Search results for: weighted approximation

Authors: Mandira Mishra, Mark Allen

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This meta-analysis explored whether rejection sensitivity relates to facets of romantic relationships. A comprehensive literature search identified 60 studies (147 effect sizes; 16,955 participants) that met inclusion criteria. Data were analysed using inverse-variance weighted random effects meta-analysis. Mean effect sizes from 21 meta-analyses provided evidence that more rejection sensitive individuals report lower levels of relationship satisfaction and relationship closeness, lower levels of perceived partner satisfaction, a greater likelihood of intimate partner violence (perpetration and victimization), higher levels of relationship concerns and relationship conflict, and higher levels of jealousy and self-silencing behaviours. There was also some evidence that rejection sensitive individuals are more likely to engage in risky sexual behaviour and are more prone to sexual compulsivity. There was no evidence of publication bias and various levels of heterogeneity in computed averages. Random effects meta-regression identified participant age and sex as important moderators of pooled mean effects. These findings provide a foundation for the theoretical development of rejection sensitivity in romantic relationships and should be of interest to relationship and marriage counsellors and other relationship professionals.

Keywords: intimate partner violence, relationship satisfaction, commitment, sexual orientation, risky sexual behaviour

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Authors: N. Mansouri, A. Asadi

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Data Grid is a geographically distributed environment that deals with data intensive application in scientific and enterprise computing. Data replication is a common method used to achieve efficient and fault-tolerant data access in Grids. In this paper, a dynamic data replication strategy, called Enhanced Latest Access Largest Weight (ELALW) is proposed. This strategy is an enhanced version of Latest Access Largest Weight strategy. However, replication should be used wisely because the storage capacity of each Grid site is limited. Thus, it is important to design an effective strategy for the replication replacement task. ELALW replaces replicas based on the number of requests in future, the size of the replica, and the number of copies of the file. It also improves access latency by selecting the best replica when various sites hold replicas. The proposed replica selection selects the best replica location from among the many replicas based on response time that can be determined by considering the data transfer time, the storage access latency, the replica requests that waiting in the storage queue and the distance between nodes. Simulation results utilizing the OptorSim show our replication strategy achieve better performance overall than other strategies in terms of job execution time, effective network usage and storage resource usage.

Keywords: data grid, data replication, simulation, replica selection, replica placement

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Authors: Gulcin Yildiz, Hao Feng

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In recent years there is growing interested in using soy protein because of several advantages compared to other protein sources, such as high nutritional value, steady supply, and low cost. Soy protein isolate (SPI) is the most refined soy protein product. It contains 90% protein in a moisture-free form and has some desirable functionalities. Creating a protein-polysaccharide conjugate to be the emulsifying agent rather than the protein alone can markedly enhance its stability. This study was undertaken to examine the effects of ultrasound treatments on the physicochemical properties of SPI-starch conjugates. The soy protein isolate (SPI, Pro-Fam® 955) samples were obtained from the Archer Daniels Midland Company. Protein concentrations were analyzed by the Bardford method using BSA as the standard. The volume-weighted mean diameters D [4,3] of protein–polysaccharide conjugates were measured by dynamic light scattering (DLS). Surface hydrophobicity of the conjugates was measured by using 1-anilino-8-naphthalenesulfonate (ANS) (Sigma-Aldrich, St. Louis, MO, USA). Increasing the pH from 2 to 12 resulted in increased protein solubility. The highest solubility was 69.2% for the sample treated with ultrasonication at pH 12, while the lowest (9.13%) was observed in the Control. For the other pH conditions, the protein solubility values ranged from 40.53 to 49.65%. The ultrasound treatment significantly decreased the particle sizes of the SPI-modified starch conjugates. While the D [4,3] for the Control was 731.6 nm, it was 293.7 nm for the samples treated by sonication at pH 12. The surface hydrophobicity (H0) of SPI-starch at all pH conditions were significantly higher than those in the Control. Ultrasonication was proven to be effective in improving the solubility and emulsifying properties of soy protein isolate-starch conjugates.

