Search results for: model transformation

Authors: Giovanni Masala, Stefania Marica

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Forecasting electricity load plays a crucial role regards decision making and planning for economical purposes. Besides, in the light of the recent privatization and deregulation of the power industry, the forecasting of future electricity load turned out to be a very challenging problem. Empirical data about electricity load highlights a clear seasonal behavior (higher load during the winter season), which is partly due to climatic effects. We also emphasize the presence of load periodicity at a weekly basis (electricity load is usually lower on weekends or holidays) and at daily basis (electricity load is clearly influenced by the hour). Finally, a long-term trend may depend on the general economic situation (for example, industrial production affects electricity load). All these features must be captured by the model. The purpose of this paper is then to build an hourly electricity load model. The deterministic component of the model requires non-linear regression and Fourier series while we will investigate the stochastic component through econometrical tools. The calibration of the parameters’ model will be performed by using data coming from the Italian market in a 6 year period (2007- 2012). Then, we will perform a Monte Carlo simulation in order to compare the simulated data respect to the real data (both in-sample and out-of-sample inspection). The reliability of the model will be deduced thanks to standard tests which highlight a good fitting of the simulated values.

Keywords: ARMA-GARCH process, electricity load, fitting tests, Fourier series, Monte Carlo simulation, non-linear regression

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Authors: Naziema B. Jappie

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Over the last 23 years leaders in government, political parties and universities have been spending much time on identifying and discussing various gaps in the system that impact systematically on students especially those from historically Black communities. Equity and access to higher education were two critical aspects that featured in achieving the transformation goals together with a funding model for those previously disadvantaged. Free education was not a feasible option for the government. Institutional leaders in higher education face many demands on their time and resources. Often, the time for crisis management planning or consideration of being proactive and preventative is not a standing agenda item. With many issues being priority in academia, people become complacent and think that crisis may not affect them or they will cross the bridge when they get to it. Historically South Africa has proven to be a country of militancy, strikes and protests in most industries, some leading to disastrous outcomes. Higher education was not different between October 2015 and late 2016 when the #Rhodes Must Fall which morphed into the # Fees Must Fall protest challenged the establishment, changed the social fabric of universities, bringing the sector to a standstill. Some institutional leaders and administrators were better at handling unexpected, high-consequence situations than others. At most crisis leadership is viewed as a situation more than a style of leadership which is usually characterized by crisis management. The objective of this paper is to show how institutions managed catastrophes of disastrous proportions, down through unexpected incidents of 2015/2016. The content draws on the vast past crisis management experience of the presenter and includes the occurrences of the recent protests giving an event timeline. Using responses from interviews with institutional leaders and administrators as well as students will ensure first-hand information on their experiences and the outcomes. Students have tasted the power of organized action and they demand immediate change, if not the revolt will continue. This paper will examine the approaches that guided institutional leaders and their crisis teams and sector crisis response. It will further expand on whether the solutions effectively changed governance in higher education or has it minimized the need for more protests. The conclusion will give an insight into the future of higher education in South Africa from a leadership perspective.

Keywords: crisis, governance, intervention, leadership, strategies, protests

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Authors: Hamish Love, Navjot Bhullar, Nicola Schutte

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Self-control and related psychological constructs have been shown to have a large role in the improvement and maintenance of healthful dietary behaviour. However, self-control for diet, and related constructs such as motivation, level of conflict between tempting desires and dietary goals, and attentional bias for tempting food, have not been studied together to establish their relationships, to the author’s best knowledge. Therefore the aim of this paper was to conduct model testing on these constructs and evaluate how they relate to affect dietary outcomes. 400 Australian adult participants will be recruited via the Qualtrics platform and will be representative across age and gender. They will complete survey and reaction timing surveys to gather data on the five target constructs: Trait Self-control, Attentional Bias for Food, Dietary Goal-Desire Incongruence, Motivation for Dietary Self-control, and Satisfaction with Dietary Behaviour. A model of moderated mediation is predicted, whereby the initial predictor (Dietary Goal-Desire Incongruence) predicts the level of the outcome variable, Satisfaction with Dietary Behaviour. We hypothesise that the relationship between these two variables will be mediated by Trait Self-Control and that the extent that Trait Self-control is allowed to mediate dietary outcome is moderated by both Attentional Bias for Food and Motivation for Dietary Self-control. The analysis will be conducted using the PROCESS module in SPSS 23. The results of model testing in this current study will be valuable to direct future research and inform which constructs could be important targets for intervention to improve dietary outcomes.

