Search results for: dynamic panel data models

Authors: Kyeong Hoon Park, Taiji Mazuda

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High damping rubber (HDR) bearings are dissipating devices mainly used in seismic isolation systems and have a great damping performance. Although many studies have been conducted on the dynamic model of HDR bearings, few models can reflect phenomena such as dependency of experienced shear strain on initial history. In order to develop a model that can represent the dependency of experienced shear strain of HDR by Mullins effect, dynamic loading test was conducted using HDR specimen. The reaction of HDR was measured by applying a horizontal vibration using a hybrid actuator under a constant vertical load. Dynamic program analysis was also performed after dynamic loading test. The dynamic model applied in program analysis is a bilinear type double-target model. This model is modified from typical bilinear model. This model can express the nonlinear characteristics related to the initial history of HDR bearings. Based on the dynamic loading test and program analysis results, equivalent stiffness and equivalent damping ratio were calculated to evaluate the mechanical properties of HDR and the feasibility of the bilinear type double-target model was examined.

Keywords: base-isolation, bilinear model, high damping rubber, loading test

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Authors: Moses Pinto, Ana Paula Monte

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The present research analyses the interactions between various categories of corporate social responsibility (CSR) that mediate the relationship between CSR and financial performance in Multinational Enterprises (MNE) in light of the present socio-political factors prevalent in the countries under observation. In the research it has been hypothesized that the absence of consensus in the empirical literature on the CSR–financial performance relationship may be explained by the existence of synergies (Complementarities) between the different CSR components. Upon investigation about whether such relationships exist, a final unbalanced panel sample of 1000 observations taken from 100 Multinational Enterprises per year functioning in the Schengen countries and one south east Asian country namely: India, over the span of 10 years i.e. from the year 2008 to 2018 has been analyzed. The empirical analysis used in the research methodology employs dynamic Panel Data in time series specifically, the system Generalized Method of Moments (GMM) which had been used to detect the varying degrees of relationships between the CSR and financial performance parameters in the background of the socio-political factors prevailing in the countries at the time and also taking into account the bilateral treaty obligations between the countries under observation. The econometric model has employed the financial ratio namely the Return on Assets (ROA) as an indicator of financial performance in order to gauge the internal performance and valuation of a firm as opposed to the Tobin’s Q that provides for the external evaluation of a firm’s financial performance which may not always be accurate. The various CSR dimensions have demonstrated significant correlations to the ‘ROA’ which include some negatively associated correlations and one positively associated correlation that is highly significant throughout the analysis of the observations, namely the correlation between the ‘ROA’ and the CSR dimension: ‘Environment’. The results provide a deeper insight in the synergistic CSR activities that managers could adapt into their Firm’s CSR strategy in order to enhance the ‘ROA’ and also to understand which interactions between the CSR dimensions can be adapted together due to their positively correlated association with each other and the ROA. The future lines of research would be inclined to investigate the effects of socio-political factors on the ROA of the MNEs through better designed econometric models.

Keywords: CSR, financial performance, complementarity, sociopolitical factors

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Authors: Keyi Wang

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Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Luiz Carlos Wrobel, Matjaz Hribersek, Jure Marn, Jurij Iljaz

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Dynamic thermography has been clinically proven to be a valuable diagnostic technique for skin tumor detection as well as for other medical applications such as breast cancer diagnostics, diagnostics of vascular diseases, fever screening, dermatological and other applications. Thermography for medical screening can be done in two different ways, observing the temperature response under steady-state conditions (passive or static thermography), and by inducing thermal stresses by cooling or heating the observed tissue and measuring the thermal response during the recovery phase (active or dynamic thermography). The numerical modelling of heat transfer phenomena in biological tissue during dynamic thermography can aid the technique by improving process parameters or by estimating unknown tissue parameters based on measured data. This paper presents a nonlinear numerical model of multilayer skin tissue containing a skin tumor, together with the thermoregulation response of the tissue during the cooling-rewarming processes of dynamic thermography. The model is based on the Pennes bioheat equation and solved numerically by using a subdomain boundary element method which treats the problem as axisymmetric. The paper includes computational tests and numerical results for Clark II and Clark IV tumors, comparing the models using constant and temperature-dependent thermophysical properties, which showed noticeable differences and highlighted the importance of using a local thermoregulation model.

