Search results for: step shoulder milling

Authors: Nicolò Vaiana, Giorgio Serino

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In this paper, a one-dimensional (1d) Parallel Elasto- Plastic Model (PEPM), able to simulate the uniaxial dynamic behavior of seismic isolators having a continuously decreasing tangent stiffness with increasing displacement, is presented. The parallel modeling concept is applied to discretize the continuously decreasing tangent stiffness function, thus allowing to simulate the dynamic behavior of seismic isolation bearings by putting linear elastic and nonlinear elastic-perfectly plastic elements in parallel. The mathematical model has been validated by comparing the experimental force-displacement hysteresis loops, obtained testing a helical wire rope isolator and a recycled rubber-fiber reinforced bearing, with those predicted numerically. Good agreement between the simulated and experimental results shows that the proposed model can be an effective numerical tool to predict the forcedisplacement relationship of seismic isolators within relatively large displacements. Compared to the widely used Bouc-Wen model, the proposed one allows to avoid the numerical solution of a first order ordinary nonlinear differential equation for each time step of a nonlinear time history analysis, thus reducing the computation effort, and requires the evaluation of only three model parameters from experimental tests, namely the initial tangent stiffness, the asymptotic tangent stiffness, and a parameter defining the transition from the initial to the asymptotic tangent stiffness.

Keywords: Base isolation, earthquake engineering, parallel elasto-plastic model, seismic isolators, softening hysteresis loops.

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Authors: Ahmed Rekik, Mourad Zribi, Ahmed Ben Hamida, Mohamed Benjelloun

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This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the use of different approaches, especially those founded on the unsupervised statistical segmentation principle. Such approaches necessitate definition of several parameters like image class number, class variables- estimation and generalised mixture distributions. Use of statistical images- attributes assured convincing and promoting results under the condition of having an optimal initialisation step with appropriated statistical distributions- affectation. Pearson system associated with a k-means clustering algorithm and Stochastic Expectation-Maximization 'SEM' algorithm could be adapted to such problem. For each image-s class, Pearson system attributes one distribution type according to different parameters and especially the Skewness 'β1' and the kurtosis 'β2'. The different adapted algorithms, K-Means clustering algorithm, SEM algorithm and Pearson system algorithm, are then applied to satellite image segmentation problem. Efficiency of those combined algorithms was firstly validated with the Mean Quadratic Error 'MQE' evaluation, and secondly with visual inspection along several comparisons of these unsupervised images- segmentation.

Keywords: Unsupervised classification, Pearson system, Satellite image, Segmentation.

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Authors: Michael Zenker, Henrik Prinzhorn, Christian Böning, Tom Strating

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Large-scale products are often assembled according to the job-site principle, meaning that during the assembly the product is located at a fixed position, while the area requirements are constantly changing. On one hand, the product itself is growing with each assembly step, whereas varying areas for storage, machines or working areas are temporarily required. This is an important factor when arranging products to be assembled within the factory. Currently, it is common to reserve a fixed area for each product to avoid overlaps or collisions with the other assemblies. Intending to be large enough to include the product and all adjacent areas, this reserved area corresponds to the superposition of the maximum extents of all required areas of the product. In this procedure, the reserved area is usually poorly utilized over the course of the entire assembly process; instead a large part of it remains unused. If the available area is a limited resource, a systematic arrangement of the products, which complies with the dynamic area requirements, will lead to an increased area utilization and productivity. This paper presents the results of a study on the arrangement of assembly objects assuming dynamic, competing area requirements. First, the problem situation is extensively explained, and existing research on associated topics is described and evaluated on the possibility of an adaptation. Then, a newly developed mathematical optimization model is introduced. This model allows an optimal arrangement of dynamic areas, considering logical and practical constraints. Finally, in order to quantify the potential of the developed method, some test series results are presented, showing the possible increase in area utilization.

Keywords: Dynamic area requirements, facility layout problem, optimization model, product assembly.

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Authors: Farhad Asadi, S. Hossein Sadati

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This paper presents a prediction performance of feedforward Multilayer Perceptron (MLP) and Echo State Networks (ESN) trained with extended Kalman filter. Feedforward neural networks and ESN are powerful neural networks which can track and predict nonlinear signals. However, their tracking performance depends on the specific signals or data sets, having the risk of instability accompanied by large error. In this study we explore this process by applying different network size and leaking rate for prediction of nonlinear or chaotic signals in MLP neural networks. Major problems of ESN training such as the problem of initialization of the network and improvement in the prediction performance are tackled. The influence of coefficient of activation function in the hidden layer and other key parameters are investigated by simulation results. Extended Kalman filter is employed in order to improve the sequential and regulation learning rate of the feedforward neural networks. This training approach has vital features in the training of the network when signals have chaotic or non-stationary sequential pattern. Minimization of the variance in each step of the computation and hence smoothing of tracking were obtained by examining the results, indicating satisfactory tracking characteristics for certain conditions. In addition, simulation results confirmed satisfactory performance of both of the two neural networks with modified parameterization in tracking of the nonlinear signals.