Keywords: particle size, solubility, soy protein isolate, ultrasonication

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Authors: Mohanad Alhabo, Li Zhang, Naveed Nawaz

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Small cell deployment in 5G networks is a promising technology to enhance capacity and coverage. However, unplanned deployment may cause high interference levels and high number of unnecessary handovers, which in turn will result in an increase in the signalling overhead. To guarantee service continuity, minimize unnecessary handovers, and reduce signalling overhead in heterogeneous networks, it is essential to properly model the handover decision problem. In this paper, we model the handover decision according to Multiple Attribute Decision Making (MADM) method, specifically Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). In this paper, we propose a hybrid TOPSIS method to control the handover in heterogeneous network. The proposed method adopts a hybrid weighting, which is a combination of entropy and standard deviation. A hybrid weighting control parameter is introduced to balance the impact of the standard deviation and entropy weighting on the network selection process and the overall performance. Our proposed method shows better performance, in terms of the number of frequent handovers and the mean user throughput, compared to the existing methods.

Keywords: handover, HetNets, interference, MADM, small cells, TOPSIS, weight

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Authors: M. Khalid, W. Rashmi, L. L. Kwan

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This work provides an overview on the experimental and numerical simulations of various nanofluids and their flow and heat transfer behavior. It was further extended to study the effect of nanoparticle concentration, fluid flow rates and thermo-physical properties on the heat transfer enhancement of Al2O3/water nanofluid in a turbulent flow circular conduit using ANSYS FLUENT™ 14.0. Single-phase approximation (homogeneous model) and two-phase (mixture and Eulerian) models were used to simulate the nanofluid flow behavior in the 3-D horizontal pipe. The numerical results were further validated with experimental correlations reported in the literature. It was found that heat transfer of nanofluids increases with increasing particle volume concentration and Reynolds number, respectively. Results showed good agreement (~9% deviation) with the experimental correlations, especially for a single-phase model with constant properties. Among two-phase models, mixture model (~14% deviation) showed better prediction compared to Eulerian-dispersed model (~18% deviation) when temperature independent properties were used. Non-drag forces were also employed in the Eulerian two-phase model. However, the two-phase mixture model with temperature dependent nanofluid properties gave slightly closer agreement (~12% deviation).

Keywords: nanofluid, CFD, heat transfer, forced convection, circular conduit

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Authors: William Chung

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This paper is to study the use of multiple subproblems in Dantzig-Wolfe decomposition of linear programming (DW-LP). Traditionally, the decomposed LP consists of one LP master problem and one LP subproblem. The master problem and the subproblem is solved alternatively by exchanging the dual prices of the master problem and the proposals of the subproblem until the LP is solved. It is well known that convergence is slow with a long tail of near-optimal solutions (asymptotic convergence). Hence, the performance of DW-LP highly depends upon the number of decomposition steps. If the decomposition steps can be greatly reduced, the performance of DW-LP can be improved significantly. To reduce the number of decomposition steps, one of the methods is to increase the number of proposals from the subproblem to the master problem. To do so, we propose to add a quadratic approximation function to the LP subproblem in order to develop a set of approximate-LP subproblems (multiple subproblems). Consequently, in each decomposition step, multiple subproblems are solved for providing multiple proposals to the master problem. The number of decomposition steps can be reduced greatly. Note that each approximate-LP subproblem is nonlinear programming, and solving the LP subproblem must faster than solving the nonlinear multiple subproblems. Hence, using multiple subproblems in DW-LP is the tradeoff between the number of approximate-LP subproblems being formed and the decomposition steps. In this paper, we derive the corresponding algorithms and provide some simple computational results. Some properties of the resulting algorithms are also given.

Keywords: approximate subproblem, Dantzig-Wolfe decomposition, large-scale models, multiple subproblems

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Authors: Ilaria Lucrezia Amerise

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The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages.

Keywords: generalized extreme values, likelihood estimation, precipitation data, Wakeby distribution

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Authors: Fuyuan Ma, Ying Wang, Xin Wang

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Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.

Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior

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Authors: Yingkun Huang, Li Guo, Zekang Lan, Kai Tian

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Hard disk drives (HDD) failure of the exascale supercomputing system may lead to service interruption and invalidate previous calculations, and it will cause permanent data loss. Therefore, initiating corrective actions before hard drive failures materialize is critical to the continued operation of jobs. In this paper, a highly accurate analysis model based on CNN-LSTM and oversampling technique was proposed, which can correctly predict the necessity of a disk replacement even ten days in advance. Generally, the learning-based method performs poorly on a training dataset with long-tail distribution, especially fault prediction is a very classic situation as the scarcity of failure data. To overcome the puzzle, a new oversampling was employed to augment the data, and then, an improved CNN-LSTM with the shortcut was built to learn more effective features. The shortcut transmits the results of the previous layer of CNN and is used as the input of the LSTM model after weighted fusion with the output of the next layer. Finally, a detailed, empirical comparison of 6 prediction methods is presented and discussed on a public dataset for evaluation. The experiments indicate that the proposed method predicts disk failure with 0.91 Precision, 0.91 Recall, 0.91 F-measure, and 0.90 MCC for 10 days prediction horizon. Thus, the proposed algorithm is an efficient algorithm for predicting HDD failure in supercomputing.

Keywords: HDD replacement, failure, CNN-LSTM, oversampling, prediction

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Authors: N. Guo, C. Xu, Z. C. Yang

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In order to ensure the high reliability of an aircraft, the accurate structural dynamics analysis has become an indispensable part in the design of an aircraft structure. Therefore, the structural finite element model which can be used to accurately calculate the structural dynamics and their transfer relations is the prerequisite in structural dynamic design. A dynamic finite element model updating method is presented to correct the uncertain parameters of the finite element model of a structure using measured modal parameters. The coordinate modal assurance criterion is used to evaluate the correlation level at each coordinate over the experimental and the analytical mode shapes. Then, the weighted summation of the natural frequency residual and the coordinate modal assurance criterion residual is used as the objective function. Moreover, the hybrid pattern search (HPS) optimization technique, which synthesizes the advantages of pattern search (PS) optimization technique and genetic algorithm (GA), is introduced to solve the dynamic FE model updating problem. A numerical simulation and a model updating experiment for GARTEUR aircraft model are performed to validate the feasibility and effectiveness of the present dynamic model updating method, respectively. The updated results show that the proposed method can be successfully used to modify the incorrect parameters with good robustness.

Keywords: model updating, modal parameter, coordinate modal assurance criterion, hybrid genetic/pattern search

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Authors: Si Chen, Le Zhang, Xian He

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The research explored the influences of public open space system on housing price through hedonic models, in order to support better open space plans and economic policies. We have three initial hypotheses: 1) public open space system has an overall positive influence on surrounding housing prices. 2) Different public open space types have different levels of influence on motivating surrounding housing prices. 3) Walking and driving accessibilities from property to public open spaces have different statistical relation with housing prices. Cook County, Illinois, was chosen to be a study area since data availability, sufficient open space types, and long-term open space preservation strategies. We considered the housing attributes, driving and walking accessibility scores from houses to nearby public open spaces, and driving accessibility scores to hospitals as influential features and used real housing sales price in 2010 as a dependent variable in the built hedonic model. Through ordinary least squares (OLS) regression analysis, General Moran’s I analysis and geographically weighted regression analysis, we observed the statistical relations between public open spaces and housing sale prices in the three built hedonic models and confirmed all three hypotheses.

Keywords: hedonic model, public open space, housing sale price, regression analysis, accessibility score

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Authors: Leandro Marcos Alves Vaz

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In this article, we analyze the different approaches to the topic Magnetism of Matter in physics textbooks of Brazilian schools. For this, we compared the approach to the concepts of the magnetic characteristics of materials (diamagnetism, paramagnetism, ferromagnetism and antiferromagnetism) in different sources of information and in different levels of education, from Higher Education to High School. In this sense, we used as reference the theory of the Didactic Transposition of Yves Chevallard, a French educational theorist, who conceived in his theory three types of knowledge – Scholarly Knowledge, Knowledge to be taught and Taught Knowledge – related to teaching practice. As a research methodology, from the reading of the works used in teacher training and those destined to basic education students, we compared the treatment of a higher education physics book, a scientific article published in a Brazilian journal of the educational area, and four high school textbooks, in order to establish in which there is a greater or lesser degree of approximation with the knowledge produced by the scholars – scholarly knowledge – or even with the knowledge to be taught (to that found in books intended for teaching). Thus, we evaluated the level of proximity of the subjects conveyed in high school and higher education, as well as the relevance that some textbook authors give to the theme.

