Search results for: generalized autoregressive score model

Authors: M. R. Gholizadeh, N. Bhuiyan, M. Salari

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In the near future, companies will be increasingly forced to shift their activities along a new road in order to decrease the harmful effects of their design, production and after-life on our environment. Products must meet environmental standards to not only prevent penalties but to consider the sustainability for future generations. However, the most important factor that companies will face is selecting a reasonable strategy to maximize their profit. Thus, companies need to have precise forecast from their profit after design stage through Trade-off analysis. This paper is an attempt to introduce a mathematical model that considers effective factors that impact the total profit when products are designed for resource and energy efficiency or recyclability. The modification is according to different strategies based on a Cost-Volume-Profit model. Here, the cost structure consists of Recycling cost, Development cost, Ramp-up cost, Production cost, and Pollution cost. Also, the model shows the effect of implementation of design for recyclable on revenue structure through revenue of used parts and revenue of recycled materials. A numerical example is used to evaluate the proposed model. Results show that fulfillment of Green Product Development not only can reduce the environmental impact of products but also it will increase profit of company in long term.

Keywords: green product, design for environment, C-V-P model, trade-off analysis

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Authors: Sana Bembli, Nahla Khraief Haddad, Safya Belghith

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This paper deals with a robust model free terminal sliding mode with gravity compensation approach used to control an exoskeleton-upper limb system. The considered system is a 2-DoF robot in interaction with an upper limb used for rehabilitation. The aim of this paper is to control the flexion/extension movement of the shoulder and the elbow joints in presence of matched disturbances. In the first part, we present the exoskeleton-upper limb system modeling. Then, we controlled the considered system by the model free terminal sliding mode with gravity compensation. A stability study is realized. To prove the controller performance, a robustness analysis was needed. Simulation results are provided to confirm the robustness of the gravity compensation combined with to the Model free terminal sliding mode in presence of uncertainties.

Keywords: exoskeleton- upper limb system, model free terminal sliding mode, gravity compensation, robustness analysis

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Authors: Samvel H. Sargsyan

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Together with the study of electron-optical properties of nanostructures and proceeding from experiment-based data, the study of the mechanical properties of nanostructures has become quite actual. For the study of the mechanical properties of fullerene, carbon nanotubes, graphene and other nanostructures one of the crucial issues is the construction of their adequate mathematical models. Among all mathematical models of graphene or carbon nano-tubes, this so-called discrete-continuous model is specifically important. It substitutes the interactions between atoms by elastic beams or springs. The present paper demonstrates the construction of the discrete-continual beam model for carbon nanotubes or graphene, where the micropolar beam model based on the theory of moment elasticity is accepted. With the account of the energy balance principle, the elastic moment constants for the beam model, expressed by the physical and geometrical parameters of carbon nanotube or graphene, are determined. By switching from discrete-continual beam model to the continual, the models of micropolar elastic cylindrical shell and micropolar elastic plate are confirmed as continual models for carbon nanotube and graphene respectively.

Keywords: carbon nanotube, discrete-continual, elastic, graphene, micropolar, plate, shell

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Authors: Alvin Han, Reema Shafi, Alishba Afaq, Jennifer Gommerman, Valeria Ramaglia, Shannon E. Dunn

