Search results for: discrete filter

Authors: Justin-Herve Noubissi, Jean Claude Kamgang, Eric Ramat, Januarius Asongu, Christophe Cambier

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The goal of our study is to analyse the impact of climatic factors in malaria transmission taking into account migration between Douala and Yaoundé, two cities of Cameroon country. We show how variations of climatic factors such as temperature and relative humidity affect the malaria spread. We propose a meta-population model of the dynamic transmission of malaria that evolves in space and time and that takes into account temperature and relative humidity and the migration between Douala and Yaoundé. We also integrate the variation of environmental factors as events also called mathematical impulsion that can disrupt the model evolution at any time. Our modelling has been done using the Discrete EVents System Specification (DEVS) formalism. Our implementation has been done on Virtual Laboratory Environment (VLE) that uses DEVS formalism and abstract simulators for coupling models by integrating the concept of DEVS.

Keywords: compartmental models, DEVS, discrete events, meta-population model, VLE

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Authors: Thierno Diop, Michel Fortin, Jean Deteix

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Since the precise formulation of the elastic part is irrelevant for the description of the algorithm, we shall consider a generic case. In practice, however, we will have to deal with a non linear material (for instance a Mooney-Rivlin model). We are interested in solving a finite element approximation of the problem, leading to large-scale non linear discrete problems and, after linearization, to large linear systems and ultimately to calculations needing iterative methods. This also implies that penalty method, and therefore augmented Lagrangian method, are to be banned because of their negative effect on the condition number of the underlying discrete systems and thus on the convergence of iterative methods. This is in rupture to the mainstream of methods for contact in which augmented Lagrangian is the principal tool. We shall first present the problem and its discretization; this will lead us to describe a general solution algorithm relying on a preconditioner for saddle-point problems which we shall describe in some detail as it is not entirely standard. We will propose an iterative approach for solving three-dimensional frictional contact problems between elastic bodies, including contact with a rigid body, contact between two or more bodies and also self-contact.

Keywords: frictional contact, three-dimensional, large-scale, iterative method

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Authors: Abdalrahman D. Alsulaili, Sheikha Y. Aljeraiwi, Athba N. Almanaie, Raghad Y. Alhajeri, Mariam Z. Almijren

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The water accompanying oil in the oil production process is increasing and due to its increasing rates a problem with handling it occurred. Current solutions like discharging into the environment, dumping water in evaporation pits, usage in the industry and reinjection in oil reservoirs to enhance oil production are used worldwide. The water injection method has been introduced to the oil industry with a process that either immediately injects water to the reservoir or goes to the filtration process before injection all depending on the porosity of the soil. Reinjection of unfiltered effluent water with high Total Suspended Solid (TSS) and Oil in Water (O/W) into soils with low porosity cause a blockage of pores, whereas soils with high porosity do not need high water quality. Our study mainly talks about the filtration and adsorption of the water using organic media as the adsorbent. An adsorbent is a substance that has the ability to physically hold another substance in its surface. Studies were done on nutshell and date pits with different surface areas and flow rates by using a 10inch filter connected with three tanks to perform as one system for the filtration process. Our approach in the filtration process using different types of medias went as follow: starting first with crushed nutshell, second with ground nutshell, and third using carbonized date pits with medium flow rate then high flow rate to compare different results. The result came out nearly as expected from our study where both O/W and TSS were reduced from our oily water sample by using this organic material. The effect of specific area was noticed when using nutshell as the filter media, where the crushed nutshell gave us better results than ground nutshell. The effect of flow rate was noticed when using carbonized date pits as the filter media whereas the treated water became more acceptable when the flow rate was on the medium level.

Keywords: date pits, nutshell, oil water, TSS

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Authors: Theo Ndereyimana, Yann Dufresne, Micael Boulet, Stephane Moreau

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The DEM (Discrete Element Method) is used a lot in the industry to simulate large-scale flows of particles; for instance, in a fluidized bed, it allows to predict of the trajectory of every particle. One of the main limits of the DEM is the computational time. The CGM (Coarse-Graining Method) has been developed to tackle this issue. The goal is to increase the size of the particle and, by this means, decrease the number of particles. The method leads to a reduction of the collision frequency due to the reduction of the number of particles. Multiple characteristics of the particle movement and the fluid flow - when there is a coupling between DEM and CFD (Computational Fluid Dynamics). The main characteristic that is impacted is the energy dissipation of the system, to regain the dissipation, an ADM (Additional Dissipative Mechanism) can be added to the model. The objective of this current work is to observe the influence of the choice of the ADM and the factor of coarse-graining on the numerical results. These results will be compared with experimental results of a fluidized bed and with a numerical model of the same fluidized bed without using the CGM. The numerical model is one of a 3D cylindrical fluidized bed with 9.6M Geldart B-type particles in a bubbling regime.