Keywords: boundary element method, dynamic thermography, static thermography, skin tumor diagnostic

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Authors: Laura M. F. Bertens

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There is a long tradition of visually representing the art historical canon, in schematic overviews and diagrams. This is indicative of the desire for scientific, ‘objective’ knowledge of the kind (seemingly) produced in the natural sciences. These diagrams will, however, always retain an element of subjectivity and the modelling methods colour our perception of the represented information. In recent decades visualisations of art historical data, such as hand-drawn diagrams in textbooks, have been extended to include digital, computational tools. These tools significantly increase modelling strength and functionality. As such, they might be used to deconstruct and amend the very problem caused by traditional visualisations of the canon. In this paper, the use of digital tools for modelling the art historical canon is studied, in order to draw attention to the artificial nature of the static models that art historians are presented with in textbooks and lectures, as well as to explore the potential of digital, dynamic tools in creating new models. To study the way diagrams of the canon mediate the represented information, two modelling methods have been used on two case studies of existing diagrams. The tree diagram Stammbaum der neudeutschen Kunst (1823) by Ferdinand Olivier has been translated to a social network using the program Visone, and the famous flow chart Cubism and Abstract Art (1936) by Alfred Barr has been translated to an ontological model using Protégé Ontology Editor. The implications of the modelling decisions have been analysed in an art historical context. The aim of this project has been twofold. On the one hand the translation process makes explicit the design choices in the original diagrams, which reflect hidden assumptions about the Western canon. Ways of organizing data (for instance ordering art according to artist) have come to feel natural and neutral and implicit biases and the historically uneven distribution of power have resulted in underrepresentation of groups of artists. Over the last decades, scholars from fields such as Feminist Studies, Postcolonial Studies and Gender Studies have considered this problem and tried to remedy it. The translation presented here adds to this deconstruction by defamiliarizing the traditional models and analysing the process of reconstructing new models, step by step, taking into account theoretical critiques of the canon, such as the feminist perspective discussed by Griselda Pollock, amongst others. On the other hand, the project has served as a pilot study for the use of digital modelling tools in creating dynamic visualisations of the canon for education and museum purposes. Dynamic computer models introduce functionalities that allow new ways of ordering and visualising the artworks in the canon. As such, they could form a powerful tool in the training of new art historians, introducing a broader and more diverse view on the traditional canon. Although modelling will always imply a simplification and therefore a distortion of reality, new modelling techniques can help us get a better sense of the limitations of earlier models and can provide new perspectives on already established knowledge.

Keywords: canon, ontological modelling, Protege Ontology Editor, social network modelling, Visone

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Authors: Abdelhak Bouchakour, Mustafa Brahami, Layachi Zaghba

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The use of photovoltaic energy offers an inexhaustible supply of energy but also a clean and non-polluting energy, which is a definite advantage. The geographical location of Algeria promotes the development of the use of this energy. Indeed, given the importance of the intensity of the radiation received and the duration of sunshine. For this reason, the objective of our work is to develop a data-processing tool (software) of calculation and optimization of dimensioning of the photovoltaic installations. Our approach of optimization is basing on mathematical models, which amongst other things describe the operation of each part of the installation, the energy production, the storage and the consumption of energy.

Keywords: solar panel, solar radiation, inverter, optimization

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Authors: Annarita Zarrillo

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This research is part of adaptive architecture, reflecting the evolution that the world of architectural design is going through. Today's architecture is no longer seen as a static system but, conversely, as a dynamic system that changes in response to the environment and the needs of users. One of the major forms of adaptivity is represented by kinetic structures. This study aims to underline the importance of experimentation on physical scale models for the study of dynamic structures and to present the case study of a modular kinetic structure designed through the use of parametric design software and created as a prototype in the laboratories of the Royal Danish Academy in Copenhagen.

Keywords: adaptive architecture, architectural application, kinetic structures, modular prototype

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Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

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A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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Authors: Reza Dezvareh

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The aim of this study is to investigate the amount of wind turbulence on the aero hydrodynamic behavior of offshore wind turbines with a monopile holder platform. Since in the sea, the wind turbine structures are under water and structures interactions, the dynamic analysis has been conducted under combined wind and wave loading. The offshore wind turbines have been investigated undertow models of normal and severe wind turbulence, and the results of this study show that the amplitude of fluctuation of dynamic response of structures including thrust force and base shear force of structures is increased with increasing the amount of wind turbulence, and this increase is not necessarily observed in the mean values of responses. Therefore, conducting the dynamic analysis is inevitable in order to observe the effect of wind turbulence on the structures' response.

