Search results for: modeling technique

Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

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This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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Authors: M. Al-Shamery, R. Young, P. Birch, C. Chatwin

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Computer Generated Holography (CGH) is employed to create digitally defined coherent wavefronts. A CGH can be created by using different techniques such as by using a detour-phase technique or by direct phase modulation to create a kinoform. The detour-phase technique was one of the first techniques that was used to generate holograms digitally. The disadvantage of this technique is that the reconstructed image often has poor quality due to the limited dynamic range it is possible to record using a medium with reasonable spatial resolution.. The kinoform (phase-only hologram) is an alternative technique. In this method, the phase of the original wavefront is recorded but the amplitude is constrained to be constant. The original object does not need to exist physically and so the kinoform can be used to reconstruct an almost arbitrary wavefront. However, the image reconstructed by this technique contains high levels of noise and is not identical to the reference image. To improve the reconstruction quality of the kinoform, iterative techniques such as the Gerchberg-Saxton algorithm (GS) are employed. In this paper the GS algorithm is described for the optimisation of a kinoform used for the reconstruction of a complex wavefront. Iterations of the GS algorithm are applied to determine the phase at a plane (with known amplitude distribution which is often taken as uniform), that satisfies given phase and amplitude constraints in a corresponding Fourier plane. The GS algorithm can be used in this way to enhance the reconstruction quality of the kinoform. Different images are employed as the reference object and their kinoform is synthesised using the GS algorithm. The quality of the reconstructed images is quantified to demonstrate the enhanced reconstruction quality achieved by using this method.

Keywords: computer generated holography, digital holography, Gerchberg-Saxton algorithm, kinoform

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Authors: Miljan B. Petrović, Dušan B. Petrović, Goran S. Nikolić

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This paper describes a method for AWGN (Additive White Gaussian Noise) variance estimation in noisy stochastic signals, referred to as Multiplicative-Noising Variance Estimation (MNVE). The aim was to develop an estimation algorithm with minimal number of assumptions on the original signal structure. The provided MATLAB simulation and results analysis of the method applied on speech signals showed more accuracy than standardized AR (autoregressive) modeling noise estimation technique. In addition, great performance was observed on very low signal-to-noise ratios, which in general represents the worst case scenario for signal denoising methods. High execution time appears to be the only disadvantage of MNVE. After close examination of all the observed features of the proposed algorithm, it was concluded it is worth of exploring and that with some further adjustments and improvements can be enviably powerful.

Keywords: noise, signal-to-noise ratio, stochastic signals, variance estimation

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Authors: A. Attaf A., I. Bouhaf Kharkhachi

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Spray ultrasonic deposition technique of tin disulfide (SnS2) thin films know wide application due to their adequate physicochemical properties for microelectronic applications and especially for solar cells. SnS2 film was deposited by spray ultrasonic technique, on pretreated glass substrates at well-determined conditions.The effect of SnS2 concentration on different optical properties of SnS2 Thin films, such us MEB, XRD, and UV spectroscopy visible spectrum was investigated. MEB characterization technique shows that the morphology of this films is uniform, compact and granular. x-ray diffraction study detects the best growth crystallinity in hexagonal structure with preferential plan (001). The results of UV spectroscopy visible spectrum show that films deposited at 0.1 mol/l is large transmittance greater than 25% in the visible region.The band gap energy is 2.54 Ev for molarity 0.1 mol/l.

Keywords: MEB, thin disulfide, thin films, ultrasonic spray, X-Ray diffraction, UV spectroscopy visible

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Authors: Kobi Kutsher

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On February 12th 2013, monitoring stations of the Preparatory Commission of the Comprehensive Nuclear Test-Ban Treaty Organization (CTBTO) detected a seismic event with explosion-like underground characteristics in the Democratic People’s Republic of Korea (DPRK). The location was found to be in the vicinity of the two previous announced nuclear tests in 2006 and 2009.The nuclear test was also announced by the government of the DPRK.After an underground nuclear explosion, radioactive fission products (mostly noble gases) can seep through layers of rock and sediment until they escape into the atmosphere. The fission products are dispersed in the atmosphere and may be detected thousands of kilometers downwind from the test site. Indeed, more than 7 weeks after the explosion, unusual detections of noble gases was reported at the radionuclide station in Takasaki, Japan. The radionuclide station is a part of the International Monitoring System, operated to verify the CTBT. This study provides an estimation of the possible source region and the total radioactivity of the release using Atmospheric Transport Modeling.