Keywords: additive dissipative mechanism, coarse-graining, discrete element method, fluidized bed

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Anjali Uday, Yuting Wang, Andres Alfonso Pena Olare

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The Discrete Element Method is a promising approach to modeling microscopic behaviors of granular materials. The quality of the simulations however depends on the model parameters utilized. The present study focuses on calibration and validation of the discrete element parameters for Cuxhaven sand based on the experimental data from triaxial and oedometer tests. A sensitivity analysis was conducted during the sample preparation stage and the shear stage of the triaxial tests. The influence of parameters like rolling resistance, inter-particle friction coefficient, confining pressure and effective modulus were investigated on the void ratio of the sample generated. During the shear stage, the effect of parameters like inter-particle friction coefficient, effective modulus, rolling resistance friction coefficient and normal-to-shear stiffness ratio are examined. The calibration of the parameters is carried out such that the simulations reproduce the macro mechanical characteristics like dilation angle, peak stress, and stiffness. The above-mentioned calibrated parameters are then validated by simulating an oedometer test on the sand. The oedometer test results are in good agreement with experiments, which proves the suitability of the calibrated parameters. In the next step, the calibrated and validated model parameters are applied to forecast the micromechanical behavior including the evolution of contact force chains, buckling of columns of particles, observation of non-coaxiality, and sample inhomogeneity during a simple shear test. The evolution of contact force chains vividly shows the distribution, and alignment of strong contact forces. The changes in coordination number are in good agreement with the volumetric strain exhibited during the simple shear test. The vertical inhomogeneity of void ratios is documented throughout the shearing phase, which shows looser structures in the top and bottom layers. Buckling of columns is not observed due to the small rolling resistance coefficient adopted for simulations. The non-coaxiality of principal stress and strain rate is also well captured. Thus the micromechanical behaviors are well described using the calibrated and validated material parameters.

Keywords: discrete element model, parameter calibration, triaxial test, oedometer test, simple shear test

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Authors: Emad Alenany, M. Adel El-Baz

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In this paper, the flow of different classes of patients into a hospital is modelled and analyzed by using the queueing network analyzer (QNA) algorithm and discrete event simulation. Input data for QNA are the rate and variability parameters of the arrival and service times in addition to the number of servers in each facility. Patient flows mostly match real flow for a hospital in Egypt. Based on the analysis of the waiting times, two approaches are suggested for improving performance: Separating patients into service groups, and adopting different service policies for sequencing patients through hospital units. The separation of a specific group of patients, with higher performance target, to be served separately from the rest of patients requiring lower performance target, requires the same capacity while improves performance for the selected group of patients with higher target. Besides, it is shown that adopting the shortest processing time and shortest remaining processing time service policies among other tested policies would results in, respectively, 11.47% and 13.75% reduction in average waiting time relative to first come first served policy.

Keywords: queueing network, discrete-event simulation, health applications, SPT

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Authors: Nur Nadhirah Rusyda Rosnan, Nursuhaili Najwa Masrol, Nurul Fatiha MD Nor, Mohammad Zafrullah Mohammad Salim, Sim Choon Cheak

