Search results for: quantile function model

Authors: Donglan Zha, Jiansong Si

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Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: bias of technical change, CES production function, elasticity of substitution, energy input

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Authors: Fen-Ling Kuo, Hsin-Chieh Lee, Han-Yun Hsiao, Jui-Chi Lin

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Background: Children with cerebral palsy (CP) usually suffered from mild to maximum upper limb dysfunction such as having difficulty in reaching and picking up objects, which profoundly affects their participation in activities of daily living (ADLs). Robot-assisted rehabilitation provides intensive physical training in improving sensorimotor function of the hand. Many researchers have extensively studied the effects of robot-assisted therapy (RT) for the paretic upper limb in patients with stroke in recent years. However, few studies have examined the effect of RT on hand function in children with CP. The purpose of this study is to investigate the effectiveness of Gloreha Sinfonia, a robotic device with a dynamic arm support system mainly focus on distal upper-limb training, on improvements of hand function and ADLs in children with CP. Methods: Seven children with moderate CP were recruited in this case series study. RT using Gloreha Sinfonia was performed 2 sessions per week, 60 min per session for 6 consecutive weeks, with 12 times in total. Outcome measures included the Fugl-Meyer Assessment-upper extremity (FMA-UE), the Box and Block Test, the electromyography activity of the extensor digitorum communis muscle (EDC) and brachioradialis (BR), a grip dynamometer for motor evaluation, and the ABILHAND-Kids for measuring manual ability to manage daily activities, were performed at baseline, after 12 sessions (end of treatment) and at the 1-month follow-up. Results: After 6 weeks of robot-assisted treatment of hand function, there were significant increases in FMA-UE shoulder/elbow scores (p=0.002), FMA-UE wrist/hand scores (p=0.002), and FMA-UE total scores (p=0.002). There were also significant improvements in the BR mean value (p = 0.015) and electrical agonist-antagonist muscle ratio (p=0.041) in grasping a 1-inch cube task. These gains were maintained for a month after the end of the intervention. Conclusion: RT using Gloreha Sinfonia for hand function training may contribute toward the improvement of upper extremity function and efficacy in recruiting BR muscle in children with CP. The results were maintained at one month after intervention.

Keywords: activities of daily living, cerebral palsy, hand function, robotic rehabilitation

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Authors: Elham Kiyani

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In this paper, we first introduce the concept of Q-efficient solutions in a real linear space not necessarily endowed with a topology, where Q is some nonempty (not necessarily convex) set. We also used the scalarization technique including the Gerstewitz function generated by a nonconvex set to characterize these Q-efficient solutions. The algebraic concepts of interior and closure are useful to study optimization problems without topology. Studying nonconvex vector optimization is valuable since topological interior is equal to algebraic interior for a convex cone. So, we use the algebraic concepts of interior and closure to define Q-weak efficient solutions and Q-Henig proper efficient solutions of set-valued optimization problems, where Q is not a convex cone. Optimization problems with set-valued maps have a wide range of applications, so it is expected that there will be a useful analytical tool in optimization theory for set-valued maps. These kind of optimization problems are closely related to stochastic programming, control theory, and economic theory. The paper focus on nonconvex problems, the results are obtained by assuming generalized non-convexity assumptions on the data of the problem. In convex problems, main mathematical tools are convex separation theorems, alternative theorems, and algebraic counterparts of some usual topological concepts, while in nonconvex problems, we need a nonconvex separation function. Thus, we consider the Gerstewitz function generated by a general set in a real linear space and re-examine its properties in the more general setting. A useful approach for solving a vector problem is to reduce it to a scalar problem. In general, scalarization means the replacement of a vector optimization problem by a suitable scalar problem which tends to be an optimization problem with a real valued objective function. The Gerstewitz function is well known and widely used in optimization as the basis of the scalarization. The essential properties of the Gerstewitz function, which are well known in the topological framework, are studied by using algebraic counterparts rather than the topological concepts of interior and closure. Therefore, properties of the Gerstewitz function, when it takes values just in a real linear space are studied, and we use it to characterize Q-efficient solutions of vector problems whose image space is not endowed with any particular topology. Therefore, we deal with a constrained vector optimization problem in a real linear space without assuming any topology, and also Q-weak efficient and Q-proper efficient solutions in the senses of Henig are defined. Moreover, by means of the Gerstewitz function, we provide some necessary and sufficient optimality conditions for set-valued vector optimization problems.