Keywords: self-control, diet, model testing, attentional bias, motivation

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Authors: Yuyang Cheng, Marcos Escobar-Anel

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This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market.

Keywords: stochastic covariance process, 4/2 stochastic volatility model, stochastic co-volatility movements, characteristic function, expected utility theory, verication theorem

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

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The growing importance of reputation in building enterprise value and achieving long-term competitive advantage creates the need for its measurement and evaluation for the management purposes (effective reputation and its risk management). The paper presents practical application of self-developed corporate reputation assessment model from the viewpoint of stock market investors. The model has a pioneer character and example analysis performed for selected industry is a form of specific test for this tool. In the proposed solution, three aspects - informational, financial and development, as well as social ones - were considered. It was also assumed that the individual sub-criteria will be based on public sources of information, and as the calculation apparatus, capable of obtaining synthetic final assessment, fuzzy logic will be used. The main reason for developing this model was to fulfill the gap in the scope of synthetic measure of corporate reputation that would provide higher degree of objectivity by relying on "hard" (not from surveys) and publicly available data. It should be also noted that results obtained on the basis of proposed corporate reputation assessment method give possibilities of various internal as well as inter-branch comparisons and analysis of corporate reputation impact.

Keywords: corporate reputation, fuzzy logic, fuzzy model, stock market investors

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Authors: A. Porshnev, A. Zaporozhtchuk

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Motivation regarded as a key factor of labor turnover, is especially important for volunteers working on an altruistic basis in NGO. Despite the motivational letter, candidate selection depends on the impression of the selection committee, which can be subject to human bias. We expect that structured and unstructured information provided in motivation letters could be used to improve candidate selection procedures. In our paper, we perform qualitative and quantitative analysis of 2280 motivation letters, create logistic regression, and build a decision tree to improve selection procedures. Our analysis showed that motivation factors are significant and enable human resources department to forecast labor turnover and provide extra information to demographic, professional and timing questions. In spite of the average level of accuracy the model demonstrates the selection procedures of company of under consideration can be improved. We also discuss interrelation between answers to open and closed motivation questions, recommend changes in motivational letter templates to ensure more relevant information about applicants and further steps to create more accurate model.

Keywords: decision trees, logistic regression, model, motivational letter, non-governmental organization, retention, turnover

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Authors: Keri̇m Emre Öksüz, Şaduman Şen, Uğur Şen

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0.5 wt. % B2O3–doped Ba (Ti1-xZrx) O3, (x=0-0.4) lead-free nanoceramics were synthesized using the solid-state reaction method by adopting the ball milling technique. The influence of the substitution content on crystallographic structure, phase transition, microstructure and sintering behaviour of BT and BZT ceramics were investigated. XRD analysis at room temperature revealed a structural transformation from tetragonal to rhombohedral with enhancement of ZrO2 content in the barium titanate matrix. The scanning electron microscope (SEM) and energy-dispersive X-ray spectroscopy (EDS) were used to investigate microstructure and surface morphology of the sintered samples. The evolution of the Raman spectra was studied for various compositions, and the spectroscopic signature of the corresponding phase was determined. Scanning Electron Microscope (SEM) observations revealed enhanced microstructural uniformity and retarded grain growth with increasing Zr content.

