Search results for: Gaussian Conditional Random Field

Authors: Harman Jaggi, David Steinsaltz, Shripad Tuljapurkar

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Understanding the effect of fluctuations on populations is crucial in the context of increasing habitat fragmentation, climate change, and biological invasions, among others. Migration in response to environmental disturbances enables populations to escape unfavorable conditions, benefit from new environments and thereby ride out fluctuations in variable environments. Would populations disperse if there is no uncertainty? Karlin showed in 1982 that when sub-populations experience distinct but fixed growth rates at different sites, greater mixing of populations will lower the overall growth rate relative to the most favorable site. Here we ask if and when environmental variability favors migration over no-migration. Specifically, in random environments, would a small amount of migration increase the overall long-run growth rate relative to the zero migration case? We use analysis and simulations to show how long-run growth rate changes with migration rate. Our results show that when fitness (dis)advantages fluctuate over time across sites, migration may allow populations to benefit from variability. When there is one best site with highest growth rate, the effect of migration on long-run growth rate depends on the difference in expected growth between sites, scaled by the variance of the difference. When variance is large, there is a substantial probability of an inferior site experiencing higher growth rate than its average. Thus, a high variance can compensate for a difference in average growth rates between sites. Positive correlations in growth rates across sites favor less migration. With multiple sites and large fluctuations, the length of shortest cycle (excursion) from the best site (on average) matters, and we explore the interplay between excursion length, average differences between sites and the size of fluctuations. Our findings have implications for conservation biology: even when there are superior sites in a sea of poor habitats, variability and habitat quality across space may be key to determining the importance of migration.

Keywords: migration, variable-environments, random, dispersal, fluctuations, habitat-quality

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Authors: Muhammad Sufyan, Muhammad D. Gogi, Muhammad Arshad, Ahmad Nawaz, Muhammad Usman

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Cotton (Gossypium hirsutum) universally known as silver fiber and is one of the most important cash crop of Pakistan. A wide array of pests constraints cotton production among which sucking insect pests cause serious losses. Mostly new chemistry insecticides used to control a wide variety of insect pests including sucking insect pests. In the present study efficacy of different neonicotinoids was evaluated against sucking insect pests of cotton in the field and in laboratory for red and dusky cotton bug. The experiment was conducted at Entomology Research Station, University of Agriculture Faisalabad, in a Randomized Complete Block Design (RCBD). Field trial was conducted to evaluate the efficacy of Confidence Ultra (Imidacloprid) 70% SL, Confidor (Imidacloprid) 20% SL, Kendo (Lambda cyhalothrin) 24.7 SC, Actara (Thiamethoxam) 25% WG, Forcast (Tebufenozide+ Emamectin benzoate) 8.8 EW and Timer (Emamectin benzoate) 1.9 EC at their recommended doses. The data was collected on per leaf basis of thrips, aphid, jassid and whitefly before 24 hours of spray. The post treatment data was recorded after 24, 48 and 72 hours. The fresh, non-infested and untreated cotton leaves was collected from the field and brought to the laboratory to assess the efficacy of neonicotinoids against red and dusky cotton bug. After data analysis all the insecticides were found effective against sucking pests. Confidence Ultra was highly effective against the aphid, jassid, and whitefly and gave maximum mortality, while showed non-significant results against thrips. In case of aphid plot which was treated with Kando 24.7 SC showed significant mortality after 72 hours of pesticide application. Similar trends were found in laboratory conditions with all these treatments by making different concentrations and had significant impact on dusky cotton bug and red cotton bug population after 24, 48 and 72 hours after application.

Keywords: cotton, laboratory and field conditions, neonicotinoids, sucking insect pests

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Authors: Hussain K. Chaiel

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The development in the field of the digital signal processing (DSP) and the microelectronics technology reduces the complexity of the iterative algorithms that need large number of arithmetic operations. Virtex-Field Programmable Gate Arrays (FPGAs) are programmable silicon foundations which offer an important solution for addressing the needs of high performance DSP designer. In this work, Virtex-7 FPGA technology is used to implement an iterative algorithm to estimate the earthquake location. Simulation results show that an implementation based on block RAMB36E1 and DSP48E1 slices of Virtex-7 type reduces the number of cycles of the clock frequency. This enables the algorithm to be used for earthquake prediction.

Keywords: DSP, earthquake, FPGA, iterative algorithm

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Authors: Salah Aguib, Noureddine Chikh, Abdelmalek Khabli, Abdelkader Nour, Toufik Djedid, Lallia Kobzili

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This study presents the behavior of a hybrid smart sandwich plate with a magnetorheological elastomer core. In order to improve the vibrational behavior of the plate, the pseudo‐fibers formed by the effect of the magnetic field on the elastomer charged by the ferromagnetic particles are oriented at 45° with respect to the direction of the magnetic field at 0°. Ritz's approach is taken to solve the physical problem. In order to verify and compare the results obtained by the Ritz approach, an analysis using the finite element method was carried out. The rheological property of the MRE material at 0° and at 45° are determined experimentally, The studied elastomer is prepared by a mixture of silicone oil, RTV141A polymer, and 30% of iron particles of total mixture, the mixture obtained is mixed for about 15 minutes to obtain an elastomer paste with good homogenization. In order to develop a magnetorheological elastomer (MRE), this paste is injected into an aluminum mold and subjected to a magnetic field. In our work, we have chosen an ideal percentage of filling of 30%, to obtain the best characteristics of the MRE. The mechanical characteristics obtained by dynamic mechanical viscoanalyzer (DMA) are used in the two numerical approaches. The natural frequencies and the modal damping of the sandwich plate are calculated and discussed for various magnetic field intensities. The results obtained by the two methods are compared. These off‐axis anisotropic MRE structures could open up new opportunities in various fields of aeronautics, aerospace, mechanical engineering and civil engineering.

