Search results for: principal agent model

Authors: Xiaogang Li, Jieqiong Miao

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As for the problem of the grey forecasting model prediction accuracy is low, an improved grey prediction model is put forward. Firstly, use trigonometric function transform the original data sequence in order to improve the smoothness of data , this model called SGM( smoothness of grey prediction model), then combine the improved grey model with support vector machine , and put forward the grey support vector machine model (SGM - SVM).Before the establishment of the model, we use trigonometric functions and accumulation generation operation preprocessing data in order to enhance the smoothness of the data and weaken the randomness of the data, then use support vector machine (SVM) to establish a prediction model for pre-processed data and select model parameters using genetic algorithms to obtain the optimum value of the global search. Finally, restore data through the "regressive generate" operation to get forecasting data. In order to prove that the SGM-SVM model is superior to other models, we select the battery life data from calce. The presented model is used to predict life of battery and the predicted result was compared with that of grey model and support vector machines．For a more intuitive comparison of the three models, this paper presents root mean square error of this three different models .The results show that the effect of grey support vector machine (SGM-SVM) to predict life is optimal, and the root mean square error is only 3.18%. Keywords: grey forecasting model, trigonometric function, support vector machine, genetic algorithms, root mean square error

Keywords: Grey prediction model, trigonometric functions, support vector machines, genetic algorithms, root mean square error

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Authors: S. Jakšić, B. Žmuk

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The paper investigates the key factors of export dynamics for a set of Central and Southeast European (CSEE) countries in the context of current economic and financial crisis. In order to model the export dynamics a Global Vector Auto Regressive (GVAR) model is defined. As opposed to models which model each country separately, the GVAR combines all country models in a global model which enables obtaining important information on spill-over effects in the context of globalization and rising international linkages. The results of the study indicate that for most of the CSEE countries, exports are mainly driven by domestic shocks, both in the short run and in the long run. This study is the first application of the GVAR model to studying the export dynamics in the CSEE countries and therefore the results of the study present an important empirical contribution.

Keywords: export, GFEVD, global VAR, international trade, weak exogeneity

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Authors: Mohammed Hmimou, Khalid Amediaz, Imane Sebari, Nabil Bounajma

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Annual crop production is one of the most important macroeconomic indicators for the majority of countries around the world. This information is valuable, especially for exporting countries which need a yield estimation before harvest in order to correctly plan the supply chain. When it comes to estimating agricultural yield, especially for arboriculture, conventional methods are mostly applied. In the case of the citrus industry, the sale before harvest is largely practiced, which requires an estimation of the production when the fruit is on the tree. However, conventional method based on the sampling surveys of some trees within the field is always used to perform yield estimation, and the success of this process mainly depends on the expertise of the ‘estimator agent’. The present study aims to propose a methodology based on the combination of unmanned aerial vehicle (UAV) images and terrestrial laser scanner (TLS) point cloud to estimate citrus production. During data acquisition, a fixed wing and rotatory drones, as well as a terrestrial laser scanner, were tested. After that, a pre-processing step was performed in order to generate point cloud and digital surface model. At the processing stage, a machine vision workflow was implemented to extract points corresponding to fruits from the whole tree point cloud, cluster them into fruits, and model them geometrically in a 3D space. By linking the resulting geometric properties to the fruit weight, the yield can be estimated, and the statistical distribution of fruits size can be generated. This later property, which is information required by importing countries of citrus, cannot be estimated before harvest using the conventional method. Since terrestrial laser scanner is static, data gathering using this technology can be performed over only some trees. So, integration of drone data was thought in order to estimate the yield over a whole orchard. To achieve that, features derived from drone digital surface model were linked to yield estimation by laser scanner of some trees to build a regression model that predicts the yield of a tree given its features. Several missions were carried out to collect drone and laser scanner data within citrus orchards of different varieties by testing several data acquisition parameters (fly height, images overlap, fly mission plan). The accuracy of the obtained results by the proposed methodology in comparison to the yield estimation results by the conventional method varies from 65% to 94% depending mainly on the phenological stage of the studied citrus variety during the data acquisition mission. The proposed approach demonstrates its strong potential for early estimation of citrus production and the possibility of its extension to other fruit trees.

