Search results for: optimal monetary policy

Authors: Alhusein Almahjoub, Dongyu Qiu

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This paper deals with the random access procedure in next-generation networks and presents the solution to reduce total service time (TST) which is one of the most important performance metrics in current and future internet of things (IoT) based networks. The proposed solution focuses on the calculation of optimal transmission probability which maximizes the success probability and reduces TST. It uses the information of several idle preambles in every time slot, and based on it, it estimates the number of backlogged IoT devices using Naïve Bayes estimation which is a type of supervised learning in the machine learning domain. The estimation of backlogged devices is necessary since optimal transmission probability depends on it and the eNodeB does not have information about it. The simulations are carried out in MATLAB which verify that the proposed solution gives excellent performance.

Keywords: random access, LTE/LTE-A, 5G, machine learning, Naïve Bayes estimation

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Authors: Marouen Dghim, Mohsen Ferchichi

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The effect of synthetic jet actuation on the roll-up and the development of a wing tip vortex downstream a square-tipped rectangular wing was investigated experimentally using hotwire anemometry. The wing is equipped with a hallow cavity designed to generate a high aspect ratio synthetic jets blowing at an angles with respect to the spanwise direction. The structure of the wing tip vortex under the effect of fluidic actuation was examined at a chord Reynolds number Re_c=8×10^4. An extensive qualitative study on the effect of actuation on the spanwise pressure distribution at c⁄4 was achieved using pressure scanner measurements in order to determine the optimal actuation parameters namely, the blowing momentum coefficient, Cμ, and the non-dimensionalized actuation frequency, F^+. A qualitative study on the effect of actuation parameters on the spanwise pressure distribution showed that optimal actuation frequencies of the synthetic jet were found within the range amplified by both long and short wave instabilities where spanwise pressure coefficients exhibited a considerable decrease by up to 60%. The vortex appeared larger and more diffuse than that of the natural vortex case. Operating the synthetic jet seemed to introduce unsteadiness and turbulence into the vortex core. Based on the ‘a priori’ optimal selected parameters, results of the hotwire wake survey indicated that the actuation achieved a reduction and broadening of the axial velocity deficit. A decrease in the peak tangential velocity associated with an increase in the vortex core radius was reported as a result of the accelerated radial transport of angular momentum. Peak vorticity level near the core was also found to be largely diffused as a direct result of the increased turbulent mixing within the vortex. The wing tip vortex a exhibited a reduced strength and a diffused core as a direct result of increased turbulent mixing due to the presence of turbulent small scale vortices within its core. It is believed that the increased turbulence within the vortex due to the synthetic jet control was the main mechanism associated with the decreased strength and increased size of the wing tip vortex as it evolves downstream. A comparison with a ‘non-optimal’ case was included to demonstrate the effectiveness of selecting the appropriate control parameters. The Synthetic Jet will be operated at various actuation configurations and an extensive parametric study is projected to determine the optimal actuation parameters.

Keywords: flow control, hotwire anemometry, synthetic jet, wing tip vortex

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Authors: Shazmeen Maroof

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The study is motivated by a desire to investigate whether there is substance to claims that, relative to traditional donors, China disregards human rights considerations when allocating overseas aid. While the stated policy of the U.S. is that consideration of potential aid recipients’ respect for human rights is mandatory, some quantitative studies have cast doubt on whether this is reflected in actual allocations. There is a lack of academic literature that formally assesses the extent to which the two countries' aid allocations differ; which is essential to test whether the criticisms of China's aid policy in comparison to that of the U.S. are justified. Using data on two standard human rights measures, 'Political Terror Scale' and 'Civil Liberties', the study analyse the two donors’ aid allocations among 125 countries over the period 2000 to 2014. The bivariate analysis demonstrated that a significant share of China’s aid flow to countries with poor human rights record. At the same time, the U.S. seems little different in providing aid to these countries. The empirical results obtained from the Fractional Logit model also provided some support to the general pessimism regarding China’s provision of aid to countries with poor human rights record, yet challenge the optimists expecting better targeted aid from the U.S. These findings are consistent with the split between humanitarian and non-humanitarian aid and in the sample of countries whose human rights record is below some threshold level.