Keywords: hybrid smart sandwich plate, vibratory behavior, FEM, Ritz approach, MRE

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Authors: Naser Ebadati

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introductory statement: Drilling operations in oil wells often involve significant risks due to varying azimuths, slopes, and the passage through layers with different lithological properties. As a result, maintaining well stability is crucial. Instability in wells can lead to costly well losses, interrupted drilling operations, and halted production from reservoirs. Objective: One of the key challenges in drilling operations is ensuring the stability of the wellbore, particularly in loose and low-resistance formations. These factors make the analysis and evaluation of well stability essential. Therefore, building a geo mechanical model for a hydrocarbon field or reservoir requires both a stress field model and a mechanical properties model of the geological formations. Numerous studies have focused on analyzing the stability of well walls, an issue known as well instability. This study aims to analyze the stability and the safe mud weight window for drilling in one of the oil fields in southern Iran. Methodology: In wellbore stability analysis, it is essential to consider the stress field model, which includes values and directions of the three principal stresses, and the mechanical properties model, which covers elastic properties and rock fracture characteristics. Wellbore instability arises from mechanical failure of the rock. Well stability can be maintained by adjusting the drilling mud weight. This study investigates wellbore stability using field data. The lithological characteristics of the well mainly consist of limestone, dolomite, and shale, as determined from log data. Wellbore logging was conducted throughout the well to calculate the required drilling mud pressure using the Mohr-Coulomb criterion. Findings: The results indicate that the safe and stable drilling mud window ranges between 17.13 MPa and 27.80 MPa. By comparing and calculating induced stresses, it was determined that the wellbore wall primarily exhibits shear fractures in the form of wide shear fractures and tensile fractures in the form of radial tensile fractures.

Keywords: drilling mud weight, formation evaluation, sheer strees, safe window

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Authors: Laraba Bala Mohammed

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Education is a very vital tool in enhancement of the general development of individuals in the society who would participate effectively in national development processes, including people with special need, educating children with special needs is one of the greatest challenges of this millennium, this is because professionals in the field of special education are operating in an exciting and rapidly changing phenomenon. Inclusive education in Nigeria is not a new development in the teaching and learning process, but the most important aspect is the utilization and effective integration of people with special needs in the society. This paper focuses on the need of parents, government, professionals in the field of special education and stakeholders to work together for the full implementation of inclusive education in Nigeria.

Keywords: inclusive education, national policy, education, special needs

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Authors: Mahzabin Afroz, Indubhushan Patnaikuni, Srikanth Venkatesan

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It is well-known that fly ash can be used in high volume as a partial replacement of cement to get beneficial effects on concrete. High volume fly ash (HVFA) concrete is currently emerging as a popular option to strengthen by fiber. Although studies have supported the use of fibers with fly ash, a unified model along with the incorporation into finite element software package to estimate the maximum flexural loads need to be developed. In this study, nonlinear finite element analysis of steel fiber reinforced high strength HVFA concrete beam under static loadings was conducted to investigate their failure modes in terms of ultimate load. First of all, the experimental investigation of mechanical properties of high strength HVFA concrete was done and validates with developed numerical model with the appropriate modeling of element size and mesh by ANSYS 16.2. To model the fiber within the concrete, three-dimensional random fiber distribution was simulated by spherical coordinate system. Three types of high strength HVFA concrete beams were analyzed reinforced with 0.5, 1 and 1.5% volume fractions of steel fibers with specific mechanical and physical properties. The result reveals that the use of nonlinear finite element analysis technique and three-dimensional random fiber orientation exhibited fairly good agreement with the experimental results of flexural strength, load deflection and crack propagation mechanism. By utilizing this improved model, it is possible to determine the flexural behavior of different types and proportions of steel fiber reinforced HVFA concrete beam under static load. So, this paper has the originality to predict the flexural properties of steel fiber reinforced high strength HVFA concrete by numerical simulations.