Keywords: BaTiO3, barium-titanate-zirconate, nanoceramics, raman spectroscopy

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Authors: Ghada Abo-Zaid

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Introduction: Oil is one of the most income source in Bahrain. Low oil price influence on the economy growth and the investment rate in Bahrain. For example, the economic growth was 3.7% in 2012, and it reduced to 2.9% in 2015. Investment rate was 9.8% in 2012, and it is reduced to be 5.9% and -12.1% in 2014 and 2015, respectively. The inflation rate is increased to the peak point in 2013 with 3.3 %. Objectives: The objectives here are to build statistical models to examine the effect of the interest rate inflation rate on the growth economy in Bahrain from 2000 to 2018. Methods: This study based on 18 years, and the multiple regression model is used for the analysis. All of the missing data are omitted from the analysis. Results: Regression model is used to examine the association between the Growth national product (GNP), the inflation rate, and real interest rate. We found that (i) Increase the real interest rate decrease the GNP. (ii) Increase the inflation rate does not effect on the growth economy in Bahrain since the average of the inflation rate was almost 2%, and this is considered as a low percentage. Conclusion: There is a positive impact of the real interest rate on the GNP in Bahrain. While the inflation rate does not show any negative influence on the GNP as the inflation rate was not large enough to effect negatively on the economy growth rate in Bahrain.

Keywords: growth national product, egypt, regression model, interest rate

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Authors: G. Punithavathy

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The research proposes a statistical model for the distributed acoustic sensor interrogation units that broadcast a laser pulse into the fiber optics, where interactions within the fiber determine the localized acoustic energy that causes light reflections known as backscatter. The backscattered signal's amplitude and phase can be calculated using explicit equations. The created model makes amplitude signal spectrum and autocorrelation predictions that are confirmed by experimental findings. Phase signal characteristics that are useful for researching optical time domain reflectometry (OTDR) system sensing applications are provided and examined, showing good agreement with the experiment. The experiment was successfully done with the use of Python coding. In this research, we can analyze the entire distributed acoustic sensing (DAS) component parts separately. This model assumes that the fiber is in a static condition, meaning that there is no external force or vibration applied to the cable, that means no external acoustic disturbances present. The backscattered signal consists of a random noise component, which is caused by the intrinsic imperfections of the fiber, and a coherent component, which is due to the laser pulse interacting with the fiber.

Keywords: distributed acoustic sensing, optical fiber devices, optical time domain reflectometry, Rayleigh scattering

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Authors: Hasan G. Elmazoghi, Aisha I. Alzayani, Lubna S. Bentaher

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Rainfall is a highly non-linear phenomena, which requires application of powerful supervised data mining techniques for its accurate prediction. In this study the Artificial Neural Network (ANN) technique is used to predict the mean monthly historical rainfall data collected from BENINA station in Benghazi for 31 years, the period of “1977-2006” and the results are compared against the observed values. The specific objective to achieve this goal was to determine the best combination of weather variables to be used as inputs for the ANN model. Several statistical parameters were calculated and an uncertainty analysis for the results is also presented. The best ANN model is then applied to the data of one year (2007) as a case study in order to evaluate the performance of the model. Simulation results reveal that application of ANN technique is promising and can provide reliable estimates of rainfall.

Keywords: neural networks, rainfall, prediction, climatic variables

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Authors: M. A. Rahman, A. O. Enikuomehin

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Sharing commitment to reach a common goal in research by harnessing available resources from two or more parties can simply be referred to as collaborative research. Asides from avoiding duplication of research, the benefits often accrued from such research alliances include time economy as well as expenses reduction in completing such studies. Likewise, it provides an avenue to produce a wider horizon of scientific knowledge sequel to gathering of skills, knowledge and resources. In institutions of higher learning and research institutes, it often gives scholars an opportunity to strengthen the teaching and research capacity of their various institutions. Between industries and institutions, collaborative research breeds promising relationship that could be geared towards addressing different research problems such as producing and enhancing industrial-based products and services, including technological transfer. For Nigeria to take advantage of this collaboration, different issues like licensing of technology, intellectual property right, confidentiality, and funding among others, which could arise during this collaborative research programme, are identified in this paper. An important tool required to achieve this height in developing economy is the use of appropriate computer model. The paper highlights the costs of the collaborations and likewise stresses the need for evaluating the effectiveness and efficiency of such collaborative research activities and proposes an appropriate computer model to assist in this regard.