Keywords: China's aid policy, foreign aid allocation, human rights, United States Foreign Assistance Act

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Authors: Olufemi Adedamola Oyedele

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Infrastructure provision in Nigeria is now at its lowest ebb in spite of its being critical to the socio-economic and political development of any nation. This is partly because the policy that will ensure its adequate provisioning is missing and partly because politics is affecting its provision. Policy is the basic principles by which a government is guided. Infrastructural development is the basis for measuring the performance of governments and it is the foundation of good governance. Demand for infrastructural development is higher and resources used in its provision are limited. Ethnic-interest agitation and lobbying for infrastructure provision are common things in multi-ethnic state like Nigeria. Most infrastructures are now decayed and need repair or replacement. Government is the system that organizes, control and sensitizes the people in a society in other for all to have an acceptable level of living. Governments have the power to put in place all measures that they deem fit will make an environment conducive for living for everybody. Infrastructure development in any environment requires needs assessment, feasibility and viability studies and carrying out physical development of the project. The challenge in Nigeria is largely carrying out development where they are not needed but where the people are loyal. There are numerous abandoned projects because they were started due to politics and not because they are feasible. Policies and politics greatly affect infrastructure provisioning in Nigeria and this is the premise of this paper.

Keywords: infrastructure challenges, infrastructure development, policy making, politics, project finance

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Authors: Xingyu Pan, Laure Tougne

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For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.

Keywords: coin, detection, character recognition, topology

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Authors: Ahmed Kiani

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The United Arab Emirates is clearly facing a multitude of challenges in curbing its greenhouse gas emissions to meet its pre-allotted framework of Kyoto protocol and COP21 targets due to its hunger for modernization, industrialization, infrastructure growth, soaring population and oil and gas activity. In this work, we focus on the bonafide zero emission electric vehicles market penetration in the country’s transport industry for emission reduction. We study the global electric vehicle market trends, the complementary battery technologies and the trends by manufacturers, emission standards across borders and prioritized advancements which will ultimately dictate the terms of future conditions for the United Arab Emirate transport industry. Based on our findings and analysis at every stage of current viability and state-of-transport-affairs, we postulate policy recommendations to local governmental entities from a supply and demand perspective covering aspects of technology, infrastructure requirements, change in power dynamics, end user incentives program, market regulators behavior and communications amongst key stakeholders. 

Keywords: electric vehicles, greenhouse gas emission reductions, market analysis, policy recommendations

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Authors: E. Tandis, E. Assareh

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Designing the optimal shape of MW wind turbine blades is provided in a number of cases through evolutionary algorithms associated with mathematical modeling (Blade Element Momentum Theory). Evolutionary algorithms, among the optimization methods, enjoy many advantages, particularly in stability. However, they usually need a large number of function evaluations. Since there are a large number of local extremes, the optimization method has to find the global extreme accurately. The present paper introduces a new population-based hybrid algorithm called Genetic-Based Bees Algorithm (GBBA). This algorithm is meant to design the optimal shape for MW wind turbine blades. The current method employs crossover and neighborhood searching operators taken from the respective Genetic Algorithm (GA) and Bees Algorithm (BA) to provide a method with good performance in accuracy and speed convergence. Different blade designs, twenty-one to be exact, were considered based on the chord length, twist angle and tip speed ratio using GA results. They were compared with BA and GBBA optimum design results targeting the power coefficient and solidity. The results suggest that the final shape, obtained by the proposed hybrid algorithm, performs better compared to either BA or GA. Furthermore, the accuracy and speed convergence increases when the GBBA is employed

Keywords: Blade Design, Optimization, Genetic Algorithm, Bees Algorithm, Genetic-Based Bees Algorithm, Large Wind Turbine

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Authors: Dini Dewi Heniarti

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In the past decades, Indonesia has suffered severe terrorist attacks, faced major terrorism challenges and has made impressive progress in countering it. The trend of terrorist groups operating in Indonesia is to focus on ‘soft’ targets. Indonesia has made notable progress in strengthening the legal regime against terrorism, in conformity with the international treaties against terrorism. Further measures are however needed to complete the legal regime building processes. This paper will demonstrate analyze socio yuridical contra and counter terrorism by Indonesia Government.

Keywords: policy, strategy, combatting terrorism, socio juridical, counter and contra terrorism

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Authors: Pham Van Nha, Le Cam Binh

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Particle swarm optimization (PSO) is a population-based stochastic optimization algorithm. PSO was inspired by the natural behavior of birds and fish in migration and foraging for food. PSO is considered as a multidisciplinary optimization model that can be applied in various optimization problems. PSO’s ideas are simple and easy to understand but PSO is only applied in simple model problems. We think that in order to expand the applicability of PSO in complex problems, PSO should be described more explicitly in the form of a mathematical model. In this paper, we represent PSO in a mathematical model and apply in the multivariate data classification. First, PSOs general mathematical model (MPSO) is analyzed as a universal optimization model. Then, Model of Optimal Centroids (MOC) is proposed for the multivariate data classification. Experiments were conducted on some benchmark data sets to prove the effectiveness of MOC compared with several proposed schemes.