Keywords: citrus, digital surface model, point cloud, terrestrial laser scanner, UAV, yield estimation, 3D modeling

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Authors: S. M. Mahbobur Rahman

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Whole building energy simulation models are widely used for predicting future energy consumption, performance diagnosis and optimum control.  Black box building energy modeling approach has been heavily studied in the past decade. The thermal response of a building can also be modeled using a network of interconnected resistors (R) and capacitors (C) at each node called R-C network. In this study, a model building, Case 600, as described in the “Standard Method of Test for the Evaluation of Building Energy Analysis Computer Program”, ASHRAE standard 140, is studied along with a 3R2C thermal network model and the ASHRAE clear sky solar radiation model. Although building an energy model involves two important parts of building component i.e., the envelope and internal mass, the effect of building internal mass is not considered in this study. All the characteristic parameters of the building envelope are evaluated as on Case 600. Finally, monthly building energy consumption from the thermal network model is compared with a simple-box energy model within reasonable accuracy. From the results, 0.6-9.4% variation of monthly energy consumption is observed because of the south-facing windows.

Keywords: ASHRAE case study, clear sky solar radiation model, energy modeling, thermal network model

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Authors: Erika Tatiana Ruiz, Wilson Adarme Jaimes

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This abstract presents the methodology for improving the logistics processes of agricultural production units belonging to the coffee, cocoa, and fruit sectors, starting from the fundamental concepts and detailing each of the phases to carry out the diagnosis, which will be the basis for the formulation of its action plan and implementation of the maturity model. As a result of this work, the maturity model is formulated to improve logistics processes. This model seeks to: generate a progressive model that is useful for all productive units belonging to these sectors at the national level, regardless of their initial conditions, focus on the improvement of logistics processes as a strategy that contributes to improving the competitiveness of the agricultural sector in Colombia and spread the implementation of good logistics practices in postharvest in all departments of the country through autonomous tools. This model has been built through a series of steps that allow the evaluation and improvement of the logistics dimensions or indicators. The potential improvements for each dimension provide the foundation on which to advance to the next level. Within the maturity model, a methodology is indicated for the design and execution of strategies to improve its logistics processes, taking into account the current state of each production unit.

Keywords: agroindustrial, characterization, logistics, maturity model, processes

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Authors: Toby Li, Julian Zhu

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In this paper, a model based on a simplified geometry is introduced to give a very conservative collision probability prediction for the Starlink satellite in its most densely clustered region. Under the model in this paper, the probability of collision for Starlink satellite where it clustered most densely is found to be 8.484 ∗ 10^−4. It is found that the predicted collision probability increased nonlinearly with the increased safety distance set. This simple model provides evidence that the continuous development of maneuver avoidance systems is necessary for the future of the orbital safety of satellites under the harsher Lower Earth Orbit environment.

Keywords: Starlink, collision probability, debris, geometry model

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Authors: Yasmina Houda Bendahma, Tewfik Bouchaour, Meriem Merad, Ulrich Maschke

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The purpose of this work is to study retention of dye dissolved in distilled water, by an hydrophilic acrylic polymer network. The polymer network considered is Poly (2-hydroxyethyl methacrylate) (PHEMA): it is prepared by photo-polymerization under UV irradiation in the presence of a monomer (HEMA), initiator and an agent cross-linker. PHEMA polymer network obtained can be used in the retention of dye molecules present in the wastewater. The results obtained are interesting in the study of the kinetics of swelling and de-swelling of cross linked polymer networks PHEMA in colored aqueous solutions. The dyes used for retention by the PHEMA networks are eosin Y and Malachite Green, dissolved in distilled water. Theoretical conformational study by a simplified molecular model of system cross linked PHEMA / dye (eosin Y and Malachite Green), is used to simulate the retention phenomenon (or Docking) dye molecules in cavities in nano-domains included in the PHEMA polymer network.