Keywords: Feedforward neural networks, nonlinear signal prediction, echo state neural networks approach, leaking rates, capacity of neural networks.

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Authors: Jafar Ahmadi, Zhohreh Asiaban, Sedigheh Fabriki Ourang

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Brassinosteroids (BRs) regulate cell elongation, vascular differentiation, senescence, and stress responses. BRs signal through the BES1/BZR1 family of transcription factors, which regulate hundreds of target genes involved in this pathway. In this research a comprehensive genome-wide analysis was carried out in BES1/BZR1 gene family in Arabidopsis thaliana, Cucumis sativus, Vitis vinifera, Glycin max and Brachypodium distachyon. Specifications of the desired sequences, dot plot and hydropathy plot were analyzed in the protein and genome sequences of five plant species. The maximum amino acid length was attributed to protein sequence Brdic3g with 374aa and the minimum amino acid length was attributed to protein sequence Gm7g with 163aa. The maximum Instability index was attributed to protein sequence AT1G19350 equal with 79.99 and the minimum Instability index was attributed to protein sequence Gm5g equal with 33.22. Aliphatic index of these protein sequences ranged from 47.82 to 78.79 in Arabidopsis thaliana, 49.91 to 57.50 in Vitis vinifera, 55.09 to 82.43 in Glycin max, 54.09 to 54.28 in Brachypodium distachyon 55.36 to 56.83 in Cucumis sativus. Overall, data obtained from our investigation contributes a better understanding of the complexity of the BES1/BZR1 gene family and provides the first step towards directing future experimental designs to perform systematic analysis of the functions of the BES1/BZR1 gene family.

Keywords: BES1/BZR1, Brassinosteroids, Phylogenetic analysis, Transcription factor.

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Authors: Mehrnoosh Omati, Mahmod Reza Sahebi

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The information on land use/land cover changing plays an essential role for environmental assessment, planning and management in regional development. Remotely sensed imagery is widely used for providing information in many change detection applications. Polarimetric Synthetic aperture radar (PolSAR) image, with the discrimination capability between different scattering mechanisms, is a powerful tool for environmental monitoring applications. This paper proposes a new boundary-based segmentation algorithm as a fundamental step for land cover change detection. In this method, first, two PolSAR images are segmented using integration of marker-controlled watershed algorithm and coupled Markov random field (MRF). Then, object-based classification is performed to determine changed/no changed image objects. Compared with pixel-based support vector machine (SVM) classifier, this novel segmentation algorithm significantly reduces the speckle effect in PolSAR images and improves the accuracy of binary classification in object-based level. The experimental results on Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) polarimetric images show a 3% and 6% improvement in overall accuracy and kappa coefficient, respectively. Also, the proposed method can correctly distinguish homogeneous image parcels.

Keywords: Coupled Markov random field, environment, object-based analysis, Polarimetric SAR images.

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Authors: Buket Metin

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Buildings cause a variety of loads on the environment due to activities performed at each stage of the building life cycle. Construction is the first stage that affects both the natural and built environments at different steps of the process, which can be defined as transportation of materials within the construction site, formation and preparation of materials on-site and the application of materials to realize the building subsystems. All of these steps require the use of technology, which varies based on the facilities that contractors and subcontractors have. Hence, environmental consequences of the construction process should be tackled by focusing on construction technology options used in every step of the process. This paper presents an environmental decision-making model for assessing on-site performances of subcontractors based on the construction technology options which they can supply. First, construction technologies, which constitute information, tools and methods, are classified. Then, environmental performance criteria are set forth related to resource consumption, ecosystem quality, and human health issues. Finally, the model is developed based on the relationships between the construction technology components and the environmental performance criteria. The Fuzzy Analytical Hierarchy Process (FAHP) method is used for weighting the environmental performance criteria according to environmental priorities of decision-maker(s), while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used for ranking on-site environmental performances of subcontractors using quantitative data related to the construction technology components. Thus, the model aims to provide an insight to decision-maker(s) about the environmental consequences of the construction process and to provide an opportunity to improve the overall environmental performance of construction sites.

Keywords: Construction process, construction technology, decision making, environmental performance, subcontractors.