Keywords: offshore wind turbine, wind turbulence, structural vibration, aero-hydro dynamic

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: S. Raja, K. M. Parammasivam, V. Aghilesh

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Fluid-structure interaction is a crucial consideration in the design of many engineering systems such as flight vehicles and bridges. Aircraft lifting surfaces and turbine blades can fail due to oscillations caused by fluid-structure interaction. Hence, it is focussed to study the fluid-structure interaction in the present research. First, the effect of free vibration over the panel is studied. It is well known that the deformation of a panel and flow induced forces affects one another. The selected panel has a span 300mm, chord 300mm and thickness 2 mm. The project is to study, the effect of cross-sectional area and the stiffener location is carried out for the same panel. The stiffener spacing is varied along both the chordwise and span-wise direction. Then for that optimal location the ideal stiffener length is identified. The effect of stiffener cross-section shapes (T, I, Hat, Z) over flutter velocity has been conducted. The flutter velocities of the selected panel with two rectangular stiffeners of cantilever configuration are estimated using MSC NASTRAN software package. As the flow passes over the panel, deformation takes place which further changes the flow structure over it. With increasing velocity, the deformation goes on increasing, but the stiffness of the system tries to dampen the excitation and maintain equilibrium. But beyond a critical velocity, the system damping suddenly becomes ineffective, so it loses its equilibrium. This estimated in NASTRAN using PK method. The first 10 modal frequencies of a simple panel and stiffened panel are estimated numerically and are validated with open literature. A grid independence study is also carried out and the modal frequency values remain the same for element lengths less than 20 mm. The current investigation concludes that the span-wise stiffener placement is more effective than the chord-wise placement. The maximum flutter velocity achieved for chord-wise placement is 204 m/s while for a span-wise arrangement it is augmented to 963 m/s for the stiffeners location of ¼ and ¾ of the chord from the panel edge (50% of chord from either side of the mid-chord line). The flutter velocity is directly proportional to the stiffener cross-sectional area. A significant increment in flutter velocity from 218m/s to 1024m/s is observed for the stiffener lengths varying from 50% to 60% of the span. The maximum flutter velocity above Mach 3 is achieved. It is also observed that for a stiffened panel, the full effect of stiffener can be achieved only when the stiffener end is clamped. Stiffeners with Z cross section incremented the flutter velocity from 142m/s (Panel with no stiffener) to 328 m/s, which is 2.3 times that of simple panel.

Keywords: stiffener placement, stiffener cross-sectional area, stiffener length, stiffener cross sectional area shape

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Authors: Ghaemi Reza, Abdollahi Hamid, Dashti Elham

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Cloud computing poses a diversity of challenges in data mining operation arising out of the dynamic structure of data distribution as against the use of typical database scenarios in conventional architecture. Due to immense number of users seeking data on daily basis, there is a serious security concerns to cloud providers as well as data providers who put their data on the cloud computing environment. Big data analytics use compute intensive data mining algorithms (Hidden markov, MapReduce parallel programming, Mahot Project, Hadoop distributed file system, K-Means and KMediod, Apriori) that require efficient high performance processors to produce timely results. Data mining algorithms to solve or optimize the model parameters. The challenges that operation has to encounter is the successful transactions to be established with the existing virtual machine environment and the databases to be kept under the control. Several factors have led to the distributed data mining from normal or centralized mining. The approach is as a SaaS which uses multi-agent systems for implementing the different tasks of system. There are still some problems of data mining based on cloud computing, including design and selection of data mining algorithms.

Keywords: cloud computing, data mining, computing models, cloud services

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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Authors: Z. Sadeghi, M. R. Omidkhah, M. E. Masoomi

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The purpose of this paper is to examine gas transport behavior of mixed matrix membranes (MMMs) combined with porous particles. Main existing models are categorized in two main groups; two-phase (ideal contact) and three-phase (non-ideal contact). A new coefficient, J, was obtained to express equations for estimating effect of the particle porosity in two-phase and three-phase models. Modified models evaluates with existing models and experimental data using Matlab software. Comparison of gas permeability of proposed modified models with existing models in different MMMs shows a better prediction of gas permeability in MMMs.