Keywords: algebraic interior, Gerstewitz function, vector closure, vector optimization

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Authors: Usha Loganathan, Haresh Pandya

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Analysis and correlation of soil properties represent an important outset for precision agriculture and is currently promoted and implemented in the developed world. Establishing relationships among indices of soil salinity has always been a challenging task in salt affected soils necessitating unique approaches for their reclamation and management to sustain long term productivity of Soil. Soil salinity indices like Electrical Conductivity (EC) and Sodium Adsorption Ratio (SAR) are normally used to characterize soils as either sodic or saline sodic. Currently, Determination of Soil sodium adsorption ratio is a more accepted and reliable measure of soil salinity. However, it involves arduous and protracted laboratory investigations which demand evolving new and economical methods to determine SAR based on simple soil salinity index. A linear regression model to predict soil SAR from soil electrical conductivity has been developed and presented in this paper as per which, soil SAR could very well be worked out as a pedotransfer function of soil EC. The present study was carried out in Orathupalayam (11.09-11.11 N latitude and 74.54-77.59 E longitude) in the vicinity of Orathupalayam Reservoir of Noyyal River Basin, India, over a period of 3 consecutive years from September 2013 through February 2016 in different locations chosen randomly through different seasons. The research findings are discussed in the light of micro level farming practices in India and recommend determination of SAR as a low cost technology aiding in the effective management of salt affected agricultural land.

Keywords: electrical conductivity, orathupalayam, pedotranfer function, sodium adsorption ratio

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Authors: M. T. Alodat

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In this paper, we propose a generalization to the Gaussian process regression(GPR) model called the extended skew Gaussian process for regression(ESGPr) model. The ESGPR model works better than the GPR model when the errors are skewed. We derive the predictive distribution for the ESGPR model at a new input. Also we apply the ESGPR model to FOREX data and we find that it fits the Forex data better than the GPR model.

Keywords: extended skew normal distribution, Gaussian process for regression, predictive distribution, ESGPr model

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Authors: Nikolay P. Brayanov, Anna V. Stoynova

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Model-based development approach is gaining more support and acceptance. Its higher abstraction level brings simplification of systems’ description that allows domain experts to do their best without particular knowledge in programming. The different levels of simulation support the rapid prototyping, verifying and validating the product even before it exists physically. Nowadays model-based approach is beneficial for modelling of complex embedded systems as well as a generation of code for many different hardware platforms. Moreover, it is possible to be applied in safety-relevant industries like automotive, which brings extra automation of the expensive device certification process and especially in the software qualification. Using it, some companies report about cost savings and quality improvements, but there are others claiming no major changes or even about cost increases. This publication demonstrates the level of maturity and autonomy of model-based approach for code generation. It is based on a real live automotive seat heater (ASH) module, developed using The Mathworks, Inc. tools. The model, created with Simulink, Stateflow and Matlab is used for automatic generation of C code with Embedded Coder. To prove the maturity of the process, Code generation advisor is used for automatic configuration. All additional configuration parameters are set to auto, when applicable, leaving the generation process to function autonomously. As a result of the investigation, the publication compares the quality of generated embedded code and a manually developed one. The measurements show that generally, the code generated by automatic approach is not worse than the manual one. A deeper analysis of the technical parameters enumerates the disadvantages, part of them identified as topics for our future work.

Keywords: embedded code generation, embedded C code quality, embedded systems, model-based development

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Authors: Mohammad Ali Tabibi, Farzad Nazemi, Nasrin Salimian