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Accurate inventories of oil palm planted areas are crucial for plantation management as this would impact the overall economy and production of oil. One of the technological advancements in the oil palm industry is semi-automated palm counting, which is replacing conventional manual palm counting via digitizing aerial imagery. Most of the semi-automated palm counting method that has been developed was limited to mature palms due to their ideal canopy size represented by satellite image. Therefore, immature palms were often left out since the size of the canopy is barely visible from satellite images. In this paper, an approach using a morphological filter and high-resolution satellite image is proposed to detect immature palm trees. This approach makes it possible to count the number of immature oil palm trees. The method begins with an erosion filter with an appropriate window size of 3m onto the high-resolution satellite image. The eroded image was further segmented using watershed segmentation to delineate immature palm tree regions. Then, local minimum detection was used because it is hypothesized that immature oil palm trees are located at the local minimum within an oil palm field setting in a grayscale image. The detection points generated from the local minimum are displaced to the center of the immature oil palm region and thinned. Only one detection point is left that represents a tree. The performance of the proposed method was evaluated on three subsets with slopes ranging from 0 to 20° and different planting designs, i.e., straight and terrace. The proposed method was able to achieve up to more than 90% accuracy when compared with the ground truth, with an overall F-measure score of up to 0.91.

Keywords: immature palm count, oil palm, precision agriculture, remote sensing

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Authors: Yuichi Kida, Takuro Kida

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In a new smart society supported by the recent development of 5G and 6G Communication systems, the im- portance of wireless power transmission is increasing. These systems contain discrete sampling systems in the middle of the transmission path and equivalent circuit representation of lossless or lossy power transmission through these systems is an important issue in circuit theory. In this paper, for the given weight function, we show that a lossless power transmission system with the given weight is expressed by an equivalent circuit representation of the Kida’s optimal signal prediction system followed by a reactance multi-port circuit behind it. Further, it is shown that, when the system is lossy, the system has an equivalent circuit in the form of connecting a multi-port positive-real circuit behind the Kida’s optimal signal prediction system. Also, for the convenience of the reader, in this paper, the equivalent circuit expression of the reactance multi-port circuit and the positive- real multi-port circuit by Cauer and Ohno, whose information is currently being lost even in the world of the Internet.

Keywords: signal prediction, pseudo inverse matrix, artificial intelligence, power transmission

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Authors: Saeed Sayyad Hagh Shomar

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Modeling users’ decisions on departure time choice is the main motivation for this research. In particular, it examines the impact of social-demographic features, household, job characteristics and trip qualities on individuals’ departure time choice. Departure time alternatives are presented as adjacent discrete time periods. The choice between these alternatives is done using a discrete choice model. Since a great deal of early morning trips and traffic congestion at that time of the day comprise work trips, the focus of this study is on the work trip over the entire day. Therefore, this study by using questionnaire of stated preference models users’ departure time choice affected by congestion pricing plan in downtown Tehran. Experimental results demonstrate efficient social-demographic impact on work trips’ departure time. These findings have substantial outcomes for the analysis of transportation planning. Particularly, the analysis shows that ignoring the effects of these variables could result in erroneous information and consequently decisions in the field of transportation planning and air quality would fail and cause financial resources loss.

Keywords: modeling, departure time, travel timing, time of the day, congestion pricing, transportation planning

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Authors: Eya Hentati, Mona Lamine, Jalel Bouzid

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In this study, a laboratory-scale was designed and fabricated to treat single house greywater in the north of Tunisia with a combination of physical and natural treatments systems. The combined system includes a bio-filter composed of LECA® (lightweight expanded clay aggregate) followed by a vertical up-flow constructed wetland planted with Iris pseudacorus and Typha Latifolia. Applied two hydraulic retention times (HRTs) with two different plants types showed that a bio-filter planted with Typha Latifolia has an optimum removal efficiency for degradation of organic matter and transformation of nitrogen and phosphate at HRT of 30 h. The optimum removal efficiency of biochemical oxygen demand (BOD), chemical oxygen demand (COD), and suspended solids (SS) ranged between 48-65%, between while the nutrients removal was in the range of 70% to 90%. Fecal coliforms dropped by three to four orders of magnitude from their initial concentration, but this steel does not meet current regulations for unlimited irrigation. Hence further improvement procedures are suggested.

Keywords: constructed wetland, greywater treatment, nutriments, organics

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Authors: Fu Jinyu, Lin Jinguan

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This paper introduces a novel approach that unifies two types of models: one is the continuous-time jump-diffusion used to model high-frequency data, and the other is discrete-time GQARCH employed to model low-frequency financial data by embedding the discrete GQARCH structure with jumps in the instantaneous volatility process. This model is named “GQARCH-It\^{o} -Jumps mode.” We adopt the realized range-based threshold estimation for high-frequency financial data rather than the realized return-based volatility estimators, which entail the loss of intra-day information of the price movement. Meanwhile, a quasi-likelihood function for the low-frequency GQARCH structure with jumps is developed for the parametric estimate. The asymptotic theories are mainly established for the proposed estimators in the case of finite activity jumps. Moreover, simulation studies are implemented to check the finite sample performance of the proposed methodology. Specifically, it is demonstrated that how our proposed approaches can be practically used on some financial data.

