Search results for: panel stochastic frontier models

Authors: Tiberiu Socaciu, Tudor Colomeischi, Eugenia Iancu

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Business failure affects in various proportions shareholders, managers, lenders (banks), suppliers, customers, the financial community, government and society as a whole. In the era in which we have telecommunications networks, exists an interdependence of markets, the effect of a failure of a company is relatively instant. To effectively manage risk exposure is thus require sophisticated support systems, supported by analytical tools to measure, monitor, manage and control operational risks that may arise. As we know, bankruptcy is a phenomenon that managers do not want no matter what stage of life is the company they direct / lead. In the analysis made by us, by the nature of economic models that are reviewed (Altman, Conan-Holder etc.), estimating the risk of bankruptcy of a company corresponds to some extent with its own business cycle tracing of the company. Various models for predicting bankruptcy take into account direct / indirect aspects such as market position, company growth trend, competition structure, characteristics and customer retention, organization and distribution, location etc. From the perspective of our research we will now review the economic models known in theory and practice for estimating the risk of bankruptcy; such models are based on indicators drawn from major accounting firms.

Keywords: Anglo-Saxon models, continental models, national models, statistical models

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Authors: Siham G. Farag

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The main objective of this paper is to provide a new methodology for road safety assessment in Oman through the development of suitable accident prediction models. GLM technique with Poisson or NBR using SAS package was carried out to develop these models. The paper utilized the accidents data of 31 un-signalized T-intersections during three years. Five goodness-of-fit measures were used to assess the overall quality of the developed models. Two types of models were developed separately; the flow-based models including only traffic exposure functions, and the full models containing both exposure functions and other significant geometry and traffic variables. The results show that, traffic exposure functions produced much better fit to the accident data. The most effective geometric variables were major-road mean speed, minor-road 85th percentile speed, major-road lane width, distance to the nearest junction, and right-turn curb radius. The developed models can be used for intersection treatment or upgrading and specify the appropriate design parameters of T- intersections. Finally, the models presented in this thesis reflect the intersection conditions in Oman and could represent the typical conditions in several countries in the middle east area, especially gulf countries.

Keywords: accidents prediction models (APMs), generalized linear model (GLM), T-intersections, Oman

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Authors: Nassim Bessaad, Qilian Bao, Zhao Jiangkang

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The fiber optics gyroscope in the strap-down inertial navigation system (FOG-SINS) suffers from precision degradation due to the influence of random errors. In this work, an enhanced Allan variance (AV) stochastic modeling method combined with discrete wavelet transform (DWT) for signal denoising is implemented to estimate the random process in the FOG signal. Furthermore, we devise a measurement-based iterative adaptive Sage-Husa nonlinear filter with augmented states to integrate a star tracker sensor with SINS. The proposed filter adapts the measurement noise covariance matrix based on the available data. Moreover, the enhanced stochastic modeling scheme is invested in tuning the process noise covariance matrix and the augmented state Gauss-Markov process parameters. Finally, the effectiveness of the proposed filter is investigated by employing the collected data in laboratory conditions. The result shows the filter's improved accuracy in comparison with the conventional Kalman filter (CKF).

Keywords: inertial navigation, adaptive filtering, star tracker, FOG

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Authors: Wheyming Tina Song, Chi-Hao Hong, Peisyuan Lin

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An important performance measure for stochastic manufacturing networks is the system reliability, defined as the probability that the production output meets or exceeds a specified demand. The system parameters include the capacity of each workstation and numbers of the conforming parts produced in each workstation. We establish that eighteen archival publications, containing twenty-one examples, provide incorrect values of the system reliability. The author recently published the Song Rule, which provides the correct analytical system-reliability value; it is, however, computationally inefficient for large networks. In this paper, we use Monte Carlo simulation (implemented in C and Flexsim) to provide estimates for the above-mentioned twenty-one examples. The simulation estimates are consistent with the analytical solution for small networks but is computationally efficient for large networks. We argue here for three advantages of Monte Carlo simulation: (1) understanding stochastic systems, (2) validating analytical results, and (3) providing estimates even when analytical and numerical approaches are overly expensive in computation. Monte Carlo simulation could have detected the published analysis errors.

