measured and the Ca2+ transients in the stained cells were imaged using Leica SP5 confocal microscope. Peak amplitude of the Ca2+ transient, rise time and decay time from the peak were measured for each transient. In contrast to GSTM2C which significantly reduced the % shortening (42.8%) in the field stimulated cells, F157A and Y160A failed to reduce the % shortening.Analysis revealed that the average amplitude of the Ca2+ transient was significantly reduced (P<0.001) in cells treated with the wild type GSTM2-2C compared to that of untreated cells. Cells treated with the mutants F157A and Y160A didn’t change the Ca2+ transient significantly compared to the control. A significant increase in the rise time (P< 0.001) and a significant reduction in the decay time (P< 0.001) were observed in cardiomyocytes treated with GSTM2-2C compared to the control but not with F157A and Y160A. These results are consistent with the observation that GSTM2-2C reduced the Ca2+ release from the cardiac SR significantly whereas the mutants, F157A and Y160A didn’t show any effect compared to the control. GSTM2-2C has an isoform-specific effect on the cardiac ryanodine receptor activity and also it inhibits RyR2 channel activity only during diastole. Selective inhibition of RyR2 by GSTM2-2C has significant clinical potential in the treatment of cardiac arrhythmias and heart failure. Since GSTM2-2C-terminal construct has no GST enzyme activity, its introduction to the cardiomyocyte would not exert any unwanted side effects that may alter its enzymatic action. The present study further confirms that GSTM2-2C is capable of decreasing the Ca2+ release from the cardiac SR during diastole. These results raise the future possibility of using GSTM2-2C as a template for therapeutics that can depress RyR2 function when the channel is hyperactive in cardiac arrhythmias and heart failure.

Keywords: arrhythmia, cardiac muscle, cardiac ryanodine receptor, GSTM2-2

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Authors: Fatéma Zahra Benchara, Mohamed Youssfi, Omar Bouattane, Hassan Ouajji, Mohamed Ouadi Bensalah

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The aim of this paper is to present a distributed implementation of the Type-2 Fuzzy algorithm in a parallel and distributed computing environment based on mobile agents. The proposed algorithm is assigned to be implemented on a SPMD (Single Program Multiple Data) architecture which is based on cooperative mobile agents as AVPE (Agent Virtual Processing Element) model in order to improve the processing resources needed for performing the big data image segmentation. In this work we focused on the application of this algorithm in order to process the big data MRI (Magnetic Resonance Images) image of size (n x m). It is encapsulated on the Mobile agent team leader in order to be split into (m x n) pixels one per AVPE. Each AVPE perform and exchange the segmentation results and maintain asynchronous communication with their team leader until the convergence of this algorithm. Some interesting experimental results are obtained in terms of accuracy and efficiency analysis of the proposed implementation, thanks to the mobile agents several interesting skills introduced in this distributed computational model.

Keywords: distributed type-2 fuzzy algorithm, image processing, mobile agents, parallel and distributed computing

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Authors: Rodrigo Montufar-Chaveznava, Fernando Brambila-Paz, Ivette Caldelas

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In this paper, we present the advances corresponding to the denoising processing of magnetotelluric signals using several filters. In particular, we use the most common spatial domain filters such as median and mean, but we are also using the Fourier and wavelet transform for frequency domain filtering. We employ three datasets obtained at the different sampling rate (128, 4096 and 8192 bps) and evaluate the mean square error, signal-to-noise relation, and peak signal-to-noise relation to compare the kernels and determine the most suitable for each case. The magnetotelluric signals correspond to earth exploration when water is searched. The object is to find a denoising strategy different to the one included in the commercial equipment that is employed in this task.

Keywords: denoising, filtering, magnetotelluric signals, wavelet transform

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Authors: P. Subbuthai, S. Muruganand

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Diabetic Retinopathy is one of the complicated diseases and it is caused by the changes in the blood vessels of the retina. Extraction of retina image through Fundus camera sometimes produced poor contrast and noises. Because of this noise, detection of blood vessels in the retina is very complicated. So preprocessing is needed, in this paper, a novel algorithm is implemented to remove the noisy pixel in the retina image. The proposed algorithm is Extended Median Filter and it is applied to the green channel of the retina because green channel vessels are brighter than the background. Proposed extended median filter is compared with the existing standard median filter by performance metrics such as PSNR, MSE and RMSE. Experimental results show that the proposed Extended Median Filter algorithm gives a better result than the existing standard median filter in terms of noise suppression and detail preservation.