Keywords: collaborative research, developing country, computerization, model

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Authors: Shingo Murakami, Shinichi Enoki

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In structures, stress concentration is a factor of fatigue fracture. Basically, the stress concentration is a phenomenon that should be avoided. However, it is difficult to avoid the stress concentration. Therefore, relaxation of the stress concentration is important. The stress concentration arises from notches and circular holes. There is a relaxation method that a composite patch covers a notch and a circular hole. This relaxation method is used to repair aerial wings, but it is not systematized. Composites are more expensive than single materials. Accordingly, we propose the relaxation method that a single material patch covers a notch and a circular hole, and aim to systematize this relaxation method. We performed FEA (Finite Element Analysis) about an object by using a three-dimensional FEA model. The object was that a patch adheres to a plate with a circular hole. And, a uniaxial tensile load acts on the patched plate with a circular hole. In the three-dimensional FEA model, it is not easy to model the adhesion layer. Basically, the yield stress of the adhesive is smaller than that of adherents. Accordingly, the adhesion layer gets to plastic deformation earlier than the adherents under the yield load of adherents. Therefore, we propose the three-dimensional FEA model which is applied a nonlinear elastic region to the adhesion layer. The nonlinear elastic region was calculated by a bilinear approximation. We compared the analysis results with the tensile test results to confirm whether the analysis model has usefulness. As a result, the analysis results agreed with the tensile test results. And, we confirmed that the analysis model has usefulness. As a result that the three-dimensional FEA model was used to the analysis, it was confirmed that an out-of-plane deformation occurred to the patched plate with a circular hole. The out-of-plane deformation causes stress increase of the patched plate with a circular hole. Therefore, we investigated that the out-of-plane deformation affects relaxation of the stress concentration in the plate with a circular hole on this relaxation method. As a result, it was confirmed that the out-of-plane deformation inhibits relaxation of the stress concentration on the plate with a circular hole.

Keywords: stress concentration, patch, out-of-plane deformation, Finite Element Analysis

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Xiu Zhang

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The Merchant of Venice focuses on identity anxiety through the contract of “a pound of flesh” and refers to the economic, legal and religious issues related to identity. The development of the emerging capitalist economy in Venetian society prompted Shylock to become a usurer. The social identity of Shylock’s lender enabled him to use the power of money to consolidate the interdependent relationship with Christians and strive for his position and living space in Venetian society. However, there have long been economical and religious conflicts between Jews and Christians. Therefore, in order to take vengeance on Antonio and take his life, so as to revenge the whole Christian society, Shylock insists on taking a pound of Antonio’s flesh in the name of abiding by the contract and the law. The choice of “a pound of flesh” is essentially the representation of human materialization and commercialization under the background of the rise of capitalism and economic transformation. At the same time, it also symbolizes Shylock’s efforts and attempts to reshape himself and his racial identity.

Keywords: merchant of Venice, ethical choices, Shylock, a pound of flesh, identity anxiety

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Authors: Hassen M. Ouakad

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In this paper, the influence of van der Waals, as well as electrostatic forces on the structural behavior of MEMS and NEMS actuators, has been investigated using of a Euler-Bernoulli beam continuous model. In the proposed nonlinear model, the electrostatic fringing-fields and the mid-plane stretching (geometric nonlinearity) effects have been considered. The nonlinear integro-differential equation governing the static structural behavior of the actuator has been derived. An original Galerkin-based reduced-order model has been developed to avoid problems arising from the nonlinearities in the differential equation. The obtained reduced-order model equations have been solved numerically using the Newton-Raphson method. The basic design parameters such as the pull-in parameters (voltage and deflection at pull-in), as well as the detachment length due to the van der Waals force of some investigated micro- and nano-actuators have been calculated. The obtained numerical results have been compared with some other existing methods (finite-elements method and finite-difference method) and the comparison showed good agreement among all assumed numerical techniques.

