Search results for: linear prediction analysis

Authors: S. B. Rushayati, R. Meilani, R. Hermawan

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A biosphere reserve is developed to create harmony amongst economic development, community development, and environmental protection, through partnership between human and nature. Giam Siak Kecil Bukit Batu Biosphere Reserve (GSKBB BR) in Riau Province, Indonesia, is unique in that it has peat soil dominating the area, many springs essential for human livelihood, high biodiversity. Furthermore, it is the only biosphere reserve covering privately managed production forest areas. In this research, we aimed at analyzing the threat of deforestation and forest fire, and the potential of CO2 emission at GSKBB BR. We used Landsat image, arcView software, and ERDAS IMAGINE 8.5 Software to conduct spatial analysis of land cover and land use changes, calculated CO2 emission based on emission potential from each land cover and land use type, and exercised simple linear regression to demonstrate the relation between CO2 emission potential and deforestation. The result showed that, beside in the buffer zone and transition area, deforestation also occurred in the core area. Spatial analysis of land cover and land use changes from years 2010, 2012, and 2014 revealed that there were changes of land cover and land use from natural forest and industrial plantation forest to other land use types, such as garden, mixed garden, settlement, paddy fields, burnt areas, and dry agricultural land. Deforestation in core area, particularly at the Giam Siak Kecil Wildlife Reserve and Bukit Batu Wildlife Reserve, occurred in the form of changes from natural forest in to garden, mixed garden, shrubs, swamp shrubs, dry agricultural land, open area, and burnt area. In the buffer zone and transition area, changes also happened, what once swamp forest changed into garden, mixed garden, open area, shrubs, swamp shrubs, and dry agricultural land. Spatial analysis on land cover and land use changes indicated that deforestation rate in the biosphere reserve from 2010 to 2014 had reached 16 119 ha/year. Beside deforestation, threat toward the biosphere reserve area also came from forest fire. The occurrence of forest fire in 2014 had burned 101 723 ha of the area, in which 9 355 ha of core area, and 92 368 ha of buffer zone and transition area. Deforestation and forest fire had increased CO2 emission as much as 24 903 855 ton/year.

Keywords: Biosphere reserve, CO2 emission, deforestation, forest fire.

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Authors: J. R. Wang, H. C. Chen, C. Shih, S. W. Chen, J. H. Yang, Y. Chiang

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In this study, we focus on the establishment of the analysis model for Maanshan PWR nuclear power plant (NPP) by using RADTRAD and SNAP codes with the FSAR, manuals, and other data. In order to evaluate the cumulative dose at the Exclusion Area Boundary (EAB) and Low Population Zone (LPZ) outer boundary, Maanshan NPP RADTRAD/SNAP model was used to perform the analysis of the DBA LOCA case. The analysis results of RADTRAD were similar to FSAR data. These analysis results were lower than the failure criteria of 10 CFR 100.11 (a total radiation dose to the whole body, 250 mSv; a total radiation dose to the thyroid from iodine exposure, 3000 mSv).

Keywords: RADionuclide, transport, removal, and dose estimation, RADTRAD, symbolic nuclear analysis package, SNAP, dose, PWR.

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Authors: Tawakal Hasnain Baluch, Adnan Masood, Javaid Iqbal, Umer Izhar, Umar Shahbaz Khan

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This paper will provide the kinematic and dynamic analysis of a lower limb exoskeleton. The forward and inverse kinematics of proposed exoskeleton is performed using Denevit and Hartenberg method. The torques required for the actuators will be calculated using Lagrangian formulation technique. This research can be used to design the control of the proposed exoskeleton.

Keywords: Dynamic Analysis, Exoskeleton, Kinematic Analysis, Lower Limb, Rehabilitation Robotics

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Authors: S. Behnia, S. Fathizadeh

Abstract:

Conductivity properties of DNA molecule is investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. This model is a tight-binding linear nanoscale chain. We have tried to study the electrical current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: Charge transfer in DNA, Chaos theory, Molecular electronics, Negative Differential resistance.