Keywords: Brazilian physics books, didactic transposition, magnetism of matter, teaching of physics

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Ghodbane Azeddine, Saad Maarouf, Boland Jean-Francois, Thibeault Claude

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This paper proposes a new design of an active fault-tolerant flight control system against abrupt actuator faults. This overall system combines a multiple time scale sliding mode controller for fault compensation and a geometric approach for fault detection and diagnosis. The proposed control system is able to accommodate several kinds of partial and total actuator failures, by using available healthy redundancy actuators. The overall system first estimates the correct fault information using the geometric approach. Then, and based on that, a new reconfigurable control law is designed based on the multiple time scale sliding mode technique for on-line compensating the effect of such faults. This approach takes advantages of the fact that there are significant difference between the time scales of aircraft states that have a slow dynamics and those that have a fast dynamics. The closed-loop stability of the overall system is proved using Lyapunov technique. A case study of the non-linear model of the F16 fighter, subject to the rudder total loss of control confirms the effectiveness of the proposed approach.

Keywords: actuator faults, fault detection and diagnosis, fault tolerant flight control, sliding mode control, multiple time scale approximation, geometric approach for fault reconstruction, lyapunov stability

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Authors: Aicha Bouhlala, Sabah Chettibi

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A systematic investigation on structural, electronic, and magnetic properties of Ce₀.₇₅A₀.₂₅O₂ (A = W, Mo) is performed using first-principles calculations within the framework Full-Potential Linear Augmented Plane Wave (FP-LAPW) method based on the Density Functional Theory (DFT). The exchange-correlation potential has been treated using the generalized gradient approximation (WC-GGA) developed by Wu-Cohen. The host compound CeO2 was doped with transition metal atoms W and Mo in the doping concentration of 25% to replace the Ce atom. In structural properties, the equilibrium lattice constant is observed for the W-doped CeO₂ compound which exists within the value of 5.314 A° and the value of 5.317 A° for Mo-doped CeO2. The present results show that Ce₀.₇₅A₀.₂₅O₂ (A=W, Mo) systems exhibit semiconducting behavior in both spin channels. Although undoped CeO₂ is a non-magnetic semiconductor. The band structure of these doped compounds was plotted and they exhibit direct band gap at the Fermi level (EF) in the majority and minority spin channels. In the magnetic properties, the doped atoms W and Mo play a vital role in increasing the magnetic moments of the supercell and the values of the total magnetic moment are found to be 1.998 μB for Ce₀.₇₅W₀.₂₅O₂ and to be 2.002 μB for Ce₀.₇₅Mo₀.₂₅O₂ compounds. Calculated results indicate that the magneto-electronic properties of the Ce₁₋ₓAₓO₂(A= W, Mo) oxides supply a new way to the experimentalist for the potential applications in spintronics devices.

Keywords: FP-LAPW, DFT, CeO₂, properties

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Authors: Beddiaf Abdelaziz

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The optical characteristics of thin films of silicon oxynitride SiOₓNy prepared by the Low-Pressure Chemical Vapor Deposition (LPCVD) technique have been studied. The films are elaborated from the SiH₂Cl₂, N₂O and NH₃ gaseous mixtures. The flows of SiH₂Cl₂ and (N₂O+NH₃) are 200 sccm and 160 sccm respectively. The deposited films have been characterized by ellipsometry, to model our silicon oxynitride SiOₓNy films. We have suggested two theoretical models (Maxwell Garnett and Bruggeman effective medium approximation (BEMA)). These models have been applied on silicon oxynitride considering the material as a heterogeneous medium formed by silicon oxide and silicon nitride. The model's validation was justified by the confrontation of theoretical spectra and those measured by ellipsometry. This result permits us to obtain the optical refractive coefficient of these films and their thickness. Ellipsometry analysis of the optical properties of the SiOₓNy films shows that the SiO₂ fraction decreases when the gaseous ratio NH₃/N₂O increases. Whereas the increase of this ratio leads to an increase of the silicon nitride Si3N4 fraction. The study also shows that the increasing gaseous ratio leads to a strong incorporation of nitrogen atoms in films. Also, the increasing of the SiOₓNy refractive coefficient until the SiO₂ value shows that this insulating material has good dielectric quality.