Keywords: dye retention, molecular modeling, photochemically crosslinked polymer network, swelling deswelling, PHEMA, HEMA

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Authors: Lei Lei, Hongbo Zhang, Donald J. Bergstrom, Bing Zhang, K. Y. Song, W. J. Zhang

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This paper presents a model for a modified T-junction device for microspheres generation. The numerical model is developed using a commercial software package: COMSOL Multiphysics. In order to test the accuracy of the numerical model, multiple variables, such as the flow rate of cross-flow, fluid properties, structure, and geometry of the microdevice are applied. The results from the model are compared with the experimental results in the diameter of the microsphere generated. The comparison shows a good agreement. Therefore the model is useful in further optimization of the device and feedback control of microsphere generation if any.

Keywords: CFD modeling, validation, microsphere generation, modified T-junction

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Authors: Ravindra Dastikop, G. S. Thyagaraju, U. P. Kulkarni

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Even though the number of context aware applications is increasing day by day along with the users, till today there is no generic programming paradigm for context aware applications. This situation could be remedied by design and developing the appropriate context modeling and programming paradigm for context aware applications. In this paper, we are proposing the static context model and metrics for validating the expressiveness and understandability of the model. The proposed context modeling is a way of describing a situation of user using context entities , attributes and relationships .The model which is an extended and hybrid version of ER model, ontology model and Graphical model is specifically meant for expressing and understanding the user situation in context aware environment. The model is useful for understanding context aware problems, preparing documentation and designing programs and databases. The model makes use of context entity attributes relationship (CEAR) diagram for representation of association between the context entities and attributes. We have identified a new set of graphical notations for improving the expressiveness and understandability of context from the end user perspective .

Keywords: user context, context entity, context entity attributes, situation, sensors, devices, relationships, actors, expressiveness, understandability

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Authors: Kai Liu

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Remote sensing-derived land surface temperature (LST) can provide an indication of the temporal and spatial patterns of surface evapotranspiration (ET). However, the spatial resolution achieved by existing commonly satellite products is ~1 km, which remains too coarse for ET estimations. This paper proposed a model that can disaggregate coarse resolution MODIS LST at 1 km scale to fine spatial resolutions at the scale of 250 m. Our approach attempted to weaken the impacts of soil moisture and growing statues on LST variations. The proposed model spatially disaggregates the coarse thermal data by using a non-linear model involving Bowen ratio, normalized difference vegetation index (NDVI) and photochemical reflectance index (PRI). This LST disaggregation model was tested on two heterogeneous landscapes in central Iowa, USA and Heihe River, China, during the growing seasons. Statistical results demonstrated that our model achieved better than the two classical methods (DisTrad and TsHARP). Furthermore, using the surface energy balance model, it was observed that the estimated ETs using the disaggregated LST from our model were more accurate than those using the disaggregated LST from DisTrad and TsHARP.

Keywords: Bowen ration, downscaling, evapotranspiration, land surface temperature

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Authors: Arpit K. Shrivastava, Nirmal K. Mohakud, Subrat Kumar, Priyadarshi S. Sahu