Keywords: Monte Carlo simulation, analytical results, leading digit rule, standard error

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Authors: Zahid Ahmad, Nauman Ali

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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: Septiany Trisnaningtyas

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Purpose: This research aims to examine the factors affecting the profitability of pharmaceutical company during the Covid-19 Pandemic in Indonesia. A sharp decline in the number of patients coming to the hospital for treatment during the pandemic has an impact on the growth of the pharmaceutical sector and brought major changes in financial position and business performance. Pharmaceutical companies that provide products related to the Covid-19 pandemic can survive and continue to grow. This study investigates the factors affecting the profitability of pharmaceutical company during the Covid-19 Pandemic in Indonesia associated with the number of Covid-19 cases. Design/methodology/approach: This study uses panel-data regression models to evaluate the influence of the number of Covid-19 confirmed cases on profitability of ninelisted pharmaceuticalcompanies in Indonesia. This research is based on four independent variables that were empirically examined for their relationship with profitability. These variables are liquidity (current ratio), growth rate (sales growth), firm size (total sales), and market power (the Lerner index). Covid-19 case is used as moderating variable. Data of nine pharmaceutical companies listed on the Indonesia Stock Exchange covering the period of 2018–2021 were extracted from companies’ quarterly annual reports. Findings: In the period during Covid-19, company growth (sales growth) and market power (lerner index) have a positive and significant relationship to ROA and ROE. Total of confirmed Covid-19 cases has a positive and significant relationship to ROA and is proven to have a moderating effect between company’s growth (sales growth) to ROA and ROE and market power (Lerner index) to ROA. Research limitations/implications: Due to data availability, this study only includes data from nine listed pharmaceutical companies in Indonesian Stock exchange and quarterly annual reportscovering the period of 2018-2021. Originality/value: This study focuses onpharmaceutical companies in Indonesia during Covid-19 pandemic. Previous study analyzes the data from pharmaceutical companies’ annual reports since 2014 and focus on universal health coverage (national health insurance) implementation from the Indonesian government. This study analyzes the data using fixed effect panel-data regression models to evaluate the influence of Covid-19 confirmed cases on profitability. Pooled ordinary least squares regression and fixed effects were used to analyze the data in previous study. This study also investigate the moderating effect of Covid-19 confirmed cases to profitability in relevant with the pandemic situation.

Keywords: profitability, indonesia, pharmaceutical, Covid-19

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Authors: Sai Hung Cheung, Zhe Shao

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It is of our great interest to quantify the risk to structural dynamic systems due to earthquake-induced tsunamis in view of recent earthquake-induced tsunamis in Padang, 2004 and Tohoku, 2011 which brought huge losses of lives and properties. Despite continuous advancement in computational simulation of the tsunami and wave-structure interaction modeling, it still remains computationally challenging to evaluate the reliability of a structural dynamic system when uncertainties related to the system and its modeling are taken into account. The failure of the structure in a tsunami-wave-structural system is defined as any response quantities of the system exceeding specified thresholds during the time when the structure is subjected to dynamic wave impact due to earthquake-induced tsunamis. In this paper, an approach based on a novel integration of a recently proposed moving least squares response surface approach for stochastic sampling and the Subset Simulation algorithm is proposed. The effectiveness of the proposed approach is discussed by comparing its results with those obtained from the Subset Simulation algorithm without using the response surface approach.

Keywords: response surface, stochastic simulation, structural reliability tsunami, risk

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Authors: Kemka C. Ihemelandu, Chukwuemeka U. Ihemelandu

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The incidence of melanoma has been increasing rapidly over the past two decades, making melanoma a current public health crisis. Unfortunately, even as screening efforts continue to expand in an effort to ameliorate the death rate from melanoma, there is a need to improve diagnostic accuracy to decrease misdiagnosis. Artificial intelligence (AI) a new frontier in patient care has the ability to improve the accuracy of melanoma diagnosis. Convolutional neural network (CNN) a form of deep neural network, most commonly applied to analyze visual imagery, has been shown to outperform the human brain in pattern recognition. However, there are noted limitations with the accuracy of the CNN models. Our aim in this study was the optimization of convolutional neural network algorithms for the automated diagnosis of melanoma. We hypothesized that Optimal selection of the momentum and batch hyperparameter increases model accuracy. Our most successful model developed during this study, showed that optimal selection of momentum of 0.25, batch size of 2, led to a superior performance and a faster model training time, with an accuracy of ~ 83% after nine hours of training. We did notice a lack of diversity in the dataset used, with a noted class imbalance favoring lighter vs. darker skin tone. Training set image transformations did not result in a superior model performance in our study.