Keywords: ellipsometry, silicon oxynitrde, model, refractive coefficient, effective medium

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Authors: K. Umbleja, M. Ichino

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Symbolic data mining has been developed to analyze data in very large datasets. It is also useful in cases when entry specific details should remain hidden. Symbolic data mining is quickly gaining popularity as datasets in need of analyzing are becoming ever larger. One type of such symbolic data is a histogram, which enables to save huge amounts of information into a single variable with high-level of granularity. Other types of symbolic data can also be described in histograms, therefore making histogram a very important and general symbolic data type - a method developed for histograms - can also be applied to other types of symbolic data. Due to its complex structure, analyzing histograms is complicated. This paper proposes a method, which allows to compare two histogram-valued variables and therefore find a dissimilarity between two histograms. Proposed method uses the Ichino-Yaguchi dissimilarity measure for mixed feature-type data analysis as a base and develops a dissimilarity measure specifically for histogram data, which allows to compare histograms with different number of bins and bin widths (so called general histogram). Proposed dissimilarity measure is then used as a measure for clustering. Furthermore, linkage method based on weighted averages is proposed with the concept of cluster compactness to measure the quality of clustering. The method is then validated with application on real datasets. As a result, the proposed dissimilarity measure is found producing adequate and comparable results with general histograms without the loss of detail or need to transform the data.

Keywords: dissimilarity measure, hierarchical clustering, histograms, symbolic data analysis

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Authors: S. Pooja Pragati, B. Sudarsan, S. Rajkumar

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Silver nanoparticles (AgNP) are known for their excellent antimicrobial agents, and thus can be used as alternative disinfectant agents. However, released silver nanoparticles is a threat to naturally occurring microorganisms. This paper exhibits information on the environmental fate, toxicological effects, and application of AgNP and the current estimate on the physicochemical and antimicrobial properties of AgNP in different aqueous solutions, as well as their application as alternative disinfectants in water-treatment systems. It also gives a better approximation and experimental data of AgNP’s antimicrobial properties at different water chemistry conditions. A saturation-type fitting curve was established, showing the survival of bacteria under different water chemistry conditions as a function of the size of the nanoparticles. The results obtained show that silver nanoparticles in surface water, ground water, and brackish water are stable. The paper demonstrates the comparative study of AgNP-impregnated point-of-use ceramic water filters and ceramic filters impregnated with silver nitrate. It is observed that AgNP-impregnated ceramic water filters are more appropriate for this application due to the lesser amount of silver desorbed. Experimental data of the comparison of a polymer-based quaternary amine functionalized silsesquioxanes compound and AgNP are also tabulated and conclusions are analysed with the goal of optimizing. The simplicity of synthesis and application of Silver nanoparticles enables us to consider its effective modified version for the purification of water.

Keywords: disinfectant agent, purification of water, nano particles, water treatment

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Authors: Sareh Rajabi, Salwa Bheiry

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In general, Covid-19 created many financial and non-financial damages to the economy and community. Level and severity of covid-19 as pandemic case varies over the region and due to different types of the projects. Covid-19 virus emerged as one of the most imperative risk management factors word-wide recently. Therefore, as part of portfolio management assessment, it is essential to evaluate severity of such risk on the project and program in portfolio management level to avoid any risky portfolio. Covid-19 appeared very effectively in South America, part of Europe and Middle East. Such pandemic infection affected the whole universe, due to lock down, interruption in supply chain management, health and safety requirements, transportations and commercial impacts. Therefore, this research proposes Analytical Hierarchy Process (AHP) to analyze and assess such pandemic case like Covid-19 and its impacts on the construction projects. The AHP technique uses four sub-criteria: Health and safety, commercial risk, completion risk and contractual risk to evaluate the project and program. The result will provide the decision makers with information which project has higher or lower risk in case of Covid-19 and pandemic scenario. Therefore, the decision makers can have most feasible solution based on effective weighted criteria for project selection within their portfolio to match with the organization’s strategies.