Keywords: finite element analysis, high volume fly ash, steel fibers, spherical coordinate system

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Authors: Nidhi Adhlakha, K. L. Yadav

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Three phase magnetoelectric (ME) composites (1-x)(0.7BiFeO3-0.3CoFe2O4)-xPbTiO3 (or equivalently written as (1-x)(0.7BFO-0.3CFO)-xPT) with x variations 0, 0.30, 0.35, 0.40, 0.45 and 1.0 were synthesized using hybrid processing route. The effects of PT addition on structural, multiferroic and optical properties have been subsequently investigated. A detailed Rietveld refinement analysis of X-ray diffraction patterns has been performed, which confirms the presence of structural phases of individual constituents in the composites. Field emission scanning electron microscopy (FESEM) images are taken for microstructural analysis and grain size determination. Transmission electron microscopy (TEM) analysis of 0.3CFO-0.7BFO reveals the average particle size to be lying in the window of 8-10 nm. The temperature dependent dielectric constant at various frequencies (1 kHz, 10 kHz, 50 kHz, 100 kHz and 500 kHz) has been studied and the dielectric study reveals that the increase of dielectric constant and decrease of average dielectric loss of composites with incorporation of PT content. The room temperature ferromagnetic behavior of composites is confirmed through the observation of Magnetization vs. Magnetic field (M-H) hysteresis loops. The variation of magnetization with temperature indicates the presence of spin glass behavior in composites. Magnetoelectric coupling is evidenced in the composites through the observation of the dependence of the dielectric constant on the magnetic field, and magnetodielectric response of 2.05 % is observed for 45 mol% addition of PT content. The fractional change of magnetic field induced dielectric constant can also be expressed as ∆ε_r~γM^2 and the value of γ is found to be ~1.08×10-2 (emu/g)-2 for composite with x=0.40. Fourier transformed infrared (FTIR) spectroscopy of samples is carried out to analyze various bonds formation in the composites.

Keywords: composite, X-ray diffraction, dielectric properties, optical properties

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Authors: Ghania Zerari, Abderrezak Guessoum, Rachid Beguenane

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This paper introduces high-performance architecture for fully parallel stochastic Low-Density Parity-Check (LDPC) field programmable gate array (FPGA) based LDPC decoder. The new approach is designed to decrease the decoding latency and to reduce the FPGA logic utilisation. To accomplish the target logic utilisation reduction, the routing of the proposed sub-variable node (VN) internal memory is designed to utilize one slice distributed RAM. Furthermore, a VN initialization, using the channel input probability, is achieved to enhance the decoder convergence, without extra resources and without integrating the output saturated-counters. The Xilinx FPGA implementation, of IEEE 802.3an standard LDPC code, shows that the proposed decoding approach attain high performance along with reduction of FPGA logic utilisation.

Keywords: low-density parity-check (LDPC) decoder, stochastic decoding, field programmable gate array (FPGA), IEEE 802.3an standard

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Authors: Salima Bouadjela, Fatima Zohra Abdoune, Lahcene Mechernene

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PDLCs are currently considered as promising materials for specific applications such as creation of window blinds controlled by electric field, fog simulators, UV protective glasses, high data storage device etc. We know that the electrical field inside the liquid crystal is low compare with the external electric field [1,2]. An addition of high magnetic and electrical, properties containing compounds to the polymer dispersed liquid crystal (PDLC) will enhance the electrical, optical, and magnetic properties of the PDLC [3,4]. Low Concentration of inorganic nanoparticles TiO2 added to nematic liquid crystals (E7) and also combined with monomers (TPGDA) and cured monomer/LC mixture to elaborate polymer-LC-NP dispersion. The presence of liquid crystal and nanoparticles in TPGDA matrix were conformed and the modified properties of PDLC due to doped nanoparticle were studied and explained by the results of FTIR, POM, UV. Incorporation of nanoparticles modifies the structure of PDLC and thus it makes increase the amount of droplets and decrease in droplet size. we found that the presence of TiO2 nanoparticles leads to a shift the nematic-isotropic transition temperature TNI.

Keywords: nanocomposites, PDLC, phases diagram, TiO2

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Authors: Jian Zheng, Xinhua Ni, Xiequan Liu

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According to isotropy of parallel fiber eutectic, the no- damage strain field in parallel fiber eutectic is obtained from the flexibility tensor of parallel fiber eutectic. Considering the damage behavior of parallel fiber eutectic, damage variables are introduced to determine the strain field of parallel fiber eutectic. The damage strains in the matrix, interphase, and fiber of parallel fiber eutectic are quantitatively analyzed. Results show that damage strains are not only associated with the fiber volume fraction of parallel fiber eutectic, but also with the damage degree.

Keywords: damage strain, initial strain, fiber volume fraction, parallel fiber eutectic

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Authors: Koushik Roy, Sourav Gur, Sudib K. Mishra

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Evidence of pulse type features in near-fault ground motions has raised serious concern to the structural engineering community, in view of their possible implications on the behavior of structures located on the fault regions. Studies in the recent past explore the effects of pulse type ground motion on the special structures, such as transmission towers in view of their high flexibility. Identically, long period sloshing of liquid in the storage tanks under dynamic loading might increase their failure vulnerability under near-fault pulses. Therefore, the behavior of the elevated liquid storage tank is taken up in this study. Simple lumped mass model is considered, with the bilinear force-deformation hysteresis behavior. Set of near-fault seismic ground acceleration time histories are adopted for this purpose, along with the far-field records for comparison. It has been demonstrated that pulse type motions lead to significant increase of the responses; in particular, sloshing of the fluid mass could be as high as 5 times, then the far field counterpart. For identical storage capacity, slender tanks are found to be more vulnerable than the broad ones.

