Search results for: multidimensional scaling

Authors: Abhijith Asok

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This paper presents a generalized approach for the simple linear data transformation, Y=bX, through an integration of multidimensional coordinate geometry, vector space theory and polygonal geometry. The scaling is performed by adding an additional ’Dummy Dimension’ to the n-dimensional data, which helps plot two dimensional component-wise straight lines on pairs of dimensions. The end result is a set of scaled extensions of observations in any of the 2n spatial divisions, where n is the total number of applicable dimensions/dataset variables, created by shifting the n-dimensional plane along the ’Dummy Axis’. The derived scaling factor was found to be dependent on the coordinates of the common point of origin for diverging straight lines and the plane of extension, chosen on and perpendicular to the ’Dummy Axis’, respectively. This result indicates the geometrical interpretation of a linear data transformation and hence, opportunities for a more informed choice of the factor ’b’, based on a better choice of these coordinate values. The paper follows on to identify the effect of this transformation on certain popular distance metrics, wherein for many, the distance metric retained the same scaling factor as that of the features.

Keywords: data transformation, dummy dimension, linear transformation, scaling

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Authors: Walid Louhichi, Mouhebeddine Berrima, Narjes Ben Rajed

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Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workload. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on colored and temporized Petri nets, for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets modeling language. The proposed models are edited, verified, and simulated with two examples implemented in CPNtools, which is a modeling tool for colored and timed Petri nets.

Keywords: cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out

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Authors: Ankur Mundhra, Shubhadeep Chakraborty, Y. R. Singh, Vishal Das

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Seismic data scaling affects the dynamic range of a data and with present day lower costs of storage and higher reliability of Hard Disk data, scaling is not suggested. However, in dealing with data of different vintages, which perhaps were processed in 16 bits or even 8 bits and are need to be processed with 32 bit available data, scaling is performed. Also, scaling amplifies low amplitude events in deeper region which disappear due to high amplitude shallow events that saturate amplitude scale. We have focused on significance of scaling data to aid interpretation. This study elucidates a proper seismic loading procedure in workstations without using default preset parameters as available in most software suites. Differences and distribution of amplitude values at different depth for seismic data are probed in this exercise. Proper loading parameters are identified and associated steps are explained that needs to be taken care of while loading data. Finally, the exercise interprets the un-certainties which might arise when correlating scaled and unscaled versions of seismic data with synthetics. As, seismic well tie correlates the seismic reflection events with well markers, for our study it is used to identify regions which are enhanced and/or affected by scaling parameter(s).

Keywords: clipping, compression, resolution, seismic scaling

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Authors: Hussien Ali, Mesfin Menza, Fitsum Hagos, Amare Haileslassie

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Climate change has perverse effects on agricultural productivity and natural resource base, negatively affecting the well-being of the households and communities. The government and NGOs promote climate smart agricultural (CSA) practices to help farmers adapt to and mitigate the negative effects of climate change. This study aims to identify widely available CSA practices and examine their impacts on food security and multi-dimensional poverty of rural farm households in the Central Rift Valley, Ethiopia. Using three-stage proportional to size sampling procedure, the study randomly selected 278 households from two kebeles from four districts each. A cross-sectional data of 2020/21 cropping season was collected using structured and pretested survey questionnaire. Food consumption score, dietary diversity score, food insecurity experience scale, and multidimensional poverty index were calculated to measure households’ welfare indicators. Multinomial endogenous switching regression model was used to assess average treatment effects of CSA on these outcome indicators on adopter and non-adopter households. The results indicate that the widely adopted CSA practices in the area are conservation agriculture, soil fertility management, crop diversification, and small-scale irrigation. Adopter households have, on average, statistically higher food consumption score, dietary diversity score and lower food insecurity access scale than non-adopters. Moreover, adopter households, on average, have lower deprivation score in multidimensional poverty compared to non-adopter households. Up scaling the adoption of CSA practices through the improvement of households’ implementation capacity and better information, technical advice, and innovative financing mechanisms is advised. Up scaling CSA practices can further promote achieving global goals such as SDG 1, SDG 2, and SDG 13 targets, aimed to end poverty and hunger and mitigate the adverse impacts of climate change, respectively.