Keywords: melanoma, convolutional neural network, momentum, batch hyperparameter

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Authors: Carlos Riobo

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This paper analyzes literature and art in Argentina from the nineteenth to the twenty-first centuries as these media used the figure of the white female captive to define a developing national identity. This identity excluded the Indians whose lands the whites were taking and who appeared as the aggressors and captors in writing and paintings. The paper identifies the complicit relationship between art and history in crafting national memory. It also identifies a movement toward purity (as defined by separation of entities) and away from mestizaje (racial and cultural mixtures).

Keywords: Argentina, borders, captives, literature, painting

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Authors: I. L. Kim, J. Y. Lee, A. K. Tekile

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In consequence of the very high urbanization rate of Korea, the number of traffic noise damages in areas congested with population and facilities is steadily increasing. The current environmental noise levels data in major cities of the country show that the noise levels exceed the standards set for both day and night times. This research was about comparative analysis in search for optimal soundproof panel shape and design factor that can minimize sound reflection noise. In addition to the normal flat-type panel shape, the reflection noise reduction of swelling-type, combined swelling and curved-type, and screen-type were evaluated. The noise source model Nord 2000, which often provides abundant information compared to models for the similar purpose, was used in the study to determine the overall noise level. Based on vehicle categorization in Korea, the noise levels for varying frequency from different heights of the sound source (directivity heights of Harmonize model) have been calculated for simulation. Each simulation has been made using the ray-tracing method. The noise level has also been calculated using the noise prediction program called SoundPlan 7.2, for comparison. The noise level prediction was made at 15m (R1), 30 m (R2) and at middle of the road, 2m (R3) receiving the point. By designing the noise barriers by shape and running the prediction program by inserting the noise source on the 2nd lane to the noise barrier side, among the 6 lanes considered, the reflection noise slightly decreased or increased in all noise barriers. At R1, especially in the cases of the screen-type noise barriers, there was no reduction effect predicted in all conditions. However, the swelling-type showed a decrease of 0.7~1.2 dB at R1, performing the best reduction effect among the tested noise barriers. Compared to other forms of noise barriers, the swelling-type was thought to be the most suitable for reducing the reflection noise; however, since a slight increase was predicted at R2, further research based on a more sophisticated categorization of related design factors is necessary. Moreover, as swellings are difficult to produce and the size of the modules are smaller than other panels, it is challenging to install swelling-type noise barriers. If these problems are solved, its applicable region will not be limited to other types of noise barriers. Hence, when a swelling-type noise barrier is installed at a downtown region where the amount of traffic is increasing every day, it will both secure visibility through the transparent walls and diminish any noise pollution due to the reflection. Moreover, when decorated with shapes and design, noise barriers will achieve a visual attraction than a flat-type one and thus will alleviate any psychological hardships related to noise, other than the unique physical soundproofing functions of the soundproof panels.

Keywords: reflection noise, shaped noise barriers, sound proof panel, traffic noise

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Authors: Adelakun O. Johnson

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The quest to mitigate the probable adverse effects of geopolitical risk on FDI inflows tends to result in more frequent changes in economic policies and, as a result, heightened policy uncertainty. In this regard, we extend the literature on the dynamics of FDI inflows to include the hypothesis of the possibility of geopolitical risk escalating the adverse effects of economic policy uncertainty on FDI inflows. To test the robustness of this hypothesis, we use the cases of different economic groups characterized by different levels of economic development and varying degrees of FDI confidence. Employing an ARDL-based dynamic panel data model that accounts for both non-stationarity and heterogeneity effects, we show result that suggests GPR and EPU retard the inflows of FDI in both economies but mainly in the short-run situation. In the long run, however, higher EPU not attributed to GPR is likely to boost the inflows of FDI rather than retarding, at least in the case of the G7 economy.

Keywords: FDI inflows, geopolitical risk, economic policy uncertainty, panel ARDL model

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Authors: Elvira Mustikawati P.H., Iis Dewi Ratih, Dita Amelia

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Bojonegoro has proclaimed a policy of zero malnutrition. Therefore, as an effort to solve the cases of malnutrition children in Bojonegoro, this study used the approach geographically Mixed Weighted Regression (MGWR) to determine the factors that influence the percentage of malnourished children under five in which factors can be divided into locally influential factor in each district and global factors that influence throughout the district. Based on the test of goodness of fit models, R2 and AIC values in GWR models are better than MGWR models. R2 and AIC values in MGWR models are 84.37% and 14.28, while the GWR models respectively are 91.04% and -62.04. Based on the analysis with GWR models, District Sekar, Bubulan, Gondang, and Dander is a district with three predictor variables (percentage of vitamin A, the percentage of births assisted health personnel, and the percentage of clean water) that significantly influence the percentage of malnourished children under five.