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Background: Peritoneal dialysis (PD) is a prevalent renal replacement therapy for patients with end-stage renal disease. Despite its benefits, PD patients often experience reduced physical activity and physical function, which can negatively impact dialysis adequacy and overall health outcomes. Despite the known benefits of maintaining physical activity in chronic disease management, the specific interplay between physical inactivity, physical function, and dialysis adequacy in PD patients remains underexplored. Understanding this relationship is essential for developing targeted interventions to enhance patient care and outcomes in this vulnerable population. This study aims to assess the impact of physical inactivity on dialysis adequacy and functional health in PD patients. Methods: This cross-sectional study included 135 peritoneal dialysis patients from multiple dialysis centers. Physical inactivity was measured using the International Physical Activity Questionnaire (IPAQ), while physical function was assessed using the Short Physical Performance Battery (SPPB). Dialysis adequacy was evaluated using the Kt/V ratio. Additional variables such as demographic data, comorbidities, and laboratory parameters were collected to control for potential confounders. Statistical analyses were performed to determine the relationships between physical inactivity, physical function, and dialysis adequacy. Results: The study cohort comprised 70 males and 65 females with a mean age of 55.4 ± 13.2 years. A significant proportion of the patients (65%) were categorized as physically inactive based on IPAQ scores. Inactive patients demonstrated significantly lower SPPB scores (mean 6.2 ± 2.1) compared to their more active counterparts (mean 8.5 ± 1.8, p < 0.001). Dialysis adequacy, as measured by Kt/V, was found to be suboptimal (Kt/V < 1.7) in 48% of the patients. There was a significant positive correlation between physical function scores and Kt/V values (r = 0.45, p < 0.01), indicating that better physical function is associated with higher dialysis adequacy. Also, there was a significant negative correlation between physical inactivity and physical function (r = -0.55, p < 0.01). Additionally, physically inactive patients had lower Kt/V ratios compared to their active counterparts (1.3 ± 0.3 vs. 1.8 ± 0.4, p < 0.05). Multivariate regression analysis revealed that physical inactivity was an independent predictor of reduced dialysis adequacy (β = -0.32, p < 0.01) and poorer physical function (β = -0.41, p < 0.01) after adjusting for age, sex, comorbidities, and dialysis vintage. Conclusion: This study underscores the critical role of physical activity and physical function in maintaining adequate dialysis in peritoneal dialysis patients. These findings highlight the need for targeted interventions to promote physical activity in this population to improve their overall health outcomes. Future research should focus on developing and evaluating exercise programs tailored for PD patients to enhance their physical function and dialysis adequacy. The findings suggest that interventions aimed at increasing physical activity and improving physical function may enhance dialysis adequacy and overall health outcomes in this population. Further research is warranted to explore the mechanisms underlying these associations and to develop targeted strategies for enhancing patient care.

Keywords: inactivity, physical function, peritoneal dialysis, dialysis adequacy

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Authors: Ulrich Wake, Eniman Syamsuddin

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The model for camera model identificaiton is trained using pretrained model ResNet43 and ResNet50. The dataset consists of 500 photos of each phone. Dataset is divided into 1280 photos for training, 320 photos for validation and 400 photos for testing. The model is trained using One Cycle Policy Method and tested using Test-Time Augmentation. Furthermore, the model is trained for 50 epoch using regularization such as drop out and early stopping. The result is 90% accuracy for validation set and above 85% for Test-Time Augmentation using ResNet50. Every model is also trained by slightly updating the pretrained model’s weights

Keywords: ​ One Cycle Policy, ResNet34, ResNet50, Test-Time Agumentation

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Authors: Yu Shan Wang

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Different from other industries, the structure of the tourism industry depends to a large degree the environmental and cultural resources. The industry has to undertake social responsibilities for its commercial behaviour. This paper refers to the seven dimensions of the KLD STATS in 1991-2011 as the indicator to CSR practices. The purpose is to investigate what CSR activities create significant impacts on accounting-based financials and firm values by delving into different CSR dimensions. Meanwhile, this paper takes into consideration S&P 500 and control variables (firm sizes and financial leverage). In fact, the commercial behavior of the tourism-related industry may result in negative impacts on the economy and the society. Therefore, this paper classifies a positive set of CSR elements and a negative set of CSR elements for the tourism-related industry in order to examine their respective effects on short-term profitability and long-term firm values. This can shed light on which CSR dimensions exhibit significant impacts on CFP better than holistic CSR indicators, and hence provide more useful information to investors and corporates. This paper uses quantile regressions to avoid the impact of outliers in the data set. This helps to offer specific information so that companies can make informed decisions.

Keywords: corporate social responsibility, CSR, firm value, tourism, corporate financial performance, CFP

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Authors: Naushad Mamode Khan

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The Com-Poisson (CMP) model is one of the most popular discrete generalized linear models (GLMS) that handles both equi-, over- and under-dispersed data. In longitudinal context, an integer-valued autoregressive (INAR(1)) process that incorporates covariate specification has been developed to model longitudinal CMP counts. However, the joint likelihood CMP function is difficult to specify and thus restricts the likelihood based estimating methodology. The joint generalized quasilikelihood approach (GQL-I) was instead considered but is rather computationally intensive and may not even estimate the regression effects due to a complex and frequently ill conditioned covariance structure. This paper proposes a new GQL approach for estimating the regression parameters (GQLIII) that are based on a single score vector representation. The performance of GQL-III is compared with GQL-I and separate marginal GQLs (GQL-II) through some simulation experiments and is proved to yield equally efficient estimates as GQL-I and is far more computationally stable.