Keywords: atmospheric transport modeling, CTBTO, nuclear tests, radioactive fission products

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

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Discrete Choice Experiments (DCE) are used to investigate how product attributes affect decision-makers’ choices. In DCEs, choice situations consisting of several alternatives are presented from which choice-makers select the preferred alternative. Standard multinomial logit models based on random utility theory can be used to estimate the utilities for the attributes. The overarching principle in these models is that respondents understand and use all the attributes when making choices. However, studies suggest that respondents sometimes ignore some attributes (commonly referred to as Attribute Non-Attendance/ANA). The choice modeling literature presents ANA as a static process, i.e., respondents’ ANA behavior does not change throughout the experiment. However, respondents may ignore attributes due to changing factors like availability of information on attributes, learning/fatigue in experiments, etc. We develop a dynamic mixture latent Markov model to model changes in ANA when information on attributes is provided. The model is illustrated on e-consumers’ webshop choices. The results indicate that the dynamic ANA model describes the behavioral changes better than modeling the impact of information using changes in parameters. Further, we find that providing information on attributes leads to an increase in the attendance probabilities for the investigated attributes.

Keywords: choice models, discrete choice experiments, dynamic models, e-commerce, statistical modeling

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.

Keywords: neural networks, decision trees, diagnosis, behaviors

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Authors: H. Shokouhmand, M. Tajerian

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At this paper velocity profile modeling and heat transfer in the micro heat pipes by using electrohydrodynamic (EHD) field at the transient regime have been studied. In the transient flow, one dimensional and two phase fluid flow and heat transfer for micro heat pipes with square cross section, have been studied. At this model Coulomb and dielectrophoretic forces are considered. Coupled, non-linear equations governed on the model (continuity, momentum, and energy equations) have been solved simultaneously by numerical methods. Transient behavior of affecting parameters e.g. substrate temperature, velocity of coolant liquid, radius of curvature and coolant liquid pressure, has been verified. By obtaining and plotting the mentioned parameters, it has been shown that the EHD field enhances the heat transfer process. So, the time required to reach the steady state regime decreases from 16 seconds to 2.4 seconds after applying EHD field. Another result has been observed implicitly that by increasing the heat input the effect of EHD field became more significant. The numerical results of model predict the experimental results available in the literature successfully, and it has been observed there is a good agreement between them.

Keywords: micro heat pipe, transient modeling, electrohydrodynamics, capillary, meniscus

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Authors: Quoc Khanh Dang, Thomas Bourdeaud’huy, Khaled Mesghouni, Armand Toguy´eni

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This paper studies a train routing and scheduling problem for busy railway stations. Our objective is to allow trains to be routed in dense areas that are reaching saturation. Unlike traditional methods that allocate all resources to setup a route for a train and until the route is freed, our work focuses on the use of resources as trains progress through the railway node. This technique allows a larger number of trains to be routed simultaneously in a railway node and thus reduces their current saturation. To deal with this problem, this study proposes an abstract model and a mixed-integer linear programming formulation to solve it. The applicability of our method is illustrated on a didactic example.

Keywords: busy railway stations, mixed-integer linear programming, offline railway station management, train platforming, train routing, train scheduling

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Authors: Mahmoud Nadir, Adel Ghenaiet

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The main purpose of this study is the thermodynamic modeling, the parametric analysis, and the optimization of three pressure level reheat HRSG (Heat Recovery Steam Generator) using PSO method (Particle Swarm Optimization). In this paper, a parametric analysis followed by a thermodynamic optimization is presented. The chosen objective function is the specific work of the steam cycle that may be, in the case of combined cycle (CC), a good criterion of thermodynamic performance analysis, contrary to the conventional steam turbines in which the thermal efficiency could be also an important criterion. The technologic constraints such as maximal steam cycle temperature, minimal steam fraction at steam turbine outlet, maximal steam pressure, minimal stack temperature, minimal pinch point, and maximal superheater effectiveness are also considered. The parametric analyses permitted to understand the effect of design parameters and the constraints on steam cycle specific work variation. PSO algorithm was used successfully in HRSG optimization, knowing that the achieved results are in accordance with those of the previous studies in which genetic algorithms were used. Moreover, this method is easy to implement comparing with the other methods.