Keywords: GWR, MGWR, R2, AIC

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Authors: Abdoullah Fath-Allah, Laila Cheikhi, Rafa E. Al-Qutaish, Ali Idri

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Many quality models have been used to measure e-government portals quality. However, the absence of an international consensus for e-government portals quality models results in many differences in terms of quality attributes and measures. The aim of this paper is to compare and analyze the existing e-government quality models proposed in literature (those that are based on ISO standards and those that are not) in order to propose guidelines to build a good and useful e-government portals quality model. Our findings show that, there is no e-government portal quality model based on the new international standard ISO 25010. Besides that, the quality models are not based on a best practice model to allow agencies to both; measure e-government portals quality and identify missing best practices for those portals.

Keywords: e-government, portal, best practices, quality model, ISO, standard, ISO 25010, ISO 9126

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Authors: F. Pagliara, F. Mauriello

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The objective of this paper is to investigate the relationship between the increase of accessibility brought by high speed rail (HSR) systems and the tourism market in Italy. The impacts of HSR projects on tourism can be quantified in different ways. In this manuscript, an empirical analysis has been carried out with the aid of a dataset containing information both on tourism and transport for 99 Italian provinces during the 2006-2016 period. Panel data regression models have been considered, since they allow modelling a wide variety of correlation patterns. Results show that HSR has an impact on the choice of a given destination for Italian tourists while the presence of a second level hub mainly affects foreign tourists. Attraction variables are also significant for both categories and the variables concerning security, such as number of crimes registered in a given destination, have a negative impact on the choice of a destination.

Keywords: tourists, overnights, high speed rail, attractions, security

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Authors: Teboho J. Mosikari, Johannes T. Tsoku, Diteboho L. Xaba

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The increase of capital mobility across emerging economies has become an interesting topic for many economic policy makers. The current study tests the validity of Feldstein–Horioka puzzle for 5 BRICS countries. The sample period of the study runs from 2001 to 2014. The study uses the following parameter estimates well known as the Fully Modified OLS (FMOLS), and Dynamic OLS (DOLS). The results of the study show that investment and savings are cointegrated in the long run. The parameters estimated using FMOLS and DOLS are 0.85 and 0.74, respectively. These results imply that policy makers within BRICS countries have to consider flexible monetary and fiscal policy instruments to influence the mobility of capital with the bloc.

Keywords: Feldstein and Horioka puzzle, saving and investment, panel models, BRICS countries

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Authors: Ayman Aboelkassem, Mahmoud Ali

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Introduction: The models of soul houses have appeared in the prehistory, old kingdom and middle kingdom period. These soul houses represented the imagination of the deceased about his house in the afterlife, some of these soul houses were two floors and the study will examine five models of soul houses which were discovered near Saqqara site by an Egyptian mission. These models had been transferred to The Grand Egyptian Museum (GEM) to be ready to display at the new museum. We focus on models of soul houses (GEM Numbers, 1276, 1280, 1281, 1282, 8711) these models of soul houses were related to the old kingdom period. These models were all made of pottery, the five models have an oval shape and were decorated with relief. Methodology: The study will focus on the development of soul houses during the different periods in ancient Egypt, the function of soul houses, the kind of offerings which were put in it and the symbolism of the offerings colors in ancient Egyptian believe. Conclusion: This study is useful for the heritage and ancient civilizations especially when we talk about opening new museums like The Grand Egyptian Museum which will display a new collection of soul houses. The study of soul houses and The kinds of offerings which put in it reflect the economic situation in the Egyptian society and kinds of oils which were famous in ancient Egypt.

Keywords: archaeology study, Grand Egyptian Museum, relief, soul houses

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Authors: John Knight, Fuchun Li, Yan Xu

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Based on a new method of the nonparametric estimator of the drift function, we propose a consistent test for the parametric specification of the drift function in the short rate diffusion process using observations from a panel of yields. The test statistic is shown to follow an asymptotic normal distribution under the null hypothesis that the parametric drift function is correctly specified, and converges to infinity under the alternative. Taking the daily 7-day European rates as a proxy of the short rate, we use our test to examine whether the drift of the short rate diffusion process is linear or nonlinear, which is an unresolved important issue in the short rate modeling literature. The testing results indicate that none of the drift functions in this literature adequately captures the dynamics of the drift, but nonlinear specification performs better than the linear specification.