Keywords: longitudinal, com-Poisson, ill-conditioned, INAR(1), GLMS, GQL

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Authors: Debasis Sengupta, Sudipta Das

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The class of life distributions with decreasing mean residual life (DMRL) is well known in the field of reliability modeling. It contains the IFR class of distributions and is contained in the NBUE class of distributions. While upper and lower bounds of the reliability distribution function of aging classes such as IFR, IFRA, NBU, NBUE, and HNBUE have discussed in the literature for a long time, there is no analogous result available for the DMRL class. We obtain the upper and lower bounds for the reliability function of the DMRL class in terms of first order finite moment. The lower bound is obtained by showing that for any fixed time, the minimization of the reliability function over the class of all DMRL distributions with a fixed mean is equivalent to its minimization over a smaller class of distribution with a special form. Optimization over this restricted set can be made algebraically. Likewise, the maximization of the reliability function over the class of all DMRL distributions with a fixed mean turns out to be a parametric optimization problem over the class of DMRL distributions of a special form. The constructive proofs also establish that both the upper and lower bounds are sharp. Further, the DMRL upper bound coincides with the HNBUE upper bound and the lower bound coincides with the IFR lower bound. We also prove that a pair of sharp upper and lower bounds for the reliability function when the distribution is increasing mean residual life (IMRL) with a fixed mean. This result is proved in a similar way. These inequalities fill a long-standing void in the literature of the life distribution modeling.

Keywords: DMRL, IMRL, reliability bounds, hazard functions

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Authors: Dení Stincer Gómez, Zuraya Monroy Nasr

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Pedagogy of science historically has given priority to teaching strategies that mobilize the cognitive mechanisms leaving out emotional. Modern epistemology, cognitive psychology and psychoanalysis begin to argue and prove that emotions are relevant epistemological functions. They are 1) the selection function: that allows the perception and reason choose, to multiple alternative explanation of a particular fact, those are relevant and discard those that are not, 2) heuristic function: that is related to the activation cognitive processes that are effective in the process of knowing; and 3) the function that called carrier content: on the latter it arises that emotions give the material reasoning that later transformed into linguistic propositions. According to these hypotheses, scientific knowledge seems to come from emotions that meet these functions. In this paper I argue that science education should start from the presence of certain emotions in the learner if it is to form citizens with scientific or cultural future scientists.

Keywords: epistemic emotions, science education, formation of citizens and scientists., philosophy of emotions

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Authors: Jhon Vargas, Gilberto Osorio-Gomez, Tatiana Manrique

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This work presents an optimal driving strategy proposal for a 125 c.c. street-type hybrid electric motorcycle with a parallel configuration. The results presented in this article are complementary regarding the control proposal of a hybrid motorcycle. In order to carry out such developments, a representative dynamic model of the motorcycle is used, in which also are described different optimization functionalities for predetermined driving modes. The purpose is to implement an off-line optimal driving strategy which distributes energy to both engines by minimizing an objective torque requirement function. An optimal dynamic contribution is found from the optimization routine, and the optimal percentage contribution for vehicle cruise speed is implemented in the proposed online PID controller.

Keywords: dynamic model, driving strategies, parallel hybrid motorcycle, PID controller, optimization

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Authors: V. Churkin, M. Lopatin

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The purpose of the paper is to estimate the US small wind turbines market potential and forecast the small wind turbines sales in the US. The forecasting method is based on the application of the Bass model and the generalized Bass model of innovations diffusion under replacement purchases. In the work an exponential distribution is used for modeling of replacement purchases. Only one parameter of such distribution is determined by average lifetime of small wind turbines. The identification of the model parameters is based on nonlinear regression analysis on the basis of the annual sales statistics which has been published by the American Wind Energy Association (AWEA) since 2001 up to 2012. The estimation of the US average market potential of small wind turbines (for adoption purchases) without account of price changes is 57080 (confidence interval from 49294 to 64866 at P = 0.95) under average lifetime of wind turbines 15 years, and 62402 (confidence interval from 54154 to 70648 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 90,7%, while in the second - 91,8%. The effect of the wind turbines price changes on their sales was estimated using generalized Bass model. This required a price forecast. To do this, the polynomial regression function, which is based on the Berkeley Lab statistics, was used. The estimation of the US average market potential of small wind turbines (for adoption purchases) in that case is 42542 (confidence interval from 32863 to 52221 at P = 0.95) under average lifetime of wind turbines 15 years, and 47426 (confidence interval from 36092 to 58760 at P = 0.95) under average lifetime of wind turbines 20 years. In the first case the explained variance is 95,3%, while in the second –95,3%.