Keywords: combined cycle, HRSG thermodynamic modeling, optimization, PSO, steam cycle specific work

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Authors: N. C. Sarkar, A. Bhaskar, Z. Zheng

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The driving behavior in area-based (i.e., non-lane based) traffic is induced by the presence of other individuals in the choice space from the driver’s visual perception area. The driving behavior of a subject vehicle is constrained by the potential leaders and leaders are frequently changed over time. This paper is to determine a stochastic model for a parameter of modified intelligent driver model (MIDM) in area-based traffic (as in developing countries). The parametric and non-parametric distributions are presented to fit the parameters of MIDM. The goodness of fit for each parameter is measured in two different ways such as graphically and statistically. The quantile-quantile (Q-Q) plot is used for a graphical representation of a theoretical distribution to model a parameter and the Kolmogorov-Smirnov (K-S) test is used for a statistical measure of fitness for a parameter with a theoretical distribution. The distributions are performed on a set of estimated parameters of MIDM. The parameters are estimated on the real vehicle trajectory data from India. The fitness of each parameter with a stochastic model is well represented. The results support the applicability of the proposed modeling for parameters of MIDM in area-based traffic flow simulation.

Keywords: area-based traffic, car-following model, micro-simulation, stochastic modeling

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Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Razieh Arian, Hadi Adibi-Asl

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This paper investigates an efficient combustion modeling for cycle simulation of internal combustion engine (ICE) studies. The term “efficient model” means that the models must generate desired simulation results while having fast simulation time. In other words, the efficient model is defined based on the application of the model. The objective of this study is to develop math-based models for control applications or shortly control-oriented models. This study compares different modeling approaches used to model the ICEs such as mean-value models, zero dimensional, quasi-dimensional, and multi-dimensional models for control applications. Mean-value models have been widely used for model-based control applications, but recently by developing advanced simulation tools (e.g. Maple/MapleSim) the higher order models (more complex) could be considered as control-oriented models. This paper presents the enhanced zero-dimensional cycle-by-cycle modeling and simulation of a spark ignition engine with a two-zone combustion model. The simulation results are cross-validated against the simulation results from GT-Power package and show a good agreement in terms of trends and values.

Keywords: Two-zone combustion, control-oriented model, wiebe function, internal combustion engine

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Authors: Issam Alnader, Aboubaker Lasebae, Rand Raheem

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Wireless sensor networks (WSNs) are distributed network systems used in a wide range of applications, including safety-critical systems. The latter provide critical services, often concerned with human life or assets. Therefore, ensuring the dependability requirements of Safety critical systems is of paramount importance. The purpose of this paper is to utilize the Hidden Markov Model (HMM) to elongate the service availability of WSNs by increasing the time it takes a node to become obsolete via optimal load balancing. We propose an HMM algorithm that, given a WSN, analyses and predicts undesirable situations, notably, nodes dying unexpectedly or prematurely. We apply this technique to improve on C. Lius’ algorithm, a scheduling-based algorithm which has served to improve the lifetime of WSNs. Our experiments show that our HMM technique improves the lifetime of the network, achieved by detecting nodes that die early and rebalancing their load. Our technique can also be used for diagnosis and provide maintenance warnings to WSN system administrators. Finally, our technique can be used to improve algorithms other than C. Liu’s.

Keywords: wireless sensor networks, IoT, dependability of safety WSNs, energy conservation, sleep awake schedule

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Authors: Mehran Dizbadi, Daniyal Safarzadeh, Behrooz Arastoo, Ansgar Brunn

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Rapid and uncontrolled expansion of cities has led to unplanned aerial development. In this way, modeling and predicting the urban growth of a city helps decision-makers. In this study, the aspect of sustainable urban development has been studied for the city of Mashhad. In general, the prediction of urban aerial development is one of the most important topics of modern town management. In this research, using the Cellular Automaton (CA) model developed for geo data of Geographic Information Systems (GIS) and presenting a simple and powerful model, a simulation of complex urban processes has been done.