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Authors: Alireza Mortezaei, Kimia Mortezaei

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Recordings from recent earthquakes have provided evidence that ground motions in the near field of a rupturing fault differ from ordinary ground motions, as they can contain a large energy, or “directivity" pulse. This pulse can cause considerable damage during an earthquake, especially to structures with natural periods close to those of the pulse. Failures of modern engineered structures observed within the near-fault region in recent earthquakes have revealed the vulnerability of existing RC buildings against pulse-type ground motions. This may be due to the fact that these modern structures had been designed primarily using the design spectra of available standards, which have been developed using stochastic processes with relatively long duration that characterizes more distant ground motions. Many recently designed and constructed buildings may therefore require strengthening in order to perform well when subjected to near-fault ground motions. Fiber Reinforced Polymers are considered to be a viable alternative, due to their relatively easy and quick installation, low life cycle costs and zero maintenance requirements. The objective of this paper is to investigate the adequacy of Artificial Neural Networks (ANN) to determine the three dimensional dynamic response of FRP strengthened RC buildings under the near-fault ground motions. For this purpose, one ANN model is proposed to estimate the base shear force, base bending moments and roof displacement of buildings in two directions. A training set of 168 and a validation set of 21 buildings are produced from FEA analysis results of the dynamic response of RC buildings under the near-fault earthquakes. It is demonstrated that the neural network based approach is highly successful in determining the response.

Keywords: Seismic evaluation, FRP, neural network, near-fault ground motion

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Authors: Seyyed Abbas Mojtabavi, Mojtaba Fatzaneh Moghadam, Masoud Mahdavi

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Steel Metal Shear Wall is one of the most common and widely used energy dissipation systems in structures, which is used today as a damping system due to the increase in the construction of metal structures. In the present study, the shear wall of the steel plate with dimensions of 5×3 m and thickness of 0.024 m was modeled with 2 floors of total height from the base level with finite element method in Abaqus software. The loading is done as a concentrated load at the upper point of the shear wall on the second floor based on step type buckle. The mesh in the model is applied in two directions of length and width of the shear wall, equal to 0.02 and 0.033, respectively, and the mesh in the models is of sweep type. Finally, it was found that the steel plate shear wall with cavity (CSPSW) compared to the SPSW model, S (Mises), Smax (In-Plane Principal), Smax (In-Plane Principal-ABS), Smax (Min Principal) increased by 53%, 70%, 68% and 43%, respectively. The presence of cavities has led to an increase in the estimated stresses, but their presence has caused critical stresses and critical deformations created to be removed from the inner surface of the shear wall and transferred to the desired sections (regular cavities) which can be suggested as a solution in seismic design and improvement of the structure to transfer possible damage during the earthquake and storm to the desired and pre-designed location in the structure.

Keywords: Steel plate shear wall, Abacus software, finite element method, boundary element, seismic structural improvement, Von misses Stress.

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Authors: Kréhi Serge Agbli, Samuel Portebos, Michaël Salomon

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Here a methodology is considered aiming at evaluating the economic benefit of the provision of a primary frequency control unit using a Battery Energy Storage System (BESS). In this methodology, two control types (basic and hysteresis) are implemented and the corresponding minimum energy storage system power allowing to maintain the frequency drop inside a given threshold under a given contingency is identified and compared using DigSilent’s PowerFactory software. Following this step, the corresponding energy storage capacity (in MWh) is calculated. As PowerFactory is dedicated to dynamic simulation for transient analysis, a first order model related to the IEEE 9 bus grid used for the analysis under PowerFactory is characterized and implemented on MATLAB-Simulink. Primary frequency control is simulated using the two control types over one-month grid's frequency deviation data on this Simulink model. This simulation results in the energy throughput both basic and hysteresis BESSs. It emerges that the 15 minutes operation band of the battery capacity allocated to frequency control is sufficient under the considered disturbances. A sensitivity analysis on the width of the control deadband is then performed for the two control types. The deadband width variation leads to an identical sizing with the hysteresis control showing a better frequency control at the cost of a higher delivered throughput compared to the basic control. An economic analysis comparing the cost of the sized BESS to the potential revenues is then performed.

Keywords: Battery Energy Storage System, electrical network frequency stability, frequency control unit, PowerFactory.

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Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

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The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe₃O₄/Al₂O₃ NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe₃O₄/Al₂O₃ NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL⁻¹, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL^-1 Fe²⁺ was 2.3%.

Keywords: Alumina-coated magnetite nanoparticles, magnetic mixed hemimicell solid-phase extraction, Fe(ΙΙ) and Fe(ΙΙΙ), pharmaceutical sample.

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: Constrained integer problems, enumerative search algorithm, Heuristic algorithm, tunneling algorithm.