Keywords: mixed matrix membrane, permeation models, porous particles, porosity

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Authors: Joanna Dauner, Jan Friedrich, Linda Elsner, Kora Kimpel

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Active materials such as Electroactive Polymers (EAPs) are promising for the development of novel shape-changing interfaces. This paper explores the potential of EAPs in a multilayer unimorph structure from a design perspective to investigate the visual qualities of the material for dynamic data visualization and data physicalization. We discuss various concepts of how the material can be used for this purpose. Multilayer unimorph EAPs are of particular interest to designers because they can be easily prototyped using everyday materials and tools. By changing the structure and geometry of the EAPs, their movement and behavior can be modified. We present the results of our preliminary user testing, where we evaluated different movement patterns. As a result, we introduce a prototype display built with EAPs for dynamic data physicalization. Finally, we discuss the potentials and drawbacks and identify further open research questions for the design discipline.

Keywords: electroactive polymer, shape-changing interfaces, smart material interfaces, data physicalization

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Authors: M. Khairudin

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This paper investigates the system identification and design quantitative feedback theory (QFT) for the robust control of a lathe spindle. The dynamic of the lathe spindle is uncertain and time variation due to the deepness variation on cutting process. System identification was used to obtain the dynamics model of the lathe spindle. In this work, real time system identification is used to construct a linear model of the system from the nonlinear system. These linear models and its uncertainty bound can then be used for controller synthesis. The real time nonlinear system identification process to obtain a set of linear models of the lathe spindle that represents the operating ranges of the dynamic system. With a selected input signal, the data of output and response is acquired and nonlinear system identification is performed using Matlab to obtain a linear model of the system. Practical design steps are presented in which the QFT-based conditions are formulated to obtain a compensator and pre-filter to control the lathe spindle. The performances of the proposed controller are evaluated in terms of velocity responses of the the lathe machine spindle in corporating deepness on cutting process.

Keywords: lathe spindle, QFT, robust control, system identification

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Authors: Lajmi Azhaar, Yab Mdallelah

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This study examines the Tunisian market in which recent events, notably financial scandals, provide an appropriate framework for studying the impact of corporate governance on the audit report lag. Moreover, very little research has been done to examine this relationship in this context. The objective of this work is, therefore, to understand the factors influencing audit report lag, drawing primarily on agency theory (Jensen and Meckling, 1976), which shows that the characteristics of the board of directors have an impact on the report lag (independence, diligence, and size). In addition, the characteristics of the committee also have an impact on the audit report lag (size, independence, diligence, and expertise). Therefore, our research provides empirical evidence on the impact of governance mechanisms attributes on audit report lag. Using a sample of forty-seven (47) Tunisian companies listed on the Tunis Stock Exchange (BVMT) during the period from 2014 to 2019, and basing on the GMM method of the dynamic panel, multivariate analysis shows that most corporate governance attributes have a significant effect on audit report lag. Specifically, the audit committee diligence and the audit committee expertise have a significant and positive effect on audit report lag. But the diligence of the board has a significant and negative effect on audit report lag. However, this study finds no evidence that the audit committee independence, the size, independence, and diligence of the director’s board are associated with the audit report lag. In addition, the results of this study also show that there is a significant effect of some control variables. Finally, we are contributing to this study by using the GMM method of the dynamic panel. We are also using an emerging context that is very poorly developed and exploited by previous studies.