Keywords: far-field motion, hysteresis, liquid storage tank, near fault earthquake, sloshing

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Authors: Brahim Fersadou, Henda Kahalerras

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This work deals with the problem of MHD mixed convection in a completely porous and differentially heated vertical channel. The model of Darcy-Brinkman-Forchheimer with the Boussinesq approximation is adopted and the governing equations are solved by the finite volume method. The effects of magnetic field and buoyancy force intensities are given by the Hartmann and Richardson numbers respectively, as well as the Joule heating represented by Eckert number on the velocity and temperature fields, are examined. The main results show an augmentation of heat transfer rate with the decrease of Darcy number and the increase of Ri and Ha when Joule heating is neglected.

Keywords: heat sources, magnetic field, mixed convection, porous channel

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Authors: H. Vargova, J. Strecka, N. Tomasovicova

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A rigorous analytical treatment, with the help of a concept of negativity, is used to study the quantum and thermal entanglement in an isotropic mixed spin-(1/2,S) Heisenberg dimer. The effect of the spin-S magnitude, as well as the effect of diversity between Landé g-factors of magnetic constituents on system entanglement, is exhaustively analyzed upon the variation of the external magnetic and electric field, respectively. It was identified that the increasing magnitude of the spin-S species in a mixed spin-(1/2,S) Heisenberg dimer with comparative Landé g-factors have always a reduction effect on a degree of the quantum entanglement, but it strikingly shifts the thermal entanglement to the higher temperatures. Surprisingly, out of the limit of identical Landé g-factors, the increasing magnitude of spin-S entities can enhance the system entanglement in both low and high magnetic fields. Besides this, we identify that the analyzed dimer with a high-enough magnitude of the spin-S entities at a sufficiently high magnetic field can exhibit unconventional thermally driven re-entrance between the entangled and unentangled mixed state. The importance of the electric-field stimuli is also discussed in detail.

Keywords: quantum and thermal entantanglement, mixed spin Heisenberg model, negativity, reentrant phase transition

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Authors: Jude Opara, Esemokumo Perewarebo Akpos

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This paper is on non-parametric linear regression over its parametric counterparts with large sample size. Data set on anthropometric measurement of primary school pupils was taken for the analysis. The study used 50 randomly selected pupils for the study. The set of data was subjected to normality test, and it was discovered that the residuals are not normally distributed (i.e. they do not follow a Gaussian distribution) for the commonly used least squares regression method for fitting an equation into a set of (x,y)-data points using the Anderson-Darling technique. The algorithms for the nonparametric Theil’s regression are stated in this paper as well as its parametric OLS counterpart. The use of a programming language software known as “R Development” was used in this paper. From the analysis, the result showed that there exists a significant relationship between the response and the explanatory variable for both the parametric and non-parametric regression. To know the efficiency of one method over the other, the Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) are used, and it is discovered that the nonparametric regression performs better than its parametric regression counterparts due to their lower values in both the AIC and BIC. The study however recommends that future researchers should study a similar work by examining the presence of outliers in the data set, and probably expunge it if detected and re-analyze to compare results.

Keywords: Theil’s regression, Bayesian information criterion, Akaike information criterion, OLS

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Authors: Mei Hong, Wei Liu, Xuemin Dai, Yanxiong Pan, Xiangling Ji

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Polyamic acid (PAA) is the precursor of polyimide (PI) prepared by a two-step method, its molecular weight and molecular weight distribution not only play an important role during the preparation and processing, but also influence the final performance of PI. However, precise characterization on molecular weight of PAA is still a challenge because of the existence of very complicated interactions in the solution system, including the electrostatic interaction, hydrogen bond interaction, dipole-dipole interaction, etc. Thus, it is necessary to establisha suitable strategy which can completely suppress these complex effects and get reasonable data on molecular weight. Herein, the gel permeation chromatography (GPC) coupled with differential refractive index (RI) and multi-angle laser light scattering (MALLS) detectors were applied to measure the molecular weight of (6FDA-DMB) PAA using different mobile phases, LiBr/DMF, LiBr/H3PO4/THF/DMF, LiBr/HAc/THF/DMF, and LiBr/HAc/DMF, respectively. It was found that combination of LiBr with HAc can shield the above-mentioned complex interactions and is more conducive to the separation of PAA than only addition of LiBr in DMF. LiBr/HAc/DMF was employed for the first time as a mild mobile phase to effectively separate PAA and determine its molecular weight. After a series of conditional experiments, 0.02M LiBr/0.2M HAc/DMF was fixed as an optimized mobile phase to measure the relative and absolute molecular weights of (6FDA-DMB) PAA prepared, and the obtained Mw from GPC-MALLS and GPC-RI were 35,300 g/mol and 125,000 g/mol, respectively. Particularly, such a mobile phase is also applicable to other PAA samples with different structures, and the final results on molecular weight are also reproducible.