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Authors: S. S. Rana, C. Janveja, S. K. Soni

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This study is concerned with the optimization of fermentation parameters for the hyper production of mannanase from Fusarium oxysporum SS-25 employing two step statistical strategy and kinetic characterization of crude enzyme preparation. The Plackett-Burman design used to screen out the important factors in the culture medium revealed 20% (w/w) wheat bran, 2% (w/w) each of potato peels, soyabean meal and malt extract, 1% tryptone, 0.14% NH4SO4, 0.2% KH2PO4, 0.0002% ZnSO4, 0.0005% FeSO4, 0.01% MnSO4, 0.012% SDS, 0.03% NH4Cl, 0.1% NaNO3 in brewer’s spent grain based medium with 50% moisture content, inoculated with 2.8×107 spores and incubated at 30oC for 6 days to be the main parameters influencing the enzyme production. Of these factors, four variables including soyabean meal, FeSO4, MnSO4 and NaNO3 were chosen to study the interactive effects and their optimum levels in central composite design of response surface methodology with the final mannanase yield of 193 IU/gds. The kinetic characterization revealed the crude enzyme to be active over broader temperature and pH range. This could result in 26.6% reduction in kappa number with 4.93% higher tear index and 1% increase in brightness when used to treat the wheat straw based kraft pulp. The hydrolytic potential of enzyme was also demonstrated on both locust bean gum and guar gum.

Keywords: Brewer’s Spent Grain, Fusarium oxysporum, Mannanase, Response Surface Methodology.

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Authors: Payam Haghparast, Mikhail V. Sorin, Hakim Nesreddine

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The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Keywords: 1D model, constant area-mixing, constant pressure-mixing, normal shock location, ejector dimensions.

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Authors: Chi-Fang Huang, Yun-Shiow Chen, Yun-Kung Chung

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In the past decade, artificial neural networks (ANNs) have been regarded as an instrument for problem-solving and decision-making; indeed, they have already done with a substantial efficiency and effectiveness improvement in industries and businesses. In this paper, the Back-Propagation neural Networks (BPNs) will be modulated to demonstrate the performance of the collaborative forecasting (CF) function of a Collaborative Planning, Forecasting and Replenishment (CPFR®) system. CPFR functions the balance between the sufficient product supply and the necessary customer demand in a Supply and Demand Chain (SDC). Several classical standard BPN will be grouped, collaborated and exploited for the easy implementation of the proposed modular ANN framework based on the topology of a SDC. Each individual BPN is applied as a modular tool to perform the task of forecasting SKUs (Stock-Keeping Units) levels that are managed and supervised at a POS (point of sale), a wholesaler, and a manufacturer in an SDC. The proposed modular BPN-based CF system will be exemplified and experimentally verified using lots of datasets of the simulated SDC. The experimental results showed that a complex CF problem can be divided into a group of simpler sub-problems based on the single independent trading partners distributed over SDC, and its SKU forecasting accuracy was satisfied when the system forecasted values compared to the original simulated SDC data. The primary task of implementing an autonomous CF involves the study of supervised ANN learning methodology which aims at making “knowledgeable" decision for the best SKU sales plan and stocks management.

Keywords: CPFR, artificial neural networks, global logistics, supply and demand chain.

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Authors: Elham Lashkari, Mehrshad Khalaj

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Rapid enlargement and physical development of cities have facilitated the emergence of a number of city life crises and decrease of environment quality. Subsequently, the need for noticing the concept of quality and its improvement in urban environments, besides quantitative issues, is obviously recognized. In the domain of urban ideas the importance of taking these issues into consideration is obvious not only in accordance to sustainable development concepts and improvement of public environment quality, but also in the enhancement of social and behavioral models. The major concern of present article is to study the nature of urban environment quality in urban development plans, which is important not only in the concept and the aim of projects but also in their execution procedure. As a result, this paper is going to utilize planning capacities caused by environmental virtues in the planning procedure of Moft Abad neighborhood. Thus, at the first step, applying the Analytical Hierarchy Process (AHP), it has assessed quantitative environmental issues. The present conditions of Moft Abad state that “the neighborhood is generally suffering from the lack of qualitative parameters, and the previously formed planning procedures could not take the sustainable and developmental paths which are aimed at environment quality virtues." The diminution of economical and environmental virtues has resulted in the diminution of residential and social virtues. Therefore, in order to enhance the environment quality in Moft Abad, the present paper has tried to supply the subject plans in order to make a safe, healthy, and lively neighborhood.

Keywords: Urban Environment Quality, Neighborhood Plan, Urban Development Plan, Analytical Hierarchy Process (AHP)

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Authors: Reyna Singh, David Lokhat, Milan Carsky