Keywords: governance mechanisms, audit committee, board of directors, audit report lag

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Authors: Nadine Yehya, Chantal Maatouk

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Low energy buildings have been developed to achieve global climate commitments in reducing energy consumption. They comprise energy efficient buildings, zero energy buildings, positive buildings and passive house buildings. The reduced energy demands in Low Energy buildings call for advanced building energy modeling that focuses on studying active building systems such as heating, cooling and ventilation, improvement of systems performances, and development of control systems. Modeling and building simulation have expanded to cover different modeling approach i.e.: detailed physical model, dynamic empirical models, and hybrid approaches, which are adopted by various simulation tools. This paper uses DesignBuilder with EnergyPlus simulation engine in order to; First, study the impact of efficiency measures on building energy behavior by comparing Low energy residential model to a conventional one in Beirut-Lebanon. Second, choose the appropriate energy systems for the studied case characterized by an important cooling demand. Third, study dynamic modeling of Variable Refrigerant Flow (VRF) system in EnergyPlus that is chosen due to its advantages over other systems and its availability in the Lebanese market. Finally, simulation of different energy systems models with different modeling approaches is necessary to confront the different modeling approaches and to investigate the interaction between energy systems and building envelope that affects the total energy consumption of Low Energy buildings.

Keywords: physical model, variable refrigerant flow heat pump, dynamic modeling, EnergyPlus, the modeling approach

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Authors: Kazuhisa Takagi

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This paper is about movies and dynamic objects for mobile phones. Dynamic objects are the software programmed by JavaScript. They consist of geometric figures and work on HTML5-compliant browsers. Mobile phones are very popular among teenagers. They like watching movies and playing games on them. So, mathematics movies and dynamic objects would enhance teaching and learning processes. In the movies, manga characters speak with artificially synchronized voices. They teach trigonometry together with dynamic mathematical objects. Many movies are created. They are Windows Media files or MP4 movies. These movies and dynamic objects are not only used in the classroom but also distributed to students. By watching movies, students can study trigonometry before or after class.

Keywords: dynamic mathematical object, javascript, google drive, transfer jet

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Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Barbara Gronostajska

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Currently, housing conditions of buildings executed in large panel technology are deteriorating. The article presents modernization solutions implemented throughout the variety of architectural activities (adding of balconies and staircases, connecting apartments) which guarantee very intriguing results that meet the needs and expectations of the modern society.

Keywords: housing estate, apartments, flats, modernization, plate blocks

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Authors: Rafal Bryk, Holger Schmidt, Thomas Mull, Ingo Ganzmann, Oliver Herbst

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Prediction of the two-phase water mixture level during fast depressurization of the Reactor Pressure Vessel (RPV) resulting from an accident scenario is an important issue from the view point of the reactor safety. Since the level swell may influence the behavior of some passive safety systems, it has been recognized that an assumption which at the beginning may be considered as a conservative one, not necessary leads to a conservative result. This paper discusses outcomes obtained during simulations of the water dynamics and heat transfer during sudden depressurization of a vessel filled up to a certain level with liquid water under saturation conditions and with the rest of the vessel occupied by saturated steam. In case of the pressure decrease e.g. due to the main steam line break, the liquid water evaporates abruptly, being a reason thereby, of strong transients in the vessel. These transients and the sudden emergence of void in the region occupied at the beginning by liquid, cause elevation of the two-phase mixture. In this work, several models calculating the water collapse and swell levels are presented and validated against experimental data. Each of the models uses different approach to calculate void fraction. The object-oriented models were developed with the Modelica modelling language and the OpenModelica environment. The models represent the RPV of the Integral Test Facility Karlstein (INKA) – a dedicated test rig for simulation of KERENA – a new Boiling Water Reactor design of Framatome. The models are based on dynamic mass and energy equations. They are divided into several dynamic volumes in each of which, the fluid may be single-phase liquid, steam or a two-phase mixture. The heat transfer between the wall of the vessel and the fluid is taken into account. Additional heat flow rate may be applied to the first volume of the vessel in order to simulate the decay heat of the reactor core in a similar manner as it is simulated at INKA. The comparison of the simulations results against the reference data shows a good agreement.

Keywords: boiling water reactor, level swell, Modelica, RPV depressurization, thermal-hydraulics

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Authors: Mouldi Djelassi, Jamel Boukhatem

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Background: A relation has been established between Islamic banks' activities and interest rates. The aim of this study was to explore the impact of interest rates on the deposits and loans held by Islamic and conventional banks in Saudi Arabia. Methods: A time series data was performed over the period 2008Q1-2020Q2 on eight conventional banks and four Islamic banks. The impacts of interest rate shocks on deposits and loans were identified through panel vector autoregressive models. Results: Impulse response function analysis showed that increasing interest rates reduce loans and conventional deposits. For Islamic banks, deposits are more affected by interest rates than lending. Variance decomposition analysis revealed that deposits contribute to 61% of the Islamic financing variation and only 25% of the conventional loans. Conclusion: Interest rates impacted Islamic banks especially through deposits, which is inconsistent with the theoretical framework. Islamic deposits played an important role in Islamic financing variation and may provide to be a channel for the transmission of the monetary policy in a dual banking system. Monetary policy in Saudi Arabia works in part through “credits” (conventional bank credits) as well as through “money” (conventional and Islamic bank deposits).