Keywords: fundus retina image, diabetic retinopathy, median filter, microaneurysms, exudates

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Authors: Doyoung Kim, Hyo Seon Park

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Studies of System Identification(SI) based on Structural Health Monitoring(SHM) have actively conducted for structural safety. Recently SI techniques have been rapidly developed with output-only SI paradigm for estimating modal parameters. The features of these output-only SI methods consist of Frequency Domain Decomposition(FDD) and Stochastic Subspace Identification(SSI) are using the algorithms based on orthogonal decomposition such as singular value decomposition(SVD). But the SVD leads to high level of computational complexity to estimate modal parameters. This paper proposes the technique to estimate mode shape with lower computational cost. This technique shows pseudo modal Operating Deflections Shape(ODS) through bandpass filter and suggests time history Modal Assurance Criterion(MAC). Finally, mode shape could be estimated from pseudo modal ODS and time history MAC. Analytical simulations of vibration measurement were performed and the results with mode shape and computation time between representative SI method and proposed method were compared.

Keywords: modal assurance criterion, mode shape, operating deflection shape, system identification

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Authors: Zhi Liu, Hui Jiang, Jin Li, Kunhao Chen, Langfang Zhang

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Fast acquisition of the seismic information and accurate assessment of the earthquake disaster is the key problem for emergency rescue after a destructive earthquake. In order to meet the requirements of the earthquake emergency response and rescue for the cities and counties, a quasi real-time comprehensive evaluation system for earthquake disaster is developed. Based on monitoring data of Micro-Electro-Mechanical Systems (MEMS) strong motion network, structure database of a county area and the real-time disaster information by the mobile terminal after an earthquake, fragility analysis method and dynamic correction algorithm are synthetically obtained in the developed system. Real-time evaluation of the seismic disaster in the county region is finally realized to provide scientific basis for seismic emergency command, rescue and assistant decision.

Keywords: quasi real-time, earthquake disaster data collection, MEMS accelerometer, dynamic correction, comprehensive evaluation

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Authors: Rujia Chen, Ajit Narayanan

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Convolutional neural networks (CNN), as typically applied in deep learning, use layer-wise backpropagation (BP) to construct filters and kernels for feature extraction. Such filters are 2D or 3D groups of weights for constructing feature maps at subsequent layers of the CNN and are shared across the entire input. BP as a gradient descent algorithm has well-known problems of getting stuck at local optima. The use of genetic algorithms (GAs) for evolving weights between layers of standard artificial neural networks (ANNs) is a well-established area of neuroevolution. In particular, the use of crossover techniques when optimizing weights can help to overcome problems of local optima. However, the application of GAs for evolving the weights of filters and kernels in CNNs is not yet an established area of neuroevolution. In this paper, a GA-based filter development algorithm is proposed. The results of the proof-of-concept experiments described in this paper show the proposed GA algorithm can find filter weights through evolutionary techniques rather than BP learning. For some simple classification tasks like geometric shape recognition, the proposed algorithm can achieve 100% accuracy. The results for MNIST classification, while not as good as possible through standard filter learning through BP, show that filter and kernel evolution warrants further investigation as a new subarea of neuroevolution for deep architectures.

Keywords: neuroevolution, convolutional neural network, genetic algorithm, filters, kernels

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Authors: Hernández Yasmín, Ochoa Alberto, Hurtado Diego

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The aim of this study is developing an intelligent tutoring system for electrical operators training with virtual reality systems at the laboratory center of partials discharges LAPEM. The electrical domain requires efficient and well trained personnel, due to the danger involved in the partials discharges field, qualified electricians are required. This paper presents an overview of the intelligent tutor adaptive learning design and user interface with VR. We propose the develop of constructing a model domain of a subset of partial discharges enables adaptive training through a trainee model which represents the affective and knowledge states of trainees. According to the success of the intelligent tutor system with VR, it is also hypothesized that the trainees will able to learn the electrical domain installations of partial discharges and gain knowledge more efficient and well trained than trainees using traditional methods of teaching without running any risk of being in danger, traditional methods makes training lengthily, costly and dangerously.