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The world crude oil demand is projected to rise to 108.5 million bbl/d by the year 2035. With reserves estimated at 869 billion tonnes worldwide, coal remains an abundant resource. The aim of this work was to produce a high value hydrocarbon liquid product using a Direct Coal Liquefaction (DCL) process at, relatively mild operating conditions. Via hydrogenation, the temperature-staged approach was investigated in a dual reactor lab-scale pilot plant facility. The objectives included maximising thermal dissolution of the coal in the presence of tetralin as the hydrogen donor solvent in the first stage with 2:1 and 3:1 solvent: coal ratios. Subsequently, in the second stage, hydrogen saturation, in particular, hydrodesulphurization (HDS) performance was assessed. Two commercial hydrotreating catalysts were investigated viz. NickelMolybdenum (Ni-Mo) and Cobalt-Molybdenum (Co-Mo). GC-MS results identified 77 compounds and various functional groups present in the first and second stage liquid product. In the first stage 3:1 ratios and liquid product yields catalysed by magnetite were favoured. The second stage product distribution showed an increase in the BTX (Benzene, Toluene, Xylene) quality of the liquid product, branched chain alkanes and a reduction in the sulphur concentration. As an HDS performer and selectivity to the production of long and branched chain alkanes, Ni-Mo had an improved performance over Co-Mo. Co-Mo is selective to a higher concentration of cyclohexane. For 16 days on stream each, Ni-Mo had a higher activity than Co-Mo. The potential to cover the demand for low–sulphur, crude diesel and solvents from the production of high value hydrocarbon liquid in the said process, is thus demonstrated. 

Keywords: Catalyst, coal, liquefaction, temperature-staged.

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Authors: Saba Gachpaz, Hamid Reza Heidari

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The sharp increase in population growth leads to more pressure on agricultural areas to satisfy the food supply. This necessitates increased resource consumption and underscores the importance of addressing sustainable agriculture development along with other environmental considerations. Land-use management is a crucial factor in obtaining optimum productivity. Machine learning is a widely used technique in the agricultural sector, from yield prediction to customer behavior. This method focuses on learning and provides patterns and correlations from our data set. In this study, nine physical control factors, namely, soil classification, electrical conductivity, normalized difference water index (NDWI), groundwater level, elevation, annual precipitation, pH of water, annual mean temperature, and slope in the alluvial plain in Khuzestan (an agricultural hotspot in Iran) are used to decide the best agricultural land use for both rainfed and irrigated agriculture for 10 different crops. For this purpose, each variable was imported into Arc GIS, and a raster layer was obtained. In the next level, by using training samples, all layers were imported into the python environment. A random forest model was applied, and the weight of each variable was specified. In the final step, results were visualized using a digital elevation model, and the importance of all factors for each one of the crops was obtained. Our results show that despite 62% of the study area being allocated to agricultural purposes, only 42.9% of these areas can be defined as a suitable class for cultivation purposes.

Keywords: Land suitability, machine learning, random forest, sustainable agriculture.

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Authors: Claude Takenga, Rolf-Dietrich Berndt, Erling Si, Markus Diem, Guohui Qiao, Melanie Gau, Michael Brandstoetter, Martin Kampel, Michael Dworzak

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In patients with acute lymphoblastic leukaemia (ALL), treatment response is increasingly evaluated with minimal residual disease (MRD) analyses. Flow Cytometry (FCM) is a fast and sensitive method to detect MRD. However, the interpretation of these multi-parametric data requires intensive operator training and experience. This paper presents a pipeline-software, as a ready-to-use FCM-based MRD-assessment tool for the daily clinical practice for patients with ALL. The new tool increases accuracy in assessment of FCM-MRD in samples which are difficult to analyse by conventional operator-based gating since computer-aided analysis potentially has a superior resolution due to utilization of the whole multi-parametric FCM-data space at once instead of step-wise, two-dimensional plot-based visualization. The system developed as a telemedical network reduces the work-load and lab-costs, staff-time needed for training, continuous quality control, operator-based data interpretation. It allows dissemination of automated FCM-MRD analysis to medical centres which have no established expertise for the benefit of an even larger community of diseased children worldwide. We established a telemedical network system for analysis and clinical follow-up and treatment monitoring of Leukaemia. The system is scalable and adapted to link several centres and laboratories worldwide.

Keywords: Data security, flow cytometry, leukaemia, telematics platform, telemedicine.

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Authors: Francesco Ruscio, Paolo Paoletti, Jens Thomas, Paul Myers, Sebastiano Fichera

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This paper presents the development of a low-cost monitoring system for a hydroponic urban vertical farm, enabling its automation and a quantitative assessment of the farm performance. Urban farming has seen increasing interest in the last decade thanks to the development of energy efficient and affordable LED lights; however, the optimal configuration of such systems (i.e. amount of nutrients, light-on time, ambient temperature etc.) is mostly based on the farmers’ experience and empirical guidelines. Moreover, even if simple, the maintenance of such systems is labor intensive as it requires water to be topped-up periodically, mixing of the nutrients etc. To unlock the full potential of urban farming, a quantitative understanding of the role that each variable plays in the growth of the plants is needed, together with a higher degree of automation. The low-cost monitoring system proposed in this paper is a step toward filling this knowledge and technological gap, as it enables collection of sensor data related to water and air temperature, water level, humidity, pressure, light intensity, pH and electric conductivity without requiring any human intervention. More sensors and actuators can also easily be added thanks to the modular design of the proposed platform. Data can be accessed remotely via a simple web interface. The proposed platform can be used both for quantitatively optimizing the setup of the farms and for automating some of the most labor-intensive maintenance activities. Moreover, such monitoring system can also potentially be used for high-level decision making, once enough data are collected.