Keywords: Islamic banking, interest rates, monetary policy transmission, panel VAR

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Authors: Ozan Kahraman, Hao Feng

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Several models such as Weibull, Modified Gompertz, Biphasic linear, and Log-logistic models have been proposed in order to describe non-linear inactivation kinetics and used to fit non-linear inactivation data of several microorganisms for inactivation by heat, high pressure processing or pulsed electric field. First-order kinetic parameters (D-values and z-values) have often been used in order to identify microbial inactivation by non-thermal processing methods such as ultrasound. Most ultrasonic inactivation studies employed first-order kinetic parameters (D-values and z-values) in order to describe the reduction on microbial survival count. This study was conducted to analyze the E. coli O157:H7 inactivation data by using five microbial survival models (First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic). First-order, Weibull, Modified Gompertz, Biphasic linear and Log-logistic kinetic models were used for fitting inactivation curves of Escherichia coli O157:H7. The residual sum of squares and the total sum of squares criteria were used to evaluate the models. The statistical indices of the kinetic models were used to fit inactivation data for E. coli O157:H7 by MTS at three temperatures (40, 50, and 60 0C) and three pressures (100, 200, and 300 kPa). Based on the statistical indices and visual observations, the Weibull and Biphasic models were best fitting of the data for MTS treatment as shown by high R2 values. The non-linear kinetic models, including the Modified Gompertz, First-order, and Log-logistic models did not provide any better fit to data from MTS compared the Weibull and Biphasic models. It was observed that the data found in this study did not follow the first-order kinetics. It is possibly because of the cells which are sensitive to ultrasound treatment were inactivated first, resulting in a fast inactivation period, while those resistant to ultrasound were killed slowly. The Weibull and biphasic models were found as more flexible in order to determine the survival curves of E. coli O157:H7 treated by MTS on apple-carrot juice.

Keywords: Weibull, Biphasic, MTS, kinetic models, E.coli O157:H7

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Authors: Freddy Munzhelele

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Setting: the empirical research has shown that the life cycle theory has an impact on the firms’ financing decisions, particularly the dividend pay-outs. Accordingly, the life cycle theory posits that as a firm matures, it gets to a level and capacity where it distributes more cash as dividends. On the other hand, the young firms prioritise investment opportunities sets and their financing; thus, they pay little or no dividends. The research on firms’ financing decisions also demonstrated, among others, the adoption of trade-off and pecking order theories on the dynamics of firms capital structure. The trade-off theory talks to firms holding a favourable position regarding debt structures particularly as to the cost and benefits thereof; and pecking order is concerned with firms preferring a hierarchical order as to choosing financing sources. The case of life cycle hypothesis explaining the financial managers’ decisions as regards the firms’ capital structure dynamics appears to be an interesting link, yet this link has been neglected in corporate finance research. If this link is to be explored as an empirical research, the financial decision-making alternatives will be enhanced immensely, since no conclusive evidence has been found yet as to the dynamics of capital structure. Aim: the aim of this study is to examine the impact of life cycle theory on the capital structure dynamics trade-off and pecking order theories of firms listed in retail, industrial and mining sectors of the JSE. These sectors are among the key contributors to the GDP in the South African economy. Design and methodology: following the postpositivist research paradigm, the study is quantitative in nature and utilises secondary data obtainable from the financial statements of sampled firm for the period 2010 – 2022. The firms’ financial statements will be extracted from the IRESS database. Since the data will be in panel form, a combination of the static and dynamic panel data estimators will used to analyse data. The overall data analyses will be done using STATA program. Value add: this study directly investigates the link between the life cycle theory and the dynamics of capital structure decisions, particularly the trade-off and pecking order theories.