Keywords: bass model, generalized bass model, replacement purchases, sales forecasting of innovations, statistics of sales of small wind turbines in the United States

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Authors: Tarek Aly

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Introduction: Maintenance of the length, providing rotational stability, and preserving functional range of forearm motion is the mainstay of both bone forearm fractures treatment. Conservative treatment in older children may lead to malunion with poor remodeling capacity. Recent studies emphasized that the rate of complications with IM nailing was obviously increased in old children. Open reduction and internal fixation have been criticized for the amount of soft tissue dissection and periosteal stripping needed for fixation and excessive scar formation. The aim of this study was to evaluate the anatomical and functional outcomes of hybrid fixation in the treatment of closed proximal radius and ulna fractures in adolescents between 12 and 17 years of age. Patients and Methods: 30 cases of diaphyseal both bone forearm fractures treated with hybrid fixation (Nail radius – Plate ulna) and were available for a follow-up period of fewer than 24 months. Results: Clinically, 72% of cases had an excellent function, 22% had a good function, 4% had a fair function, and 2% had a poor function. Radiologically, signs of the union had appeared in the radius 2weeks earlier than in the ulna in 55% of cases. Conclusion: A hybrid fixation technique in adolescent proximal both-bones forearm fractures could be a viable option in managing these injuries.

Keywords: hyprid fixation, both bones, forearm, fractures

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Authors: Peng Guo

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Objective To investigate the clinical characteristics and changes of video-polysomnography (v-PSG) in Parkinson disease (PD) patients accompanied with cognitive impairment. Methods Three hundred and ninety-four patients with PD were enrolled in Beijing Tiantan Hospital, according to CI level, the patients were divided into PD without cognitive impairment (PD-NCI), PD with mild cognitive impairment (PD-MCI), and PD with dementia (PDD) group. Collect patient's demographic data, including gender, onset age, education level and duration. The cognitive function of PD patients was evaluated by Montreal cognitive assessment (MoCA) scale, and the overall cognitive function and cognitive domains of the three groups were compared.Using v-PSG to assess the sleep status of patients. Correlation analysis of MoCA Scale and v-PSG results in PD-CI group. Results 1. In 394 cases of PD, 94 cases (23.86%) in PD-NCI group , 177 cases(44.92%) in PD-MCI group , 123 cases (31.22%) in PDD group. 2.There was no significant difference in gender, age of onset, education level and duration in PD-NCI group, PD-MCI group and PDD group （P＞0.05）. 3. The total score of MoCA scale in PD-NCI group, PD-MCI group and PDD group decreased one by one. In PD-NCI group, PD-MCI group and PDD group, the scores of each cognitive domain in MoCA scale decreased significantly（P<0.05）. 4.Compared with the PD-MCI group, PDD group had lower total sleep time, lower sleep efficiency （P<0.05）. Compared with PD-NCI group, PDD group had lower total sleep time and lower sleep efficiency （P<0.05）.5. The sleep efficiency of PD-CI patients is positively correlated with the total score of MoCA scale, visual spatial function, executive function, delayed recall and attention score（P<0.05). Conclusions The incidence of CI in PD patients was high; The cognitive function and cognitive domains of PD-CI patients were significantly impaired; In patients with PD-CI, total sleep time decreased, sleep efficiency decreased, and it was related to overall cognitive function and partial cognitive impairment.

Keywords: Parkinson disease, cognitive impairment, clinical characteristics, sleep disorders, video-polysomnography

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Authors: Merouane Salhi, Toufik Zebbiche

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When the stagnation pressure of perfect gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with this pressure. The gas doesn’t remain perfect. Its state equation change and it becomes for a real gas. In this case, the effects of molecular size and intermolecular attraction forces intervene to correct the state equation. The aim of this work is to show and discuss the effect of stagnation pressure on supersonic thermodynamical, physical and geometrical flow parameters, to find a general case for real gas. With the assumptions that Berthelot’s state equation accounts for the molecular size and intermolecular force effects, expressions are developed for analyzing supersonic flow for thermally and calorically imperfect gas lower than the dissociation molecules threshold. The designs parameters for supersonic nozzle like thrust coefficient depend directly on stagnation parameters of the combustion chamber. The application is for air. A computation of error is made in this case to give a limit of perfect gas model compared to real gas model.