Keywords: It\^{o} process, GQARCH, leverage effects, threshold, realized range-based volatility estimator, quasi-maximum likelihood estimate

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Authors: Fisayo G. Ojo, Shamala K. Subramaniam, Zuriati Ahmad Zukarnain

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As technology is advancing and wireless applications are becoming dependable sources, while the physical layer of the applications are been embedded into tiny layer, so the more the problem on energy efficiency and consumption. This paper reviews works done in recent years in wireless applications and distributed computing, we discovered that applications are becoming dependable, and resource allocation sharing with other applications in distributed computing. Applications embedded in distributed system are suffering from power stability and efficiency. In the reviews, we also prove that discrete event simulation has been left behind untouched and not been adapted into distributed system as a simulation technique in scheduling of each event that took place in the development of distributed computing applications. We shed more lights on some researcher proposed techniques and results in our reviews to prove the unsatisfactory results, and to show that more work still have to be done on issues of energy efficiency in wireless applications, and congestion in distributed computing.

Keywords: discrete event simulation (DES), distributed computing, energy efficiency (EE), internet of things (IOT), quality of service (QOS), user equipment (UE), wireless mesh network (WMN), wireless sensor network (wsn), worldwide interoperability for microwave access x (WiMAX)

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Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Abdelaziz Fellah, Allaoua Maamir

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We propose a domain-independent merging-cluster filter approach complemented with a set of algorithms for identifying approximate duplicate entities efficiently and accurately within a single and across multiple data sources. The near-optimal merging-cluster filter (MCF) approach is based on the Monge-Elkan well-tuned algorithm and extended with an affine variant of the Smith-Waterman similarity measure. Then we present constant, variable, and function threshold algorithms that work conceptually in a divide-merge filtering fashion for detecting near duplicates as hierarchical clusters along with their corresponding representatives. The algorithms take recursive refinement approaches in the spirit of filtering, merging, and updating, cluster representatives to detect approximate duplicates at each level of the cluster tree. Experiments show a high effectiveness and accuracy of the MCF approach in detecting approximate duplicates by outperforming the seminal Monge-Elkan’s algorithm on several real-world benchmarks and generated datasets.

Keywords: data mining, data cleaning, approximate duplicates, near-duplicates detection, data mining applications and discovery

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Authors: L. Angiuli, L. Trizio, R. Giua, A. Digilio, M. Tutino, P. Dambruoso, F. Mazzone, C. M. Placentino

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In the winter of 2014 a series of measurements were performed to evaluate the behavior of real-time PAHs and black carbon analyzers in a coke oven plant located in Taranto, a city of Southern Italy. Data were collected both insides than outside the plant, at air quality monitoring sites. Contemporary measures of PM2.5 and PM1 were performed. Particle-bound PAHs were measured by two methods: (1) aerosol photoionization using an Ecochem PAS 2000 analyzer, (2) PM2.5 and PM1 quartz filter collection and analysis by gas chromatography/mass spectrometry (GC/MS). Black carbon was determined both in real-time by Magee Aethalometer AE22 analyzer than by semi-continuous Sunset Lab EC/OC instrument. Detected PM2.5 and PM1 levels were higher inside than outside the plant while PAHs real-time values were higher outside than inside. As regards PAHs, inside the plant Ecochem PAS 2000 revealed concentrations not significantly different from those determined on the filter during low polluted days, but at increasing concentrations the automated instrument underestimated PAHs levels. At the external site, Ecochem PAS 2000 real-time concentrations were steadily higher than those on the filter. In the same way, real-time black carbon values were constantly lower than EC concentrations obtained by Sunset EC/OC in the inner site, while outside the plant real-time values were comparable to Sunset EC values. Results showed that in a coke plant real-time analyzers of PAHs and black carbon in the factory configuration provide qualitative information, with no accuracy and leading to the underestimation of the concentration. A site specific calibration is needed for these instruments before their installation in high polluted sites.