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Authors: Chongyang Ye, Rong Liu

Abstract:

Compression textiles such as compression stockings (CSs) have been extensively applied for the prevention and treatment of chronic venous insufficiency of lower extremities. The involvement of multiple mechanical factors such as interface pressure, frictional force, and elastic materials make the interactions between lower limb and CSs to be complex. Determination of Poisson’s ratio and elastic moduli of CS materials are critical for constructing finite element (FE) modeling to numerically simulate a complex interactive system of CS and lower limb. In this study, a mixed approach, including an analytic model based on the orthotropic Hooke’s Law and experimental study (uniaxial tension testing and pure shear testing), has been proposed to determine Young’s modulus, Poisson’s ratio, and shear modulus of CS fabrics. The results indicated a linear relationship existing between the stress and strain properties of the studied CS samples under controlled stretch ratios (< 100%). The proposed method and the determined key mechanical properties of elastic orthotropic CS fabrics facilitate FE modeling for analyzing in-depth the effects of compression material design on their resultant biomechanical function in compression therapy.

Keywords: Elastic compression stockings, Young’s modulus, Poisson’s ratio, shear modulus, mechanical analysis.

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Authors: Lili Wang

Abstract:

By using the estimation of the Cauchy matrix of linear impulsive differential equations and Banach fixed point theorem as well as Gronwall-Bellman’s inequality, some sufficient conditions are obtained for the existence and exponential stability of almost periodic solution for an impulsive neural networks with distributed delays. An example is presented to illustrate the feasibility and  effectiveness of the results.

Keywords: Almost periodic solution, Exponential stability, Neural networks, Impulses.

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Authors: Chen Zhang, Bernhard Schwarz-Röhr, Alexander Härting

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To acquire accurate ship motions at the center of gravity, a single low-cost inertial sensor is utilized and applied on board to measure ship oscillating motions. As observations, the three axes accelerations and three axes rotational rates provided by the sensor are used. The mathematical model of processing the observation data includes determination of the distance vector between the sensor and the center of gravity in x, y, and z directions. After setting up the transfer matrix from sensor’s own coordinate system to the ship’s body frame, an extended Kalman filter is applied to deal with nonlinearities between the ship motion in the body frame and the observation information in the sensor’s frame. As a side effect, the method eliminates sensor noise and other unwanted errors. Results are not only roll and pitch, but also linear motions, in particular heave and surge at the center of gravity. For testing, we resort to measurements recorded on a small vessel in a well-defined sea state. With response amplitude operators computed numerically by a commercial software (Seaway), motion characteristics are estimated. These agree well with the measurements after processing with the suggested method.

Keywords: Extended Kalman filter, nonlinear estimation, sea trial, ship motion estimation.

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life due to the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or COVID-19 induced pneumonia. The early prediction and classification of such lung diseases help reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans are pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publicly available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scans, COVID-19, deep learning, image processing, pneumonia, lung disease.

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Authors: Gregor A. Morrison, Dominic P. Searson, Mark J. Willis

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The purpose of this paper is to demonstrate the ability of a genetic programming (GP) algorithm to evolve a team of data classification models. The GP algorithm used in this work is “multigene" in nature, i.e. there are multiple tree structures (genes) that are used to represent team members. Each team member assigns a data sample to one of a fixed set of output classes. A majority vote, determined using the mode (highest occurrence) of classes predicted by the individual genes, is used to determine the final class prediction. The algorithm is tested on a binary classification problem. For the case study investigated, compact classification models are obtained with comparable accuracy to alternative approaches.

Keywords: classification, genetic programming.

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Authors: Mahmood Ahmad, Ghulam Murtaza, Sonia Khiljee, Muhammad Asadullah Madni

Abstract:

A new reverse phase-high performance liquid chromatography (RP-HPLC) method with fluorescent detector (FLD) was developed and optimized for Norfloxacin determination in human plasma. Mobile phase specifications, extraction method and excitation and emission wavelengths were varied for optimization. HPLC system contained a reverse phase C18 (5 μm, 4.6 mm×150 mm) column with FLD operated at excitation 330 nm and emission 440 nm. The optimized mobile phase consisted of 14% acetonitrile in buffer solution. The aqueous phase was prepared by mixing 2g of citric acid, 2g sodium acetate and 1 ml of triethylamine in 1 L of Milli-Q water was run at a flow rate of 1.2 mL/min. The standard curve was linear for the range tested (0.156–20 μg/mL) and the coefficient of determination was 0.9978. Aceclofenac sodium was used as internal standard. A detection limit of 0.078 μg/mL was achieved. Run time was set at 10 minutes because retention time of norfloxacin was 0.99 min. which shows the rapidness of this method of analysis. The present assay showed good accuracy, precision and sensitivity for Norfloxacin determination in human plasma with a new internal standard and can be applied pharmacokinetic evaluation of Norfloxacin tablets after oral administration in human.

Keywords: Norfloxacin, Aceclofenac sodium, Methodoptimization, RP-HPLC method, Fluorescent detection, Calibrationcurve.

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Authors: S. Mousavian, D. Ashouri, F. Mousavian, V. Nikkhah Rashidabad, N. Ghazinia

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PH, temperature and time of extraction of each stage,  agitation speed and delay time between stages effect on efficiency of  zinc extraction from concentrate. In this research, efficiency of zinc  extraction was predicted as a function of mentioned variable by  artificial neural networks (ANN). ANN with different layer was  employed and the result show that the networks with 8 neurons in  hidden layer has good agreement with experimental data.

 

Keywords: Zinc extraction, Efficiency, Neural networks, Operating condition.

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Authors: Yu Shi, Rong Liu, Jingyun Lv

Abstract:

Compression textiles with ergonomic-fit and controllable pressure performance have demonstrated positive effect on prevention and treatment of chronic venous insufficiency (CVI). Well-designed compression textile products contribute to improving user compliance in their daily application. This study explored the effects of multiple knitting variables (yarn-machinery settings) on the physical-mechanical properties and the produced pressure magnitudes of tubular compression fabrics (TCFs) through experimental testing and multiple regression modeling. The results indicated that fabric physical (stitch densities and circumference) and mechanical (tensile) properties were affected by the linear density of inlay yarns, which, to some extent, influenced pressure magnitudes of the TCFs. Knitting variables (e.g., feeding velocity of inlay yarns and loop size settings) can alter circumferences and tensile properties of tubular fabrics, respectively, and significantly varied pressure values of the TCFs. This study enhanced the understanding of the effects of knitting factors on pressure controlling of TCFs, thus facilitating dimension and pressure design of compression textiles in future development.

Keywords: Laid-in knitted fabric, yarn-machinery settings, pressure magnitudes, quantitative analysis, compression textiles.

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Authors: Grace Sahaya Sheba, P. Omegala Priyakumari, M. Gunasekaran

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L-asparagine admixture Paranitrophenol (LAPNP) single crystals were grown successfully by solution method with slow evaporation technique at room temperature. Crystals of size 12mm×5 mm×3mm have been obtained in 15 days. The grown crystals were Brown color and transparent. The solubility of the grown samples has been found out at various temperatures. The lattice parameters of the grown crystals were determined by X-ray diffraction technique. The reflection planes of the sample were confirmed by the powder X-ray diffraction study and diffraction peaks were indexed. Fourier transform infrared (FTIR) studies were used to confirm the presence of various functional groups in the crystals. UV–visible absorption spectrum was recorded to study the optical transparency of grown crystal. The nonlinear optical (NLO) property of the grown crystal was confirmed by Kurtz–Perry powder technique and a study of its second harmonic generation efficiency in comparison with potassium dihydrogen phosphate (KDP) has been made. The mechanical strength of the crystal was estimated by Vickers hardness test. The grown crystals were subjected to thermo gravimetric and differential thermal analysis (TG/DTA). The dielectric behavior of the sample was also studied

Keywords: Characterization, Microhardnes, Non-linear optical materials, Solution growth, Spectroscopy, XRD.