Keywords: supersonic flow, real gas model, Berthelot’s state equation, Simpson’s method, condensation function, stagnation pressure

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Authors: Safa'a M. Rasheed, Saba A. Gheni, Wadood T. Mohamed

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Phenolic compounds are the most carcinogenic pollutants in waste water in effluents of refineries and pulp industry. Catalytic wet air oxidation is an efficient industrial treatment process to oxidize phenolic compounds into unharmful organic compounds. Mode of flow of the fluid to be treated is a dominant factor in determining effectiveness of the catalytic process. The present study aims to obtain a mathematical model describing the conversion of phenolic compounds as a function of the process variables; mode of flow (trickling and pulsing), temperature, pressure, along with a high concentration of phenols and a platinum supported alumina catalyst. The model was validated with the results of experiments obtained in a fixed bed reactor. High pressure and temperature were employed at 8 bar and 140 °C. It has been found that conversion of phenols is highly influenced by mode of flow and the change is caused by changes occurred in hydrodynamic regime at the time of pulsing flow mode, thereby a temporal variation in wetting efficiency of platinum prevails; which in turn increases and/or decreases contact time with phenols in wastewater. The model obtained was validated with experimental results, and it is found that the model is a good agreement with the experimental results.

Keywords: wastewater, phenol, pulsing flow, wet oxidation, high pressure

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Authors: Muhammad Imran Ahmad, Ruzelita Ngadiran, Mohd Nazrin Md Isa, Nor Ashidi Mat Isa, Mohd ZaizuIlyas, Raja Abdullah Raja Ahmad, Said Amirul Anwar Ab Hamid, Muzammil Jusoh

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This paper presents two technique, local feature extraction using image spectrum and low frequency spectrum modelling using GMM to capture the underlying statistical information to improve the performance of face recognition system. Local spectrum features are extracted using overlap sub block window that are mapping on the face image. For each of this block, spatial domain is transformed to frequency domain using DFT. A low frequency coefficient is preserved by discarding high frequency coefficients by applying rectangular mask on the spectrum of the facial image. Low frequency information is non Gaussian in the feature space and by using combination of several Gaussian function that has different statistical properties, the best feature representation can be model using probability density function. The recognition process is performed using maximum likelihood value computed using pre-calculate GMM components. The method is tested using FERET data sets and is able to achieved 92% recognition rates.

Keywords: local features modelling, face recognition system, Gaussian mixture models, Feret

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Authors: Aboussalih Amira, Zarza Tahar, Fedaoui Kamel, Hammoudi Saleh

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This work focuses on the simulation of the prediction of the behaviour of austenitic stainless steel (SS) 304L under complex loading in stress and imposed strain. The Chaboche model is a cable to describe the response of the material by the combination of two isotropic and nonlinear kinematic work hardening, the model is implemented in the ZébuLon computer code. First, we represent the evolution of the axial stress as a function of the plastic strain through hysteresis loops revealing a hardening behaviour caused by the increase in stress by stress in the direction of tension/compression. In a second step, the study of the ratcheting phenomenon takes a key place in this work by the appearance of the average stress. In addition to the solicitation of the material in the biaxial direction in traction / torsion.

Keywords: damage, 304L, Ratcheting, plastic strain

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Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

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Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, implementation, MATLAB

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Authors: Ebrahim H. Kapeel, Ehab Safwat, Hossam Hendy, Ahmed M. Kamel, Yehia Z. Elhalwagy

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Motivated by the problem of the availability of high-fidelity flight simulation models for small unmanned aerial vehicles (UAVs). This paper focuses on the geometric-mass inertia modeling and the actuation system modeling for the small fixed-wing UAVs. The UAV geometric parameters for the body, wing, horizontal and vertical tail are physically measured. Pendulum experiment with high-grade sensors and data analysis using MATLAB is used to estimate the airplane moment of inertia (MOI) model. Finally, UAV’s actuation system is modeled by estimating each servo transfer function by using the system identification, which uses experimental measurement for input and output angles through using field-programmable gate array (FPGA). Experimental results for the designed models are given to illustrate the effectiveness of the methodology. It also gives a very promising result to finalize the open-loop flight simulation model through modeling the propulsion system and the aerodynamic system.