Keywords: black carbon, coke oven plant, PAH, PAS, aethalometer

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Authors: S. Abeysekera, M. Bazghaleh, M. P. L. Ooi, Y. C. Kuang, V. Kalavally

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Smart LED-based lighting systems have significant advantages over traditional lighting systems due to their capability of producing tunable light spectrums on demand. The main challenge in the design of smart lighting systems is to produce sufficient luminous flux and uniformly accurate output spectrum for sufficiently broad area. This paper outlines the programmable LED lighting system design principles of design to achieve the two aims. In this paper, a seven-channel design using low-cost discrete LEDs is presented. Optimization algorithms are used to calculate the number of required LEDs, LEDs arrangements and optimum LED separation distance. The results show the illumination uniformity for each channel. The results also show that the maximum color error is below 0.0808 on the CIE1976 chromaticity scale. In conclusion, this paper considered the simulation and design of a seven-channel programmable lighting system using low-cost discrete LEDs to produce sufficient luminous flux and uniformly accurate output spectrum for sufficiently broad area.

Keywords: light spectrum control, LEDs, smart lighting, programmable LED lighting system

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Authors: Galo D. Soria, Jenny S. Casame, Eddy F. Pazmino

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In Ecuador, mining operations have significantly impacted water sources. Artisanal mining extensively relies in mercury amalgamation. Mercury is a neurotoxic substance even at low concentrations. The objective of this investigation is to exploit Hg-removal capacity of sulfur-limonene polysulfide (SLP), which is a low-cost polymer, in order to prepare granular media (sand) coated with SLP to be used in laboratory scale column-filtration systems. Preliminary results achieved 85% removal of Hg⁺⁺ from synthetic effluents using 20-cm length and 5-cm diameter columns at 119m/day average pore water velocity. During elution of the column, the SLP-coated sand indicated that Hg⁺⁺ is permanently fixed to the collector surface, in contrast, uncoated sand showed reversible retention in Hg⁺⁺ in the solid phase. Injection of 50 pore volumes decreased Hg⁺⁺ removal to 46%. Ongoing work has been focused in optimizing the synthesis of SLP and the polymer content in the porous media coating process to improve Hg⁺⁺ removal and extend the lifetime of the column-filter.

Keywords: column-filter, mercury, mining, polysulfide, water treatment

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Authors: Mohammad Ranjbar, Mohammad Bazyar, Blake Angell, Thomas Lung, Yibeltal Assefa

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Background: Current health insurance programs in Iran suffer from low enrolment and are not sufficient to attain the country to universal health coverage (UHC). We hypothesize that improving the enrollment rate and moving towards a more sustainable UHC can be achieved by improving the benefits package and providing new incentives. The objective of this study is to assess public preferences and willingness to pay (WTP) for social health insurance (SHI) in Iran. Methods: A discrete choice experiment (DCE) was conducted in 2021, using a self-administered questionnaire on 500 participants to estimate WTP and determine individual preferences for the SHI in Yazd, Iran. Respondents were presented with an eight-choice set and asked to select their preferred one. In each choice set, scenarios were described by eight attributes with varying levels. The conditional logit regression model was used to analyze the participants' preferences. Willingness to pay for each attribute was also calculated. Results: Most included attributes were significant predictors of the choice of a health insurance package. The maximum coverage of hospitalization costs in the private sector, ancillary services such as glasses, canes, etc., as well as coverage for hospitalization costs in the public sector and drug costs, were the most important determining factors for this choice. Coverage of preventive dental care did not significantly influence respondent choices. Estimating WTP showed that individuals are willing to pay more for higher financial protection, particularly against private sector costs; the WTP to increase the coverage of hospitalization costs in the private sector from 50% to 90% is estimated at 362,068 IR, Rials per month. Conclusion: This study identifies the key factors that the population value with regard to health insurance and the tradeoffs they are willing to make between them. Hospitalization, drugs, and ancillary services were the most important determining factors for their choice. The data suggest that additional resources coming into the Iranian health system might best be prioritized to cover hospitalization and drug costs and those associated with ancillary services.