Keywords: diffusion process, nonparametric estimation, derivative security price, drift function and volatility function

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Authors: Ozgu Turgut

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Water scarcity is a problem for many regions which requires immediate action, and solutions cannot be postponed for a long time. It is known that farming consumes a significant portion of usable water. Although in recent years, the efforts to make the transition to dripping or spring watering systems instead of using surface watering started to pay off. It is also known that this transition is not necessarily translated into an increase in the capacity dedicated to other water consumption channels such as city water or power usage. In order to control and allocate the water resource more purposefully, new watering systems have to be used with monitoring abilities that can limit the usage capacity for each farm. In this study, a decision support model which relies on a bi-objective stochastic linear optimization is proposed, which takes crop yield and price volatility into account. The model generates annual planting plans as well as water usage limits for each farmer in the region while taking the total value (i.e., profit) of the overall harvest. The mathematical model is solved using the L-shaped method optimally. The decision support model can be especially useful for regional administrations to plan next year's planting and water incomes and expenses. That is why not only a single optimum but also a set of representative solutions from the Pareto set is generated with the proposed approach.

Keywords: decision support, farming, water, tactical planning, optimization, stochastic, pareto

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Authors: Tomoaki Hashimoto

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Recently, feedback control systems using random dither quantizers have been proposed for linear discrete-time systems. However, the constraints imposed on state and control variables have not yet been taken into account for the design of feedback control systems with random dither quantization. Model predictive control is a kind of optimal feedback control in which control performance over a finite future is optimized with a performance index that has a moving initial and terminal time. An important advantage of model predictive control is its ability to handle constraints imposed on state and control variables. Based on the model predictive control approach, the objective of this paper is to present a control method that satisfies probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization. In other words, this paper provides a method for solving the optimal control problems subject to probabilistic state constraints for linear discrete-time feedback control systems with random dither quantization.

Keywords: optimal control, stochastic systems, random dither, quantization

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

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This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: Wiriranai Brilliant Masara

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The African Peace and Security Architecture is widely celebrated and revered as a paragon of the will to address peace and security challenges in Africa. However, like any other institution, it is embedded with operational and institutional challenges that prevent it from effectively carrying out its mandate and turning goals into achieved results. The article examines the fundamental flaws and weaknesses of the African Peace and Security Architecture by focusing on its institutions, norms, instruments, and its relationship to Africa’s Regional Economic Communities. Therefore, the article reviews the flaws of the five elements of the African Peace and Security Architecture which are the Peace and Security Council, Panel of the Wise, Continental Early Warning System, African Standby Force, and Peace Fund.

Keywords: African Union, African Peace and Security Architecture, peace and security council, continental early warning system, African Standby Force, Panel of the Wise, Peace Fund

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Authors: T. Parhizkar, H. Jafarian, F. Aramoun, Y. Saboohi

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Applying motorized shades have substantial effect on reducing energy consumption in building sector. Moreover, the combination of motorized shades with lighting systems and PV panels can lead to considerable reduction in the energy demand of buildings. In this paper, a model is developed to assess and find an optimum combination from shade designs, lighting control systems (dimming and on/off) and implementing PV panels in shades point of view. It is worth mentioning that annual saving for all designs is obtained during hourly simulation of lighting, solar heat flux and electricity generation with the use of PV panel. From 12 designs in general, three designs, two lighting control systems and PV panel option is implemented for a case study. The results illustrate that the optimum combination causes a saving potential of 792kW.hr per year.