Keywords: climate-smart agriculture, food security, multidimensional poverty, upscaling CSA, Ethiopia

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Authors: Zouari Ezzeddine, Ghraieb Ikram

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From the results of the academic literature which evokes the limitations of previous studies, this article shows the reasons for multidimensionality Prediction of financial bubbles. A new framework for modeling study predicting financial bubbles by linking a set of variable presented on several dimensions dictating its multidimensional character. It takes into account the preferences of financial actors. A multicriteria anticipation of the appearance of bubbles in international financial markets helps to fight against a possible crisis.

Keywords: classical measures, predictions, financial bubbles, multidimensional, artificial neural networks

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Authors: E. Arcos, E. Bautista, F. Méndez

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In this work, a scaling analysis of the liquefaction phenomena is presented. The characteristic scales are obtained by balancing term by term of the well-known partial dynamics governing equations, (U − P). From the above, the order of magnitude of the horizontal displacement is very smaller compared with the vertical displacement and therefore the governing equation is only a function of the dependent vertical variables. The U − P approximation is reduced and presented in its dimensionless version. This scaling analysis can be used to obtain analytical solutions of the liquefaction phenomena under the action of the water waves.

Keywords: approximation U-P, porous seabed, scaling analysis, water waves

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Authors: M. A. Salman, G. Al-Nuwaibit, M. Safar, M. Rughaibi, A. Al-Mesri

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Barium sulfate (BaSO₄) is a hard scaling usually precipitates on the surface of equipment in many industrial systems, as oil and gas production, desalination and cooling and boiler operation. It is a scale that extremely resistance to both chemical and mechanical cleaning. So, BaSO₄ is a problematic and expensive scaling. Although barium ions are present in most natural waters at a very low concentration as low as 0.008 mg/l, it could result of scaling problems in the presence of high concentration of sulfate ion or when mixing with incompatible waters as in oil produced water. The scaling potential of BaSO₄ using seawater at the intake of seven desalination plants in Kuwait, brine water and Kuwait oil produced water was calculated and compared then the best location in regards of barium sulfate scaling was reported. Finally, a physical treatment method (magnetic treatment method) and chemical treatment method were used to control BaSO₄ scaling using saturated solutions at different operating temperatures, flow velocities, feed pHs and different magnetic strengths. The results of the two methods were discussed, and the more economical one with the reasonable performance was recommended, which is the physical treatment method.

Keywords: magnetic field strength, flow velocity, retention time, barium sulfate

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Authors: Ouzayr Rabhi, Ibtissam Arrassen

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To provide a complete analysis of the organization and to help decision-making, leaders need to have relevant data; Data Warehouses (DW) are designed to meet such needs. However, designing DW is not trivial and there is no formal method to derive a multidimensional schema from heterogeneous databases. In this article, we present a Model-Driven based approach concerning the design of data warehouses. We describe a multidimensional meta-model and also specify a set of transformations starting from a Unified Modeling Language (UML) metamodel. In this approach, the UML metamodel and the multidimensional one are both considered as a platform-independent model (PIM). The first meta-model is mapped into the second one through transformation rules carried out by the Query View Transformation (QVT) language. This proposal is validated through the application of our approach to generating a multidimensional schema of a Balanced Scorecard (BSC) DW. We are interested in the BSC perspectives, which are highly linked to the vision and the strategies of an organization.

Keywords: data warehouse, meta-model, model-driven architecture, transformation, UML

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Authors: Ramya Rachel S.