Keywords: intelligent tutoring system, artificial intelligence, virtual reality, partials discharges, adaptive learning

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Authors: Essam Al Daoud

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This study solves a phylogeny problem by using modified wild dog pack optimization. The least squares error is considered as a cost function that needs to be minimized. Therefore, in each iteration, new distance matrices based on the constructed trees are calculated and used to select the alpha dog. To test the suggested algorithm, ten homologous genes are selected and collected from National Center for Biotechnology Information (NCBI) databanks (i.e., 16S, 18S, 28S, Cox 1, ITS1, ITS2, ETS, ATPB, Hsp90, and STN). The data are divided into three categories: 50 taxa, 100 taxa and 500 taxa. The empirical results show that the proposed algorithm is more reliable and accurate than other implemented methods.

Keywords: least square, neighbor joining, phylogenetic tree, wild dog pack

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Authors: P. G. Kaviya, B. Muthupandian, R. Ganesan

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On-chip routers typically have buffers are used input or output ports for temporarily storing packets. The buffers are consuming some router area and power. The multiple queues in parallel as in VC router. While running a traffic trace, not all input ports have incoming packets needed to be transferred. Therefore large numbers of queues are empty and others are busy in the network. So the time consumption should be high for the high traffic. Therefore using a RoShaQ, minimize the buffer area and time The RoShaQ architecture was send the input packets are travel through the shared queues at low traffic. At high load traffic the input packets are bypasses the shared queues. So the power and area consumption was reduced. A parallel cross bar architecture is proposed in this project in order to reduce the power consumption. Also a new adaptive weighted routing algorithm for 8-port router architecture is proposed in order to decrease the delay of the network on chip router. The proposed system is simulated using Modelsim and synthesized using Xilinx Project Navigator.

Keywords: buffer, RoShaQ architecture, shared queue, VC router, weighted routing algorithm

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Authors: Yuan-Lin Chen

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This paper presents an approaching forward collision probability index (AFCPI) for alerting and assisting driver in keeping safety distance to avoid the forward collision accident in highway driving. The time to collision (TTC) and time headway (TH) are used to evaluate the TTC forward collision probability index (TFCPI) and the TH forward collision probability index (HFCPI), respectively. The Mamdani fuzzy inference algorithm is presented combining TFCPI and HFCPI to calculate the approaching collision probability index of the vehicle. The AFCPI is easier to understand for the driver who did not even have any professional knowledge in vehicle professional field. At the same time, the driver’s behavior is taken into account for suiting each driver. For the approaching index, the value 0 is indicating the 0% probability of forward collision, and the values 0.5 and 1 are indicating the 50% and 100% probabilities of forward collision, respectively. The AFCPI is useful and easy-to-understand for alerting driver to avoid the forward collision accidents when driving in highway.

Keywords: approaching index, forward collision probability, time to collision, time headway

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Authors: Nazish Iftikhar, Adil Jhangeer, Tayyaba Naz

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The universe is expanding at an accelerated rate. Symmetries are useful in understanding universe’s behavior. Emmy Noether reported the relation between symmetries and conservation laws. These symmetries are known as Noether symmetries which correspond to a conserved quantity. In differential equations, conservation laws play an important role. Noether symmetries are helpful in modified theories of gravity. Time independent plane symmetric spacetime was classified by Noether`s theorem. By using Noether`s theorem, set of linear partial differential equations was obtained having A(r), B(r) and F(r) as unknown radial functions. The Lagrangian corresponding to considered spacetime in the Noether equation was used to get Noether operators. Different possibilities of radial functions were considered. Firstly, all functions were same. All the functions were considered as non-zero constant, linear, reciprocal and exponential respectively. Secondly, two functions were proportional to each other keeping third function different. Second case has four subcases in which four different relationships between A(r), B(r) and F(r) were discussed. In all cases, we obtained nontrivial Noether operators including gauge term. Conserved quantities for each Noether operators were also presented.

Keywords: Noether gauge symmetries, radial function, Noether operator, conserved quantities

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Authors: Hai Quang Hong Dam, Hai Ho, Minh Hoang Le Ngo

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This paper investigates the problem of blind speech separation from the speech mixture of two speakers. A voice activity detector employing the Steered Response Power - Phase Transform (SRP-PHAT) is presented for detecting the activity information of speech sources and then the desired speech signals are extracted from the speech mixture by using an optimal beamformer. For evaluation, the algorithm effectiveness, a simulation using real speech recordings had been performed in a double-talk situation where two speakers are active all the time. Evaluations show that the proposed blind speech separation algorithm offers a good interference suppression level whilst maintaining a low distortion level of the desired signal.