Keywords: urban modeling, sustainable development, fuzzy cellular automaton, geo-information system

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Authors: Kavitha A.S., L.Govindaraju

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Reinforced earth walls offer excellent solution to many problems associated with earth retaining structures especially under seismic conditions. Use of cohesive soils as backfill material reduces the cost of reinforced soil walls if proper drainage measures are taken. This paper presents a numerical study on the application of a new technique called sandwich technique in reinforced earth walls. In this technique, a thin layer of granular soil is placed above and below the reinforcement layer to initiate interface friction and the remaining portion of the backfill is filled up using the existing insitu cohesive soil. A 6 m high reinforced earth wall has been analysed as a two-dimensional plane strain finite element model. Three types of reinforcing elements such as geotextile, geogrid and metallic strips were used. The horizontal wall displacements and the tensile loads in the reinforcement were used as the criteria to evaluate the results at the end of construction and dynamic excitation phases. Also to verify the effectiveness of sandwich layer on the performance of the wall, the thickness of sand fill surrounding the reinforcement was varied. At the end of construction stage it is found that the wall with sandwich type backfill yielded lower displacements when compared to the wall with cohesive soil as backfill. Also with sandwich backfill, the reinforcement loads reduced substantially when compared to the wall with cohesive soil as backfill. Further, it is found that sandwich technique as backfill and geogrid as reinforcement is a good combination to reduce the deformations of geosynthetic reinforced walls during seismic loading.

Keywords: geogrid, geotextile, reinforced earth, sandwich technique

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Authors: Debjani Chakraborty, Abhijit Chatterjee, Aishwaryaprajna

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Posynomials, a special type of polynomials, having singularities, pose difficulties while solving geometric programming problems. In this paper, a methodology has been proposed and used to obtain extreme values for geometric programming problems by nth degree polynomial interpolation technique. Here the main idea to optimise the posynomial is to fit a best polynomial which has continuous gradient values throughout the range of the function. The approximating polynomial is smoothened to remove the discontinuities present in the feasible region and the objective function. This spatial interpolation method is capable to optimise univariate and multivariate geometric programming problems. An example is solved to explain the robustness of the methodology by considering a bivariate nonlinear geometric programming problem. This method is also applicable for signomial programming problem.

Keywords: geometric programming problem, multivariate optimisation technique, posynomial, spatial interpolation

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Authors: Sayed M. Soleimani, Nader H. Ghareeb, Nourhan H. Shaker, Muhammad B. Siddiqui

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Honeycomb sandwich panels have been widely used as protective structural elements against blast loading. The main advantages of these panels include their light weight due to the presence of voids, as well as their energy absorption capability. Terrorist activities have imposed new challenges to structural engineers to design protective measures for vital structures. Since blast loading is not usually considered in the load combinations during the design process of a structure, researchers around the world have been motivated to study the behavior of potential elements capable of resisting sudden loads imposed by the detonation of explosive materials. One of the best candidates for this objective is the honeycomb sandwich panel. Studying the effects of explosive materials on the panels requires costly and time-consuming experiments. Moreover, these type of experiments need permission from defense organizations which can become a hurdle. As a result, modeling and simulation using an appropriate tool can be considered as a good alternative. In this research work, the finite element package ABAQUS® is used to study the behavior of hexagonal and squared honeycomb steel sandwich panels under the explosive effects of different amounts of trinitrotoluene (TNT). The results of finite element modeling of a specific honeycomb configuration are initially validated by comparing them with the experimental results from literature. Afterwards, several configurations including different geometrical properties of the honeycomb wall are investigated and the results are compared with the original model. Finally, the effectiveness of the core shape and wall thickness are discussed, and conclusions are made.