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Adolescents engaged in contact-sports can suffer from recurrent brain concussions with no loss of consciousness and no need for hospitalization, yet they face the possibility of long-term neurocognitive problems. Recent studies suggest that head concussive injuries during adolescence can also predispose individuals to multiple sclerosis (MS). The underlying mechanisms of how brain concussions predispose to MS is not understood. Here, we hypothesize that: (1) recurrent brain concussions prime microglial cells, the tissue resident myeloid cells of the brain, setting them up for exacerbated responses when exposed to additional challenges later in life; and (2) brain concussions lead to the sensitization of myelin-specific T cells in the peripheral lymphoid organs. Towards addressing these hypotheses, we implemented a mouse model of closed head injury that uses a weight-drop device. First, we calibrated the model in male 12 week-old mice and established that a weight drop from a 3 cm height induced mild neurological symptoms (mean neurological score of 1.6+0.4 at 1 hour post-injury) from which the mice fully recovered by 72 hours post-trauma. Then, we performed immunohistochemistry on the brain of concussed mice at 72 hours post-trauma. Despite mice having recovered from all neurological symptoms, immunostaining for leukocytes (CD45) and IBA-1 revealed no peripheral immune infiltration, but an increase in the intensity of IBA1+ staining compared to uninjured controls, suggesting that resident microglia had acquired a more active phenotype. This microglia activation was most apparent in the white matter tracts in the brain and in the olfactory bulb. Immunostaining for the microglia-specific homeostatic marker TMEM119, showed a reduction in TMEM119+ area in the brain of concussed mice compared to uninjured controls, confirming a loss of this homeostatic signal by microglia after injury. Future studies will test whether single or repetitive concussive injury can worsen or accelerate autoimmunity in male and female mice. Understanding these mechanisms will guide the development of timed and targeted therapies to prevent MS from getting started in people at risk.

Keywords: concussion, microglia, microglial priming, multiple sclerosis

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Authors: Ibrahim Suliman Hanaish

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Disaggregation daily rainfall using stochastic models formulated based on multivariate approach (MuDRain) is discussed in this paper. Seven rain gauge stations are considered in this study for different distances from the referred station starting from 4 km to 160 km in Peninsular Malaysia. The hourly rainfall data used are covered the period from 1973 to 2008 and July and November months are considered as an example of dry and wet periods. The cross-correlation among the rain gauges is considered for the available hourly rainfall information at the neighboring stations or not. This paper discussed the applicability of the MuDRain model for disaggregation daily rainfall to hourly rainfall for both sources of cross-correlation. The goodness of fit of the model was based on the reproduction of fitting statistics like the means, variances, coefficients of skewness, lag zero cross-correlation of coefficients and the lag one auto correlation of coefficients. It is found the correlation coefficients based on extracted correlations that was based on daily are slightly higher than correlations based on available hourly rainfall especially for neighboring stations not more than 28 km. The results showed also the MuDRain model did not reproduce statistics very well. In addition, a bad reproduction of the actual hyetographs comparing to the synthetic hourly rainfall data. Mean while, it is showed a good fit between the distribution function of the historical and synthetic hourly rainfall. These discrepancies are unavoidable because of the lowest cross correlation of hourly rainfall. The overall performance indicated that the MuDRain model would not be appropriate choice for disaggregation daily rainfall.

Keywords: rainfall disaggregation, multivariate disaggregation rainfall model, correlation, stochastic model

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Authors: Weigao. Wu, Stefano. Utili

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Based on the kinematic approach of limit analysis, a full set of upper bound solutions for the stability of homogeneous rock slopes subjected to tension cracks are obtained. The generalized Hoek-Brown failure criterion is employed to describe the non-linear strength envelope of rocks. In this paper, critical failure mechanisms are determined for cracks of known depth but unspecified location, cracks of known location but unknown depth, and cracks of unspecified location and depth. It is shown that there is a nearly up to 50% drop in terms of the stability factors for the rock slopes intersected by a tension crack compared with intact ones. Tables and charts of solutions in dimensionless forms are presented for ease of use by practitioners.

Keywords: Hoek-Brown failure criterion, limit analysis, rock slope, tension cracks

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Authors: Amadou Banda Ndione, Charles Awono Onana

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In this paper the compartmental approach is applied to build a macroeconomic model characterized by countries. We consider a total of N countries that are subdivided into three compartments according to their economic status: D(t) denotes the compartment of developing countries at time t, E(t) stands for the compartment of emerging countries at time t while A(t) represents advanced countries at time t. The model describes the process of economic development and includes the notion of openness through collaborations between countries. Two delays appear in this model to describe the average time necessary for collaborations between countries to become efficient for their development process. Our model represents the different stages of development. It further gives the conditions under which a country can change its economic status and demonstrates the short-term positive effect of openness on economic growth. In addition, we investigate bifurcation by considering the delay as a bifurcation parameter and examine the onset and termination of Hopf bifurcations from a positive equilibrium. Numerical simulations are provided in order to illustrate the theoretical part and to support discussion.