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Acute diarrhea is one of the major causes of morbidity and mortality among children less than five years of age. Multiple etiologies have been implicated for infectious gastroenteritis causing acute diarrhea. In our study fecal samples (n=165) were collected from children (<5 years) presenting with symptoms of acute diarrhea. Samples were screened for viral, bacterial, and parasitic etiologies such as Rotavirus, Adenovirus, Diarrhoeagenic Escherichia coli (EPEC, EHEC, STEC, O157, O111), Shigella spp., Salmonella spp., Vibrio cholera, Cryptosporidium spp., and Giardia spp. The overall results from our study showed that 57% of children below 5 years of age with acute diarrhea were positive for at least one infectious etiology. Diarrhoeagenic Escherichia coli was detected to be the major etiological agent (29.09%) followed by Rotavirus (24.24%), Shigella (21.21%), Adenovirus (5.45%), Cryptosporidium (2.42%), and Giardia (0.60%). Among the different DEC strains, EPEC was detected significantly higher in <2 years children in comparison to >2 years age group (p =0.001). Concurrent infections with two or more pathogens were observed in 47 of 160 (28.48%) cases with a predominant incidence particularly in <2-year-old children (66.66%) compared to children of 2 to 5 years age group. Co-infection of Rotavirus with Shigella was the most frequent combination, which was detected in 17.94% cases, followed by Rotavirus with EPEC (15.38%) and Shigella with STEC (12.82%). Detection of multiple infectious etiologies and diagnosis of the right causative agent(s) can immensely help in better management of acute childhood diarrhea. In future more studies focusing on the detection of cases with concurrent infections must be carried out, as we believe that the etiological agents might be complementing each other’s strategies of pathogenesis resulting in severe diarrhea.

Keywords: children, co-infection, infectious diarrhea, Odisha

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Authors: Razieh Shamsi, Mehdi Faezipour, Ali Abdolkhani

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In this research, the characteristics of composites prepared from waste silk fibers and recycled polycarbonate polymer (used compacted boards) at four levels of 0, 10, 20, and 30% (silk fibers) and using 2% N- 2-Aminoethyl-3-Aminopropyltrimethoxysilane was investigated as a coupling agent and melt process method. Silk fibers (carpet weaving waste) with dimensions of 8-18 mm were prepared, and recycled polymer with 9 mesh grading was ground. Production boards in 3 thicknesses, 3 mm (tensile test samples), 5 mm (bending test samples, water absorption, and thickness shrinkage), 7 mm (impact resistance test samples) ) with a specific weight of 1 gram per cubic centimeter, hot pressing time and temperature of 12 minutes and 190 degrees Celsius with a pressure of 130 bar, cold pressing time of 6 minutes with a pressure of 50 bar and using the coupling agent N- (2- Aminoethyl)-3-aminopropyltrimethoxysilane was prepared in a constant amount of 2% of the dry weight of the filler. The results showed that, in general, by adding silk fibers to the base polymer, compared to the control samples (pure recycled polycarbonate polymer) and also by increasing the amount of silk fibers, almost all the resistances increased. The amount of water absorption of the constructed composite increased with the increase in the amount of silk fibers, and the thickness absorption was equal to 0% even after 72 hours of immersion in water. The thermal resistance of the pure recycled polymer was higher than the prepared composites, and by adding silk fibers to the base polymer and also by increasing the amount of silk fibers from 10 to 30%, the thermal resistance of the composites decreased.

Keywords: wood composite, recycled polycarbonate, silk fibers, polymer

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Authors: Woosik Jang, Seung H. Han

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The optimal partner selection is one of the most important factors to pursue the project’s success. However, in practice, there is a gaps in perception of success depending on the role of the enterprises for the projects. This frequently makes a relations between the partner evaluation results and the project’s final performances, insufficiently. To meet this challenges, this study proposes a strategic partner evaluation model considering the perception gaps between enterprises. A total 3 times of survey was performed; factor selection, perception gap analysis, and case application. After then total 8 factors are extracted from independent sample t-test and Borich model to set-up the evaluation model. Finally, through the case applications, only 16 enterprises are re-evaluated to “Good” grade among the 22 “Good” grade from existing model. On the contrary, 12 enterprises are re-evaluated to “Good” grade among the 19 “Bad” grade from existing model. Consequently, the perception gaps based evaluation model is expected to improve the decision making quality and also enhance the probability of project’s success.