Keywords: Polyamic acids, Polyelectrolyte effects, Gel permeation chromatography, Mobile phase, Molecular weight

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Authors: Sheng-Po Tseng, Che-Hua Yang

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Motivation and Objective: Ultrasonic guided waves become an important tool for nondestructive evaluation of structures and components. Guided waves are used for the purpose of identifying defects or evaluating material properties in a nondestructive way. While guided waves are applied for evaluating material properties, instead of knowing the properties directly, preliminary signals such as time domain signals or frequency domain spectra are first revealed. With the measured ultrasound data, inversion calculation can be further employed to obtain the desired mechanical properties. Methods: This research is development of high speed inversion calculation technique for obtaining full-field mechanical properties from the quantitative laser ultrasound visualization system (QLUVS). The quantitative laser ultrasound visualization system (QLUVS) employs a mirror-controlled scanning pulsed laser to generate guided acoustic waves traveling in a two-dimensional target. Guided waves are detected with a piezoelectric transducer located at a fixed location. With a gyro-scanning of the generation source, the QLUVS has the advantage of fast, full-field, and quantitative inspection. Results and Discussions: This research introduces two important tools to improve the computation efficiency. Firstly, graphic procession unit (GPU) with large amount of cores are introduced. Furthermore, combining the CPU and GPU cores, parallel procession scheme is developed for the inversion of full-field mechanical properties based on the QLUVS data. The newly developed inversion scheme is applied to investigate the computation efficiency for single-layered and double-layered plate-like samples. The computation efficiency is shown to be 80 times faster than unparalleled computation scheme. Conclusions: This research demonstrates a high-speed inversion technique for the characterization of full-field material properties based on quantitative laser ultrasound visualization system. Significant computation efficiency is shown, however not reaching the limit yet. Further improvement can be reached by improving the parallel computation. Utilizing the development of the full-field mechanical property inspection technology, full-field mechanical property measured by non-destructive, high-speed and high-precision measurements can be obtained in qualitative and quantitative results. The developed high speed computation scheme is ready for applications where full-field mechanical properties are needed in a nondestructive and nearly real-time way.

Keywords: guided waves, material characterization, nondestructive evaluation, parallel processing

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Authors: Sevilay Çankaya

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The detection of deception in children’s interviews is essential for statement veracity. The widely used method for deception detection is building cognitive load, which is the logic of the cognitive interview (CI), and its effectiveness for adults is approved. This meta-analysis delves into the effectiveness of inducing cognitive load as a means of enhancing veracity detection during interviews with children. Additionally, the effectiveness of cognitive load on children's total number of events recalled is assessed as a second part of the analysis. The current meta-analysis includes ten effect sizes from search using databases. For the effect size calculation, Hedge’s g was used with a random effect model by using CMA version 2. Heterogeneity analysis was conducted to detect potential moderators. The overall result indicated that cognitive load had no significant effect on veracity outcomes (g =0.052, 95% CI [-.006,1.25]). However, a high level of heterogeneity was found (I² = 92%). Age, participants’ characteristics, interview setting, and characteristics of the interviewer were coded as possible moderators to explain variance. Age was significant moderator (β = .021; p = .03, R2 = 75%) but the analysis did not reveal statistically significant effects for other potential moderators: participants’ characteristics (Q = 0.106, df = 1, p = .744), interview setting (Q = 2.04, df = 1, p = .154), and characteristics of interviewer (Q = 2.96, df = 1, p = .086). For the second outcome, the total number of events recalled, the overall effect was significant (g =4.121, 95% CI [2.256,5.985]). The cognitive load was effective in total recalled events when interviewing with children. All in all, while age plays a crucial role in determining the impact of cognitive load on veracity, the surrounding context, interviewer attributes, and inherent participant traits may not significantly alter the relationship. These findings throw light on the need for more focused, age-specific methods when using cognitive load measures. It may be possible to improve the precision and dependability of deceit detection in children's interviews with the help of more studies in this field.

Keywords: deceit detection, cognitive load, memory recall, children interviews, meta-analysis

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Authors: Shahbaz Ahmad, Muhammad Ali, Sahar Naz

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Corm rot is caused by the fungus Fusarium oxysporum f.sp. gladioli and it causes remarkable losses to the growers. Experiment was conducted in order to find some viable recommendations for this agronomically as well as economically important problem. Four fungicides, namely Carbendazim, Mancozeb, Thiophanate methyl and Chlorothalonil were used to control corm rot in gladiolus field. Fungicides were applied singly as foliar, in irrigation as well as with sulphuric acid in variable doses. The results revealed that application of all fungicides was variably effective to control corm rot in acid mixed irrigation followed by fungicide in irrigation. The application of all fungicides in various combinations was observed to be ineffective at all three doses.

Keywords: gladiolus, corm rot, Fusarium oxysporum, fungicides

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Authors: Omer Cahana, Maya Herman, Ofer Levi

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Magnetic resonance imaging (MRI) is a long medical scan that stems from a long acquisition time. This 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. In order to achieve that, two properties have to exist: i) the signal must be sparse under a known transform domain, ii) the sampling method must be incoherent. In addition, a nonlinear reconstruction algorithm needs to be applied to recover the signal. While the rapid advance in the deep learning (DL) field, which has demonstrated tremendous successes in various computer vision task’s, the field of MRI reconstruction is still in an early stage. In this paper, we present an extension of the state-of-the-art model in MRI reconstruction -VarNet. We utilize VarNet by using dilated convolution in different scales, which extends the receptive field to capture more contextual information. Moreover, we simplified the sensitivity map estimation (SME), for it holds many unnecessary layers for this task. Those improvements have shown significant decreases in computation costs as well as higher accuracy.