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For women in a developing country like India, poverty is an ever-clinging problem which has rooted itself without any trace of absolute abolition. Poverty is a deprivation of many imminent needs and must be measured accordingly. Therefore, it is important to study the dimensions of education, health, and standard of living to understand the true nature of the impoverished. The study focused on studying the deprivation on these aspects using the Alkire-Foster methodology to estimate the Multidimensional Poverty Index. The study has utilized the individual data of women aged 15 to 49 of the National Family Health Survey (NFHS) for the year 2015-16. Findings reveal that women in India still face extreme levels of deprivation in various dimensions. More than one-third of the total women aged 15 to 24 in India were multidimensionally poor. Dimensional breakdown of the levels of multidimensional poverty indicates that the dimension of Education is the highest contributor to poverty. Decomposition of the multidimensional poverty among various demographic sub-groups, reveals that the multidimensional poverty level increases with age. Results point out that deprivations were higher among widowed and married women, and among women who lived alone. There was also a huge rural-urban divide with respect to poverty. The basic needs of these women must be targeted and met so that they are withdrawn from all forms of poverty.

Keywords: deprivations, multidimensional poverty, sub-group decomposition, women

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Authors: Masoud Sheidai

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Biologists with a special field of population genetics and phylogeny have different research tasks such as populations’ genetic variability and divergence, species relatedness, the evolution of genetic and morphological characters, and identification of DNA SNPs with adaptive potential. To tackle these problems and reach a concise conclusion, they must use the proper and efficient statistical and bioinformatic methods as well as suitable genetic and morphological characteristics. In recent years application of different bioinformatic and statistical methods, which are based on various well-documented assumptions, are the proper analytical tools in the hands of researchers. The species delineation is usually carried out with the use of different clustering methods like K-means clustering based on proper distance measures according to the studied features of organisms. A well-defined species are assumed to be separated from the other taxa by molecular barcodes. The species relationships are studied by using molecular markers, which are analyzed by different analytical methods like multidimensional scaling (MDS) and principal coordinate analysis (PCoA). The species population structuring and genetic divergence are usually investigated by PCoA and PCA methods and a network diagram. These are based on bootstrapping of data. The Association of different genes and DNA sequences to ecological and geographical variables is determined by LFMM (Latent factor mixed model) and redundancy analysis (RDA), which are based on Bayesian and distance methods. Molecular and morphological differentiating characters in the studied species may be identified by linear discriminant analysis (DA) and discriminant analysis of principal components (DAPC). We shall illustrate these methods and related conclusions by giving examples from different edible and medicinal plant species.

Keywords: GWAS analysis, K-Means clustering, LFMM, multidimensional scaling, redundancy analysis

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Authors: Bidyadhar Dehury, Sanjay Kumar Mohanty

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According to the Right to Education Act of India, education is the fundamental right of all children of age group 6-14 year irrespective of their status. Using the unit level data from India Human Development Survey (IHDS), we tried to understand the inter-relationship between the level of poverty and the academic performance of the children aged 8-11 years. The level of multidimensional poverty is measured using five dimensions and 10 indicators using Alkire-Foster approach. The weighted deprivation score was obtained by giving equal weight to each dimension and indicators within the dimension. The weighted deprivation score varies from 0 to 1 and grouped into four categories as non-poor, vulnerable, multidimensional poor and sever multidimensional poor. The academic performance index was measured using three variables reading skills, math skills and writing skills using PCA. The bivariate and multivariate analysis was used in the analysis. The outcome variable was ordinal. So the predicted probabilities were calculated using the ordinal logistic regression. The predicted probabilities of good academic performance index was 0.202 if the child was sever multidimensional poor, 0.235 if the child was multidimensional poor, 0.264 if the child was vulnerable, and 0.316 if the child was non-poor. Hence, if the level of poverty among the children decreases from sever multidimensional poor to non-poor, the probability of good academic performance increases.