Keywords: partner evaluation model, project based enterprise, decision making, perception gap, project performance

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Authors: Jose Flores, Nadia Gamboa

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A proper water quality management requires the establishment of a monitoring network. Therefore, evaluation of the efficiency of water quality monitoring networks is needed to ensure high-quality data collection of critical quality chemical parameters. Unfortunately, in some Latin American countries water quality monitoring programs are not sustainable in terms of recording historical data or environmentally representative sites wasting time, money and valuable information. In this study, multivariate statistical techniques, such as principal components analysis (PCA) and hierarchical cluster analysis (HCA), are applied for identifying the most significant monitoring sites as well as critical water quality parameters in the monitoring network of the Jequetepeque River basin, in northern Peru. The Jequetepeque River basin, like others in Peru, shows socio-environmental conflicts due to economical activities developed in this area. Water pollution by trace elements in the upper part of the basin is mainly related with mining activity, and agricultural land lost due to salinization is caused by the extensive use of groundwater in the lower part of the basin. Since the 1980s, the water quality in the basin has been non-continuously assessed by public and private organizations, and recently the National Water Authority had established permanent water quality networks in 45 basins in Peru. Despite many countries use multivariate statistical techniques for assessing water quality monitoring networks, those instruments have never been applied for that purpose in Peru. For this reason, the main contribution of this study is to demonstrate that application of the multivariate statistical techniques could serve as an instrument that allows the optimization of monitoring networks using least number of monitoring sites as well as the most significant water quality parameters, which would reduce costs concerns and improve the water quality management in Peru. Main socio-economical activities developed and the principal stakeholders related to the water management in the basin are also identified. Finally, water quality management programs will also be discussed in terms of their efficiency and sustainability.

Keywords: PCA, HCA, Jequetepeque, multivariate statistical

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Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

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Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

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Authors: Yanshuang Zhang, Byungho Jeong

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In many cases, there is a time lag between the consumption of inputs and the production of outputs. This time lag effect should be considered in evaluating the performance of organizations. Recently, a couple of DEA models were developed for considering time lag effect in efficiency evaluation of research activities. Multi-periods input(MpI) and Multi-periods output(MpO) models are integrated models to calculate simple efficiency considering time lag effect. However, these models can’t discriminate efficient DMUs because of the nature of basic DEA model in which efficiency scores are limited to ‘1’. That is, efficient DMUs can’t be discriminated because their efficiency scores are same. Thus, this paper suggests a super-efficiency model for efficiency evaluation under the consideration of time lag effect based on the MpO model. A case example using a long-term research project is given to compare the suggested model with the MpO model.

Keywords: DEA, super-efficiency, time lag, multi-periods input

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Authors: Adi Goldiner

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Historically, the social model of disability has played a pivotal role in bringing rights discourse into the disability debate. Against this backdrop, the paper explores the conceptual alignment between the social model’s account of disability and the nature of rights. Specifically, the paper examines the possibility that the social model conceptualizes disability in a way that aligns with the nature of rights and thus motivates the invocation of disability rights. Methodologically, the paper juxtaposes the literature on the social model of disability, primarily the work of the Union of the Physically Impaired Against Segregation in the UK and related scholarship, with theories of moral rights. By focusing on the interplay between the social model of disability and rights, the paper provides a conceptual explanation for the rise of disability rights. In addition, the paper sheds light on the nature of rights, their function and limitations, in the context of disability rights. The paper concludes that the social model’s conceptualization of disability is hospitable to rights, because it opens up the possibility that there are duties that correlate with disability rights. Under the social model, disability is a condition that can be eliminated by the removal of social, structural, and attitudinal barriers. Accordingly, the social model dispels the idea that the actions of others towards disabled people will have a marginal impact on their interests in not being disabled. Equally important, the social model refutes the idea that in order to significantly serve people's interest in not being disabled, it is necessary to cure bodily impairments, which is not always possible. As rights correlate with duties that are possible to comply with, as well as those that significantly serve the interests of the right holders, the social model’s conceptualization of disability invites the reframing of problems related to disability in terms of infringements of disability rights. A possible objection to the paper’s argument is raised, according to which the social model is at odds with the invocation of disability rights because disability rights are ineffective in realizing the social model's goal of improving the lives of disabled by eliminating disability. The paper responds to this objection by drawing a distinction between ‘moral rights,’ which, conceptually, are not subject to criticism of ineffectiveness, and ‘legal rights’ which are.