Keywords: portfolio management, risk management, COVID-19, analytical hierarchy process technique

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Authors: Rahul S. Raj

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Electro-mechanical impedance technique is a recently developed non-destructive method for structural health monitoring. This system comprises of piezo electric patch, bonded to the structure using an adhesive/epoxy and electrically excited to determine the health of the component. The subjected electric field actuates the PZT patch harmonically and imparts a force on the host structure. The structural response thus produced by the host component is in the form of peaks and valleys which further shows the admittance signatures of the structure for the given excitation frequency. Adhesives have the capability to change the structural signatures, in EMI technique, by transforming conductance and susceptance signatures. The static approximation provide a justifiable result where adhesive bond lines are thin and stiff. The epoxy adhesive bonds limits design flexibility due to poor bond strengths, hence to enhance the performance of the joints, a new technique is developed for joining PZT, i.e. the alloy bonding technique. It is a metallic joining compound which contains many active elements including Titanium, that reacts with the tenacious surface films of the ceramic and composites to create excellent bonds. This alloy-based bonding technique will be used for better strain interaction and rigorous stress transfer between PZT patch and the host structure.

Keywords: EMI technique, conductance, susceptance, admittance, alloy bonding

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Authors: Diana Ruth Caga-Anan

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Classroom management is a critical skill but the styles are constantly evolving. It is constantly under pressure particularly in the college education level due to diversity in student profiles, modes of delivery, and marketization of higher education. This study sought to analyze the extent of implementation of classroom management practices (CMPs) of the college instructors of the Hotel, Restaurant, and Institution Management of a premier university in the Philippines. It was also determined if their length of teaching affects their classroom management style. A questionnaire with sixteen 'evidenced-based' CMPs grouped into five critical features of classroom management, adopted from the literature search of Simonsen et al. (2008), was administered to 4 instructor-respondents and to their 88 students. Weighted mean scores of each of the CMPs revealed that there were differences between the instructors’ self-scores and their students’ ratings on their implementation of CMPs. The critical feature of classroom management 'actively engage students in observable ways' got the highest mean score, corresponding to 'always' from the instructors’ self-rating and 'frequently' from their students’ ratings. However, 'use a continuum of strategies to respond to inappropriate behaviors' got the lowest scores from both the instructors and their students corresponding only to 'occasionally'. Analysis of variance showed that the only CMP affected by the length of teaching is the practice of 'prompting students to respond'. Based on the findings, some recommendations for the instructors to improve on the critical feature where they scored low are discussed and suggestions are included for future research.

Keywords: classroom management, CMPs, critical features, evidence-based classroom management practices

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Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng

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To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.

Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation

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Authors: Graziela D. de Azevedo, Livia M. Pagotto, Mario P. Monzoni, Neto

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This article aims to discuss partnerships between public administration and private social investment aimed at territorial development. There has been some approximation in Brazil from private social investors with initiatives aiming at territorial development policies in highly vulnerable territories or in places where the business sector operates. This represents this paper’s major justification: on the advance of academic debate about how businesses, institutes, and foundations have been working alongside local governments, taking the territory as the reference for joint action. The research was based on the literature on governance and territorial development and adopted a mixed iterative approach (inductive and deductive) through an interpretative lens so as to develop an analysis structure that complements and expands knowledge about the contribution of public policies and private social investments for territorial development in Brazil. The analysis of 15 cases based on three distinct blocks (territorial development plans, articulation for education, and thematic approaches) has made it possible to identify common elements regarding the motivations of partnerships, the specific needs of the actors involved, and the priority drivers for stimulating development. Findings include discussion on the leading role of territories in their development paths, on the institutionalization and strengthening of capacities, and on long-term perspectives in development strategies.

Keywords: private social investment, public administration, territorial governance, territorial development

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Authors: Javad Rahimipour Anaraki, Saeed Samet, Mahdi Eftekhari, Chang Wook Ahn

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Feature selection and attribute reduction are crucial problems, and widely used techniques in the field of machine learning, data mining and pattern recognition to overcome the well-known phenomenon of the Curse of Dimensionality. This paper presents a feature selection method that efficiently carries out attribute reduction, thereby selecting the most informative features of a dataset. It consists of two components: 1) a measure for feature subset evaluation, and 2) a search strategy. For the evaluation measure, we have employed the fuzzy-rough dependency degree (FRFDD) of the lower approximation-based fuzzy-rough feature selection (L-FRFS) due to its effectiveness in feature selection. As for the search strategy, a modified version of a binary shuffled frog leaping algorithm is proposed (B-SFLA). The proposed feature selection method is obtained by hybridizing the B-SFLA with the FRDD. Nine classifiers have been employed to compare the proposed approach with several existing methods over twenty two datasets, including nine high dimensional and large ones, from the UCI repository. The experimental results demonstrate that the B-SFLA approach significantly outperforms other metaheuristic methods in terms of the number of selected features and the classification accuracy.