Keywords: multidimensional poverty, academic performance index, reading skills, math skills, writing skills, India

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Authors: Joseph Siani

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Over the last decades, dissatisfaction with global indicators of economic performance, such as GDP (Gross Domestic Product) per capita, has shifted the attention to what is now referred to as multidimensional poverty. In this framework, poverty goes beyond income to incorporate aspects of well-being not captured by income measures alone. This paper applies the totally fuzzy approach to estimate the fuzzy index of poverty (FIP) in fourteen Sub-Saharan African (SSA) countries using Demographic and Health Survey (DHS) data and explores whether pictures created by the standard headcount ratio at $1.90 a day and the fuzzy index of poverty tell a similar story. The results suggest that there is indeed considerable mismatch between poverty headcount and the fuzzy index of multidimensional poverty, meaning that the majority of the most deprived people (as identified by the fuzzy index of multidimensional poverty) would not be identified by the poverty headcount ratio. Moreover, we find that poverty is distributed differently by colonial heritage (language). In particular, the most deprived countries in SSA are French-speaking.

Keywords: fuzzy set approach, multidimensional poverty, poverty headcount, overlap, Sub-Saharan Africa

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Authors: M. B. Neace, Xin GAo

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Small entrepreneurs are ubiquitous. Regardless of location their success depends on several behavioral characteristics and several market conditions. In this concept paper, we extend this paradigm to include elements from the science of chaos. Our observations, research findings, literature search and intuition lead us to the proposition that all entrepreneurs seek increasing returns, as did the many small entrepreneurs we have interviewed over the years. There will be a few whose initial perturbations may create tsunami-like waves of increasing returns over time resulting in very large market consequences–the butterfly impact. When small entrepreneurs perturb the market-place and their initial efforts take root a series of phase-space transitions begin to occur. They sustain the stream of increasing returns by scaling up. Chaos theory contributes to our understanding of this phenomenon. Sustaining and nourishing increasing returns of small entrepreneurs as complex adaptive systems requires scaling. In this paper we focus on the most critical element of the small entrepreneur scaling process–the mindset of the owner-operator.

Keywords: entrepreneur, increasing returns, scaling, chaos

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Authors: Maha Salman, Gada Al-Nuwaibit

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The effect of anti-scale magnetic method (AMM) in retarding scaling deposition is confirmed by many researchers, to result in new crystal morphology, the crystal which has the tendency to remain suspended more than precipitated. AMM is considered as an economic method when compared to other common methods used for scale prevention in desalination plant as acid treatment and addition of antiscalant. The current project was initiated to evaluate the effectiveness of AMM in preventing calcium carbonate scaling. The AMM was tested at different flow velocities (1.0, 0.5, 0.3, 0.1, and 0.003 m/s), different operating temperatures (50, 70, and 90°C), different feed pH and different magnetic field strength. The results showed that AMM was effective in retarding calcium carbonate scaling deposition, and the performance of AMM depends strongly on the flow velocity. The scaling retention time was found to be affected by the operating temperatures, flow velocity, and magnetic strength (MS), and in general, it was found that as the operating temperatures increased the effectiveness of the AMM in retarding calcium carbonate (CaCO₃) scaling increased.

Keywords: magnetic treatment, field strength, flow velocity, magnetic scale retention time

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Authors: Flora Elvistia Firdaus

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The chemical structure of soybean oils have to be chemically modified through its tryglyceride to attain resemblance properties with petrochemicals. Sulfur acid catalyst in peracetic acid co-reagent has good performance on modified soybean oil strucutures through its unsaturated fatty acid moiety to the desired hydroxyl functional groups. A series of screening reactions have indicated that the ratio of acetic/peroxide acid 1:7.25 (mol/mol) with temperature of 600°C for soy-epoxide synthesis are prevailed for up-scaling of bodied soybean into 10 and 20 folds from initials. A two-step process was conducted for the preparation of soy-polyol in designated temperatures.

Keywords: soybean, polyol, up-scaling, polyurethane

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Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: torsional vibration, full-size model, scale model, scaling laws

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Authors: Khosrow Maleknejad, Yaser Rostami

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In this paper, semi-orthogonal B-spline scaling functions and wavelets and their dual functions are presented to approximate the solutions of integro-differential equations.The B-spline scaling functions and wavelets, their properties and the operational matrices of derivative for this function are presented to reduce the solution of integro-differential equations to the solution of algebraic equations. Here we compute B-spline scaling functions of degree 4 and their dual, then we will show that by using them we have better approximation results for the solution of integro-differential equations in comparison with less degrees of scaling functions.