Keywords: compartmental systems, delayed dynamical system, economic development, fiscal policy, hopf bifurcation

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Authors: Kadda Amara, Mohammed Elkeurti, Mostefa Zemouli, Yassine Benallou

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In this work, we present a study of the structural, elastic and electronic properties of the cubic antiperovskites XNMg3 (X=P, As, Sb and Bi) using the full-potential augmented plane wave plus local orbital (FP-LAPW+lo) within the Generalized Gradient Approximation based on PBEsol, Perdew 2008 functional. We determined the lattice parameters, the bulk modulus B and their pressure derivative B'. In addition, the elastic properties such as elastic constants (C11, C12 and C44), the shear modulus G, the Young modulus E, the Poisson's ratio ν and the B/G ratio are also given. For the band structure, density of states and charge density the exchange and correlation effects were treated by the Tran-Blaha modified Becke-Johnson potential to prevent the shortcoming of the underestimation of the energy gaps in both LDA and GGA approximations. The obtained results are compared to available experimental data and to other theoretical calculations.

Keywords: XNMg3 compounds, GGA-PBEsol, TB-mBJ, elastic properties, electronic properties

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Authors: Rifilwe Victor Modiba, Stefan Hendric Foord

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Alien invasive plants (IAP’s) have considerable negative impacts on freshwater habitats and South Africa has implemented an innovative Work for Water (WfW) programme for the systematic removal of these plants aimed at, amongst other objectives, restoring biodiversity and ecosystem services in these threatened habitats. These restoration processes are expensive and have to be evidence-based. In this study in-stream macroinvertebrate and adult Odonata assemblages were used as indicators of restoration success by quantifying the response of biodiversity metrics for these two groups to the removal of IAP’s in a strategic water resource of South Africa that is extensively invaded by invasive alien plants (IAP’s). The study consisted of a replicated design that included 45 sampling units, viz. 15 invaded, 15 uninvaded and 15 cleared sites stratified across the upper reaches of six sub-catchments of the Luvuvhu river catchment, Limpopo Province. Cleared sites were only considered if they received at least two WfW treatments in the last 3 years. The Benthic macroinvertebrate and adult Odonate assemblages in each of these sampling were surveyed from between November and March, 2013/2014 and 2014/2015 respectively. Generalized Linear Models (GLM) with a log link function and Poisson error distribution were done for metrics (invaded, cleared, and uninvaded) whose residuals were not normally distributed or had unequal variance and for abundance. RDA was done for EPTO genera (Ephemeroptera, Plecoptera, Trichoptera and Odonata) and adult Odonata species abundance. GLM was done to for the abundance of Genera and Odonates that had the association with the RDA environmental factors. Sixty four benthic macroinvertebrate families, 57 EPTO genera, and 45 adult Odonata species were recorded across all 45 sampling units. There was no significant difference between the SASS5 total score, ASPT, and family richness of the three invasion classes. Although clearing only had a weak positive effect on the adult Odonate species richness it had a positive impact on DBI scores. These differences were mainly the result of significantly larger DBI scores in the cleared sites as compared to the invaded sites. Results suggest that water quality is positively impacted by repeated clearing pointing to the importance of follow up procedures after initial clearing. Adult Odonate diversity as measured by richness, endemicity, threat and distribution respond positively to all forms of the clearing. The clearing had a significant impact on Odonate assemblage structure but did not affect EPTO structure. Variation partitioning showed that 21.8% of the variation in EPTO assemblage can be explained by spatial and environmental variables, 16% of the variation in Odonate structure was explained by spatial and environmental variables. The response of the diversity metrics to clearing increased in significance at finer taxonomic resolutions, particularly of adult Odonates whose metrics significantly improved with clearing and whose structure responded to both invasion and clearing. The study recommends the use of DBI for surveying river health when hydraulic biotopes are poor.