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Authors: K. Paisal

Abstract:

The purposes of this research were (1) to create a learning activity for constructivism, (2) study the Mathematical Analysis courses learning achievement, and (3) study students’ attitude toward the learning activity for constructivism. The samples in this study were divided into 2 parts including 3 Mathematical Analysis courses instructors of Suan Sunandha Rajabhat University who provided basic information and attended the seminar and 17 Mathematical Analysis courses students who were studying in the academic and engaging in the learning activity for constructivism. The research instruments were lesson plans constructivism, subjective Mathematical Analysis courses achievement test with reliability index of 0.8119, and an attitude test concerning the students’ attitude toward the Mathematical Analysis courses learning activity for constructivism. The result of the research show that the efficiency of the Mathematical Analysis courses learning activity for constructivism is 73.05/72.16, which is more than expected criteria of 70/70. The research additionally find that the average score of learning achievement of students who engaged in the learning activities for constructivism are equal to 70% and the students’ attitude toward the learning activity for constructivism are at the medium level.

Keywords: Constructivism, learning management, Mathematical Analysis courses.

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Authors: J. Grira, Y. Bédard, S. Roche

Abstract:

The aim of this research is to design a collaborative framework that integrates risk analysis activities into the geospatial database design (GDD) process. Risk analysis is rarely undertaken iteratively as part of the present GDD methods in conformance to requirement engineering (RE) guidelines and risk standards. Accordingly, when risk analysis is performed during the GDD, some foreseeable risks may be overlooked and not reach the output specifications especially when user intentions are not systematically collected. This may lead to ill-defined requirements and ultimately in higher risks of geospatial data misuse. The adopted approach consists of 1) reviewing risk analysis process within the scope of RE and GDD, 2) analyzing the challenges of risk analysis within the context of GDD, and 3) presenting the components of a risk-based collaborative framework that improves the collection of the intended/forbidden usages of the data and helps geo-IT experts to discover implicit requirements and risks.

Keywords: Collaborative risk analysis, intention of use, Geospatial database design, Geospatial data misuse.

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Authors: Jae-Neung Lee, Sung-Bum Pan, Keun-Chang Kwak

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This paper describes an analysis of Yacht Simulator international trends and also explains about Yacht. The results are summarized as follows. Attached to the cockpit are sensors that feed -back information on rudder angle, boat heel angle and mainsheet tension to the computer. Energy expenditure of the sailor measure indirectly using expired gas analysis for the measurement of VO2 and VCO2. At sea course configurations and wind conditions can be preset to suit any level of sailor from complete beginner to advanced sailor.

Keywords: Trends Analysis, Yacht Simulator, Sailing.

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Authors: Ameur Abdelkader, Abed Bouarfa Hafida

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Since its inception, predictive analysis has revolutionized the IT industry through its robustness and decision-making facilities. It involves the application of a set of data processing techniques and algorithms in order to create predictive models. Its principle is based on finding relationships between explanatory variables and the predicted variables. Past occurrences are exploited to predict and to derive the unknown outcome. With the advent of big data, many studies have suggested the use of predictive analytics in order to process and analyze big data. Nevertheless, they have been curbed by the limits of classical methods of predictive analysis in case of a large amount of data. In fact, because of their volumes, their nature (semi or unstructured) and their variety, it is impossible to analyze efficiently big data via classical methods of predictive analysis. The authors attribute this weakness to the fact that predictive analysis algorithms do not allow the parallelization and distribution of calculation. In this paper, we propose to extend the predictive analysis algorithm, Classification And Regression Trees (CART), in order to adapt it for big data analysis. The major changes of this algorithm are presented and then a version of the extended algorithm is defined in order to make it applicable for a huge quantity of data.

Keywords: Predictive analysis, big data, predictive analysis algorithms. CART algorithm.

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Authors: W.S. Lim, M.V.C. Rao

Abstract:

In this paper, the processing of sonar signals has been carried out using Minimal Resource Allocation Network (MRAN) and a Probabilistic Neural Network (PNN) in differentiation of commonly encountered features in indoor environments. The stability-plasticity behaviors of both networks have been investigated. The experimental result shows that MRAN possesses lower network complexity but experiences higher plasticity than PNN. An enhanced version called parallel MRAN (pMRAN) is proposed to solve this problem and is proven to be stable in prediction and also outperformed the original MRAN.