Keywords: ıntegro-differential equations, quartic B-spline wavelet, operational matrices, dual functions

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Authors: B. Schmid, C. Kexel, E. Djafarova

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Understanding consumers is elementary for practitioners in marketing. Consumers of sports events, the sports spectators, are a particularly complex consumer crowd. In order to identify and define their profiles different segmentation approaches can be found in literature, one of them being multidimensional segmentation. Multidimensional segmentation models correspond to the broad range of attitudes, behaviours, motivations and beliefs of sports spectators, other than earlier models. Moreover, in sports there are some well-researched disciplines (e.g. football or North American sports) where consumer profiles and marketing strategies are elaborate and others where no research at all can be found. For example, there is almost no research on athletics spectators. This paper explores the current state of research on sports spectators segmentation. An in-depth literature review provides the framework for a spectators segmentation in athletics. On this basis, additional potential consumer groups and implications for social media marketing will be explored. The findings are the basis for further research.

Keywords: multidimensional segmentation, social media, sports marketing, sports spectators segmentation

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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Statistical down scaling models are required to connect the global climate model outputs and the local weather variables for climate change impact prediction. For reliable climate change impact studies, the uncertainty associated with the model including natural variability, uncertainty in the climate model(s), down scaling model, model inadequacy and in the predicted results should be quantified appropriately. In this work, a new approach is developed by the authors for statistical classification, statistical down scaling and uncertainty assessment and is applied to Singapore rainfall. It is a robust Bayesian uncertainty analysis methodology and tools based on coupling dependent modeling error with classification and statistical down scaling models in a way that the dependency among modeling errors will impact the results of both classification and statistical down scaling model calibration and uncertainty analysis for future prediction. Singapore data are considered here and the uncertainty and prediction results are obtained. From the results obtained, directions of research for improvement are briefly presented.

Keywords: statistical downscaling, global climate model, climate change, uncertainty

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Authors: Diogo Silva, Fadul Rodor, Carlos Moraes

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This work compares the results of multidimensional function approximation using two algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum Particle Swarm Optimization (QPSO). These algorithms were both tested on three functions - The Rosenbrock, the Rastrigin, and the sphere functions - with different characteristics by increasing their number of dimensions. As a result, this study shows that the higher the function space, i.e. the larger the function dimension, the more evident the advantages of using the QPSO method compared to the PSO method in terms of performance and number of necessary iterations to reach the stop criterion.

Keywords: PSO, QPSO, function approximation, AI, optimization, multidimensional functions

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Authors: Samira Ghizellaoui, Manel Boumagoura

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The municipality of Constantine in eastern Algeria draws water from the Hamma groundwater source. The high fouling capacity is due to the high content of bicarbonate (442 mg/L) and calcium (136 mg/L). This work focuses on the use of three new green inhibitors for reducing calcium carbonate scale formation: gallic acid, quercetin and alginate, and on the comparison between them. These inhibitors have proven to be green antiscalants because they have no impact on the environment. Electrochemical methods (chronoamperometry and impedancemetry) were used to evaluate their performance. According to the study, these inhibitors are excellent green chemical inhibitors of scaling, and the best inhibitor is quercetin because it gave a good result with a lower concentration (2mg/L) compared to others inhibitors.