Keywords: DBI, evidence-based conservation, EPTO, macroinvetebrates

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Authors: Karim Hamidi Machekposhti, Hossein Sedghi

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This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

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Authors: M. Derraz, M.Farhaoui

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In the water treatment processes, the determination of the optimal dose of the coagulant is an issue of particular concern. Coagulant dosing is correlated to raw water quality which depends on some parameters (turbidity, ph, temperature, conductivity…). The objective of this study is to provide water treatment operators with a tool that enables to predict and replace, sometimes, the manual method (jar testing) used in this plant to predict the optimum coagulant dose. The model is constructed using actual process data for a water treatment plant located in the middle of Morocco (Meknes).

Keywords: coagulation process, aluminum sulfate, model, coagulant dose

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Authors: Nermeen El Kashef, Yasser Fouad, Khaled Mahar

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No AI-complete system can model the human brain or behavior, without looking at the totality of the whole situation and incorporating a combination of senses. This paper proposes a Pattern Recognition model based on Simulation of Chemical Senses (SCS) for separation and classification of sign language. The model based on human taste controlling strategy. The main idea of the introduced model is motivated by the facts that the tongue cluster input substance into its basic tastes first, and then the brain recognizes its flavor. To implement this strategy, two level architecture is proposed (this is inspired from taste system). The separation-level of the architecture focuses on hand posture cluster, while the classification-level of the architecture to recognizes the sign language. The efficiency of proposed model is demonstrated experimentally by recognizing American Sign Language (ASL) data set. The recognition accuracy obtained for numbers of ASL is 92.9 percent.

Keywords: artificial intelligence, biocybernetics, gustatory system, sign language recognition, taste sense

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Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

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This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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Authors: Yi Huang, Clemens Guehmann

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In order to monitor the thermal behavior of an asynchronous machine with squirrel cage rotor, a 9th-order extended Kalman filter (EKF) algorithm is implemented to estimate the temperatures of the stator windings, the rotor cage and the stator core. The state-space equations of EKF are established based on the electrical, mechanical and the simplified thermal models of an asynchronous machine. The asynchronous machine with simplified thermal model in Dymola is compiled as DymolaBlock, a physical model in MATLAB/Simulink. The coolant air temperature, three-phase voltages and currents are exported from the physical model and are processed by EKF estimator as inputs. Compared to the temperatures exported from the physical model of the machine, three parts of temperatures can be estimated quite accurately by the EKF estimator. The online EKF estimator is independent from the machine control algorithm and can work under any speed and load condition if the stator current is nonzero current system.

Keywords: asynchronous machine, extended Kalman filter, resistance, simulation, temperature estimation, thermal model

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Authors: T. Nozu, K. Hibi, T. Nishiie

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This paper discusses the applicability of the numerical model for a damage prediction method of the accidental hydrogen explosion occurring in a hydrogen facility. The numerical model was based on an unstructured finite volume method (FVM) code “NuFD/FrontFlowRed”. For simulating unsteady turbulent combustion of leaked hydrogen gas, a combination of Large Eddy Simulation (LES) and a combustion model were used. The combustion model was based on a two scalar flamelet approach, where a G-equation model and a conserved scalar model expressed a propagation of premixed flame surface and a diffusion combustion process, respectively. For validation of this numerical model, we have simulated the previous two types of hydrogen explosion tests. One is open-space explosion test, and the source was a prismatic 5.27 m3 volume with 30% of hydrogen-air mixture. A reinforced concrete wall was set 4 m away from the front surface of the source. The source was ignited at the bottom center by a spark. The other is vented enclosure explosion test, and the chamber was 4.6 m × 4.6 m × 3.0 m with a vent opening on one side. Vent area of 5.4 m2 was used. Test was performed with ignition at the center of the wall opposite the vent. Hydrogen-air mixtures with hydrogen concentrations close to 18% vol. were used in the tests. The results from the numerical simulations are compared with the previous experimental data for the accuracy of the numerical model, and we have verified that the simulated overpressures and flame time-of-arrival data were in good agreement with the results of the previous two explosion tests.