Keywords: motorized shades, daylight, cooling load, shade control, hourly simulation

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Authors: Ayoola Femi J., Kayode Balogun

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In some African Countries, increase in Gross Domestic Products (GDP) has not translated to real development as expected by common-man in his household. For decades, a lot of contests on economic growth and development has been a nagging issues. The focus of this study is to analysing the effects of economic determinants/factors on economic advances in some African Countries by employing panel data analysis. The yearly (1990-2013) data were obtained from the world economic outlook database of the International Monetary Fund (IMF), for probing the effects of these variables on growth rate in some selected African countries which include: Nigeria, Algeria, Angola, Benin, Botswana, Burundi, Cape-Verde, Cameroun, Central African Republic, Chad, Republic Of Congo, Cote di’ Voire, Egypt, Equatorial-Guinea, Ethiopia, Gabon, Ghana, Guinea Bissau, Kenya, Lesotho, Madagascar, Mali, Mauritius, Morocco, Mozambique, Niger, Rwanda, Senegal, Seychelles, Sierra Leone, South Africa, Sudan, Swaziland, Tanzania, Togo, Tunisia, and Uganda. The effects of 6 macroeconomic variables on GDP were critically examined. We used 37 Countries GDP as our dependent variable and 6 independent variables used in this study include: Total Investment (totinv), Inflation (inf), Population (popl), current account balance (cab), volume of imports of goods and services (vimgs), and volume of exports of goods and services (vexgs). The results of our analysis shows that total investment, population and volume of exports of goods and services strongly affect the economic growth. We noticed that population of these selected countries positively affect the GDP while total investment and volume of exports negatively affect GDP. On the contrary, inflation, current account balance and volume of imports of goods and services’ contribution to the GDP are insignificant. The results of our analysis shows that total investment, population and volume of exports of goods and services strongly affect the economic growth. We noticed that population of these selected countries positively affect the GDP while total investment and volume of exports negatively affect GDP. On the contrary, inflation, current account balance and volume of imports of goods and services’ contribution to the GDP are insignificant. The results of this study would be useful for individual African governments for developing a suitable and appropriate economic policies and strategies. It will also help investors to understand the economic nature and viability of Africa as a continent as well as its individual countries.

Keywords: African countries, economic growth and development, gross domestic products, static panel data models

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Authors: Liam Fassam, Pouria Liravi, Jacquie Bridgman

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Introduction: The way we travel is rapidly changing, car ownership and use are declining among young people and those residents in urban areas. Also, the increasing role and popularity of sharing economy companies like Uber highlight a movement towards consuming transportation solutions as a service [Mobility of a Service]. This research looks to bridge the knowledge gap that exists between city mobility, smart cities, sharing economy and social entrepreneurship business models. Understanding of this subject is crucial for smart city design, as access to affordable transport has been identified as a contributing factor to social isolation leading to issues around health and wellbeing. Methodology: To explore the current fit vis-a-vis transportation business models and social impact this research undertook a comparative analysis between a systematic literature review and a Delphi study. The systematic literature review was undertaken to gain an appreciation of the current academic thinking on ‘social entrepreneurship and smart city mobility’. The second phase of the research initiated a Delphi study across a group of 22 participants to review future opinion on ‘how social entrepreneurship can assist city mobility sharing models?’. The Delphi delivered an initial 220 results, which once cross-checked for duplication resulted in 130. These 130 answers were sent back to participants to score importance against a 5-point LIKERT scale, enabling a top 10 listing of areas for shared user transports in society to be gleaned. One further round (4) identified no change in the coefficient of variant thus no further rounds were required. Findings: Initial results of the literature review returned 1,021 journals using the search criteria ‘social entrepreneurship and smart city mobility’. Filtering allied to ‘peer review’, ‘date’, ‘region’ and ‘Chartered associated of business school’ ranking proffered a resultant journal list of 75. Of these, 58 focused on smart city design, 9 on social enterprise in cityscapes, 6 relating to smart city network design and 3 on social impact, with no journals purporting the need for social entrepreneurship to be allied to city mobility. The future inclusion factors from the Delphi expert panel indicated that smart cities needed to include shared economy models in their strategies. Furthermore, social isolation born by costs of infrastructure needed addressing through holistic A-political social enterprise models, and a better understanding of social benefit measurement is needed. Conclusion: In investigating the collaboration between key public transportation stakeholders, a theoretical model of social enterprise transportation models that positively impact upon the smart city needs of reduced transport poverty and social isolation was formed. As such, the research has identified how a revised business model of Mobility of a Service allied to a social entrepreneurship can deliver impactful measured social benefits associated to smart city design existent research.