Keywords: scaling, green inhibitor, chronoamperometry, impedancemetry

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Authors: Muhammad Usman, Munir Ahmed

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The demand of high-rise buildings has grown fast during the past decades. The design of these buildings by using RC core wall have been widespread nowadays in many countries. The RC core wall (RCCW) buildings encompasses central core wall and boundary columns joined through post tension slab at different floor levels. The core wall often provides greater stiffness as compared to the collective stiffness of the boundary columns. Hence, the core wall dominantly resists lateral loading i.e. wind or earthquake load. Non-linear response history analysis (NLRHA) procedure is the finest seismic design procedure of the times for designing high-rise buildings. The modern design tools for nonlinear response history analysis and performance based design has provided more confidence to design these structures for high-rise buildings. NLRHA requires selection and scaling of ground motions to match design spectrum for site specific conditions. Designers use several techniques for scaling ground motion records (time series). Time domain and frequency domain scaling are most commonly used which comprises their own benefits and drawbacks. Due to lengthy process of NLRHA, application of only one technique is conceivable. To the best of author’s knowledge, no consensus on the best procedures for the selection and scaling of the ground motions is available in literature. This research aims to provide the finest ground motion scaling technique specifically for designing 40 story high-rise RCCW buildings. Seismic response of 40 story RCCW building is checked by applying both the frequency domain and time domain scaling. Variable sites are selected in three critical seismic zones of Pakistan. The results indicates that there is extensive variation in seismic response of building for these scaling. There is still a need to build a consensus on the subjected research by investigating variable sites and buildings heights.

Keywords: 40-storied RC core wall building, nonlinear response history analysis, ground motions, time domain scaling, frequency domain scaling

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Authors: Ben Mansour Mouin, Elloumi Abdelkarim

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We will discuss the problem of routing a fleet of different vehicles from a central depot to different types of infrastructure-defaults with dynamic maintenance requests, modified time windows, and control of default maintained. For this reason, we propose a modified metaheuristicto to solve our mathematical model. SVRDP-CMTW is a variant VRP of an optimal vehicle plan that facilitates the maintenance task of different types of infrastructure-defaults. This task will be monitored after the maintenance, based on its priorities, the degree of danger associated with each default, and the neighborhood at the black-spots. We will present, in this paper, a multidimensional genetic algorithm “MGA” by detailing its characteristics, proposed mechanisms, and roles in our work. The coding of this algorithm represents the necessary parameters that characterize each infrastructure-default with the objective of minimizing a combination of cost, distance and maintenance times while satisfying the priority levels of the most urgent defaults. The developed algorithm will allow the dynamic integration of newly detected defaults at the execution time. This result will be displayed in our programmed interactive system at the routing time. This multidimensional genetic algorithm replaces N genetic algorithm to solve P different type problems of infrastructure defaults (instead of N algorithm for P problem we can solve in one multidimensional algorithm simultaneously who can solve all these problemsatonce).

Keywords: mathematical model, VRP, multidimensional genetic algorithm, metaheuristics

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Authors: Nadereh Sohrabi Shegefti, Siamak Samani

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Level of adjustment is the first index to check mental health. The aim of this study was developing a valid and reliable Multidimensional Adjustment Scale (MAS). The sample consisted of 150 college students. Multidimensional adjustment scale and Depression, Anxiety, and stress scale (DASS) were used in this study. Principle factor analysis, Pearson correlation coefficient, and Cornbach's Alpha were used to check the validity and reliability of the MAS. Principle component factor analysis showed a 5 factor solution for the MAS. Alpha coefficients for the MAS sub scales were ranged between .69 to .83. Test-retest reliability for MAS was .88 and the mean of sub scales- total score correlation was .88. All these indexes revealed an acceptable reliability and validity for the MAS. The MAS is a short assessment instrument with good acceptable psychometric properties to use in clinical filed.

Keywords: psychological adjustment, psychometric properties, validity, Pearson correlation

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Authors: Saurabh Chaudhury, Sanjeet Kumar Sinha