Keywords: social health insurance, preferences, discrete choice experiment, willingness to pay

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Authors: Adewole A. Ayoade, Marshall R. Sweatt, John P. H. Steele, Qi Han, Khaled Al-Wahedi, Hamad Karki, William A. Yearsley

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Understanding the behavioral characteristics of sensors is a crucial step in fusing data from several sensors of different types. This paper introduces a practical, real-time approach to integrate heterogeneous sensor data to achieve higher accuracy than would be possible from any one individual sensor in localizing a mobile robot. We use this approach in both indoor and outdoor environments and it is especially appropriate for those environments like oil and gas refineries due to their sparse and featureless nature. We have studied the individual contribution of each sensor data to the overall combined accuracy achieved from the fusion process. A Sequential Update Extended Kalman Filter(EKF) using validation gates was used to integrate GPS data, Compass data, WiFi data, Inertial Measurement Unit(IMU) data, Vehicle Velocity, and pose estimates from Fiducial marker system. Results show that the approach can enable a mobile robot to navigate autonomously in any environment using a priori information.

Keywords: inspection mobile robot, navigation, sensor fusion, sequential update extended Kalman filter

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Authors: Zhang Tianci, Ding Meng, Zuo Hongfu, Zeng Lina, Sun Zejun

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Automation of airport operations can greatly improve ground movement efficiency. In this paper, we study the speed profile design problem for advanced airport ground movement control and guidance. The problem is constrained by the surface four-dimensional trajectory generated in taxi planning. A decomposed approach of two stages is presented to solve this problem efficiently. In the first stage, speeds are allocated at control points which ensure smooth speed profiles can be found later. In the second stage, detailed speed profiles of each taxi interval are generated according to the allocated control point speeds with the objective of minimizing the overall fuel consumption. We present a swarm intelligence based algorithm for the first-stage problem and a discrete variable driven enumeration method for the second-stage problem since it only has a small set of discrete variables. Experimental results demonstrate the presented methodology performs well on real world speed profile design problems.

Keywords: airport ground movement, fuel consumption, particle swarm optimization, smoothness, speed profile design

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Authors: Karitikeya Sonker

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Religion as a discrete system through its lawful internal working produces an output in the form of realised spatial order with its social logic and a social order with its spatial logic. Thus, it appears to exhibit its duality of spatial and trans-spatial. The components of this system share a relevance forming a collective. This shared relevance creates meaning forming a group where all collectives share one identity. This group with its new social order and its spatial logic revive the already existing spatial order. These religious groups do so having a tendency to expand resulting in the production of space in a situation of encounter where they have found relevance. But an encounter without a lawful internal working of a discrete system results in anomaly because groups do not find relevance due to the absence of collective identity. Events happen all around. One of the main reasons we could say that something became an event is because of conflict. Conflict not in its definitive sense but any occurrence that happens because of an intervention that creates an event worth remembering. The unfolding of such events creates Cities and Urban spaces which exhibit their duality of spatial and trans-spatial by behaving as a discrete system. This system through its lawful internal working produces an output in the form of realized spatial order with its social logic and a social order with spatial logic. The components of this system form a collective through a shared a relevance. This shared relevance creates meaning forming a group where all collectives share one identity. This group with its new social order and its spatial logic revives the already existing spatial order. These groups do so having a tendency to expand resulting in the production of space in a situation of encounter where they have found relevance. But an encounter without a lawful internal working of the discrete system results in anomaly because groups do not find relevance due to the absence of collective identity. This paper makes an effort to explore one such even in the case of Babri Mosque and Ramjanmabhumi, Ayodhya to explain the anomaly as transposition of social and spatial. The paper through the case studies makes an attempt to generate an equation explaining the two different situations of religious encounters, former reviving the social and spatial order and the other resulting in anomaly. Through the case study, it makes an attempt to generate an equation explaining the two different situations of religious encounters, former reviving the social and spatial order and the other resulting in anomaly.

Keywords: Babri Masjid, Ayodhya, conflict, religion

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Authors: Yonathan Audhitya Suthihono, Ratih Dyah Kusumastuti

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The radiology department in a tertiary referral hospital faces service operation challenges such as huge and various patient arrival, which can increase the probability of patient queuing. During the COVID-19 pandemic, it is mandatory to apply social distancing protocol in the radiology department. A strategy to prevent the accumulation of patients at one spot would be required. The aim of this study is to identify an alternative solution which can reduce the patient’s waiting time in radiology department. Discrete event simulation (DES) is used for this study by constructing several improvement scenarios with Arena simulation software. Statistical analysis is used to test the validity of the base case scenario model and to investigate the performance of the improvement scenarios. The result of this study shows that the selected scenario is able to reduce patient waiting time significantly, which leads to more efficient services in a radiology department, be able to serve patients more effectively, and thus increase patient satisfaction. The result of the simulation can be used by the hospital management to improve the operational performance of the radiology department.