Keywords: life cycle theory, trade-off theory, pecking order theory, capital structure, JSE listed firms

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Authors: Zahid Ahmad, Nauman Ali

Abstract:

This study has estimated the trade between USA and individual members of European Union using Gravity Model of Trade as The USA has a complex trade relationship with the European countries consist of a large number of consumers, which make USA dependent on EU for major of its total world trade. However, among the member of EU, the trade potential of USA with individual members of EU is not known. Panel data techniques e.g. Random Effect, Fixed Effect and Pooled Panel have been applied to secondary quantitative data to analyze the Trade between USA and EU. Trade Potential of USA with individual members of EU has been obtained using the ratio of Actual trade of USA with EU members and the trade as predicted by Gravity Model. The Study concluded that the USA has greater trade potential with 16 members of EU, including Croatia, Portugal and United Kingdom on top. On the other hand, Finland, Ireland, and France are the top countries with which the USA has exhaustive trade potential.

Keywords: analytical technique, economic, gravity, international trade, significant

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Authors: Haowei Lu, Anaya Aaron

Abstract:

Understanding historical solar generation and forecasting future solar generation from interconnected Distributed Energy Resources (DER) is crucial for utility planning and interconnection studies. The existing methodology, which relies on solar radiation, weather data, and common inverter models, is becoming less accurate. Rapid advancements in DER technologies have resulted in more diverse project sites, deviating from common patterns due to various factors such as DC/AC ratio, solar panel performance, tilt angle, and the presence of DC-coupled battery energy storage systems. In this paper, the authors review 10,000 DER projects within the system and analyze the Advanced Metering Infrastructure (AMI) data for various types to demonstrate the impact of different parameters. An updated methodology is proposed for redefining historical and future solar generation in distribution feeders.

Keywords: photovoltaic system, solar energy, fluctuations, energy storage, uncertainty

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Authors: Alam Ali, Ashok Kumar Pathak

Abstract:

Path analysis is a statistical technique used to evaluate the direct and indirect effects of variables in path models. One or more structural regression equations are used to estimate a series of parameters in path models to find the better fit of data. However, sometimes the assumptions of classical regression models, such as ordinary least squares (OLS), are violated by the nature of the data, resulting in insignificant direct and indirect effects of exogenous variables. This article aims to explore the effectiveness of a copula-based regression approach as an alternative to classical regression, specifically when variables are linked through an elliptical copula.

Keywords: path analysis, copula-based regression models, direct and indirect effects, k-fold cross validation technique

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Authors: R. Bhattu Babajee, Marie Sandrine Estelle Benoit

Abstract:

The past decades have witnessed a considerable institutional shift towards Central Bank Independence across economies of the world. The motivation behind such a change is the acceptance that increased central bank autonomy has the power of alleviating inflation bias. Hence, studying whether Central Bank Independence acts as a significant factor behind the price stability in the African economies or whether this macroeconomic aim in these countries result from other economic, political or social factors is a pertinent issue. The main research objective of this paper is to assess the relationship between central bank autonomy and inflation in African economies where inflation has proved to be a serious problem. In this optic, we shall measure the degree of CBI in Africa by computing the turnover rates of central banks governors thereby studying whether decisions made by African central banks are affected by external forces. The purpose of this study is to investigate empirically the association between Central Bank Independence (CBI) and inflation for 10 African economies over a period of 17 years, from 1995 to 2012. The sample includes Botswana, Egypt, Ghana, Kenya, Madagascar, Mauritius, Mozambique, Nigeria, South Africa, and Uganda. In contrast to empirical research, we have not been using the usual static panel model for it is associated with potential mis specification arising from the absence of dynamics. To this issue a dynamic panel data model which integrates several control variables has been used. Firstly, the analysis includes dynamic terms to explain the tenacity of inflation. Given the confirmation of inflation inertia, that is very likely in African countries there exists the need for including lagged inflation in the empirical model. Secondly, due to known reverse causality between Central Bank Independence and inflation, the system generalized method of moments (GMM) is employed. With GMM estimators, the presence of unknown forms of heteroskedasticity is admissible as well as auto correlation in the error term. Thirdly, control variables have been used to enhance the efficiency of the model. The main finding of this paper is that central bank independence is negatively associated with inflation even after including control variables.

Keywords: central bank independence, inflation, macroeconomic variables, price stability

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