Keywords: MRI, deep learning, variational network, computer vision, compress sensing

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Authors: Ana Paula S. A. Correa, Allan K. R. Galardo, Luana A. Lima, Talita F. Sobral, Josiane N. Muller, Jessica F. S. Barroso, Nercy V. R. Furtado, Ednaldo C. Rêgo., Jose B. P. Lima

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Malaria is a public health problem in the Brazilian Legal Amazon. Among the integrated approaches for anopheline control, the Indoor Residual Spraying (IRS) remains one of the main tools in the basic strategy applied in the Amazonian States, where the National Malaria Control Program currently uses one of the insecticides from the pyrethroid class, the Etofenprox WP. Understanding the residual efficacy of insecticides on different surfaces is essential to determine the spray cycles, in order to maintain a rational use and to avoid product waste. The aim of this study was to evaluate the residual efficacy of Etofenprox - VECTRON ® 20 WP on surfaces of Unplastered Cement (UC) and Unpainted Wood (UW) on panels, in field, and in semi-field evaluation of Brazil’s Amapa State. The evaluation criteria used was the cone bioassay test, following the World Health Organization (WHO) recommended method, using plastic cones and female mosquitos of Anopheles sp. The tests were carried out in laboratory panels, semi-field evaluation in a “test house” built in the Macapa municipality, and in the field in 20 houses, being ten houses per surface type (UC and UW), in an endemic malaria area in Mazagão’s municipality. The residual efficacy was measured from March to September 2017, starting one day after the spraying, repeated monthly for a period of six months. The UW surface presented higher residual efficacy than the UC. In fact, the UW presented a residual efficacy of the insecticide throughout the period of this study with a mortality rate above 80% in the panels (= 95%), in the "test house" (= 86%) and in field houses ( = 87%). On the UC surface it was observed a mortality decreased in all the tests performed, with a mortality rate of 45, 47 and 29% on panels, semi-field and in field, respectively; however, the residual efficacy ≥ 80% only occurred in the first evaluation after the 24-hour spraying bioassay in the "test house". Thus, only the UW surface meets the specifications of the World Health Organization Pesticide Evaluation Scheme (WHOPES) regarding the duration of effective action (three to six months). To sum up, the insecticide residual efficacy presented variability on the different surfaces where it was sprayed. Although the IRS with Etofenprox WP was efficient on UW surfaces, and it can be used in spraying cycles at 4-month intervals, it is important to consider the diversity of houses in the Brazilian Legal Amazon, in order to implement alternatives for vector control, including the evaluation of new products or different formulations types for insecticides.

Keywords: Anopheles, vector control, insecticide, bioassay

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Authors: Sujay Bisht

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The purpose of the study was to evaluate and find out the effect of Hill interval training on VO₂ MAX among field Hockey players. Thirty male field hockey players were selected from LNIPE, Guwahati who were studied in B.P.Ed course. The selected subjects were aged between 18 to 23 years. The VO₂ MAX was calculated and they were divided into two group. One group (N=15) considered as control group that did not participated in any special training apart from regular scheduled/curriculum and another group (N=15) considered as an experimental group which underwent four week Hill Training program. The selected criterion variable such VO₂ Max was measured by the cooper 12min/run/walk test and scores was recorded in ml/kg/min. The subjects were tested on selected criterion variable such as VO₂ Max prior and immediately after the training program. The pretest and posttest data were evaluate by the Analysis of Covariance (ANCOVA) to find out the significance difference if any between the experimental and control group on selected criterion variable. The level of significance was set at 0.05 level of confidence. After applied ANCOVA it was revealed that there was a significant different among the experimental and control group on VO₂ Max. Finally it was concluded that 4 week of Hill interval training effect the VO₂ max performance of field hockey players.

Keywords: VO₂ max, hill interval training, ANCOVA, experimental group

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Authors: Priti Bajpai, Mohammed Shibil

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This paper utilizes a comparative case study design to examine a regional onion market. The particular case of onion markets is used to understand perishable product supply chains. The site for the study is Dubai, United Arab Emirates. Results from a six-month field study are outlined. In particular, the findings suggest that firms should examine adding additional destinations to their supply chain. Further, we argue that utilizing Dubai as a supply chain hub is in certain cases counterproductive. Implications for food supply chains and regional trade are discussed.