Keywords: analysis of optimization, artificial intelligence based optimization, optimization for learning and data analysis, global optimization

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Authors: Pius W. Molo Chin

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Real life problems such as the Huxley equation are always modeled as nonlinear differential equations. These problems need accurate and reliable methods for their solutions. In this paper, we propose a nonstandard finite difference method in time and the Galerkin combined with the compactness method in the space variables. This coupled method, is used to analyze a two dimensional Huxley equation for the existence and uniqueness of the continuous solution of the problem in appropriate spaces to be defined. We proceed to design a numerical scheme consisting of the aforementioned method and show that the scheme is stable. We further show that the stable scheme converges with the rate which is optimal in both the L2 as well as the H1-norms. Furthermore, we show that the scheme replicates the decaying qualities of the exact solution. Numerical experiments are presented with the help of an example to justify the validity of the designed scheme.

Keywords: Huxley equations, non-standard finite difference method, Galerkin method, optimal rate of convergence

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: Shantol McIntosh

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Due to environmental and underlying health disparities, the COVID-19 pandemic has caused an added set of economic implications worldwide. Black and Hispanic individuals are more susceptible to contract COVID-19, and if they do, they are more likely to have a severe case that necessitates hospitalization or results in death (Altarum et al., 2020). The literature shows that disparities in health and health treatment are nothing new as they have been recorded for decades and indicate systemic and structural imbalances rooted in racism and discrimination. The purpose of this study is to determine the frequency with which these populations have access to healthcare and treatment. The study will also highlight the key drivers of health disparities. Findings and implications for research and policy will be discussed.

Keywords: COVID-19, racial and ethnic disparities, discrimination, policy

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Authors: Ayelet Gur

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Background: In recent years we are witnessing a welcome trend in which more children/persons with disabilities are living at home with their families and within their communities. This trend is related to various policy innovations as the UN Convention on the Rights of People with Disabilities that reflect a shift from the medical-institutional model to a human rights approach. We also witness the emergence of family centered approaches that perceive the family and not just the individual with the disability as a worthy target of policy planning, implementation and evaluation efforts. The current investigation aims to explore economic, psychological and social factors among households of families of children or adults with intellectual disabilities in Israel and to present policy recommendation. Methods: A national sample of 301 households was recruited through the education and employment settings of persons with intellectual disability. The main caregiver of the person with the disability (a parent) was interviewed. Measurements included the income and expense surveys; assets and debts questionnaire; the questionnaire on resources and stress; the social involvement questionnaire and Personal Wellbeing Index. Results: Findings indicate significant gaps in financial circumstances between households of families of children with intellectual disabilities and households of the general Israeli society. Households of families of children with intellectual disabilities report lower income and higher expenditures and loans than the general society. They experience difficulties in saving and coping with unexpected expenses. Caregivers (the parents) experience high stress, low social participation, low financial support from family, friend and non-governmental organizations and decreased well-being. They are highly dependent on social security allowances which constituted 40% of the household's income. Conclusions: Households' dependency on social security allowances may seem contradictory to the encouragement of persons with intellectual disabilities to favor independent living in light of the human rights approach to disability. New policy should aim at reducing caregivers' stress and enhance their social participation and support, with special emphasis on families of lower socio-economic status. Finally, there is a need to continue monitoring the economic and psycho-social needs of households of families of children with intellectual disabilities and other developmental disabilities.

Keywords: disability policy, family policy, intellectual and developmental disabilities, Israel, households study, parents of children with disabilities

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Authors: Tomoaki Hashimoto

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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 time and a moving terminal time. This paper examines the stability of model predictive control for linear discrete-time systems with additive stochastic disturbances. A sufficient condition for the stability of the closed-loop system with model predictive control is derived by means of a linear matrix inequality. The objective of this paper is to show the results of computational simulations in order to verify the validity of the obtained stability condition.