Keywords: disability rights, duties, moral rights, social model

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Authors: Li Li, Kai-Hsuan Chu

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It is well known that the real estate price depends on a lot of factors. Each house current value is dependent on the location, room number, transportation, living convenience, year and surrounding environments. Although, there are different experienced models for housing agent to estimate the price, it is a case by case study without overall dynamic variation investigation. However, many economic parameters may more or less influence the real estate price variation. Here, the influences of most macroeconomic parameters on real estate price are investigated individually based on least-square scheme and grey correlation strategy. Then those parameters are classified into leading indices, simultaneous indices and laggard indices. In addition, the leading time period is evaluated based on least square method. The important leading and simultaneous indices can be used to establish an artificial intelligent neural network model for real estate price variation prediction. The real estate price variation of Taipei, Taiwan during 2005 ~ 2017 are chosen for this research data analysis and validation. The results show that the proposed method has reasonable prediction function for real estate business reference.

Keywords: real estate price, least-square, grey correlation, macroeconomics

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Authors: Queen Suraajini Rajendran, Sai Hung Cheung

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

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

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Authors: Asma Hanif, A. I. K. Butt, Shabir Ahmad, Rahim Ud Din, Mustafa Inc

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This paper is devoted to a study of the fuzzy fractional mathematical model reviewing the transmission dynamics of the infectious disease Covid-19. The proposed dynamical model consists of susceptible, exposed, symptomatic, asymptomatic, quarantine, hospitalized and recovered compartments. In this study, we deal with the fuzzy fractional model defined in Caputo’s sense. We show the positivity of state variables that all the state variables that represent different compartments of the model are positive. Using Gronwall inequality, we show that the solution of the model is bounded. Using the notion of the next-generation matrix, we find the basic reproduction number of the model. We demonstrate the local and global stability of the equilibrium point by using the concept of Castillo-Chavez and Lyapunov theory with the Lasalle invariant principle, respectively. We present the results that reveal the existence and uniqueness of the solution of the considered model through the fixed point theorem of Schauder and Banach. Using the fuzzy hybrid Laplace method, we acquire the approximate solution of the proposed model. The results are graphically presented via MATLAB-17.

Keywords: Caputo fractional derivative, existence and uniqueness, gronwall inequality, Lyapunov theory

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Authors: Zhiyuan Tang, Ju Zhang, Wenyuan Wu

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In this research, a car-following model with consideration of the status of the brake light is proposed. The numerical results show that the stability of the traffic flow is improved. The ability of the brake light to reduce car accident is also showed.

Keywords: brake light, car-following model, traffic flow, regional planning, transportation

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Authors: Doğan Yıldız, Aydan Müşerref Erkmen

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The controller of the octocopter is mostly based on the PID controller. For complex maneuvers, PID controllers have limited performance capability like in collision avoidance. When an octocopter needs avoidance from an obstacle, it must instantly show an agile maneuver. Also, this kind of maneuver is affected severely by the nonlinear characteristic of octocopter. When these kinds of limitations are considered, the situation is highly challenging for the PID controller. In the proposed study, these challenges are tried to minimize by using the model predictive controller (MPC) for collision avoidance with a nonlinear octocopter model. The aim is to show that MPC-based collision avoidance has the capability to deal with fast varying conditions in case of obstacle detection and diminish the nonlinear effects of octocopter with varying disturbances.

Keywords: model predictive control, nonlinear octocopter model, collision avoidance, obstacle detection

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Authors: Samuel Oluwafemi Oyamakin, Angela Unna Chukwu

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Richrads growth equation being a generalized logistic growth equation was improved upon by introducing an allometric parameter using the hyperbolic sine function. The integral solution to this was called hyperbolic Richards growth model having transformed the solution from deterministic to a stochastic growth model. Its ability in model prediction was compared with the classical Richards growth model an approach which mimicked the natural variability of heights/diameter increment with respect to age and therefore provides a more realistic height/diameter predictions using the coefficient of determination (R2), Mean Absolute Error (MAE) and Mean Square Error (MSE) results. The Kolmogorov-Smirnov test and Shapiro-Wilk test was also used to test the behavior of the error term for possible violations. The mean function of top height/Dbh over age using the two models under study predicted closely the observed values of top height/Dbh in the hyperbolic Richards nonlinear growth models better than the classical Richards growth model.