Keywords: supply chains, food markets, onion trade, field study

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Authors: Zhi Zhu, Boquan Zhang, Tian Jing, Jingjing Li, Tao Wang

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Data assimilation is a model and data hybrid-driven method that dynamically fuses new observation data with a numerical model to iteratively approach the real system state. It is widely used in state prediction and parameter inference of continuous systems. Because of the discrete event system’s non-linearity and non-Gaussianity, traditional Kalman Filter based on linear and Gaussian assumptions cannot perform data assimilation for such systems, so particle filter has gradually become a technical approach for discrete event simulation data assimilation. Hence, we proposed a particle filter-based discrete event simulation data assimilation method and took the unmanned aerial vehicle (UAV) maintenance service system as a proof of concept to conduct simulation experiments. The experimental results showed that the filtered state data is closer to the real state of the system, which verifies the effectiveness of the proposed method. This research can provide a reference framework for the data assimilation process of other complex nonlinear systems, such as discrete-time and agent simulation.

Keywords: discrete event simulation, data assimilation, particle filter, model and data-driven

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Authors: Amin Naboureh, Ainong Li, Jinhu Bian, Guangbin Lei, Hamid Ebrahimy

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Large-scale land cover mapping has become a new challenge in land change and remote sensing field because of involving a big volume of data. Moreover, selecting the right classification method, especially when there are different types of landscapes in the study area is quite difficult. This paper is an attempt to compare the performance of different machine learning (ML) algorithms for generating a land cover map of the China-Central Asia–West Asia Corridor that is considered as one of the main parts of the Belt and Road Initiative project (BRI). The cloud-based Google Earth Engine (GEE) platform was used for generating a land cover map for the study area from Landsat-8 images (2017) by applying three frequently used ML algorithms including random forest (RF), support vector machine (SVM), and artificial neural network (ANN). The selected ML algorithms (RF, SVM, and ANN) were trained and tested using reference data obtained from MODIS yearly land cover product and very high-resolution satellite images. The finding of the study illustrated that among three frequently used ML algorithms, RF with 91% overall accuracy had the best result in producing a land cover map for the China-Central Asia–West Asia Corridor whereas ANN showed the worst result with 85% overall accuracy. The great performance of the GEE in applying different ML algorithms and handling huge volume of remotely sensed data in the present study showed that it could also help the researchers to generate reliable long-term land cover change maps. The finding of this research has great importance for decision-makers and BRI’s authorities in strategic land use planning.

Keywords: land cover, google earth engine, machine learning, remote sensing

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Authors: Yousif Mohamed Y. Abdallah, Eltayeb Wagallah

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Image enhancement allows the observer to see details in images that may not be immediately observable in the original image. Image enhancement is the transformation or mapping of one image to another. The enhancement of certain features in images is accompanied by undesirable effects. To achieve maximum image quality after denoising, a new, low order, local adaptive Gaussian scale mixture model and median filter were presented, which accomplishes nonlinearities from scattering a new nonlinear approach for contrast enhancement of bones in bone scan images using both gamma correction and negative transform methods. The usual assumption of a distribution of gamma and Poisson statistics only lead to overestimation of the noise variance in regions of low intensity but to underestimation in regions of high intensity and therefore to non-optional results. The contrast enhancement results were obtained and evaluated using MatLab program in nuclear medicine images of the bones. The optimal number of bins, in particular the number of gray-levels, is chosen automatically using entropy and average distance between the histogram of the original gray-level distribution and the contrast enhancement function’s curve.

Keywords: bone scan, nuclear medicine, Matlab, image processing technique

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Authors: Eman W. Boghdady, A. R. Shehata, M. A. Azem

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Database (DB) security demands permitting authorized users and prohibiting non-authorized users and intruders actions on the DB and the objects inside it. Organizations that are running successfully demand the confidentiality of their DBs. They do not allow the unauthorized access to their data/information. They also demand the assurance that their data is protected against any malicious or accidental modification. DB protection and confidentiality are the security concerns. There are four types of controls to obtain the DB protection, those include: access control, information flow control, inference control, and cryptographic. The cryptographic control is considered as the backbone for DB security, it secures the DB by encryption during storage and communications. Current cryptographic techniques are classified into two types: traditional classical cryptography using standard algorithms (DES, AES, IDEA, etc.) and chaos cryptography using continuous (Chau, Rossler, Lorenz, etc.) or discreet (Logistics, Henon, etc.) algorithms. The important characteristics of chaos are its extreme sensitivity to initial conditions of the system. In this paper, DB-security systems based on chaotic algorithms are described. The Pseudo Random Numbers Generators (PRNGs) from the different chaotic algorithms are implemented using Matlab and their statistical properties are evaluated using NIST and other statistical test-suits. Then, these algorithms are used to secure conventional DB (plaintext), where the statistical properties of the ciphertext are also tested. To increase the complexity of the PRNGs and to let pass all the NIST statistical tests, we propose two hybrid PRNGs: one based on two chaotic Logistic maps and another based on two chaotic Henon maps, where each chaotic algorithm is running side-by-side and starting from random independent initial conditions and parameters (encryption keys). The resulted hybrid PRNGs passed the NIST statistical test suit.