Keywords: MEMS, NEMS, fringing-fields, mid-plane stretching, Galerkin

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Authors: Nafiseh Ebrahimi, Amir Jafari

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The study of humanoid character is of great interest to researchers in the field of robotics and biomechanics. One might want to know the forces and torques required to move a limb from an initial position to the desired destination position. Inverse dynamics is a helpful method to compute the force and torques for an articulated body limb. It enables us to know the joint torques required to rotate a link between two positions. Our goal in this study was to control a human-like articulated manipulator for a specific task of path tracking. For this purpose, the human arm was modeled with a three-link planar manipulator activated by Hill muscle model. Applying a proportional controller, values of force and torques applied to the joints were calculated by inverse dynamics, and then joints and muscle forces trajectories were computed and presented. To be more accurate to say, the kinematics of the muscle-joint space was formulated by which we defined the relationship between the muscle lengths and the geometry of the links and joints. Secondary, the kinematic of the links was introduced to calculate the position of the end-effector in terms of geometry. Then, we considered the modeling of Hill muscle dynamics, and after calculation of joint torques, finally, we applied them to the dynamics of the three-link manipulator obtained from the inverse dynamics to calculate the joint states, find and control the location of manipulator’s end-effector. The results show that the human arm model was successfully controlled to take the designated path of an ellipse precisely.

Keywords: arm manipulator, hill muscle model, six-muscle model, three-link lodel

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Authors: Ankur Sachan

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The ability to make quick yet intelligent and value-added decisions to develop new fields has always been of great significance. In situations where the capital expenses and subsurface risk are high, carefully analyzing the inherent uncertainties in the reservoir and how they impact the predicted hydrocarbon accumulation and production becomes a daunting task. The problem is compounded in offshore environments, especially in the presence of heavy oils and disconnected sands where the margin for error is small. Uncertainty refers to the degree to which the data set may be in error or stray from the predicted values. To understand and quantify the uncertainties in reservoir model is important when estimating the reserves. Uncertainty parameters can be geophysical, geological, petrophysical etc. Identification of these parameters is necessary to carry out the uncertainty analysis. With so many uncertainties working at different scales, it becomes essential to have a consistent and efficient way of incorporating them into our analysis. Ranking the uncertainties based on their impact on reserves helps to prioritize/ guide future data gathering and uncertainty reduction efforts. Assigning probabilistic ranges to key uncertainties also enables the computation of probabilistic reserves. With this in mind, this paper, with the help the uncertainty and optimization process in petrel RE shows how the most influential uncertainties can be determined efficiently and how much impact so they have on the reservoir model thus helping in determining a cost effective and accurate model of the reservoir.

Keywords: uncertainty, reservoir model, parameters, optimization analysis

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Authors: Anastasios Charisis, Evangelos Kaisar, Steven Spana, Lili Du

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Logistics play a vital role in the prosperity of today’s cities, but current urban logistics practices are proving problematic, causing negative effects such as traffic congestion and environmental impacts. This paper proposes an alternative urban logistics system, leasing hubs inside cities for designated time intervals, and using handcarts for last-mile deliveries. A mathematical model for selecting the locations of hubs and allocating customers, while also scheduling the optimal times during the day for leasing hubs is developed. The proposed model is compared to current delivery methods requiring door-to-door truck deliveries. It is shown that truck traveled distances decrease by more than 60%. In addition, analysis shows that in certain conditions the approach can be economically competitive and successfully applied to address real problems.

Keywords: hub location, last-mile, logistics, optimization

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Authors: Alexandra Lipitakis, Evangelia A. E. C. Lipitakis

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In this article, a class of e-business strategy planning parameters are introduced and their effect on financial and non-financial performance of e-businesses and organizations is investigated. The relationships between these strategic planning parameters, i.e. Formality, Participation, Sophistication, Thoroughness, Synergy and Cooperation, Entropic Factor, Adaptivity, Uncertainty and Financial and Non-Financial Performance are examined and the directions of these relationships are given. A conceptual model has been constructed and quantitative research methods can be used to test the considered eight hypotheses. In the framework of e-business strategy planning this research study clearly demonstrates how strategic planning components have positive relationships with e-business strategy management and performance.