Keywords: height, diameter at breast height, DBH, hyperbolic sine function, Pinus caribaea, Richards' growth model

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Authors: Mohamed Zaher Bouaziz

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Our study examines the Ohlson Model, which links a company's market value to its equity and net earnings, in the context of the evolution of the Canadian accounting model, characterized by more extensive use of fair value and a broader measure of performance after IFRS adoption. Our hypothesis is that if equity is reported at its fair value, this valuation is closely linked to market capitalization, so the weight of earnings weakens or even disappears in the Ohlson Model. Drawing on Canada's adoption of the International Financial Reporting Standards (IFRS), our results support our hypothesis that equity appears to include most of the relevant information for investors, while earnings have become less important. However, the predictive power of earnings does not disappear.

Keywords: fair value accounting, Ohlson model, IFRS adoption, value-relevance of equity and earnings

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Authors: Ratchada Sopakayang, Gerhard A. Holzapfel

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In this study, a new constitutive model is developed to describe the hyperelastic behavior of collagenous tissues with a parallel arrangement of collagen fibers such as ligaments and tendons. The model is formulated using a continuum approach incorporating the structural changes of the main tissue components: collagen fibers, proteoglycan-rich matrix and fiber-matrix interaction. The mechanical contribution of the interaction between the fibers and the matrix is simply expressed by a coupling term. The structural change of the collagen fibers is incorporated in the constitutive model to describe the activation of the fibers under tissue straining. Finally, the constitutive model can easily describe the stress-stretch nonlinearity which occurs when a ligament/tendon is axially stretched. This study shows that the interaction between the fibers and the matrix contributes to the mechanical tissue response. Therefore, the model may lead to a better understanding of the physiological mechanisms of ligaments and tendons under axial loading.

Keywords: constitutive model, fiber-matrix, hyperelasticity, interaction, ligament, tendon

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Authors: Muhammad A. Muhammad

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Butenafine (N-4-tert-butyl benzyl-N-methyl-1-naphthylene methylamine hydrochloride) is a benzylamine antimycotic (antifungal) agent that has a broad spectrum of action. The quest for improved antimycotic action brought about many research on the structure-activity properties of butenafine in relation to other antifungal agents. Of all those research, only little or no effort was recorded on the substituents attached to the aromatic systems in butenafine. In this research, N-(4-(tert-butyl) benzyl)-1-(4-tert-butyl) phenyl)-N-methyl methanaminium chloride, which is a butenafine analogue was synthesised from tert-butyl benzyl derivatives, by reductive amination using various solvents through a direct approach, where 1,2-dichloroethane gave the best solvent action at 40 °C (Yield: 75%) and of all the reducing agents used, sodium borohydride was found to give the best reducing action in the presence of silica chloride at room temperature (Yield: 50%). Characterization of the compound by 1H NMR showed a singlet peak of 18 hydrogen atoms with a chemical shift at 1.3-1.5 ppm for the presence of 6 methyl groups in the two tert-butyl substituents, the 13C NMR also indicated the presence of the two tert-butyl substituents by the peak with a chemical shift at 31-32 ppm for the six methyl carbon atoms, the IR indicated the presence of a tertiary ammonium ion by a strong band at 2460 cm-1 and finally the EIS-MS confirmed the molar mass of the compound by a mass to charge ratio of 324.2693. These results suggested that the target molecule was actually synthesised and therefore, 1,2-dichloroethane is a good solvent for this synthesis, and the most suitable reducing agent is sodium borohydride.