Keywords: Automation, hydroponics, internet of things, monitoring system, urban farming.

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Authors: S. Halofaki, D. R. Seenivasagam, P. Bijay, K. Singh, R. Ananthanarayanan

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This comprehensive literature review delves into the effects and applications of work system design on the performance of Small and Medium-sized Enterprises (SMEs). The review process involved three independent reviewers who screened 514 articles through a four-step procedure: removing duplicates, assessing keyword relevance, evaluating abstract content, and thoroughly reviewing full-text articles. Various criteria such as relevance to the research topic, publication type, study type, language, publication date, and methodological quality were employed to exclude certain publications. A portion of articles that met the predefined inclusion criteria were included as a result of this systematic literature review. These selected publications underwent data extraction and analysis to compile insights regarding the influence of work system design on SME performance. Additionally, the quality of the included studies was assessed, and the level of confidence in the body of evidence was established. The findings of this review shed light on how work system design impacts SME performance, emphasizing important implications and applications. Furthermore, the review offers suggestions for further research in this critical area and summarizes the current state of knowledge in the field. Understanding the intricate connections between work system design and SME success can enhance operational efficiency, employee engagement, and overall competitiveness for SMEs. This comprehensive examination of the literature contributes significantly to both academic research and practical decision-making for SMEs.

Keywords: Literature review, productivity, small and medium-sized enterprises, SMEs, work system design.

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Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

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Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of acquiring new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used in this work is to analyze the dynamics of different brain areas during a cognitive activity to find the relationships between the other areas analyzed to understand the functioning of neural networks better. Also, the latest advances in neuroscience have revealed the exis-tence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neurodevelopmental difficulties for their subsequent assessment and therapy. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process, specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho-pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, learning disabilities, neural networks

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Authors: Etim, Victoria Enefiok, Dada, Oluseyi Akintunde, Bassey Okon

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Phonological disorder is a serious and disturbing issue to many parents and teachers. Efforts towards resolving the problem have been undermined by other specific disabilities which were hidden to many regular and special education teachers. It is against this background that this study was motivated to provide data on the prevalence of phonological disorders in children with specific language impairment (CWSLI) as the first step towards critical intervention. The study was a survey of 15 CWSLI from St. Louise Inclusive schools, Ikot Ekpene in Akwa Ibom State of Nigeria. Phonological Processes Diagnostic Scale (PPDS) with 17 short sentences, which cut across the five phonological processes that were examined, were validated by experts in test measurement, phonology and special education. The respondents were made to read the sentences with emphasis on the targeted sounds. Their utterances were recorded and analyzed in the language laboratory using Praat Software. Data were also collected through friendly interactions at different times from the clients. The theory of generative phonology was adopted for the descriptive analysis of the phonological processes. Data collected were analyzed using simple percentage and composite bar chart for better understanding of the result. The study found out that CWSLI exhibited the five phonological processes under investigation. It was revealed that 66.7%, 80%, 73.3%, 80%, and 86.7% of the respondents have severe deficit in fricative stopping, velar fronting, liquid gliding, final consonant deletion and cluster reduction, respectively. It was therefore recommended that a nationwide survey should be carried out to have national statistics of CWSLI with phonological deficits and develop intervention strategies for effective therapy to remediate the disorder.

Keywords: Language disorders, phonology, phonological processes, specific language impairment.

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Authors: M. Z. Bin Mohd Ghazali, N. C. Wilson, A. F. Bin Ahmad Fuad, M. A. H. B. Musa, M. U. Mohamad Sani, F. Zulkifli, M. S. Zainal Abidin

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Physical activity levels are low in Malaysia and this study was undertaken to determine if a four week work-based intervention program would be effective in changing physical activity levels. The study was conducted in a Malaysian Government Department and had three stages: baseline data collection, four-week intervention and two-month post intervention data collection. During the intervention and two-month post intervention phases, physical activity levels (determined by a pedometer) and basic health profiles (BMI, abdominal obesity, blood pressure) were measured. Staff (58 males, 47 females) with an average age of 33 years completed baseline data collection. Pedometer steps averaged 7,102 steps/day at baseline, although male step counts were significantly higher than females (7,861 vs. 6114). Health profiles were poor: over 50% were overweight/obese (males 66%, females 40%); hypertension (males 23%, females 6%); excess waist circumference (males 52%, females 17%). While 86 staff participated in the intervention, only 49 regularly reported their steps. There was a significant increase (17%) in average daily steps from 8,965 (week 1) to 10,436 (week 4). Unfortunately, participation in the intervention program was avoided by the less healthy staff. Two months after the intervention there was no significant difference in average steps/day, despite the fact that 89% of staff reporting they planned to make long-term changes to their lifestyle. An unexpected average increase of 2kg in body weight occurred in participants, although this was less than the 5.6kg in non-participants. A number of recommendations are made for future interventions, including the conclusion that pedometers were a useful tool and popular with participants.