Keywords: computational simulations, optimal control, predictive control, stochastic systems, discrete-time systems

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Authors: C. O. Igberi, M. U. Amadi

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This research paper on the impact of import restriction on rice production in Nigeria is aimed at finding/proffering valid solutions to the age long problem of rice self-sufficiency, through a better understanding of policy measures used in the past, in this case, the effectiveness of rice import restriction of the early 90’s. It tries to answer the questions of; import restriction boosting domestic rice production and the macroeconomic determining factors of Gross Domestic Rice Product (GDRP). The research probe is investigated through literature and analytical frameworks, such that time series data on the GDRP, Gross Fixed Capital Formation (GFCF), average foreign rice producers’ prices(PPF), domestic producers’ prices (PPN) and the labour force (LABF) are collated for analysis (with an import restriction dummy variable, POL1). The research objectives/hypothesis are analysed using; Cointegration, Vector Error Correction Model (VECM), Impulse Response Function (IRF) and Granger Causality Test(GCT) methodologies. Results show that in the short-run error correction specification for GDRP, a percentage (1%) deviation away from the long-run equilibrium in a current quarter is only corrected by 0.14% in the subsequent quarter. Also, the rice import restriction policy had no significant effect on the GDRP at this time. Other findings show that the policy period has, in fact, had effects on the PPN and LABF. The choice variables used are valid macroeconomic factors that explain the GDRP of Nigeria, as adduced from the IRF and GCT, and in the long-run. Policy recommendations suggest that the import restriction is not disqualified as a veritable tool for improving domestic rice production, rather better enforcement procedures and strict adherence to the policy dictates is needed. Furthermore, accompanying policies which drive public and private capital investment and accumulation must be introduced. Also, employment rate and labour substitution in the agricultural sector should not be drastically changed, rather its welfare and efficiency be improved.

Keywords: import restriction, gross domestic rice production, cointegration, VECM, Granger causality, impulse response function

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Authors: Ons Triki, Fathi Abid

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Along with the increase in the use of leasing contracts in corporate finance, multiple studies aim to model the credit risk of the lease in order to cover the losses of the lessor of the asset if the lessee goes bankrupt. In the current research paper, a convertible lease contract is elaborated in a continuous time stochastic universe aiming to ensure the financial stability of the firm and quickly recover the losses of the counterparties to the lease in case of default. This work examines the term structure of the lease rates taking into account the credit default risk and the capital structure of the firm. The interaction between the lessee's capital structure and the equilibrium lease rate has been assessed by applying the competitive lease market argument developed by Grenadier (1996) and the endogenous structural default model set forward by Leland and Toft (1996). The cumulative probability of default was calculated by referring to Leland and Toft (1996) and Yildirim and Huan (2006). Additionally, the link between lessee credit risk and lease rate was addressed so as to explore the impact of convertible lease financing on the term structure of the lease rate, the optimal leverage ratio, the cumulative default probability, and the optimal firm value by applying an endogenous conversion threshold. The numerical analysis is suggestive that the duration structure of lease rates increases with the increase in the degree of the market price of risk. The maximal value of the firm decreases with the effect of the optimal leverage ratio. The results are indicative that the cumulative probability of default increases with the maturity of the lease contract if the volatility of the asset service flows is significant. Introducing the convertible lease contract will increase the optimal value of the firm as a function of asset volatility for a high initial service flow level and a conversion ratio close to 1.

Keywords: convertible lease contract, lease rate, credit-risk, capital structure, default probability

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Authors: Lana Dalawr Jalal

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This paper addresses the problem of offline path planning for Unmanned Aerial Vehicles (UAVs) in complex three-dimensional environment with obstacles, which is modelled by 3D Cartesian grid system. Path planning for UAVs require the computational intelligence methods to move aerial vehicles along the flight path effectively to target while avoiding obstacles. In this paper Modified Particle Swarm Optimization (MPSO) algorithm is applied to generate the optimal collision free 3D flight path for UAV. The simulations results clearly demonstrate effectiveness of the proposed algorithm in guiding UAV to the final destination by providing optimal feasible path quickly and effectively.

Keywords: obstacle avoidance, particle swarm optimization, three-dimensional path planning unmanned aerial vehicles

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Authors: Vivek Anand, Rainer Naegele