Keywords: deflagration, large eddy simulation, turbulent combustion, vented enclosure

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Authors: Maziar Ramezani, Thomas Neitzert, Timotius Pasang

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This paper aims at experimental and numerical investigation of springback behavior of sheet metals during L-bending process with emphasis on Stribeck-type friction modeling. The coefficient of friction in Stribeck curve depends on sliding velocity and contact pressure. The springback behavior of mild steel and aluminum alloy 6022-T4 sheets was studied experimentally and using numerical simulations with ABAQUS software with two types of friction model: Coulomb friction and Stribeck friction. The influence of forming speed on springback behavior was studied experimentally and numerically. The results showed that Stribeck-type friction model has better results in predicting springback in sheet metal forming. The FE prediction error for mild steel and 6022-T4 AA is 23.8%, 25.5% respectively, using Coulomb friction model and 11%, 13% respectively, using Stribeck friction model. These results show that Stribeck model is suitable for simulation of sheet metal forming especially at higher forming speed.

Keywords: friction, L-bending, springback, Stribeck curves

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Authors: Minzheong Song

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The purpose of this paper is to see a case of smart energy evolution of the UK along with government projects and smart city project like 'Smart London Plan (SLP)' in 2013 with the logic of business model innovation (BMI). For this, it discusses the theoretical logic and formulates a research framework of evolving smart energy from silo to integrated system. The starting point is the silo system with no connection and in second stage, the private investment in smart meters, smart grids implementation, energy and water nexus, adaptive smart grid systems, and building marketplaces with platform leadership. As results, the UK’s smart energy sector has evolved from smart meter device installation through smart grid to new business models such as water-energy nexus and microgrid service within the smart energy city system.

Keywords: smart city, smart energy, business model, business model innovation (BMI)

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Authors: H. N. Cheung

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Self-compassion encourages one to accept oneself, reduce self-criticism and self-judgment, and see one’s shortcomings and setbacks in a balanced view. Adolescent self-compassion is a crucial protective factor against mental illness. It is, however, affected by gender. Given the scarcity of self-compassion scales for adolescents, the current study evaluates the Self-Compassion Scale for Youth (SCS-Y) in a large cross-cultural sample and investigates how the subscales of SCS-Y relate to the dimensions of depressive symptoms across gender. Through the internet-based Qualtrics, a total of 2881 teenagers aged 12 to 18 years were recruited from Hong Kong (HK), China, and the United Kingdom. A Multiple Indicator Multiple Cause (MIMIC) model was used to evaluate measurement invariance of the SCS-Y, and differential item functioning (DIF) was checked across gender. Upon the establishment of the best model, a multigroup structural equation model (SEM) was built between factors of SCS-Y and Multidimensional depression assessment scale (MDAS) which assesses four dimensions of depressive symptoms (emotional, cognitive, somatic and interpersonal). The SCS-Y was shown to have good reliability and validity. The MIMIC model produced a good model fit for a hypothetical six-factor model (CFI = 0.980; TLI = 0.974; RMSEA = 0.038) and no item was flagged for DIF across gender. A gender difference was observed between SCS-Y factors and depression dimensions. Conclusions: The SCS-Y exhibits good psychometric characteristics, including measurement invariance across gender. The study also highlights the gender difference between self-compassion factors and depression dimensions.