Keywords: social enterprise, collaborative transportation, new models of ownership, transport social impact

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Tai-Yue Wang, Yi-Ho Chen

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In this study, we investigate a two-echelon supply chain with two suppliers and three retailers among which one retailer dominates other retailers. A price competition demand function is used to model this dominant retailer, which is leading market. The promotion strategies and negotiation schemes are integrated to form decision-making models under different scenarios. These models are then formulated into different mathematical programming models. The decision variables such as promotional costs, retailer prices, wholesale price, and order quantity are included in these models. At last, the distributions of promotion costs under different cost allocation strategies are discussed. Finally, an empirical example used to validate our models. The results from this empirical example show that the profit model will create the largest profit for the supply chain but with different profit-sharing results. At the same time, the more risk a member can take, the more profits are distributed to that member in the utility model.

Keywords: supply chain, price promotion, mathematical models, dominant retailer

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Authors: Joaquim Rubens Fontes-Filho, Felipe Buchbinder, Marcelo Desterro

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The study aims to identify the effects of an economic recession on the compensation of executives of listed companies. Market-based and labor environment explanations have received particular attention, both to explain the reasons for a growth in this compensation and to indicate that they may increase agency problems rather than mitigate them. In this sense, labor forces, especially related to the market for executives, contribute to defining the terms of compensation packages and represent a significant external control mechanism to moderate agency problems, but may be of little effect if the executives are entrenched and concentrate enough power to have a say in his/her compensation. Based on a five-year data panel related to executive compensation in 250 listed companies in Brazil, we examine whether the economic recession in the last two years produced any impact in this compensation, controlling for the sector and level of governance of the company.

Keywords: agency problems, executive compensation, control mechanisms, corporate governance

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Authors: S. Hamid Mirmohammadi, Shahrazad Tamjidzad

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This paper is concerned with the single-item continuous review inventory system in which demand is stochastic and discrete. The budget consumed for purchasing the ordered items is not restricted but it incurs extra cost when exceeding specific value. The unit purchasing price depends on the quantity ordered under the all-units discounts cost structure. In many actual systems, the budget as a resource which is occupied by the purchased items is limited and the system is able to confront the resource shortage by charging more costs. Thus, considering the resource shortage costs as a part of system costs, especially when the amount of resource occupied by the purchased item is influenced by quantity discounts, is well motivated by practical concerns. In this paper, an optimization problem is formulated for finding the optimal (R, Q) policy, when the system is influenced by the budget limitation and a discount pricing simultaneously. Properties of the cost function are investigated and then an algorithm based on a one-dimensional search procedure is proposed for finding an optimal (R, Q) policy which minimizes the expected system costs .

Keywords: (R, Q) policy, stochastic demand, backorders, limited resource, quantity discounts

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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: Ahmed E. Hodaib, Mohamed A. Hashem

Abstract:

In engineering applications, a design has to be as fully perfect as possible in some defined case. The designer has to overcome many challenges in order to reach the optimal solution to a specific problem. This process is called optimization. Generally, there is always a function called “objective function” that is required to be maximized or minimized by choosing input parameters called “degrees of freedom” within an allowed domain called “search space” and computing the values of the objective function for these input values. It becomes more complex when we have more than one objective for our design. As an example for Multi-Objective Optimization Problem (MOP): A structural design that aims to minimize weight and maximize strength. In such case, the Pareto Optimal Frontier (POF) is used, which is a curve plotting two objective functions for the best cases. At this point, a designer should make a decision to choose the point on the curve. Engineers use algorithms or iterative methods for optimization. In this paper, we will discuss the Evolutionary Algorithms (EA) which are widely used with Multi-objective Optimization Problems due to their robustness, simplicity, suitability to be coupled and to be parallelized. Evolutionary algorithms are developed to guarantee the convergence to an optimal solution. An EA uses mechanisms inspired by Darwinian evolution principles. Technically, they belong to the family of trial and error problem solvers and can be considered global optimization methods with a stochastic optimization character. The optimization is initialized by picking random solutions from the search space and then the solution progresses towards the optimal point by using operators such as Selection, Combination, Cross-over and/or Mutation. These operators are applied to the old solutions “parents” so that new sets of design variables called “children” appear. The process is repeated until the optimal solution to the problem is reached. Reliable and robust computational fluid dynamics solvers are nowadays commonly utilized in the design and analyses of various engineering systems, such as aircraft, turbo-machinery, and auto-motives. Coupling of Computational Fluid Dynamics “CFD” and Multi-Objective Evolutionary Algorithms “MOEA” has become substantial in aerospace engineering applications, such as in aerodynamic shape optimization and advanced turbo-machinery design.

Keywords: mathematical optimization, multi-objective evolutionary algorithms "MOEA", computational fluid dynamics "CFD", aerodynamic shape optimization

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