Keywords: unmanned aerial vehicle, geometric-mass inertia model, system identification, Simulink

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Authors: Cara DiGirolamo

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In his 2017 Ph.D. thesis, script doctor David Baboulene presented a theory of fiction in which differences in the knowledge states between participants in a literary experience, including reader, author, and characters, create many story elements, among them suspense, expectations, subtext, theme, metaphor, and allegory. This theory can be adjusted and modeled by incorporating a formal pragmatic approach that understands narrative as a speech act with a conversational function. This approach requires both the Speaker and the Listener to be understood as participants in the discourse. It also uses theories of cooperativity and the QUD to identify the existence of implicit questions. This approach predicts that what an effective literary narrative must do: provide a conversational context early in the story so the reader can engage with the text as a conversational participant. In addition, this model incorporates schema theory. Schema theory is a cognitive model for learning and processing information about the world and transforming it into functional knowledge. Using this approach can extend the QUD model. Instead of describing conversation as a form of information gathering restricted to question-answer sets, the QUD can include knowledge modeling and understanding as a possible outcome of a conversation. With this model, Baboulene’s “Knowledge Gaps” can provide real insight into storytelling as a conversational move, and extend the QUD to be able to simply and effectively apply to a more diverse set of conversational interactions and also to narrative texts.

Keywords: literature, speech acts, QUD, literary theory

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Authors: Ruslan Safarov, Zhanat Shomanova, Yuri Nossenko, Zhandos Mussayev, Ayana Baltabek

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Geochemical maps of distribution of polluting elements V, Cr, Mn, Co, Ni, Cu, Zn, Mo, Cd, Pb on the territory of the Pavlodar city (Kazakhstan), which is an industrial hub were designed. The samples of soil were taken from 100 locations. Elemental analysis has been performed using XRF. The obtained data was used for training of the computational model with gradient boosting algorithm. The optimal parameters of model as well as the loss function were selected. The computational model was used for prediction of polluting elements concentration for 1000 evenly distributed points. Based on predicted data geochemical maps were created. Additionally, the total pollution index Zc was calculated for every from 1000 point. The spatial distribution of the Zc index was visualized using GIS (QGIS). It was calculated that the maximum coverage area of the territory of the Pavlodar city belongs to the moderately hazardous category (89.7%). The visualization of the obtained data allowed us to conclude that the main source of contamination goes from the industrial zones where the strategic metallurgical and refining plants are placed.

Keywords: Pavlodar, geochemical map, gradient boosting, CatBoost, QGIS, spatial distribution, heavy metals

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Authors: Ahmed Abbou

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This paper present a sensorless controller designed by the backstepping approach for the speed control of induction motor. In this strategy of control, we also combined the method Fuzzy MRAS to estimate the rotor speed and the observer type Luenburger to observe Rotor flux. The control model involves a division by the flux variable that may lead to unbounded solutions. Such a risk is avoided by basing the controller design on Lyapunov function that accounts for the model singularity. On the other hand, this mixed method gives better results in Sensorless operation and especially at low speed. The response time at 5% of the flux is 20ms while the error between the speed with sensor and the estimated speed remains in the range of ±0.8 rad/s for the rated functioning and ±1.5 rad/s for low speed.

Keywords: backstepping approach, fuzzy logic, induction motor, luenburger observer, sensorless MRAS

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Authors: Sulaiman Yunus

Abstract:

The need for modeling response to urban fire disaster cannot be over emphasized, as recurrent fire outbreaks have gutted most cities of the world. This necessitated the need for a prompt and efficient response system in order to mitigate the impact of the disaster. Promptness, as a function of time, is seen to be the fundamental determinant for efficiency of a response system and magnitude of a fire disaster. Delay, as a result of several factors, is one of the major determinants of promptgness of a response system and also the magnitude of a fire disaster. Response Delay Model (RDM) intends to bridge the gap in urban fire disaster response system through incorporating and synchronizing the delay moments in measuring the overall efficiency of a response system and determining the magnitude of a fire disaster. The model identified two delay moments (pre-notification and Intra-reflex sequence delay) that can be elastic and collectively plays a significant role in influencing the efficiency of a response system. Due to variation in the elasticity of the delay moments, the model provides for measuring the length of delays in order to arrive at a standard average delay moment for different parts of the world, putting into consideration geographic location, level of preparedness and awareness, technological advancement, socio-economic and environmental factors. It is recommended that participatory researches should be embarked on locally and globally to determine standard average delay moments within each phase of the system so as to enable determining the efficiency of response systems and predicting fire disaster magnitudes.