Keywords: Ultrasonic sensing, target classification, minimalresource allocation network (MRAN), probabilistic neural network(PNN), stability-plasticity dilemma.

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Authors: N. Mamode Khan, V. Jowaheer

Abstract:

In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Keywords: Breakdowns, under-dispersion, com-poisson, generalized linear model, marginal quasi-likelihood estimation, joint quasi-likelihood estimation.

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Authors: U. Chattaraj, K. Dhusiya, M. Raviteja

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Perception reaction time of drivers is an outcome of human thought process, which is vague and approximate in nature and also varies from driver to driver. So, in this study a fuzzy logic based model for prediction of the same has been presented, which seems suitable. The control factors, like, age, experience, intensity of driving of the driver, speed of the vehicle and distance of stimulus have been considered as premise variables in the model, in which the perception reaction time is the consequence variable. Results show that the model is able to explain the impacts of the control factors on perception reaction time properly.

Keywords: Driver, fuzzy logic, perception reaction time, premise variable.

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Authors: Moustafa Osman Mohammed

Abstract:

This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: Air dispersion model, landfill management, spatial analysis, environmental impact and risk assessment.

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Authors: Jailan Mohamed El Demerdash

Abstract:

Millennials are a distinctive and dominant consumer group whose behavior, preferences and purchase decisions are broadly explored but not fully understood yet. Making up the largest market segment in the world, and in Egypt, they have the power to reinvent the hospitality industry and contribute to forming prospective demand for green hotels by showing willingness to adopting their environmental-friendly practices. The current study aims to enhance better understanding of Millennials' perception about sustainable initiatives and to increase the prediction power of their intentions regarding green hotel practices in Egypt. In doing so, the study is exploring the relation among different factors; Millennials' environmental awareness, their acceptance of green practices and their willingness to pay more for them. Millennials' profile, their preferences and environmental decision-making process are brought under light to stimulate actions of hospitality decision-makers and hoteliers. Bearing in mind that responsible consumerism is depending on understanding the different influences on consumption. The study questionnaire was composed of four sections and it was distributed to random Egyptian travelers' blogs and Facebook groups, with approximately 8000 members. Analysis of variance test (ANOVA) was used to examine the study variables. The findings indicated that Millennials' environmental awareness will not be a significant factor in their acceptance of hotel green practices, as well as, their willingness to pay more for them. However, Millennials' acceptance of the level of hotel green practices will have an impact on their willingness to pay more. Millennials were found to have a noticeable level of environmental awareness but lack commitment to tolerating hotel green practices and their associated high prices.

Keywords: Millennials, environment, awareness, green practices, paying more, Egypt.

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Authors: M. H. Mehrabi, S. S. Ghodsi, Zainah Ibrahim, Meldi Suhatril

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Standard routes for upgrading existing buildings to improve their seismic response can be expensive in terms of both time and cost due to the modifications required to the foundations. As a result, interest has grown in the installation of viscoelastic dampers (VEDs) in mid and high-rise buildings. Details of a low-cost viscoelastic passive control device, the rotary rubber braced damper (RRBD), are presented in this paper. This design has the added benefits of being lightweight and simple to install. Experimental methods and finite element modeling were used to assess the performance of the proposed VED design and its effect on building response during earthquakes. The analyses took into account the behaviors of non-linear materials and large deformations. The results indicate that the proposed RRBD provides high levels of energy absorption, ensuring the stable cyclical response of buildings in all scenarios considered. In addition, time history analysis was employed in this study to evaluate the RRBD’s ability to control the displacements and accelerations experienced by steel frame structures. It was demonstrated that the device responds well even at low displacements, highlighting its suitability for use in seismic events of varying severity.

Keywords: Dynamic response, passive control, performance test, seismic protection.

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Authors: Sidhartha Panda, N. P. Padhy

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This paper investigates the application of Particle Swarm Optimization (PSO) technique for coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC)-based controller to enhance the power system stability. The design problem of PSS and TCSC-based controllers is formulated as a time domain based optimization problem. PSO algorithm is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected power system. The eigenvalue analysis and non-linear simulation results are presented to show the effectiveness of the coordinated design approach over individual design. The simulation results show that the proposed controllers are effective in damping low frequency oscillations resulting from various small disturbances like change in mechanical power input and reference voltage setting.