Keywords: algorithms and data structure, DB security, encryption, chaotic algorithms, Matlab, NIST

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Authors: Mohammad Karimi Moridani, Mohammad Abdi Zadeh, Zahra Shahiazar Mazraeh

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In recent years, the use of intelligent systems in biomedical engineering has increased dramatically, especially in the diagnosis of various diseases. Also, due to the relatively simple recording of the electrocardiogram signal (ECG), this signal is a good tool to show the function of the heart and diseases associated with it. The aim of this paper is to design an intelligent system for automatically detecting a normal electrocardiogram signal from abnormal one. Using this diagnostic system, it is possible to identify a person's heart condition in a very short time and with high accuracy. The data used in this article are from the Physionet database, available in 2016 for use by researchers to provide the best method for detecting normal signals from abnormalities. Data is of both genders and the data recording time varies between several seconds to several minutes. All data is also labeled normal or abnormal. Due to the low positional accuracy and ECG signal time limit and the similarity of the signal in some diseases with the normal signal, the heart rate variability (HRV) signal was used. Measuring and analyzing the heart rate variability with time to evaluate the activity of the heart and differentiating different types of heart failure from one another is of interest to the experts. In the preprocessing stage, after noise cancelation by the adaptive Kalman filter and extracting the R wave by the Pan and Tampkinz algorithm, R-R intervals were extracted and the HRV signal was generated. In the process of processing this paper, a new idea was presented that, in addition to using the statistical characteristics of the signal to create a return map and extraction of nonlinear characteristics of the HRV signal due to the nonlinear nature of the signal. Finally, the artificial neural networks widely used in the field of ECG signal processing as well as distinctive features were used to classify the normal signals from abnormal ones. To evaluate the efficiency of proposed classifiers in this paper, the area under curve ROC was used. The results of the simulation in the MATLAB environment showed that the AUC of the MLP and SVM neural network was 0.893 and 0.947, respectively. As well as, the results of the proposed algorithm in this paper indicated that the more use of nonlinear characteristics in normal signal classification of the patient showed better performance. Today, research is aimed at quantitatively analyzing the linear and non-linear or descriptive and random nature of the heart rate variability signal, because it has been shown that the amount of these properties can be used to indicate the health status of the individual's heart. The study of nonlinear behavior and dynamics of the heart's neural control system in the short and long-term provides new information on how the cardiovascular system functions, and has led to the development of research in this field. Given that the ECG signal contains important information and is one of the common tools used by physicians to diagnose heart disease, but due to the limited accuracy of time and the fact that some information about this signal is hidden from the viewpoint of physicians, the design of the intelligent system proposed in this paper can help physicians with greater speed and accuracy in the diagnosis of normal and patient individuals and can be used as a complementary system in the treatment centers.

Keywords: neart rate variability, signal processing, linear and non-linear features, classification methods, ROC Curve

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Authors: Pankhuri Bansal, Sanjeev Kumar

Abstract:

We examined the exotic role of electrical poling of layered BCZT-NZFO bulk composite for sustainable advancement of magnetoelectric (ME) technology. Practically, it seems quite difficult to access the full potential of ME composites due to their weak ME coupling performances. Using a standard poling protocol, we successfully deployed the coupling performance of laminated ME composite, comprised of a ferroelectric (FE) layer of BCZT and a ferrite layer of NZFO. However, the ME coupling constant of laminated composite is optimized by lowering the volume fraction of the FE component to strengthen the mechanical strain in the piezoelectric layer while fixing the thickness of the magnetostrictive ferrite layer. Here, we employed systematic zero field cooled (ZFC) and field cooled (FC) electrical poling protocol on morphotropic phase boundary (MPB) based BCZT composition, well-appreciated for it’s remarkable electromechanical activity. We report a record augmentation in magnetoelectric coupling as a consequence of a prudent field-cooled poling mechanism. On the basis of our findings, we emphasize that the degree of magnetoelectricity may be significantly improved for the miniaturization of efficient devices via proper execution of the poling technique.

Keywords: magnetoelectric, lead-free, ferroelctric, ferromagnetic, energy harvesting

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Authors: Ayat Bani Rashaid, Zain Khasawneh, Mazin Alqhazo, Shreen Nusair, Mohammad El-Khateeb, Mahmoud Bashtawi

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Autism Spectrum disorder (ASD) is a psychiatric disorder with unknown etiology that mainly affects children in the first three years of life. Alterations of amino acid levels are believed to contribute to ASD. The levels of six essential amino acids (methionine, histidine, valine, leucine, threonine, and phenylalanine), five conditional amino acids (proline, tyrosine, glutamine, cysteine, and cystine), and five non-essential amino acids (asparagine, aspartic acid, alanine, serine, and glutamic acid) in hair samples of children with ASD (n = 25) were analyzed and compared to corresponding levels in healthy age-matched controls (n = 25). The results showed that the levels of methionine, alanine, and asparagine were significantly lower in the hair samples of ASD group compared to those of the control group (p ≤ 0.05). However, the levels of glutamic acid were significantly higher in the ASD group than the control group (p ≤ 0.05). The current findings could contribute towards further understanding of ASD etiology and provide specialists with a hair amino acid profile utilized as a biomarker for early diagnosis of ASD. Such biomarkers could participate in future developments of therapies that reduce ASD-related symptoms.

Keywords: autism spectrum disorder, amino acids, liquid chromatography-tandem mass spectrometry, human hair

Procedia PDF Downloads 138