Keywords: blind speech separation, voice activity detector, SRP-PHAT, optimal beamformer

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Authors: Soban Najam, S. M. Jahanzeb, Ahmed Sohail, Faraz Idris Khan

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With the recent increase in reliance on Gas as the primary source of energy across the world, there has been a lot of research conducted on gas distribution networks. As the complexity and size of these networks grow, so does the leakage of gas in the distribution network. One of the most crucial factors in the production and distribution of gas is UFG or Unaccounted for Gas. The presence of UFG signifies that there is a difference between the amount of gas distributed, and the amount of gas billed. Our approach is to use information that we acquire from several specified points in the network. This information will be used to calculate the loss occurring in the network using the developed algorithm. The Algorithm can also identify the leakages at any point of the pipeline so we can easily detect faults and rectify them within minimal time, minimal efforts and minimal resources.

Keywords: FLA, fault location analysis, GDN, gas distribution network, GIS, geographic information system, NMS, network Management system, OMS, outage management system, SSGC, Sui Southern gas company, UFG, unaccounted for gas

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Authors: Mitat Uysal, Aynur Uysal

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Computer engineering and mathematics share a deep and symbiotic relationship, with mathematics providing the foundational theories and models for computer engineering advancements. From algorithm development to optimization techniques, mathematics plays a pivotal role in solving complex computational problems. This paper explores key mathematical principles that underpin computer engineering, illustrating their significance through a case study that demonstrates the application of optimization techniques using Python code. The case study addresses the well-known vehicle routing problem (VRP), an extension of the traveling salesman problem (TSP), and solves it using a genetic algorithm.

Keywords: VRP, TSP, genetic algorithm, computer engineering, optimization

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Authors: Flóra Karsai-Rektenwald, Khongorzul Odgerel, Vanda Villányi, Zoltán Gábor Tóth, Zsófia Bánfalvi

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GIGANTEA (GI) is a plant-specific, circadian clock-regulated, nuclear protein involved in diverse processes from flowering to stress responses. In the obligate short-day tuberising Andigenum Group potatoes, GI is indirectly involved in determination of the time of tuber initiation. The goal of our study was to get information on the function of GI in the day-length independent tuberising commercial potato cultivar ‘Désirée’, a tetraploid plant carrying two GI genes, one on chromosome 4 (GI.04) and another one on chromosome 12 (GI.12). Functional analysis of the two GI genes was attempted by targeted mutagenesis using the CRISPR-Cas9 system. Two sets of mutants were generated. The mutations were mapped at nucleotide level and the plants grown in a greenhouse. GI is located in the nucleus and interacts with at least five proteins. Three out of them, two photoreceptors and FKF1, bind on GI close to the nuclear localisation (NLS) signal to the so called LOV domain. In Andigenum Group potatoes, FKF1 interacts not only with GI but form a triplex with CDF1, a positive regulator of tuberisation, and transport it to proteasomes, where CDF1 is degraded. Three GI.04 and three GI.12 null mutants were selected from the first set of mutagenesis. Although, the deletions did not reach the NLS and LOV domain in any of the six mutants all GI. 04 and two GI.12 mutants were shorter than the control suggesting that both GIs are involved in vegetative growth regulation and the deleted region might be important in terms of conformation or stability of the proteins. From the second set of mutagenesis, three null mutants carrying mutations in one of the two GI genes and three mutants carrying mutations in both GI genes were selected for detailed analysis. Deletions in the GI mutants of this set disrupted the NLS and extended to the LOV domain. Nevertheless, none of the single GI gene mutations influenced the time of tuberisation or the tuber number and yield, whereas one of the GI.04 and all GI.12 mutants were shorter than the ‘Désirée’ control. Furthermore, all GI.12 mutants showed early senescence. The early senescence of mutants carrying mutations in both GI genes was even more pronounced, resulting in substantial yield loss in one of the double mutants. These results raise the possibility that the two GI genes can substitute each other in term of tuberisation or they are not involved in it, the yield loss is due to the early death of the plants. To distinguish between the two possibilities yeast two-hybrid experiments were initiated to detect the interaction between the GI proteins and FKF1 and between FKF1 and CDF1 originated from ‘Désirée’.

Keywords: gene editing, tuberisation, senescence, Solanum tuberosum

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Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

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A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30dB SNR as a reference for voice activity.