Keywords: e-business management, e-business model, e-business performance assessments, strategy management methodologies, strategy planning, quantitative methods

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Authors: Amartya Hatua, Trung Nguyen, Andrew Sung

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In this paper, we study the information diffusion process on Twitter as a multivariate time series problem. Our model concerns three measures (volume, network influence, and sentiment of tweets) based on 10 features, and we collected 27 million tweets to build our information diffusion time series dataset for analysis. Then, different time series clustering techniques with Dynamic Time Warping (DTW) distance were used to identify different patterns of information diffusion. Finally, we built the information diffusion prediction models for new hashtags which comprise two phrases: The first phrase is recognizing the pattern using k-NN with DTW distance; the second phrase is building the forecasting model using the traditional Autoregressive Integrated Moving Average (ARIMA) model and the non-linear recurrent neural network of Long Short-Term Memory (LSTM). Preliminary results of performance evaluation between different forecasting models show that LSTM with clustering information notably outperforms other models. Therefore, our approach can be applied in real-world applications to analyze and predict the information diffusion characteristics of selected topics or memes (hashtags) in Twitter.

Keywords: ARIMA, DTW, information diffusion, LSTM, RNN, time series clustering, time series forecasting, Twitter

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Authors: Shohel Ahmed, Md. Abdul Alim, Sumaiya Rahman

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Optimal control can be helpful to test and compare different vaccination strategies of a certain disease. The mathematical model of HIV we consider here is a set of ordinary differential equations (ODEs) describing the interactions of CD4+T cells of the immune system with the human immunodeficiency virus (HIV). As an early treatment setting, we investigate an optimal chemotherapy strategy where control represents the percentage of effect the chemotherapy has on the system. The aim is to obtain a new optimal chemotherapeutic strategy where an isoperimetric constraint on the chemotherapy supply plays a crucial role. We outline the steps in formulating an optimal control problem, derive optimality conditions and demonstrate numerical results of an optimal control for the model. Numerical results illustrate how such a constraint alters the optimal vaccination schedule and its effect on cell-virus interactions.

Keywords: chemotherapy of HIV, optimal control involving ODEs, optimality conditions, Pontryagin’s maximum principle

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Authors: Homa Ghave, Parmis Shahmaleki

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This paper presents a new multi-criteria stochastic mathematical model for a single machine scheduling with outsourcing allowed. There are multiple jobs processing in batch. For each batch, all of job or a quantity of it can be outsourced. The jobs have stochastic processing time and lead time and deterministic due dates arrive randomly. Because of the stochastic inherent of processing time and lead time, we use the chance constrained programming for modeling the problem. First, the problem is formulated in form of stochastic programming and then prepared in a form of deterministic mixed integer linear programming. The objectives are considered in the model to minimize the maximum tardiness and outsourcing cost simultaneously. Several procedures have been developed to deal with the multi-criteria problem. In this paper, we utilize the concept of satisfaction functions to increases the manager’s preference. The proposed approach is tested on instances where the random variables are normally distributed.

Keywords: single machine scheduling, multi-criteria mathematical model, outsourcing strategy, uncertain lead times and processing times, chance constrained programming, satisfaction function

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Authors: A. Aulinger, A. M. Backes, J. Bieser, V. Matthias, M. Quante

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High concentrations of particles pose a threat to human health. Thus, legal maximum concentrations of PM10 and PM2.5 in ambient air have been steadily decreased over the years. In central Europe, the inorganic species ammonium sulphate and ammonium nitrate make up a large fraction of fine particles. Many studies investigate the influence of emission reductions of sulfur- and nitrogen oxides on aerosol concentration. Here, we focus on the influence of ammonia (NH3) emissions. While emissions of sulphate and nitrogen oxides are quite well known, ammonia emissions are subject to high uncertainty. This is due to the uncertainty of location, amount, time of fertilizer application in agriculture, and the storage and treatment of manure from animal husbandry. For this study, we implemented a crop growth model into the SMOKE emission model. Depending on temperature, local legislation, and crop type individual temporal profiles for fertilizer and manure application are calculated for each model grid cell. Additionally, the diffusion from soils and plants and the direct release from open and closed barns are determined. The emission data was used as input for the Community Multiscale Air Quality (CMAQ) model. Comparisons to observations from the EMEP measurement network indicate that the new ammonia emission module leads to a better agreement of model and observation (for both ammonia and ammonium). Finally, the ammonia emission model was used to create emission scenarios. This includes emissions based on future European legislation, as well as a dynamic evaluation of the influence of different agricultural sectors on particle formation. It was found that a reduction of ammonia emissions by 50% lead to a 24% reduction of total PM2.5 concentrations during winter time in the model domain. The observed reduction was mainly driven by reduced formation of ammonium nitrate. Moreover, emission reductions during winter had a larger impact than during the rest of the year.