Keywords: self compassion, gender, depression, structural equation modelling, MIMIC model

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Authors: Zhifang Liao, Yanbing Li, Li Xu, Yan Zhang, Xiaoping Fan, Jinsong Wu

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Pull Request (PR) is the primary method for code contributions from the external contributors in Github. PR review is an essential part of open source software developments for maintaining the quality of software. Matching a new PR of an appropriate integrator will make the PR review more effective. However, PR and integrator matching are now organized manually in Github. To reduce this cost, we presented an AIPM model to predict highly relevant integrator of incoming PRs. AIPM uses topic model to extract topics from the PRs, and builds a one-to-one correspondence between topics and integrators. Then, AIPM finds the most suitable integrator according to the maximum entry of the topic-document distribution. On average, AIPM can reach a precision of 60%, and even in some projects, can reach a precision of 80%.

Keywords: pull Request, integrator matching, Github, open source project, topic model

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Authors: Kazuyoshi Mori

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In this paper, we consider the parametrization of Anantharam’s model within the framework of the factorization approach. In the parametrization, we investigate the number of required parameters of Anantharam’s model. We consider single-input single-output systems in this paper. By the investigation, we find three cases that are (1) there exist plants which require only one parameter and (2) two parameters, and (3) the number of parameters is at most three.

Keywords: linear systems, parametrization, coprime factorization, number of parameters

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: air dispersion model, environmental management, SCADA systems, GIS system, integration power system

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we present the human action recognition method using the variational Bayesian HMM with the Dirichlet process mixture (DPM) of the Gaussian-Wishart emission model (GWEM). First, we define the Bayesian HMM based on the Dirichlet process, which allows an infinite number of Gaussian-Wishart components to support continuous emission observations. Second, we have considered an efficient variational Bayesian inference method that can be applied to drive the posterior distribution of hidden variables and model parameters for the proposed model based on training data. And then we have derived the predictive distribution that may be used to classify new action. Third, the paper proposes a process of extracting appropriate spatial-temporal feature vectors that can be used to recognize a wide range of human behaviors from input video image. Finally, we have conducted experiments that can evaluate the performance of the proposed method. The experimental results show that the method presented is more efficient with human action recognition than existing methods.

Keywords: human action recognition, Bayesian HMM, Dirichlet process mixture model, Gaussian-Wishart emission model, Variational Bayesian inference, prior distribution and approximate posterior distribution, KTH dataset

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Authors: Muna Tabuni

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The paper contains an investigation of the notion of Q algebras. A brief introduction to quantum mechanics is given, in that systems the state defined by a vector in a complex vector space H which have Hermitian inner product property. H may be finite or infinite-dimensional. In quantum mechanics, operators must be hermitian. These facts are saved by Lie algebra operators but not by those of quantum algebras. A Hilbert space H consists of a set of vectors and a set of scalars. Lie group is a differentiable topological space with group laws given by differentiable maps. A Lie algebra has been introduced. Q-algebra has been defined. A brief introduction to BCI-algebra is given. A BCI sub algebra is introduced. A brief introduction to BCK=BCH-algebra is given. Every BCI-algebra is a BCH-algebra. Homomorphism maps meanings are introduced. Homomorphism maps between two BCK algebras are defined. The mathematical formulations of quantum mechanics can be expressed using the theory of unitary group representations. A generalization of Q algebras has been introduced, and their properties have been considered. The Q- quantum algebra has been studied, and various examples have been given.

Keywords: Q-algebras, BCI, BCK, BCH-algebra, quantum mechanics

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Authors: Ariful Islam, Showkat Ahmad Lone

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The Mukherjee-Islam Model is commonly used as a simple life time distribution to assess system reliability. The model exhibits a better fit for failure information and provides more appropriate information about hazard rate and other reliability measures as shown by various authors. It is possible to introduce a location parameter at a time (i.e., a time before which failure cannot occur) which makes it a more useful failure distribution than the existing ones. Even after shifting the location of the distribution, it represents a decreasing, constant and increasing failure rate. It has been shown to represent the appropriate lower tail of the distribution of random variables having fixed lower bound. This study presents the reliability computations and probability weighted moment estimation of three parameter model. A comparative analysis is carried out between three parameters finite range model and some existing bathtub shaped curve fitting models. Since probability weighted moment method is used, the results obtained can also be applied on small sample cases. Maximum likelihood estimation method is also applied in this study.