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The MOSFET has been the main building block in high performance and low power VLSI chips for the last several decades. Device scaling is fundamental to technological advancements, which allows more devices to be integrated on a single die providing greater functionality per chip. Ultimately, the goal of scaling is to build an individual transistor that is smaller, faster, cheaper, and consumes less power. Scaling continued following Moore's law initially and now we see an exponential growth in today's nano scaled chip. However, device scaling to deep nano meter regime leads to exponential increase in leakage currents and excessive heat generation. Moreover, fabrication process variability causing a limitation to further scaling. Researchers believe that with a mix of chemistry, physics, and engineering, nano electronics may provide a solution to increasing fabrication costs and may allow integrated circuits to be scaled beyond the limits of the modern transistor. Carbon nano tube (CNT) and nano wires (NW) based FETs have been analyzed and characterized in laboratory and also been demonstrated as prototypes. This work presents an extensive simulation based study and analysis of CNTFET and NW-FET devices and comparison of the results with conventional MOSFET. From this study, we can conclude that these devices have got some excellent properties and favorable characteristics which will definitely lead the future semiconductor devices in post silicon era.

Keywords: carbon nanotube, nanowire FET, low power, nanoscaled devices, VLSI

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Authors: Ehsan Derikvand, Hamid Kaykha, Rooholah Mansoori Yekta, Taleb Javanmard, Mohsen Mehdi Zadeh

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Corrosion and scaling are one of the most complicated and costly problems of drinking water supply. Corrosion has adverse effect on general health and public acceptance of water source and drinking water supply costs. The present study aimed to determine the potentials of corrosion and scaling of potable water supply reservoirs of Ilam city in June 2013 and August 2014 by Langelier Index (LI) and Reynar. The results of experiments and calculations show that the mean index of LSI in the first and second sampling stages is 0.34, 0.2, respectively and the mean index RSI in the first and second stages of sampling is 7.15 and 7.22, respectively. Based on LSI index of reservoirs water in the first phase, none of stations are corrosive and only one station in the second sampling phase has corrosive tendency. According to RSI index, there is no corrosive tendency in two phases. Based on the results, the water of drinking water reservoirs in Ilam city has no corrosion tendency and the analyses and results of Langelier Index (LI) and Ryznar are in relatively good condition.

Keywords: corrosion, scaling, water reservoirs, langelier and ryznar indices, Ilam city

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Authors: A. U. Haque, W. Asrar, A. A Omar, E. Sulaeman, J. S. M. Ali

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Buoyancy force applied on deformable symmetric bodies can be estimated by using Archimedes Principle. Such bodies like ellipsoidal bodies have high volume to surface ratio and are isometrically scaled for mass, length, area and volume to follow square cube law. For scaling up such bodies, it is worthwhile to find out the scaling relationship between the other physical quantities that represent thermodynamic, structural and inertial response etc. So, dimensionless similarities to find an allometric scale can be developed by using Bukingham π theorem which utilizes physical dimensions of important parameters. Base on this fact, physical dependencies of buoyancy system are reviewed to find the set of physical variables for deformable bodies of revolution filled with expandable gas like helium. Due to change in atmospheric conditions, this gas changes its volume and this change can effect the stability of elongated bodies on the ground as well as in te air. Special emphasis was given on the existing similarity parameters which can be used in the design of experiments of such bodies whose shape is affected by the external force like a drag, surface tension and kinetic loads acting on the surface. All these similarity criteria are based on non-dimensionalization, which also needs to be consider for scaling up such bodies.

Keywords: Bukhigham pi theorem, similitude, scaling, buoyancy

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Authors: M. Chukhryaeva, R. Skhalyakho, J. Kagazegeva, E. Pocheshkhova, L. Yepiskopossyan, O. Balanovsky, E. Balanovska