Keywords: Particle swarm optimization, Phillips-Heffron model, power system stability, PSS, TCSC.

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Authors: Jiaji Zhou, Le Liang, Long Chen

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Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.

Keywords: Geographic profiling, Centrography model, K-means algorithm

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Authors: José Julio de C. Pituba

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This work deals with the initial applications and formulation of an anisotropic plastic-damage constitutive model proposed for non-linear analysis of reinforced concrete structures submitted to a loading with change of the sign. The original constitutive model is based on the fundamental hypothesis of energy equivalence between real and continuous medium following the concepts of the Continuum Damage Mechanics. The concrete is assumed as an initial elastic isotropic medium presenting anisotropy, permanent strains and bimodularity (distinct elastic responses whether traction or compression stress states prevail) induced by damage evolution. In order to take into account the bimodularity, two damage tensors governing the rigidity in tension or compression regimes are introduced. Then, some conditions are introduced in the original version of the model in order to simulate the damage unilateral effect. The three-dimensional version of the proposed model is analyzed in order to validate its formulation when compared to micromechanical theory. The one-dimensional version of the model is applied in the analyses of a reinforced concrete beam submitted to a loading with change of the sign. Despite the parametric identification problems, the initial applications show the good performance of the model.

Keywords: Damage model, plastic strain, unilateral effect.

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Authors: M. Zarei Mahmoudabadi, M. Sadighi

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In the study of honeycomb crushing under quasistatic loading, two parameters are important, the mean crushing stress and the wavelength of the folding mode. The previous theoretical models did not consider the true cylindrical curvature effects and the flow stress in the folding mode of honeycomb material. The present paper introduces a modification on Wierzbicki-s model based on considering two above mentioned parameters in estimating the mean crushing stress and the wavelength through implementation of the energy method. Comparison of the results obtained by the new model and Wierzbicki-s model with existing experimental data shows better prediction by the model presented in this paper.

Keywords: Crush strength, Flow stress, Honeycomb, Quasistatic load.

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Authors: Carlo Bellettini, Alessandro Marchetto, Andrea Trentini

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Web applications have become very complex and crucial, especially when combined with areas such as CRM (Customer Relationship Management) and BPR (Business Process Reengineering), the scientific community has focused attention to Web applications design, development, analysis, and testing, by studying and proposing methodologies and tools. This paper proposes an approach to automatic multi-dimensional concern mining for Web Applications, based on concepts analysis, impact analysis, and token-based concern identification. This approach lets the user to analyse and traverse Web software relevant to a particular concern (concept, goal, purpose, etc.) via multi-dimensional separation of concerns, to document, understand and test Web applications. This technique was developed in the context of WAAT (Web Applications Analysis and Testing) project. A semi-automatic tool to support this technique is currently under development.

Keywords: Concepts Analysis, Concerns Mining, Multi-Dimensional Separation of Concerns, Impact Analysis.

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Authors: T Panigrahi, G Panda, Mulgrew

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This paper introduces a new approach for the performance analysis of adaptive filter with error saturation nonlinearity in the presence of impulsive noise. The performance analysis of adaptive filters includes both transient analysis which shows that how fast a filter learns and the steady-state analysis gives how well a filter learns. The recursive expressions for mean-square deviation(MSD) and excess mean-square error(EMSE) are derived based on weighted energy conservation arguments which provide the transient behavior of the adaptive algorithm. The steady-state analysis for co-related input regressor data is analyzed, so this approach leads to a new performance results without restricting the input regression data to be white.

Keywords: Error saturation nonlinearity, transient analysis, impulsive noise.

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Authors: H. Y. Jung, Ju H. Park, S. M. Lee

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Sampled-data controller is presented for solid oxide fuel cell systems which is expressed by a sector bounded nonlinear model. The proposed control law is obtained by solving a convex problem satisfying several linear matrix inequalities. Simulation results are given to show the effectiveness of the proposed design method.

Keywords: Sampled-data control, Sector bound, Solid oxide fuel cell, Time-delay.

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