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Industry 4.0 is a global mega-trend revolutionizing the world of advanced manufacturing, but also bringing up challenges for SMEs. In response, many regional, as well as digital Industry 4.0 Platforms, have been set up to boost the competencies of established enterprises as well as SMEs. The concept of 'Clusters' is a policy tool that aims to be a starting point to establish sustainable and self-supporting structures in industries of a region by identifying competencies and supporting cluster actors with services that match their growth needs. This paper is motivated by the idea that Clusters have the potential to enable firms, particularly SMEs, to accelerate the innovation process and transition to digital technologies. In this research, the efficacy of Industry 4.0 platforms as Cluster ecosystems is evaluated, especially for SMEs. Focusing on the Baden Wurttemberg region in Germany, an action research method is employed to study how SMEs leverage other actors on Industry 4.0 Platforms to further their Industry 4.0 journeys. The aim is to evaluate how such Industry 4.0 platforms stimulate innovation, cooperation and competitiveness. Additionally, the barriers to these platforms fulfilling their promise to serve as capacity building cluster ecosystems for SMEs in a region will also be identified. The findings will be helpful for academicians and policymakers alike, who can leverage a ‘cluster policy’ to enable Industry 4.0 ecosystems in their regions. Furthermore, relevant management and policy implications stem from the analysis. This will also be of interest to the various players in a cluster ecosystem - like SMEs and service providers - who benefit from the cooperation and competition. The paper will improve the understanding of how a dialogue orientation, a bottom-up approach and active integration of all involved cluster actors enhance the potential of Industry 4.0 Platforms. A strong collaborative culture is a key driver of digital transformation and technology adoption across sectors, value chains and supply chains; and will position Industry 4.0 Platforms at the forefront of the industrial renaissance. Motivated by this argument and based on the results of the qualitative research, a roadmap will be proposed to position Industry 4.0 Platforms as effective clusters ecosystems to support Industry 4.0 adoption in a region.

Keywords: cluster policy, digital transformation, industry 4.0, innovation clusters, innovation policy, SMEs and startups

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Authors: Vickie Knox

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Since the ‘urgent humanitarian crisis’ of the arrival of tens of thousands of Central American minors at the Mexico-US border in early 2014, the USA has increasingly externalised migration controls to Mexico. Although the resulting policy ‘Plan Frontera Sur’ claimed to protect migrants’ human rights, it has manifested as harshly delivered in-country controls and an alarming increase in deportations, particularly of minors. This is of particular concern given the ongoing situation of forced migration caused by criminal violence in Central America because these deportations do not all comply with Mexico’s international obligations and with its own legal framework for international protection that allows inter alia verbal asylum claims and grants minors additional protection against deportation. Notably, the volume of deportations, the speed with which they are carried out and the lack of adequate screening indicate non-compliance with the principle of non-refoulement and the right to claim asylum or other forms of protection. Based on qualitative data gathered in fieldwork in 2015 and quantitative data covering the period 2014-2016, this research details three types of adverse outcome resulting from these externalised controls: human rights violations perpetrated in order to deliver the policy–namely, deportations that may not comply with the principle of non-refoulement or the protection of minors; human rights violations perpetrated in the execution of policy–such as violations by state actors during apprehension and detention; and adverse consequences of the policy – such as increased risk during transit. This research has particular resonance as the Trump era brings tighter enforcement in the region, and has broader relevance for the study of externalisation tools on a global level.

Keywords: deportation, externalisation, forced migration, non-refoulement

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Authors: Zhong-Dan Tu, Wang-Xi Fan, Yi-Chen Huang, Jen-Taut Yeh

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Novel ultrahigh molecular weight polyethylene (UHMWPE)/cellulose nanofiber (CNF) (F100CNFy) and UHMWPE/modified cellulose nanofiber (MCNF) (F100MCNFxy) as-prepared nanocomposite fibers were prepared by spinning F100CNFy and F100MCNFxy gel solutions, respectively. Cellulose nanofibers were successfully prepared by proper acid treatment of cotton fibers using sulfuric acid solutions. The best prepared CNF is with specific surface areas around 120 m2/g and a nanofiber diameter of 20 nm. Modified cellulose nanofiber was prepared by grafting maleic anhydride grafted polyethylene (PE-g-MAH) onto cellulose nanofibers. The achievable draw ratio (Dra) values of each F100MCNFxy as-prepared fiber series specimens approached a maximal value as their MCNF contents reached the optimal value at 0.05 phr. In which, the maximum Dra value obtained for F100MCNFx0.05 as-prepared fiber specimen prepared at the optimal MCNF content reached another maximum value as the weight ratio of PE-g-MAH to CNF approach an optimal value at 6. Similar to those found for the achievable drawing properties of the as-prepared fibers, the orientation factor, tensile strength (σ f) and initial modulus (E) values of drawn F100MCNF6y fiber series specimens with a fixed draw ratio reach a maximal value as their MCNF contents approach the optimal value, wherein the σ f and E values of the drawn F100MCNFxy fiber specimens are significantly higher than those of the drawn F100 fiber specimens and corresponding drawn F100CNFy fiber specimens prepared at the same draw ratios and CNF contents but without modification. To understand the interesting ultradrawing, thermal, orientation and tensile properties of F100CNFy and F100MCNFxy fiber specimens, Fourier transform infra-red, specific surface areas, and transmission electron microcopic analyses of the original and modified CNF nanofillers were performed in this study.