Keywords: atomic decomposition, gabor, gammatone, matching pursuit, voice activity detection

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Authors: Mehdi Shahbazian, Alireza Aarabi, Mohsen Hadiyan

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Proportional-Integral-Derivative (PID) controllers are the most widely used controllers in industry because of its simplicity and robustness. Different values of PID parameters make different step response, so an increasing amount of literature is devoted to proper tuning of PID controllers. The problem merits further investigation as traditional tuning methods make large control signal that can damages the system but using evolutionary algorithms based tuning methods improve the control signal and closed loop performance. In this paper three tuning methods for PID controllers have been studied namely Ziegler and Nichols, which is traditional tuning method and evolutionary algorithms based tuning methods, that are, Genetic algorithm and particle swarm optimization. To examine the validity of PSO and GA tuning methods a comparative analysis of DC motor plant is studied. Simulation results reveal that evolutionary algorithms based tuning method have improved control signal amplitude and quality factors of the closed loop system such as rise time, integral absolute error (IAE) and maximum overshoot.

Keywords: evolutionary algorithm, genetic algorithm, particle swarm optimization, PID controller

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Authors: J. G. Batista, T. S. Santiago, E. A. Ribeiro, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measure and/or expected values.

Keywords: modeling, AC servomotor, permanent magnet synchronous motor-PMSM, genetic algorithm, vector control, robotic manipulator, control

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Authors: Anamika Paul, Sudipto Sarkar

Abstract:

The flow behaviour of non-Newtonian fluid is quite complicated, although both the pseudoplastic (n < 1, n being the power index) and dilatant (n > 1) fluids under this category are used immensely in chemical and process industries. A limited research work is carried out for flow over a bluff body in non-Newtonian flow environment. In the present numerical simulation we control the vortices of a square cylinder by placing an upstream vertical splitter plate for pseudoplastic (n=0.8), Newtonian (n=1) and dilatant (n=1.2) fluids. The position of the upstream plate is also varied to calculate the critical distance between the plate and cylinder, below which the cylinder vortex shedding suppresses. Here the Reynolds number is considered as Re = 150 (Re = U∞a/ν, where U∞ is the free-stream velocity of the flow, a is the side of the cylinder and ν is the maximum value of kinematic viscosity of the fluid), which comes under laminar periodic vortex shedding regime. The vertical plate is having a dimension of 0.5a × 0.05a and it is placed at the cylinder centre-line. Gambit 2.2.30 is used to construct the flow domain and to impose the boundary conditions. In detail, we imposed velocity inlet (u = U∞), pressure outlet (Neumann condition), symmetry (free-slip boundary condition) at upper and lower domain. Wall boundary condition (u = v = 0) is considered both on the cylinder and the splitter plate surfaces. The unsteady 2-D Navier Stokes equations in fully conservative form are then discretized in second-order spatial and first-order temporal form. These discretized equations are then solved by Ansys Fluent 14.5 implementing SIMPLE algorithm written in finite volume method. Here, fine meshing is used surrounding the plate and cylinder. Away from the cylinder, the grids are slowly stretched out in all directions. To get an account of mesh quality, a total of 297 × 208 grid points are used for G/a = 3 (G being the gap between the plate and cylinder) in the streamwise and flow-normal directions respectively after a grid independent study. The computed mean flow quantities obtained from Newtonian flow are agreed well with the available literatures. The results are depicted with the help of instantaneous and time-averaged flow fields. Qualitative and quantitative noteworthy differences are obtained in the flow field with the changes in rheology of fluid. Also, aerodynamic forces and vortex shedding frequencies differ with the gap-ratio and power index of the fluid. We can conclude from the present simulation that fluent is capable to capture the vortex dynamics of unsteady laminar flow regime even in the non-Newtonian flow environment.

Keywords: CFD, critical gap-ratio, splitter plate, wake-wake interactions, dilatant, pseudoplastic

Procedia PDF Downloads 112

Authors: A. Belmeguenai, K. Mansouri, R. Djemili

Abstract:

This work present a new algorithm based on the nonlinear filter generator for speech encryption and decryption. The proposed algorithm consists on the use a linear feedback shift register (LFSR) whose polynomial is primitive and nonlinear Boolean function. The purpose of this system is to construct Keystream with good statistical properties, but also easily computable on a machine with limited capacity calculated. This proposed speech encryption scheme is very simple, highly efficient, and fast to implement the speech encryption and decryption. We conclude the paper by showing that this system can resist certain known attacks.

Keywords: nonlinear filter generator, stream ciphers, speech encryption, security analysis

Procedia PDF Downloads 297