Keywords: Abaqus, blast loading, finite element modeling, steel honeycomb sandwich panel

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Authors: Sadam Elayah, Yang Li, Bing Shi

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Background: The impact of relaxing incisions on maxillofacial growth during palatoplasty remains a topic of debate, and further research is needed to understand its effects fully. Thus, the current study is the first long-term study that aimed to assess the maxillofacial growth of patients with isolated cleft palate following the Sommerlad-Furlow modified (S.F) technique and to estimate the impact of relaxing incisions on maxillofacial growth following S.F technique in patients with isolated cleft palate. Methods: A total of 85 participants, 55 patients with non-syndromic isolated soft and hard cleft palate underwent primary palatoplasty with our technique (30 patients received the Sommerlad-Furlow modified technique without relaxing incision (S.F+RI group), and 25 received Sommerlad-Furlow modified technique without relaxing (S.F-RI group) with no significant difference found between them regarding the cleft type, cleft width, and age at repair. While the other 30 were normal participants with skeletal class I pattern (C group). The control group was matched with the study group in number, age, and sex. All the study variables were measured using stable landmarks, including 12 linear and 10 angular variants. Results: The mean ages at collection of cephalograms were 6.03±0.80 in the S.F+RI group, 5.96±0.76 in the S.F-RI group, and 5.91±0.87 in the C group. Regarding cranial base, the results showed no statistically significant differences between the three groups in S-N and S-N-Ba. The S.F+R.I group had a significantly shorter S-Ba than the S.F-R.I & C groups (P= 0.01). However, there was no statistically significant difference between the S.F-R.I & C groups (P=0.80). Regarding the skeletal maxilla, there was no significant difference between the S.F+R.I and S.F-R.I groups in all linear measurements (N-ANS, S- PM & SN-PP ) except Co-A, the S.F+R.I group had significantly shorter Co-A than the S.F-R.I & C groups (P= <0.01). While the angular measurement, S.F+R.I group had significantly less SNA angle than the S.F-R.I & C groups (P= <0.01). Regarding mandibular bone, there were no statistically significant differences in all linear and angular mandibular measurements between the S.F+R.I and S.F-R.I groups. Regarding intermaxillary relation, the S.F+R.I group had significant differences in Co-Gn - Co-A and ANB compared to the S.F-R.I & C groups (P= <0.01). There was no statistically significant difference in PP-MP among the three groups. Conclusion: As a preliminary report, the Sommerlad-Furlow modified technique without relaxing incisions was found to have good maxillary positioning in the face and a satisfactory intermaxillary relationship compared to the Sommerlad-Furlow modified technique with relaxing incisions.

Keywords: relaxing incisions, cleft palate, palatoplasty, maxillofacial growth

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Authors: Hueiwang Anna Jeng, Norou Diawara, Nancy Welch, Cynthia Jackson, Rekha Singh, Kyle Curtis, Raul Gonzalez, David Jurgens, Sasanka Adikari

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Modeling effort is needed to predict the COVID-19 trends for developing management strategies and adaptation measures. The objective of this study was to assess whether SARS-CoV-2 viral load in wastewater could serve as a predictor for forecasting COVID-19 cases, hospitalization cases, and death cases using copula-based time series modeling. SARS-CoV-2 RNA load in raw wastewater in Chesapeake VA was measured using the RT-qPCR method. Gaussian copula time series marginal regression model, incorporating an autoregressive moving average model and the copula function, served as a forecasting model. COVID-19 cases were correlated with wastewater viral load, hospitalization cases, and death cases. The forecasted trend of COVID-19 cases closely paralleled one of the reported cases, with over 90% of the forecasted COVID-19 cases falling within the 99% confidence interval of the reported cases. Wastewater SARS-CoV-2 viral load could serve as a predictor for COVID-19 cases and hospitalization cases.

Keywords: COVID-19, modeling, time series, copula function

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Authors: Y. Ruchi, A. Prerna, S. Deepshikha

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Amyotrophic lateral sclerosis (ALS), also known as “Lou Gehrig’s disease”. It is a neurodegenerative disease associated with degeneration of motor neurons in the cerebral cortex, brain stem, and spinal cord characterized by distal muscle weakness, atrophy, normal sensation, pyramidal signs and progressive muscular paralysis reflecting. ALS2 is a juvenile autosomal recessive disorder, slowly progressive, that maps to chromosome 2q33 and is associated with mutations in the alsin gene, a putative GTPase regulator. In this paper we have done homology modeling of alsin2 protein using multiple templates (3KCI_A, 4LIM_A, 402W_A, 4D9S_A, and 4DNV_A) designed using the Prime program in Schrödinger software. Further modeled structure is used to identify effective binding sites on the basis of structural and physical properties using sitemap program in Schrödinger software, structural and function analysis is done by using Prosite and ExPASy server that gives insight into conserved domains and motifs that can be used for protein classification. This paper summarizes the structural, functional and binding site property of alsin2 protein. These binding sites can be potential drug target sites and can be used for docking studies.