Keywords: discrete event simulation, hospital management patient queuing model, radiology department services

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Authors: Pogula Rakesh, T. Kishore Kumar

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Speech enhancement is a long standing problem with numerous applications like teleconferencing, VoIP, hearing aids, and speech recognition. The motivation behind this research work is to obtain a clean speech signal of higher quality by applying the optimal noise cancellation technique. Real-time adaptive filtering algorithms seem to be the best candidate among all categories of the speech enhancement methods. In this paper, we propose a speech enhancement method based on Recursive Least Squares (RLS) adaptive filter of speech signals. Experiments were performed on noisy data which was prepared by adding AWGN, Babble and Pink noise to clean speech samples at -5dB, 0dB, 5dB, and 10dB SNR levels. We then compare the noise cancellation performance of proposed RLS algorithm with existing NLMS algorithm in terms of Mean Squared Error (MSE), Signal to Noise ratio (SNR), and SNR loss. Based on the performance evaluation, the proposed RLS algorithm was found to be a better optimal noise cancellation technique for speech signals.

Keywords: adaptive filter, adaptive noise canceller, mean squared error, noise reduction, NLMS, RLS, SNR, SNR loss

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Authors: Sayed Hessam Bahmani, Rolsndo P. Orense

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From an engineering point of view, pumice particles are problematic because of their crushability and compressibility due to their vesicular nature. Currently, information on the geotechnical characteristics of pumice sands is limited. While extensive empirical and laboratory tests can be implemented to characterize their behavior, these are generally time-consuming and expensive. These drawbacks have motivated attempts to study the effects of particle breakage of pumice sand through the Discrete Element Method (DEM). This method provides insights into the behavior of crushable granular material at both the micro and macro-level. In this paper, the results of single-particle crushing tests conducted in the laboratory are simulated using DEM through the open-source code YADE. This is done to better understand the parameters necessary to represent the pumice microstructure that governs its crushing features, and to examine how the resulting microstructure evolution affects a particle’s properties. The DEM particle model is then used to simulate the behavior of pumice sand during consolidated drained triaxial tests. The results indicate the importance of incorporating particle porosity and unique surface textures in the material characterization and show that interlocking between the crushed particles significantly influences the drained behavior of the pumice specimen.

Keywords: pumice sand, triaxial compression, simulation, particle breakage

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Authors: Jayotpaul Chaudhuri, Lutz Goedeke, Torsten Hallenga, Peter Ehrhard

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Purification of gases from aerosols or airborne particles via filters is widely applied in the industry and in our daily lives. This separation especially in the micron and submicron size range is a necessary step to protect the environment and human health. Fibrous filters are often employed due to their low cost and high efficiency. For designing any filter the two most important performance parameters are capture efficiency and pressure drop. Since the capture efficiency is directly proportional to the pressure drop which leads to higher operating costs, a detailed investigation of the separation mechanism is required to optimize the filter designing, i.e., to have a high capture efficiency with a lower pressure drop. Therefore a two-dimensional flow simulation around a single fiber using Ansys CFX and Matlab is used to get insight into the separation process. Instead of simulating a solid fiber, the present Ansys CFX model uses a fictitious domain approach for the fiber by implementing a momentum loss model. This approach has been chosen to avoid creating a new mesh for different fiber sizes, thereby saving time and effort for re-meshing. In a first step, only the flow of the continuous fluid around the fiber is simulated in Ansys CFX and the flow field data is extracted and imported into Matlab and the particle trajectory is calculated in a Matlab routine. This calculation is a Lagrangian, one way coupled approach for particles with all relevant forces acting on it. The key parameters for the simulation in both Ansys CFX and Matlab are the porosity ε, the diameter ratio of particle and fiber D, the fluid Reynolds number Re, the Reynolds particle number Rep, the Stokes number St, the Froude number Fr and the density ratio of fluid and particle ρf/ρp. The simulation results were then compared to the single fiber theory from the literature.