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The Middle East is crossroad of different populations at different times. The Kurds are of particular interest in this region. Historical sources suggested that the origin of the Kurds is associated with Medes. Therefore, it was especially interesting to compare gene pool of Kurds with other supposed descendants of Medes-Tats. Yezidis are ethno confessional group of Kurds. Yezidism as a confessional teaching was formed in the XI-XIII centuries in Iraq. Yezidism has caused reproductively isolation of Yezidis from neighboring populations for centuries. Also, isolation helps to retain Yezidian caste system. It is unknown how the history of Yezidis affected its genу pool because it has never been the object of researching. We have examined the Y-chromosome variation in Yezidis and Kurdish males to understand their gene pool. We collected DNA samples from 90 Yezidi males and 24 Kurdish males together with their pedigrees. We performed Y-STR analysis of 17 loci in the samples collected (Yfiler system from Applied Biosystems) and analysis of 42 Y-SNPs by real-time PCR. We compared our data with published data from other Kurdish groups and from European, Caucasian, and West Asian populations. We found that gene pool of Yezidis contains haplogroups common in the Middle East (J-M172(xM67,M12)- 24%, E-M35(xM78)- 9%) and in South Western Asia (R-M124- 8%) and variant with wide distribution area - R-M198(xM458- 9%). The gene pool of Kurdish has higher genetic diversity than Yezidis. Their dominants haplogroups are R-M198- 20,3 %, E-M35- 9%, J-M172- 9%. Multidimensional scaling also shows that the Kurds and Yezidis are part of the same frontier Asian cluster, which, in addition, included Armenians, Iranians, Turks, and Greeks. At the same time, the peoples of the Caucasus and Europe form isolated clusters that do not overlap with the Asian clusters. It is noteworthy that Kurds from our study gravitate towards Tats, which indicates that most likely these two populations are descendants of ancient Medes population. Multidimensional scaling also reveals similarity between gene pool of Yezidis, Kurds with Armenians and Iranians. The analysis of Yezidis pedigrees and their STR variability did not reveal a reliable connection between genetic diversity and caste system. This indicates that the Yezidis caste system is a social division and not a biological one. Thus, we showed that, despite many years of isolation, the gene pool of Yezidis retained a common layer with the gene pool of Kurds, these populations have common spectrum of haplogroups, but Yezidis have lower genetic diversity than Kurds. This study received primary support from the RSF grant No. 16-36-00122 to MC and grant No. 16-06-00364 to EP.

Keywords: gene pool, haplogroup, Kurds, SNP and STR markers, Yezidis

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Authors: Yang Xiong, Hua Cheng

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In this paper, for the basic problem of wireless sensor network topology control and deployment, the Roesser model in rectangular grid sensor networks is presented. In addition, a general constructive realization procedure will be proposed. The procedure enables a distributed implementation of linear systems on a sensor network. A non-trivial example is illustrated.

Keywords: grid sensor networks, Roesser model, state-space realization, multidimensional systems

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Authors: Driouiche Ali, Karmal Ilham

Abstract:

The Agadir region is characterized by a dry climate, ranging from arid attenuated by oceanic influences to hyper-arid. The water mobilized in the agricultural sector of greater Agadir is 95% of underground origin and comes from the water table of Chtouka. The rest represents the surface waters of the Youssef Ben Tachfine dam. These waters are intended for the irrigation of 26880 hectares of modern agriculture. More than 120 boreholes and wells are currently exploited. Their depth varies between 10 m and 200 m and the unit flow rates of the boreholes are 5 to 50 l/s. A drop in the level of the water table of about 1.5 m/year, on average, has been observed during the last five years. Farmers are thus called upon to improve irrigation methods. Thus, localized or drip irrigation is adopted to allow rational use of water. The importance of this irrigation system is due to the fact that water is applied directly to the root zone and its compatibility with fertilization. However, this irrigation system faces a thorny problem which is the clogging of pipes and drippers. This leads to a lack of uniformity of irrigation over time. This so-called scaling phenomenon, the consequences of which are harmful (cleaning or replacement of pipes), leads to considerable unproductive expenditure. The objective set by this work is the search for green inhibitors likely to prevent this phenomenon of scaling. This study requires a better knowledge of these waters, their physico-chemical characteristics and their scaling power. Thus, using the "LCGE" controlled degassing technique, we initially evaluated, on pure calco-carbonic water at 30°F, the scaling-inhibiting power of some available plant extracts in our region of Souss-Massa. We then carried out a comparative study of the efficacy of these green inhibitors. The action of the most effective green inhibitor on real agricultural waters was then studied.

Keywords: green inhibitors, localized irrigation, plant extracts, scaling inhibition

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