Keywords: ultradrawing, cellulose nanofibers, ultrahigh molecular weight polyethylene, nanocomposite fibers

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Authors: Hervice Roméo Fogno Fotsoa, Germaine Djuidje Kenmoe, Claude Vidal Aloyem Kazé

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One of the main applications of machine learning is the prediction of time series. But a more accurate prediction requires a more optimal model of machine learning. Several optimization techniques have been developed, but without considering the input variables disposition of the system. Thus, this work aims to present a new machine learning architecture optimization technique based on their optimal input variables disposition. The validations are done on the prediction of wind time series, using data collected in Cameroon. The number of possible dispositions with four input variables is determined, i.e., twenty-four. Each of the dispositions is used to perform the prediction, with the main criteria being the training and prediction performances. The results obtained from a static architecture and a dynamic architecture of neural networks have shown that these performances are a function of the input variable's disposition, and this is in a different way from the architectures. This analysis revealed that it is necessary to take into account the input variable's disposition for the development of a more optimal neural network model. Thus, a new neural network training algorithm is proposed by introducing the search for the optimal input variables disposition in the traditional back-propagation algorithm. The results of the application of this new optimization approach on the two single neural network architectures are compared with the previously obtained results step by step. Moreover, this proposed approach is validated in a collaborative optimization method with a single objective optimization technique, i.e., genetic algorithm back-propagation neural networks. From these comparisons, it is concluded that each proposed model outperforms its traditional model in terms of training and prediction performance of time series. Thus the proposed optimization approach can be useful in improving the accuracy of time series forecasts. This proves that the proposed optimization approach can be useful in improving the accuracy of time series prediction based on machine learning.

Keywords: input variable disposition, machine learning, optimization, performance, time series prediction

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Authors: Haitao Yang, Jianming Lv, Fei Xu, Xintong Wang, Yilin Huang, Lanting Xia, Xuewu Zhu

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Given a fixed fund, purchasing fewer hosts of higher capability or inversely more of lower capability is a must-be-made trade-off in practices for building a Hadoop big data platform. An exploratory study is presented for a Housing Big Data Platform project (HBDP), where typical big data computing is with SQL queries of aggregate, join, and space-time condition selections executed upon massive data from more than 10 million housing units. In HBDP, an empirical formula was introduced to predict the performance of host clusters potential for the intended typical big data computing, and it was shaped via a regression approach. With this empirical formula, it is easy to suggest an optimal cluster configuration. The investigation was based on a typical Hadoop computing ecosystem HDFS+Hive+Spark. A proper metric was raised to measure the performance of Hadoop clusters in HBDP, which was tested and compared with its predicted counterpart, on executing three kinds of typical SQL query tasks. Tests were conducted with respect to factors of CPU benchmark, memory size, virtual host division, and the number of element physical host in cluster. The research has been applied to practical cluster procurement for housing big data computing.

Keywords: Hadoop platform planning, optimal cluster scheme at fixed-fund, performance predicting formula, typical SQL query tasks

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Authors: Elena Vinogradova, Aleksei Pleshakov, Aleksei Yakovlev

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During the flight of a supersonic aircraft under various conditions (altitude, Mach, etc.), it becomes necessary to coordinate the operating modes of the air intake and engine. On the supersonic aircraft, it’s been done by changing various control factors (the angle of rotation of the wedge panels and etc.). This paper investigates the possibility of using modern optimization methods to determine the optimal position of the supersonic air intake wedge panels in order to maximize the total pressure recovery coefficient. Modern software allows us to conduct auto-optimization, which determines the optimal position of the control elements of the investigated product to achieve its maximum efficiency. In this work, the flow in the supersonic aircraft inlet has investigated and optimized the operation of the flaps of the supersonic inlet in an aircraft in a 2-D setting. This work has done using ANSYS CFX software. The supersonic aircraft inlet is a flat adjustable external compression inlet. The braking surface is made in the form of a three-stage wedge. The IOSO NM software package was chosen for optimization. Change in the position of the panels of the input device is carried out by changing the angle between the first and second steps of the three-stage wedge. The position of the rest of the panels is changed automatically. Within the framework of the presented work, the position of the moving air intake panel was optimized under fixed flight conditions of the aircraft under a certain engine operating mode. As a result of the numerical modeling, the distribution of total pressure losses was obtained for various cases of the engine operation, depending on the incoming flow velocity and the flight altitude of the aircraft. The results make it possible to obtain the maximum total pressure recovery coefficient under given conditions. Also, the initial geometry was set with a certain angle between the first and second wedge panels. Having performed all the calculations, as well as the subsequent optimization of the aircraft input device, it can be concluded that the initial angle was set sufficiently close to the optimal angle.