Keywords: binary shuffled frog leaping algorithm, feature selection, fuzzy-rough set, minimal reduct

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Authors: Villiam Ambong, Kevin Banawag, Wynne Shane Bugatan, Mark Alvin Jay Carpio, Hwan Hee Choi, Moises Kevin Chungalao

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This survey research investigated the perception of primary school teachers on the efficacy of MTB-MLE in SLU-LES, Baguio City. SLU-LES has a total of 21 primary school teachers who served as respondents of this study in an attempt to answer the major questions regarding the efficacy of MTB-MLE among primary school teachers. A questionnaire was used in collecting the data which were analyzed using weighted mean and ANOVA. The questionnaire was validated by a statistician and it was administered to a school which does not differ from the intended respondents for further validation of the items. Findings revealed from the intended respondents that they perceive MTB-MLE as effective; however, they do not prefer the use of Mother Tongue as a medium of instruction. A research on the same topic was conducted in Ibadan, Nigeria by Dr. David O. Fakeye and although his respondents were students; the results came out that the respondents do perceive MTB-MLE to be efficacious. The results of this study also showed that years of teaching experience and the number of languages spoken by the teachers have no bearing on the preference of the respondents between MT medium and English medium gave that the respondents are in melting pot community. Comparative studies between rural and urban schools are encouraged. Future researchers should include questions that elicit reasons of the respondents on the efficacy of mother tongue as well as their preference between mother tongue medium and English.

Keywords: mother tongue, primary teachers, perception, multilingual education

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Authors: Muhammad Anwar, Ameen Ullah, Intakhab Alam Qadri

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This study presents a technique utilizing the Iterative Rational Krylov Algorithm (IRKA) to reduce the order of large-scale descriptor systems. Descriptor systems, which incorporate differential and algebraic components, pose unique challenges in Model Order Reduction (MOR). The proposed method partitions the descriptor system into polynomial and strictly proper parts to minimize approximation errors, applying IRKA exclusively to the strictly adequate component. This approach circumvents the unbounded errors that arise when IRKA is directly applied to the entire system. A comparative analysis demonstrates the high accuracy of the reduced model and a significant reduction in computational burden. The reduced model enables more efficient simulations and streamlined controller designs. The study highlights IRKA-based MOR’s effectiveness in optimizing complex systems’ performance across various engineering applications. The proposed methodology offers a promising solution for reducing the complexity of large-scale descriptor systems while maintaining their essential characteristics and facilitating their analysis, simulation, and control design.

Keywords: model order reduction, descriptor systems, iterative rational Krylov algorithm, interpolatory model reduction, computational efficiency, projection methods, H₂-optimal model reduction

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Authors: Villiam C. Ambong, Kevin G. Banawag, Wynne Shane B. Bugatan, Mark Alvin Jay R. Carpio, Hwan Hee Choi, Moses Kevin L. Chungalao

Abstract:

This survey research investigated the perception of primary school teachers on the efficacy of MTB-MLE in SLU-LES, Baguio City. SLU-LES has a total of 21 primary school teachers who served as the respondents of this study in an attempt to answer three major questions regarding the efficacy of MTB-MLE among primary school teachers. A questionnaire was used in collecting the data which were analyzed using weighted mean and ANOVA. The questionnaire was validated by a statistician and it was administered to a school which does not differ from the intended respondents for further validation of the items. Findings revealed from the intended respondents that they perceive MTB-MLE as effective; however, they do not prefer the use of Mother Tongue as medium of instruction. A research of the same topic was conducted in Ibadan, Nigeria by Dr. David O. Fakeye and although his respondents were students; the results came out that the respondents do perceive MTB-MLE to be efficacious. The results of this study also showed that years of teaching experience and number of languages spoken by the teachers have no bearing on the preference of the respondents between MT medium and English medium given that the respondents are in a melting pot community. Comparative studies between rural schools and urban schools are encouraged. Future researches should include questions that elicit reasons of the respondents on the efficacy of mother tongue as well as their preference between mother tongue medium and English.