Keywords: ALS, binding site, homology modeling, neuronal degeneration

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Authors: Haifa Saleh, Kamiran Abduka, Robin Kalfat, Riadh Al-Mahaidi

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The effectiveness of using pre-stressing steel bars for shear strengthening of high strength reinforced concrete (RC) slabs was assessed. Two large-scale RC slabs were tested, one without shear reinforcement and the second strengthened against punching shear failure using pre-stressing steel bars. The two slabs had the same dimensions, flexural reinforcement ratio, loading and support arrangements. The experimental program including the method of strengthening, set up and instrumentation are described in this paper. The experimental results are analyzed and discussed in terms of the structural behavior of the RC slabs, the performance of pre-stressing steel bolts and failure modes. The results confirmed that the shear strengthening technique increased the shear capacity, ductility and yield capacity of the slab by up to 15%, 44%, and 22%, respectively compared to the unstrengthened slab. The strengthening technique also successfully contributed to changing the failure mode from a brittle punching shear mode to ductile flexural failure mode. Vic3D digital image correlation system (photogrammetry) was also used in this research. This technique holds several advantages over traditional contact instrumentations including that it is inexpensive, it produces results that are simple to analyze and it is remote visualization technique. The displacement profile along the span of the slab and rotation has been found and compared with the results obtained from traditional sensors. The performance of the photogrammetry technique was very good and the results of both measurements were in very close agreement.

Keywords: flat slab, photogrammetry, punching shear, strengthening

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Authors: Ergun Kaya

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Apple mosaic virus (ApMV) is an ilarvirus causing harmful damages and product loses in many plant species. Because of xylem and phloem vessels absence, plant meristem tissues used for meristem cultures are virus-free, but sometimes only meristem cultures are not sufficient for virus elimination. Cryotherapy, a new method based on cryogenic techniques, is used for virus elimination. In this technique, 0.1-0.3mm meristems are excised from organized shoot apex of a selected in vitro donor plant and these meristems are frozen in liquid nitrogen (-196 °C) using suitable cryogenic technique. The aim of this work was to develop an efficient procedure for ApMV-free hazelnut via cryotherapy technique and confirmation of virus-free plants using Reverse Transcriptase-PCR technique. 100% virus free plantlets were obtained using droplet-vitrification method involved cold hardening in vitro cultures of hazelnut, 24 hours sucrose preculture of meristems on MS medium supplemented with 0.4M sucrose, and a 90 min PVS2 treatment in droplets.

Keywords: droplet vitrification, hazelnut, liquid nitrogen, PVS2

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Authors: Mohamed Haffar, Khalil Al-Hyari, Mohammed Khair Abu Zaid, Ramadane Djbarni, Mohammed Hamdan

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While employee readiness for change (ERFC) is recognised as critical for total quality management (TQM) implementation, there is a lack of systematic and empirical studies regarding the relationship between ERFC dimensions and TQM. Therefore, this study proposes to fill this gap by providing empirical evidence leading to advancement in the understanding of the influences of ERFC components on TQM implementation. The empirical data for this study was drawn from a survey of 400 middle and senior managers of Jordanian firms. The analysis of the collected data, which was conducted using Structural Equation Modeling technique, revealed that three of the ERFC components, namely personally beneficial, change self-efficacy and management support are the most supportive ERFC dimensions for TQM implementation. Therefore, this paper makes a novel contribution by providing a refined and deeper comprehension of the relationships between ERFCs and TQM implementation.

Keywords: total quality management, employee readiness for change, manufacturing organisations, Jordan

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Authors: Vassilios Moussas, Dimos N. Pantazis, Panagioths Stratakis

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The aim of this paper is to present the optimization methodology developed in the frame of a Coastal Transport Information System. The system will be used for the effective design of coastal transportation lines and incorporates subsystems that implement models, tools and techniques that may support the design of improved networks. The role of the optimization and decision subsystem is to provide the user with better and optimal scenarios that will best fulfill any constrains, goals or requirements posed. The complexity of the problem and the large number of parameters and objectives involved led to the adoption of an evolutionary method (Genetic Algorithms). The problem model and the subsystem structure are presented in detail, and, its support for simulation is also discussed.