Keywords: optimal angle, optimization, supersonic air intake, total pressure recovery coefficient

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Authors: Sareh Edalati, Nasrin Omidvar, Arezoo Haghighian Roudsari, Delaram Ghodsi, Azizollaah Zargaran

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Background and aim: Improving consumer’s food choices and providing a healthy food environment by governments is one of the essential approaches to prevent non-communicable diseases and to fulfill the sustainable development goals (SDGs). The present study aimed to provide an analysis of the nutrition labeling policy as one of the main components of the healthy food environment to provide learning lessons for the country and other low and middle-income countries. Methods: Data were collected by reviewing documents and conducting semi-structured interviews with stakeholders. Respondents were selected through purposive and snowball sampling and continued until data saturation. MAXQDA software was used to manage data analysis. A deductive content analysis was used by applying the Kingdon multiple streams and the policy triangulation framework. Results: Iran is the first country in the Middle East and North Africa region, which has implemented nutrition traffic light labeling. The implementation process has gone through two phases: voluntary and mandatory. In the voluntary labeling, volunteer food manufacturers who chose to have the labels would receive an honorary logo and this helped to reduce the food-sector resistance gradually. After this phase, the traffic light labeling became mandatory. Despite these efforts, there has been poor involvement of media for public awareness and sensitization. Also, the inconsistency of nutrition traffic light colors which are based on food standard guidelines, lack of consistency between nutrition traffic light colors, the healthy/unhealthy nature of some food products such as olive oil and diet cola and the absence of a comprehensive evaluation plan were among the pitfalls and policy challenges identified. Conclusions: Strengthening the governance through improving collaboration within health and non-health sectors for implementation, more transparency of truthfulness of nutrition traffic labeling initiating with real ingredients, and applying international and local scientific evidence or any further revision of the program is recommended. Also, developing public awareness campaigns and revising school curriculums to improve students’ skills on nutrition label applications should be highly emphasized.

Keywords: nutrition labeling, policy analysis, food environment, Iran

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Authors: Habib Ur Rahman Habib

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Renewable energy resources are being realized as suitable options in hybrid energy planning for on-grid and micro grid. In this paper, operation, planning and optimal design of on-grid distributed energy resources based hybrid system are investigated. The aim is to minimize the cost of the overall energy system keeping in view the environmental emission and minimum penetration of conventional energy resources. Seven grid connected different case studies including diesel only, diesel-renewable based, and renewable based only are designed to perform economic analysis, operational planning and emission. Sensitivity analysis is implemented to investigate the impact of different parameters on the performance of energy resources.

Keywords: data management, renewable energy, distributed energy, smart grid, micro-grid, modeling, energy planning, design optimization

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Authors: Won Mog Choi, Seong Kyeong Hong, Seok Young Jeong

Abstract:

The stress on the buried pipeline under pavement is significantly affected by vehicle loads and elastic modulus of the soil surrounding the pipeline. The correct elastic modulus of soil has to be applied to the finite element model to investigate the effect of the vehicle loads on the buried pipeline using finite element analysis. The purpose of this study is to establish the approach to calculating the correct elastic modulus of soil using the optimization process. The optimal elastic modulus of soil, which minimizes the difference between the strain measured from vehicle driving test at the velocity of 35km/h and the strain calculated from finite element analyses, was calculated through the optimization process using multi-response surface methodology. Three elastic moduli of soil (road layer, original soil, dense sand) surrounding the pipeline were defined as the variables for the optimization. Further analyses with the optimal elastic modulus at the velocities of 4.27km/h, 15.47km/h, 24.18km/h were performed and compared to the test results to verify the applicability of multi-response surface methodology. The results indicated that the strain of the buried pipeline was mostly affected by the elastic modulus of original soil, followed by the dense sand and the load layer, as well as the results of further analyses with optimal elastic modulus of soil show good agreement with the test.