Keywords: comparative analysis, maximum likelihood estimation, Mukherjee-Islam failure model, probability weighted moment estimation, reliability

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Authors: Junjie Peng, Jinbao Chen, Shuai Kong, Danxu Liu

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On the basis of traditional resource allocation strategies, the usage of resources on physical servers in cloud data center is great uncertain. It will cause waste of resources if the assignment of tasks is not enough. On the contrary, it will cause overload if the assignment of tasks is too much. This is especially obvious when the applications are the same type because of its resource preferences. Considering CPU intensive application is one of the most common types of application in the cloud, we studied the optimization strategy for CPU intensive applications on the same server. We used resource preferences to analyze the case that multiple CPU intensive applications run simultaneously, and put forward a model which can predict the execution time for CPU intensive applications which run simultaneously. Based on the prediction model, we proposed the method to select the appropriate number of applications for a machine. Experiments show that the model can predict the execution time accurately for CPU intensive applications. To improve the execution efficiency of applications, we propose a scheduling model based on priority for CPU intensive applications. Extensive experiments verify the validity of the scheduling model.

Keywords: cloud computing, CPU intensive applications, resource optimization, strategy

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Authors: Kholod Hajo

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In this study COMSOL Multiphysics was used to design lateral flow biosensors (LFBs) which provide advantages in low cost, simplicity, rapidity, stability and portability thus making LFBs popular in biomedical, agriculture, food and environmental sciences. This study was focused on simulation model of biosensor based on gold nanoparticles (GNPs) designed using software package (COMSOL Multiphysics), the magnitude of the laminar velocity field in the flow cell, concentration distribution in the analyte stream and surface coverage of adsorbed species and average fractional surface coverage of adsorbed analyte were discussed from the model and couples of suggestion was given in order to functionalize GNPs and to increase the accuracy of the biosensor design, all above were obtained acceptable results.

Keywords: model, gold nanoparticles, biosensor, COMSOL Multiphysics

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Authors: Takashi Kaburagi, Masashi Takenaka, Yosuke Kurihara, Takashi Matsumoto

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Major depressive disorder (MDD) is one of the most common mental illnesses today. It is believed to be caused by a combination of several factors, including stress. Stress can be quantitatively evaluated using the State-Trait Anxiety Inventory (STAI), one of the best indices to evaluate anxiety. Although STAI scores are widely used in applications ranging from clinical diagnosis to basic research, the scores are calculated based on a self-reported questionnaire. An objective evaluation is required because the subject may intentionally change his/her answers if multiple tests are carried out. In this article, we present a modified index called the “multi-channel Laterality Index at Rest (mc-LIR)” by recording the brain activity from a wider area of the frontal lobe using multi-channel functional near-infrared spectroscopy (fNIRS). The presented index aims to measure multiple positions near the F_pz defined by the international 10-20 system positioning. Using 24 subjects, the dependencies on the number of measuring points used to calculate the mc-LIR and its correlation coefficients with the STAI scores are reported. Furthermore, a simple linear regression was performed to estimate the STAI scores from mc-LIR. The cross-validation error is also reported. The experimental results show that using multiple positions near the Fpz will improve the correlation coefficients and estimation than those using only two positions.

Keywords: frontal lobe, functional near-infrared spectroscopy, state-trait anxiety inventory score, stress

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Authors: Nai-Chia Chao, Meng-Chi Shih

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Under today’s fast technology and massive data era, the working method start to change. In this study, based under literature meaning of “Co-working” we had implemented the new “Co-working innovation model”. Research concluded that co-working innovation model shall not be limited in co-working space but use under different field when applying multiple art integration stragies. Research show co-working should not be limited in special field or group, should be use or adapt whenever different though or ideas where found, it should be use under different field and plans.