Keywords: BBO-equation, capture efficiency, CFX, Matlab, fibrous filter, particle trajectory

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Authors: Leonard Maaya, Michel Meulders, Martina Vandebroek

Abstract:

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: Insaf Ajili, Malik Mallem, Jean-Yves Didier

Abstract:

Human motion recognition has been extensively increased in recent years due to its importance in a wide range of applications, such as human-computer interaction, intelligent surveillance, augmented reality, content-based video compression and retrieval, etc. However, it is still regarded as a challenging task especially in realistic scenarios. It can be seen as a general machine learning problem which requires an effective human motion representation and an efficient learning method. In this work, we introduce a descriptor based on Laban Movement Analysis technique, a formal and universal language for human movement, to capture both quantitative and qualitative aspects of movement. We use Discrete Hidden Markov Model (DHMM) for training and classification motions. We improve the classification algorithm by proposing two DHMMs for each motion class to process the motion sequence in two different directions, forward and backward. Such modification allows avoiding the misclassification that can happen when recognizing similar motions. Two experiments are conducted. In the first one, we evaluate our method on a public dataset, the Microsoft Research Cambridge-12 Kinect gesture data set (MSRC-12) which is a widely used dataset for evaluating action/gesture recognition methods. In the second experiment, we build a dataset composed of 10 gestures(Introduce yourself, waving, Dance, move, turn left, turn right, stop, sit down, increase velocity, decrease velocity) performed by 20 persons. The evaluation of the system includes testing the efficiency of our descriptor vector based on LMA with basic DHMM method and comparing the recognition results of the modified DHMM with the original one. Experiment results demonstrate that our method outperforms most of existing methods that used the MSRC-12 dataset, and a near perfect classification rate in our dataset.

Keywords: human motion recognition, motion representation, Laban Movement Analysis, Discrete Hidden Markov Model

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Authors: Mohammed Cherifi, Abderrahmane Benbrik, Siham Laouar-Meftah, Denis Lemonnier

Abstract:

The present study was conducted to numerically investigate the interaction of non-gray-gas radiation with opposed mixed convection in a vertical two-sided lid-driven square cavity. The opposing flows are simultaneously generated by the vertical boundary walls which slide at a constant speed and the natural convection due to the gradient temperature of differentially heated cavity. The horizontal walls are thermally insulated and perfectly reflective. The enclosure is filled with air-H2O-CO2 gas mixture, which is considered as a non-gray, absorbing, emitting and not scattering medium. The governing differential equations are solved by a finite-volume method, by adopting the SIMPLER algorithm for pressure–velocity coupling. The radiative transfer equation (RTE) is solved by the discrete ordinates method (DOM). The spectral line weighted sum of gray gases model (SLW) is used to account for non-gray radiation properties. Three cases of the effects of radiation (transparent, gray and non-gray medium) are studied. Comparison is also made with the parametric studies of the effect of the mixed convection parameter, Ri (0.1, 1, 10), on the fluid flow and heat transfer have been performed.

Keywords: opposed mixed convection, non-gray-gas radiation, two-sided lid-driven cavity, discrete ordinate method, SLW model

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Authors: Hooman Dabirmanesh, Attila M. Zsaki

Abstract:

Traditionally, rock slope stability is carried out using limit equilibrium analysis when investigating toppling failure. In these equilibrium methods, internal forces exerted between columns are not clearly defined, and to the authors’ best knowledge, there is no consensus in literature with respect to the results of analysis. A discrete element method-based numerical model was developed and applied to simulate the behavior of rock layers subjected to toppling failure. Based on this calibrated numerical model, a study of the location and distribution of internal forces that result in equilibrium was carried out. The sum of side forces was applied at a point on a block which properly represents the force to determine the inter-column force distribution. In terms of the side force distribution coefficient, the result was compared to those obtained from laboratory centrifuge tests. The results of the simulation show the suitable criteria to select the correct position for the internal exerted force between rock layers. In addition, the numerical method demonstrates how a theoretical method could be reliable by considering the interaction between the rock layers.

Keywords: contact bond, discrete element, force distribution, limit equilibrium, tensile stress

Procedia PDF Downloads 122