Keywords: Pedometers, walking, health, intervention.

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Authors: Takeshi Sato, Mizuki Nakajima, Macky Kato, Shoji Igawa

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The purpose of study was to investigate the effect of varying pole weights on energy expenditure, upper limb and lower limb muscle activity as Electromyogram during Nordic walking (NW). Four healthy men [age = 22.5 (±1.0) years, body mass = 61.4 (±3.6) kg, height = 170.3 (±4.3) cm] and three healthy women [age = 22.7 (±2.9) years, body mass = 53.0 (±1.7) kg, height = 156.7 (±4.5) cm] participated in the experiments after informed consent. Seven healthy subjects were tested on the treadmill, walking, walking (W) with Nordic Poles (NW) and walking with 1kg weight Nordic Poles (NW+1). Walking speed was 6 km per hours in all trials. Eight EMG activities were recorded by bipolar surface methods in biceps brachii, triceps brachii, trapezius, deltoideus, tibialis anterior, medial gastrocnemius, rectus femoris and biceps femoris muscles. And heart rate (HR), oxygen uptake (VO₂), and rate of perceived exertion (RPE) were measured. The level of significance was set at a = 0.05, with p < 0.05 regarded as statistically significant. Our results confirmed that use of NW poles increased HR at a given upper arm muscle activity but decreased lower limb EMGs in comparison with W. Moreover NW was able to increase more step lengths with hip joint extension during NW rather than W. Also, EMG revealed higher activation of upper limb for almost all NW and 1kgNW tests plus added masses compared to W (p < 0.05). Therefore, it was thought either of NW and 1kgNW were to have benefit as a physical exercise for safe, feasible, and readily training for a wide range of aged people in the quality of daily life. However, there was no significant effected in leg muscles activity by using 1kgNW except for upper arm muscle activity during Nordic pole walking.

Keywords: Nordic walking, electromyogram, heart rate.

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Authors: Afrah Saad Mohsen Al-Mahfadi

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In rural areas of developing countries, participation of all stakeholders in water supply projects is an important step towards further development. As most of the beneficiaries are women, it is important that they should be involved to achieve successful and sustainable water supply projects. Women are responsible for the management of water both inside and outside home, and often spend more than six-hours a day fetching drinking water from distant water sources. The problem is that rural women play a role of little importance in the water supply projects’ phases in rural Yemen. Therefore, this research aimed at analyzing the different reasons of their lack of participation in projects and in what way a full participation -if achieved- could contribute to sustainable water supply projects in the rural mountainous areas in Yemen. Four water supply projects were selected as a case study in Al-Della'a Alaala sub-district in the Al-Mahweet governorate, two of them were implemented by the Social Fund and Development (SFD), while others were implemented by the General Authority for Rural Water Supply Projects (GARWSSP). Furthermore, the successful Al-Galba project, which is located in Badan district in Ibb governorate, was selected for comparison. The rural women's active participation in water projects have potential consequences including continuity and maintenance improvement, equipment security, and improvement in the overall health and education status of these areas. The majority of respondents taking part in GARWSSP projects estimated that there is no reason to involve women in the project activities. In the comparison project - in which a woman worked as a supervisor and implemented the project – all respondents indicated that the participation of women is vital for sustainability. Therefore, the results of this research are intended to stimulate rural women's participation in the mountainous areas of Yemen.

Keywords: Assessment, rural woman, sustainability, water management.

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Authors: Souvik Bhattacharyya, Gautam Sanyal

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Over last two decades, due to hostilities of environment over the internet the concerns about confidentiality of information have increased at phenomenal rate. Therefore to safeguard the information from attacks, number of data/information hiding methods have evolved mostly in spatial and transformation domain.In spatial domain data hiding techniques,the information is embedded directly on the image plane itself. In transform domain data hiding techniques the image is first changed from spatial domain to some other domain and then the secret information is embedded so that the secret information remains more secure from any attack. Information hiding algorithms in time domain or spatial domain have high capacity and relatively lower robustness. In contrast, the algorithms in transform domain, such as DCT, DWT have certain robustness against some multimedia processing.In this work the authors propose a novel steganographic method for hiding information in the transform domain of the gray scale image.The proposed approach works by converting the gray level image in transform domain using discrete integer wavelet technique through lifting scheme.This approach performs a 2-D lifting wavelet decomposition through Haar lifted wavelet of the cover image and computes the approximation coefficients matrix CA and detail coefficients matrices CH, CV, and CD.Next step is to apply the PMM technique in those coefficients to form the stego image. The aim of this paper is to propose a high-capacity image steganography technique that uses pixel mapping method in integer wavelet domain with acceptable levels of imperceptibility and distortion in the cover image and high level of overall security. This solution is independent of the nature of the data to be hidden and produces a stego image with minimum degradation.