Keywords: arts integration, co-working, children's musical

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Authors: Ammar Asma, Bouafia Nabiha, Ghammam Rim, Ezzi Olfa, Ben Cheikh Asma, Mahjoub Mohamed, Helali Radhia, Sma Nesrine, Chouchène Imed, Boussarsar Hamadi, Njah Mansour

Abstract:

Background: Central venous catheter associated infections (CVC-AI) are among the serious hospital-acquired infections. The aims of this study are to determine the incidence of CVC-AI, and their risk factors among patients followed in a Tunisian medical intensive care unit (ICU). Materials / Methods: A prospective cohort study conducted between September 15th, 2015 and November 15th, 2016 in an 8-bed medical ICU including all patients admitted for more than 48h. CVC-AI were defined according to CDC of ATLANTA criteria. The enrollment was based on clinical and laboratory diagnosis of CVC-AI. For all subjects, age, sex, underlying diseases, SAPS II score, ICU length of stay, exposure to CVC (number of CVC placed, site of insertion and duration catheterization) were recorded. Risk factors were analyzed by conditional stepwise logistic regression. The p-value of < 0.05 was considered significant. Results: Among 192 eligible patients, 144 patients (75%) had a central venous catheter. Twenty-eight patients (19.4%) had developed CVC-AI with density rate incidence 20.02/1000 CVC-days. Among these infections, 60.7% (n=17) were systemic CVC-AI (with negative blood culture), and 35.7% (n=10) were bloodstream CVC-AI. The mean SAPS II of patients with CVC-AI was 32.76 14.48; their mean Charlson index was 1.77 1.55, their mean duration of catheterization was 15.46 10.81 days and the mean duration of one central line was 5.8+/-3.72 days. Gram-negative bacteria was determined in 53.5 % of CVC-AI (n= 15) dominated by multi-drug resistant Acinetobacter baumani (n=7). Staphylococci were isolated in 3 CVC-AI. Fourteen (50%) patients with CVC-AI died. Univariate analysis identified men (p=0.034), the referral from another hospital department (p=0.03), tobacco (p=0.006), duration of sedation (p=0.003) and the duration of catheterization (p=0), as possible risk factors of CVC-AI. Multivariate analysis showed that independent factors of CVC-AI were, male sex; OR= 5.73, IC 95% [2; 16.46], p=0.001, Ramsay score; OR= 1.57, IC 95% [1.036; 2.38], p=0.033, and duration of catheterization; OR=1.093, IC 95% [1.035; 1.15], p=0.001. Conclusion: In a monocenter cohort, CVC-AI had a high density and is associated with poor outcome. Identifying the risk factors is necessary to find solutions for this major health problem.

Keywords: central venous catheter associated infection, intensive care unit, prospective cohort studies, risk factors

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Authors: Alper Taner, Yesim Benal Oztekin, Huseyin Duran

Abstract:

In this study, an Artificial Neural Network (ANN) was developed in order to classify barley varieties. For this purpose, physical properties of barley varieties were determined and ANN techniques were used. The physical properties of 8 barley varieties grown in Turkey, namely thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain, were determined and it was found that these properties were statistically significant with respect to varieties. As ANN model, three models, N-l, N-2 and N-3 were constructed. The performances of these models were compared. It was determined that the best-fit model was N-1. In the N-1 model, the structure of the model was designed to be 11 input layers, 2 hidden layers and 1 output layer. Thousand kernel weight, geometric mean diameter, sphericity, kernel volume, surface area, bulk density, true density, porosity and colour parameters of grain were used as input parameter; and varieties as output parameter. R2, Root Mean Square Error and Mean Error for the N-l model were found as 99.99%, 0.00074 and 0.009%, respectively. All results obtained by the N-l model were observed to have been quite consistent with real data. By this model, it would be possible to construct automation systems for classification and cleaning in flourmills.

Keywords: physical properties, artificial neural networks, barley, classification

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