Keywords: ammonia, ammonia abatement strategies, ctm, seasonal impact, secondary aerosol formation

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Authors: Mark Jackson

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Description: This paper is based on an theoretical analysis of the efficacy of the dominant model of policing in western jurisdictions. Those results are then compared with a similar analysis of a traditional reactive model. It is found that neither model provides for optimal delivery of services. Instead optimal service can be achieved by a synchronous hybrid model, termed the Convectory Policing approach. Methodology and Findings: For over three decades problem oriented policing (PO) has been the dominant model for western police agencies. Initially based on the work of Goldstein during the 1970s the problem oriented framework has spawned endless variants and approaches, most of which embrace a problem solving rather than a reactive approach to policing. This has included the Area Policing Concept (APC) applied in many smaller jurisdictions in the USA, the Scaled Response Policing Model (SRPM) currently under trial in Western Australia and the Proactive Pre-Response Approach (PPRA) which has also seen some success. All of these, in some way or another, are largely based on a model that eschews a traditional reactive model of policing. Convectory Policing (CP) is an alternative model which challenges the underpinning assumptions which have seen proliferation of the PO approach in the last three decades and commences by questioning the economics on which PO is based. It is argued that in essence, the PO relies on an unstated, and often unrecognised assumption that resources will be available to meet demand for policing services, while at the same time maintaining the capacity to deploy staff to develop solutions to the problems which were ultimately manifested in those same calls for service. The CP model relies on the observations from a numerous western jurisdictions to challenge the validity of that underpinning assumption, particularly in fiscally tight environment. In deploying staff to pursue and develop solutions to underpinning problems, there is clearly an opportunity cost. Those same staff cannot be allocated to alternative duties while engaged in a problem solution role. At the same time, resources in use responding to calls for service are unavailable, while committed to that role, to pursue solutions to the problems giving rise to those same calls for service. The two approaches, reactive and PO are therefore dichotomous. One cannot be optimised while the other is being pursued. Convectory Policing is a pragmatic response to the schism between the competing traditional and contemporary models. If it is not possible to serve either model with any real rigour, it becomes necessary to taper an approach to deliver specific outcomes against which success or otherwise might be measured. CP proposes that a structured roster-driven approach to calls for service, combined with the application of what is termed a resource-effect response capacity has the potential to resolve the inherent conflict between traditional and models of policing and the expectations of the community in terms of community policing based problem solving models.

Keywords: policing, reactive, proactive, models, efficacy

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Authors: P. W. Chen, C. T. Chang, Y. Peng, J. Y. Wu, D. J. Jan, Md. Manirul Ali

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In the last decade, the nature of cathode spot splitting and the current per spot depended on an oblique magnetic field was investigated. This model for cathode current splitting is developed that we have investigated with relationship the magnetic pressures produced by kinetic pressure, self-magnetic pressure, and changed with an external magnetic field. We propose a theoretical model that has been established to an external magnetic field with components normal and tangential to the cathode surface influenced on magnetic pressure strength. We mainly focus on developed to understand the current per spot influenced with the tangential magnetic field strength and normal magnetic field strength.