Keywords: delay moment, fire disaster, reflex sequence, response, response delay moment

Procedia PDF Downloads 207

Authors: Le Kang

Abstract:

According to the nature of the university, as a free and responsible academic community, USR is based on a different foundation —academic responsibility, so the Pyramid and the IC Model of CSR could not fully explain the most distinguished feature of USR. This paper sought to put forward a new model— Ferris Wheel Model, to illustrate the nature of USR and the process of achievement. The Ferris Wheel Model of USR shows the university creates a balanced, fairness and neutrality systemic structure to afford social responsibilities; that makes the organization could obtain a synergistic effect to achieve more extensive interests of stakeholders and wider social responsibilities.

Keywords: USR, achievement model, ferris wheel model, social responsibilities

Procedia PDF Downloads 725

Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

This paper presents a model predictive control (MPC) of a utility interactive three phase inverter (TPI) for a photovoltaic (PV) system at commercial level. The proposed model uses phase locked loop (PLL) to synchronize TPI with the power electric grid (PEG) and performs MPC control in a dq reference frame. TPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a three leg voltage source inverter (VSI). Operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a 35.7 kW PV system in Matlab/Simulink. Implementation and results show simplicity and accuracy, as well as reliability of the model.

Keywords: model predictive control, three phase voltage source inverter, PV system, Matlab/simulink

Procedia PDF Downloads 596

Authors: Martín Pratto Burgos

Abstract:

The Engineering School of the University of the Republic in Uruguay offers an Introductory Mathematical Course from the second semester of 2019. This course has been designed to assist students in preparing themselves for math courses that are essential for Engineering Degrees, namely Math1, Math2, and Math3 in this research. The research proposes to build a model that can accurately predict the student's activity and academic progress based on their performance in the three essential Mathematical courses. Additionally, there is a need for a model that can forecast the incidence of the Introductory Mathematical Course in the three essential courses approval during the first academic year. The techniques used are Principal Component Analysis and predictive modelling using the Generalised Linear Model. The dataset includes information from 5135 engineering students and 12 different characteristics based on activity and course performance. Two models are created for a type of data that follows a binomial distribution using the R programming language. Model 1 is based on a variable's p-value being less than 0.05, and Model 2 uses the stepAIC function to remove variables and get the lowest AIC score. After using Principal Component Analysis, the main components represented in the y-axis are the approval of the Introductory Mathematical Course, and the x-axis is the approval of Math1 and Math2 courses as well as student activity three years after taking the Introductory Mathematical Course. Model 2, which considered student’s activity, performed the best with an AUC of 0.81 and an accuracy of 84%. According to Model 2, the student's engagement in school activities will continue for three years after the approval of the Introductory Mathematical Course. This is because they have successfully completed the Math1 and Math2 courses. Passing the Math3 course does not have any effect on the student’s activity. Concerning academic progress, the best fit is Model 1. It has an AUC of 0.56 and an accuracy rate of 91%. The model says that if the student passes the three first-year courses, they will progress according to the timeline set by the curriculum. Both models show that the Introductory Mathematical Course does not directly affect the student’s activity and academic progress. The best model to explain the impact of the Introductory Mathematical Course on the three first-year courses was Model 1. It has an AUC of 0.76 and 98% accuracy. The model shows that if students pass the Introductory Mathematical Course, it will help them to pass Math1 and Math2 courses without affecting their performance on the Math3 course. Matching the three predictive models, if students pass Math1 and Math2 courses, they will stay active for three years after taking the Introductory Mathematical Course, and also, they will continue following the recommended engineering curriculum. Additionally, the Introductory Mathematical Course helps students to pass Math1 and Math2 when they start Engineering School. Models obtained in the research don't consider the time students took to pass the three Math courses, but they can successfully assess courses in the university curriculum.

Keywords: machine-learning, engineering, university, education, computational models

Procedia PDF Downloads 94

Authors: Petr Jizba, Jan Korbel

Abstract:

We combine an axiomatics of Rényi with the q-deformed version of Khinchin axioms to obtain a measure of information (i.e., entropy) which accounts both for systems with embedded self-similarity and non-extensivity. We show that the entropy thus obtained is uniquely solved in terms of a one-parameter family of information measures. The ensuing maximal-entropy distribution is phrased in terms of a special function known as the Lambert W-function. We analyze the corresponding ‘high’ and ‘low-temperature’ asymptotics and reveal a non-trivial structure of the parameter space.

Keywords: multifractals, Rényi information entropy, THC entropy, MaxEnt, heavy-tailed distributions

Procedia PDF Downloads 443