Keywords: mother tongue, primary teachers, perception, multilingual education

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Authors: Bindu Kumari, Bindu Kumari Singh

Abstract:

Endosulfan is known to be one of the highly toxic agricultural pesticides commonly used in our societies. With the widespread use of Endosulfan in agriculture, human beings are most likely to be exposed to it, either orally by eating Endosulfan-contaminated foods or by nose and whole body inhalation in the farms during its application. The present study was conducted to observe the changes in the serum uric acid level of the Swiss albino rats due to the administration of Endosulfan. 3.0 mg Endosulfan/kg body weight was daily administered orally to albino rats for 28 days period. Alterations in their K.F.T. parameters were recorded at a regular interval of 7 days within this 28 days period and were compared with those of control rats. All rats were monitored for any observable toxic symptoms throughout the experimental period and they also were weighted weekly to monitor body weight gain. Alteration recorded in K.F.T. parameters within the groups were due to Endosulfan exposure and serum uric acid level was significantly elevated in the 3mg/kg dose group. Pathological changes of rats treated with Endosulfan were observed with typical signs of toxicity. Uric acid is a heterocyclic compound formed as an end product of metabolism of purine nucleotides. It forms ions and salts known as urate and acid urate which are harmful to our health. Uric acid clearance is one of the numerous important functions of the kidney. Defects in this process resulted in Gout, kidney stone or Kidney failure.

Keywords: KFT parameters, blood uric acid level, endosulfan, eat

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Authors: Jie Huo, Jonathan Wu

Abstract:

Segmentation of anatomical structures in medical images is essential for scientific inquiry into the complex relationships between biological structure and clinical diagnosis, treatment and assessment. As a method of incorporating the prior knowledge and the anatomical structure similarity between a target image and atlases, multi-atlas segmentation has been successfully applied in segmenting a variety of medical images, including the brain, cardiac, and abdominal images. The basic idea of multi-atlas segmentation is to transfer the labels in atlases to the coordinate of the target image by matching the target patch to the atlas patch in the neighborhood. However, this technique is limited by the pairwise registration between target image and atlases. In this paper, a novel multi-atlas segmentation approach is proposed by introducing a dynamic energy model. First, the target is mapped to each atlas image by minimizing the dynamic energy function, then the segmentation of target image is generated by weighted fusion based on the energy. The method is tested on MICCAI 2012 Multi-Atlas Labeling Challenge dataset which includes 20 target images and 15 atlases images. The paper also analyzes the influence of different parameters of the dynamic energy model on the segmentation accuracy and measures the dice coefficient by using different feature terms with the energy model. The highest mean dice coefficient obtained with the proposed method is 0.861, which is competitive compared with the recently published method.

Keywords: brain MRI segmentation, dynamic energy model, multi-atlas segmentation, energy minimization

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Authors: Anupam Sibal

Abstract:

Whatever is measured tends to improve. With a view to objectively measuring and improving clinical quality across the Apollo Group Hospitals, the initiative of ACE @ 25 (Apollo Clinical Excellence@25) was launched on Jan 09. ACE @ 25 is a clinically balanced scorecard incorporating 25 clinical quality parameters involving complication rates, mortality rates, one-year survival rates and average length of stay after major procedures like liver and renal transplant, CABG, TKR, THR, TURP, PTCA, endoscopy, large bowel resection and MRM covering all major specialties. Also included are hospital acquired infection rates, pain satisfaction and medication errors. Benchmarks have been chosen from the world’s best hospitals. There are weighted scores for outcomes color coded green, orange and red. The cumulative score is 100. Data is reported monthly by 43 Group Hospitals online on the Lighthouse platform. Action taken reports for parameters falling in red are submitted quarterly and reviewed by the board. An audit team audits the data at all locations every six months. Scores are linked to appraisal of the medical head and there is an “ACE @ 25” Champion Award for the highest scorer. Scores for different parameters were variable from green to red at the start of the initiative. Most hospitals showed an improvement in scores over the last four years for parameters where they had showed scores in red or orange at the start of the initiative. The overall scores for the group have shown an increase from 72 in 2010 to 81 in 2015.

Keywords: benchmarks, clinical quality, lighthouse, platform, scores

Procedia PDF Downloads 301