Keywords: Cover Image, Pixel Mapping Method (PMM), StegoImage, Integer Wavelet Tranform.

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Authors: Gorazd Karer

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When performing a diagnostic procedure or surgery in general anesthesia (GA), a proper introduction and dosing of anesthetic agents is one of the main tasks of the anesthesiologist. That being said, depth of anesthesia (DoA) also seems to be a suitable process for closed-loop control implementation. To implement such a system, one must be able to acquire the relevant signals online and in real-time, as well as stream the calculated control signal to the infusion pump. However, during a procedure, patient monitors and infusion pumps are purposely unable to connect to an external (possibly medically unapproved) device for safety reasons, thus preventing closed-loop control. This paper proposes a conceptual solution to the aforementioned problem. First, it presents some important aspects of contemporary clinical practice. Next, it introduces the closed-loop-control-system structure and the relevant information flow. Focusing on transferring the data from the patient to the computer, it presents a non-invasive image-based system for signal acquisition from a patient monitor for online depth-of-anesthesia assessment. Furthermore, it introduces a User-Datagram-Protocol-based (UDP-based) communication method that can be used for transmitting the calculated anesthetic inflow to the infusion pump. The proposed system is independent of medical-device manufacturer and is implemented in MATLAB-Simulink, which can be conveniently used for DoA control implementation. The proposed scheme has been tested in a simulated GA setting and is ready to be evaluated in an operating theatre. However, the proposed system is only a step towards a proper closed-loop control system for DoA, which could routinely be used in clinical practice.

Keywords: Closed-loop control, Depth of Anesthesia, DoA, optical signal acquisition, Patient State index, PSi, UDP communication protocol.

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Authors: Foad Hassaninejadafarahani, Scott Ormiston

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Reflux condensation occurs in vertical channels and tubes when there is an upward core flow of vapour (or gas-vapour mixture) and a downward flow of the liquid film. The understanding of this condensation configuration is crucial in the design of reflux condensers, distillation columns, and in loss-of-coolant safety analyses in nuclear power plant steam generators. The unique feature of this flow is the upward flow of the vapour-gas mixture (or pure vapour) that retards the liquid flow via shear at the liquid-mixture interface. The present model solves the full, elliptic governing equations in both the film and the gas-vapour core flow. The computational mesh is non-orthogonal and adapts dynamically the phase interface, thus produces a sharp and accurate interface. Shear forces and heat and mass transfer at the interface are accounted for fundamentally. This modeling is a big step ahead of current capabilities by removing the limitations of previous reflux condensation models which inherently cannot account for the detailed local balances of shear, mass, and heat transfer at the interface. Discretisation has been done based on finite volume method and co-located variable storage scheme. An in-house computer code was developed to implement the numerical solution scheme. Detailed results are presented for laminar reflux condensation from steam-air mixtures flowing in vertical parallel plate channels. The results include velocity and gas mass fraction profiles, as well as axial variations of film thickness.

Keywords: Reflux Condensation, Heat Transfer, Channel, Laminar Flow

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Authors: Ajay Sharma, R.S. Jangid

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Analytical seismic response of multi-story building supported on base isolation system is investigated under real earthquake motion. The superstructure is idealized as a shear type flexible building with lateral degree-of-freedom at each floor. The force-deformation behaviour of the isolation system is modelled by the bi-linear behaviour which can be effectively used to model all isolation systems in practice. The governing equations of motion of the isolated structural system are derived. The response of the system is obtained numerically by step-by-method under three real recorded earthquake motions and pulse motions associated in the near-fault earthquake motion. The variation of the top floor acceleration, interstory drift, base shear and bearing displacement of the isolated building is studied under different initial stiffness of the bi-linear isolation system. It was observed that the high initial stiffness of the isolation system excites higher modes in base-isolated structure and generate floor accelerations and story drift. Such behaviour of the base-isolated building especially supported on sliding type of isolation systems can be detrimental to sensitive equipment installed in the building. On the other hand, the bearing displacement and base shear found to reduce marginally with the increase of the initial stiffness of the initial stiffness of the isolation system. Further, the above behaviour of the base-isolated building was observed for different parameters of the bearing (i.e. post-yield stiffness and characteristic strength) and earthquake motions (i.e. real time history as well as pulse type motion).

Keywords: base isolation, base shear, bi-linear, earthquake, floor accelerations, inter-story drift, multi-story building, pulsemotion, stiffness ratio.

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