Keywords: cathode spot, vacuum arc discharge, oblique magnetic field, tangential magnetic field

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Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

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Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic

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Authors: Hanaa A. S. Oraby, Amal A. M. Hassan, Mahmoud M. Sakr, Atef A. A. Haiba

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Applying the profiling approach for the assessment of proteomic variations due to genetic modification of the Egyptian tomato cultivar "Edkawy", three complementary approaches were used. These methods are amino acids analysis, gel electrophoresis, and Gas chromatography coupled with mass spectrometry (GC/MS). The results of the present study Show evidence of proteomic variations between both modified tomato and its non-modified counterpart. Amino acids concentrations, and the protein patterns separation on the 1D SDS-PAGE were not similar in the case of transformed tomato compared to that of the non-transformed counterpart. These detected differences are most likely derived from the process of transformation. Results also revealed that the efficiency of GC/MS approach to identify a mixture of unknown proteins is limited. GC/MS analysis was only able to identify few number of protein molecules. Therefore, more advanced and specific technologies like MALDI-TOF-MS are recommended to be employed.

Keywords: GMOs, unintended effects, proteomic variations, 1D SDS-PAGE, GC/MS

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Authors: Muhammad A. Alsubaie

Abstract:

An iterative learning control framework designed in state feedback structure suffers a lack in investigating load disturbance considerations. The presented work discusses the controller previously designed, highlights the disturbance problem, finds new conditions using singular value principle to assure safe operation conditions with error convergence and reference tracking under the influence of load disturbance. It is known that periodic disturbances can be represented by a delay model in a positive feedback loop acting on the system input. This model can be manipulated by isolating the delay model and finding a controller for the overall system around the delay model to remedy the periodic disturbances using the small signal theorem. The overall system is the base for control design and load disturbance investigation. The major finding of this work is the load disturbance condition found which clearly sets safe operation condition under the influence of load disturbances such that the error tends to nearly zero as the system keeps operating trial after trial.

Keywords: iterative learning control, singular values, state feedback, load disturbance

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Authors: Danielle M. Barna, Kolbjørn Engeland, Thordis Thorarinsdottir, Chong-Yu Xu

Abstract:

Design flood values give estimates of flood magnitude within a given return period and are essential to making adaptive decisions around land use planning, infrastructure design, and disaster mitigation. Often design flood values are needed at locations with insufficient data. Additionally, in hydrologic applications where flood retention is important (e.g., floodplain management and reservoir design), design flood values are required at different flood durations. A statistical approach to this problem is a development of a regression model for extremes where some of the parameters are dependent on flood duration in addition to being covariate-dependent. In hydrology, this is called a regional flood-duration-frequency (regional-QDF) model. Typically, the underlying statistical distribution is chosen to be the Generalized Extreme Value (GEV) distribution. However, as the support of the GEV distribution depends on both its parameters and the range of the data, special care must be taken with the development of the regional model. In particular, we find that the GEV is problematic when developing a GAMLSS-type analysis due to the difficulty of proposing a link function that is independent of the unknown parameters and the observed data. We discuss these challenges in the context of developing a regional QDF model for Norway.

Keywords: design flood values, bayesian statistics, regression modeling of extremes, extreme value analysis, GEV

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Authors: Ratima Damkham, Natasha Dejdumrong, Priyakorn Pusawiro

Abstract:

This paper explored the solution in game design to help game designers in the educational game designing using digital educational game model canvas (DEGMC) and digital educational game form (DEGF) based on Outcome-based Education program. DEGMC and DEGF can help designers develop an overview of the game while designing and planning their own game. The way to clearly assess players’ ability from learning outcomes and support their game learning design is by using the tools. Designers can balance educational content and entertainment in designing a game by using the strategies of the Business Model Canvas and design the gameplay and players’ ability assessment from learning outcomes they need by referring to the Constructive Alignment. Furthermore, they can use their design plan in this research to write their Game Design Document (GDD). The success of the research was evaluated by four experts’ perspectives in the education and computer field. From the experiments, the canvas and form helped the game designers model their game according to the learning outcomes and analysis of their own game elements. This method can be a path to research an educational game design in the future.

Keywords: constructive alignment, constructivist theory, educational game, outcome-based education

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