Keywords: antimicrobial agents, antimycotic agents, butenafine, chemotherapeutic agents, semisynthetic agents

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Authors: Achouri Fatima, Chouicha Kaddour

Abstract:

The main parameters affecting the workability are the water content, particle size, and the total surface of the grains, as long as the mixing water begins by wetting the surface of the grains and then fills the voids between the grains to form entrapped water, the quantity of water remaining is called free water. The aim is to undertake a fractal approach through the relationship between the concrete formulation parameters and workability, to develop this approach a series of concrete taken from the literature was investigated by varying formulation parameters such as G / S, the quantity of cement C and the quantity of mixing water E. We also call on other model as the model for the thickness of the water layer and model of the thickness of the paste layer to judge their relevance, hence the following results : the relevance of the model of the thickness of the water layer is considered relevant when there is a variation in the water quantity, the model of the thickness of the layer of the paste is only applicable if we consider that the paste is made with the grain value Dmax = 2.85: value from which we see a stable model.

Keywords: concrete, fractal method, paste thickness, water thickness, workability

Procedia PDF Downloads 374

Authors: Sanjeev K. Singh, Maloy B. Mandal, Revand R.

Abstract:

The physiology of baroreceptors and chemoreceptors present in large blood vessels of the heart is well known in regulation of cardiorespiratory functions. Since large blood vessels and peripheral blood vessels are of same mesodermal origin, therefore, involvement of the latter in regulation of cardiorespiratory system is expected. Role of perivascular nerves in mediating cardiorespiratory alterations produced after intra-arterial injection of a nociceptive agent (bradykinin) was examined in urethane anesthetized male rats. Respiratory frequency, blood pressure, and heart rate were recorded for 30 min after the retrograde injection of bradykinin/saline in the femoral artery. In addition, paw edema was determined and water content was expressed as percentage of wet weight. Injection of bradykinin produced immediate tachypnoeic, hypotensive and bradycardiac responses of shorter latency (5-8 s) favoring the neural mechanisms involved in it. Injection of equi-volume of saline did not produce any responses and served as time matched control. Paw edema was observed in the ipsilateral hind limb. Pretreatment with diclofenac sodium significantly attenuated the bradykinin-induced responses and also blocked the paw edema. Ipsilateral femoral and sciatic nerve sectioning attenuated bradykinin-induced responses significantly indicating the origin of responses from the local vascular bed. Administration of bradykinin in the segment of an artery produced reflex cardiorespiratory changes by stimulating the perivascular nociceptors involving prostaglandins. This is a novel study exhibiting the role of peripheral blood vessels in regulation of cardiorespiratory system.

Keywords: vasosensory reflex, cardiorespiratory changes, nociceptive agent, bradykinin, VR1 receptors

Procedia PDF Downloads 141

Authors: Abdullah E. Al-Mazrooei

Abstract:

In this paper, we present a new kind of the bilinear systems in the form of state space model. The evolution of this system depends on the product of state vector by its self. The well known Lotak Volterra and Lorenz models are special cases of this new model. We also present here a generalization of Kalman filter which is suitable to work with the new bilinear model. An application to real measurements is introduced to illustrate the efficiency of the proposed algorithm.

Keywords: bilinear systems, state space model, Kalman filter, application, models

Procedia PDF Downloads 429

Authors: S. A. Al-Qallaf, S. A. Al-Mawsawi, A. Haider

Abstract:

In order to evaluate the performance of a unified power flow controller (UPFC), mathematical models for steady state and dynamic analysis are to be developed. The steady state model is mainly concerned with the incorporation of the UPFC in load flow studies. Several load flow models for UPFC have been introduced in literature, and one of the most reliable models is the decoupled UPFC model. In spite of UPFC decoupled load flow model simplicity, it is more robust compared to other UPFC load flow models and it contains unique capabilities. Some shortcoming such as additional set of nonlinear equations are to be solved separately after the load flow solution is obtained. The aim of this study is to investigate the different control strategies that can be realized in the decoupled load flow model (individual control and combined control), and the impact of the location of the UPFC in the network on its control parameters.

Keywords: UPFC, decoupled model, load flow, control parameters

Procedia PDF Downloads 546