Keywords: pipeline, optimization, elastic modulus of soil, response surface methodology

Procedia PDF Downloads 362

Authors: Nadia Elouaer

Abstract:

Tax revenue is the main state resource and one of the important variables in tax policy. Nevertheless, this resource is continually decreasing, so it is important to focus on the reasons for this decline. Several studies show that the taxpayer is reluctant to pay taxes, especially in countries at risk or in countries in transition, including Tunisia. This study focuses on the tax evasion behavior of a Tunisian taxpayer under the influence of his political beliefs, as well as the influence of different tax compliance variables. Using a questionnaire, a sample of 500 Tunisian taxpayers is used to examine the relationship between political beliefs and taxpayer affiliations and tax compliance variables, as well as the study of the causal link between political beliefs and fraudulent behavior. The data were examined using correlation, factor, and regression analysis and found a positive and statistically significant relationship between the different tax compliance variables and the tax evasion behavior. There is also a positive and statistically significant relationship between tax evasion and political beliefs and affiliations. The study of the relationship between political beliefs and compliance variables shows that they are closely related. The conclusion is to admit that tax evasion and political beliefs are closely linked, and the government should update its tax policy and modernize its administration in order to strengthen the credibility and disclosure of information in order to restore a relationship of trust between public authorities and the taxpayer.

Keywords: fiscal policy, political beliefs, tax evasion, taxpayer behavior

Procedia PDF Downloads 133

Authors: Hidefumi Kawakatsu, Dong Li, Kosuke Kato

Abstract:

In Japan, meat-type chickens are mainly classified into three categories: (1) Broilers, (2) Branded chickens, and (3) Jidori (Free-range local traditional pedigree chickens). The Jidori chickens are certified by the Japanese Ministry of Agriculture, whilst, for the Branded chickens, there is no regulation with respect to their breed (genotype) or methods for rearing them. It is, therefore, relatively easy for poultry farmers to introduce Branded than Jidori chickens. The Branded chickens are normally fed a low-calorie diet with ingredients such as herbs, which lengthens their breeding period (compared with that of the Broilers) and increases their market value. In the field of inventory management, fast-growing animals such as broilers are categorised as ameliorating items. To the best of our knowledge, there are no previous studies that have explicitly considered smaller sized poultry farmers with limited breeding areas. This study develops an inventory model for a small sized poultry farmer that produces both the Broilers (Product 1) and the Branded chickens (Product 2) with different amelioration rates. The poultry farmer’s total profit per unit of time is formulated as a function of selling prices by using a price-dependent demand function. The existence of a unique optimal selling price for each product, which maximises the total profit, established. It has also been confirmed through numerical examples that, when the breeding area is fixed, the total profit could increase if the poultry farmer reduced the product quantity of Product 1 to introduce Product 2.

Keywords: amelioration, deterioration, small sized poultry farmers, optimal price

Procedia PDF Downloads 194

Authors: Smita Lakhotia, C. Kew, S. H. M. Siraj, B. Chern

Abstract:

Up to 50% of those with endometriosis may suffer from infertility due to either distorted pelvic anatomy/impaired oocyte release or inhibit ovum pickup and transport, altered peritoneal function, endocrine and anovulatory disorders, including LUF, impaired implantation, progesterone resistance or decreased levels of cellular immunity. The dilemma continues as to whether the surgery or IVF is the optimal management for such recurrent endometriomas. The core question is whether surgery adds anything of value for infertile women with recurrent endometriosis or not. Complete and detailed information on risks and benefits of treatment alternatives must be offered to patients, giving a realistic estimate of chances of success of repetitive surgery and of multiple IVF cycles in order to allow unbiased choices between different possible optionsAn individualized treatment plan should be developed taking into account patient age, duration of infertility, previous pregnancies and specific clinical conditions and wish.

Keywords: recurrent endometriosis, infertility, oocyte release, pregnancy

Procedia PDF Downloads 224

Authors: Abdollah Kavousi Fard

Abstract:

This paper addresses the optimal scheduling of hybrid reconfigurable microgrids considering hybrid electric vehicle charging demands. A stochastic framework based on unscented transform to model the high uncertainties of renewable energy sources including wind turbine and photovoltaic panels, as well as the hybrid electric vehicles’ charging demand. In order to get to the optimal scheduling, the network reconfiguration is employed as an effective tool for changing the power supply path and avoiding possible congestions. The simulation results are analyzed and discussed in three different scenarios including coordinated, uncoordinated and smart charging demand of hybrid electric vehicles. A typical grid-connected microgrid is employed to show the satisfying performance of the proposed method.

Keywords: microgrid, renewable energy sources, reconfiguration, optimization

Procedia PDF Downloads 256