Keywords: coastal transport, modeling, optimization

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Authors: M. Ziółkowska, J. T. Duda, J. Milewska-Duda

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This paper describes an approach to the adsorption phenomena modeling aimed at specifying the adsorption mechanisms on localized or nonlocalized adsorbent sites, when applied to the nanocarbons. The concept comes from the fundamental thermodynamic description of adsorption equilibrium and is based on numerical calculations of the hydrogen adsorbed particles volume on the surface of selected nanocarbons: single-walled nanotube and nanocone. This approach enables to obtain information on adsorption mechanism and then as a consequence to take appropriate mathematical adsorption model, thus allowing for a more reliable identification of the material porous structure. Theoretical basis of the approach is discussed and newly derived results of the numerical calculations are presented for the selected nanocarbons.

Keywords: adsorption, mathematical modeling, nanocarbons, numerical analysis

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Authors: Surinder Sood, Debajyoti Mukherjee

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Formal verification techniques have become widely popular in pre-silicon verification as an alternate to constrain random simulation based techniques. This paper proposed a novel formal verification-based coverage augmentation technique in verifying complex RTL functional verification faster. The proposed approach relies on augmenting coverage analysis coming from simulation and formal verification. Besides this, the functional qualification framework not only helps in improving the coverage at a faster pace but also aids in maturing and qualifying the formal verification infrastructure. The proposed technique has helped to achieve faster verification sign-off, resulting in faster time-to-market. The design picked had a complex control and data path and had many configurable options to meet multiple specification needs. The flow is generic, and tool independent, thereby leveraging across the projects and design will be much easier

Keywords: COI (cone of influence), coverage, formal verification, fault injection

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Authors: Arun Prabhakar

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Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

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Authors: F. Clara Fang, Hernan Castaneda

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The Connecticut Department of Transportation (ConnDOT) has constructed four roundabouts in the State of Connecticut within the past ten years. VISSIM traffic simulation software was utilized to analyze these roundabouts during their design phase. The queue length and level of service observed in the field appear to be better than predicted by the VISSIM model. The objectives of this project are to: identify VISSIM input variables most critical to accurate modeling; recommend VISSIM calibration factors; and, provide other recommendations for roundabout traffic operations modeling. Traffic data were collected at these roundabouts using Miovision Technologies. Cameras were set up to capture vehicle circulating activity and entry behavior for two weekdays. A large sample size of filed data was analyzed to achieve accurate and statistically significant results. The data extracted from the videos include: vehicle circulating speed; critical gap estimated by Maximum Likelihood Method; peak hour volume; follow-up headway; travel time; and, vehicle queue length. A VISSIM simulation of existing roundabouts was built to compare both queue length and travel time predicted from simulation with measured in the field. The research investigated a variety of simulation parameters as calibration factors for describing driver behaviors at roundabouts. Among them, critical gap is the most effective calibration variable in roundabout simulation. It has a significant impact to queue length, particularly when the volume is higher. The results will improve the design of future roundabouts in Connecticut and provide decision makers with insights on the relationship between various choices and future performance.

Keywords: driver critical gap, roundabout analysis, simulation, VISSIM modeling

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Authors: Hadi Ardiny, Amir Mohammad Beigzadeh

Abstract:

Through the utilization of a combination of various sensors and data fusion methods, the detection of potential nuclear threats can be significantly enhanced by extracting more information from different data. In this research, an experimental and modeling approach was employed to track a radioactive source by combining a surveillance camera and a radiation detector (NaI). To run this experiment, three mobile robots were utilized, with one of them equipped with a radioactive source. An algorithm was developed in identifying the contaminated robot through correlation between camera images and camera data. The computer vision method extracts the movements of all robots in the XY plane coordinate system, and the detector system records the gamma-ray count. The position of the robots and the corresponding count of the moving source were modeled using the MCNPX simulation code while considering the experimental geometry. The results demonstrated a high level of accuracy in finding and locating the target in both the simulation model and experimental measurement. The modeling techniques prove to be valuable in designing different scenarios and intelligent systems before initiating any experiments.

Keywords: nuclear threats, radiation detector, MCNPX simulation, modeling techniques, intelligent systems

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