Search results for: national models

Authors: Flora Babongo, Valerie Chavez

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Inferring causality from observational data is one of the fundamental subjects, especially in quantitative finance. So far most of the papers analyze additive noise models with either linearity, nonlinearity or Gaussian noise. We fill in the gap by providing a nonlinear and non-gaussian causal multiplicative noise model that aims to distinguish the cause from the effect using a two steps method based on Bayesian additive models for location, scale and shape (BAMLSS) and on causal additive models (CAM). We have tested our method on simulated and real data and we reached an accuracy of 0.86 on average. As real data, we considered the causality between financial indices such as S&P 500, Nasdaq, CAC 40 and Nikkei, and companies' log-returns. Our results can be useful in inferring causality when the data is heteroskedastic or non-injective.

Keywords: causal inference, DAGs, BAMLSS, financial index

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Authors: Jamil Ahmed

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Access control models aim to decide whether a user should be denied or granted access to the user‟s requested activity. Various access control models have been established and proposed. The most prominent of these models include role-based, attribute-based, policy based access control models as well as role-centric attribute based access control model. In this paper, a novel access control model is presented called “Role centric Attribute based Policy Driven Access Control (RAPDAC) model”. RAPDAC incorporates the concept of “policy” in the “role centric attribute based access control model”. It leverages the concept of "policy‟ by precisely combining the evaluation of conditions, attributes, permissions and roles in order to allow authorization access. This approach allows capturing the "access control policy‟ of a real time application in a well defined manner. RAPDAC model allows making access decision at much finer granularity as illustrated by the case study of a real time library information system.

Keywords: authorization, access control model, role based access control, attribute based access control

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Authors: Nadarajah I. Ramesh

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Much of the research on stochastic point process models for rainfall has focused on Poisson cluster models constructed from either the Neyman-Scott or Bartlett-Lewis processes. The doubly stochastic Poisson process provides a rich class of point process models, especially for fine-scale rainfall modelling. This paper provides an account of recent development on this topic and presents the results based on some of the fine-scale rainfall models constructed from this class of stochastic point processes. Amongst the literature on stochastic models for rainfall, greater emphasis has been placed on modelling rainfall data recorded at hourly or daily aggregation levels. Stochastic models for sub-hourly rainfall are equally important, as there is a need to reproduce rainfall time series at fine temporal resolutions in some hydrological applications. For example, the study of climate change impacts on hydrology and water management initiatives requires the availability of data at fine temporal resolutions. One approach to generating such rainfall data relies on the combination of an hourly stochastic rainfall simulator, together with a disaggregator making use of downscaling techniques. Recent work on this topic adopted a different approach by developing specialist stochastic point process models for fine-scale rainfall aimed at generating synthetic precipitation time series directly from the proposed stochastic model. One strand of this approach focused on developing a class of doubly stochastic Poisson process (DSPP) models for fine-scale rainfall to analyse data collected in the form of rainfall bucket tip time series. In this context, the arrival pattern of rain gauge bucket tip times N(t) is viewed as a DSPP whose rate of occurrence varies according to an unobserved finite state irreducible Markov process X(t). Since the likelihood function of this process can be obtained, by conditioning on the underlying Markov process X(t), the models were fitted with maximum likelihood methods. The proposed models were applied directly to the raw data collected by tipping-bucket rain gauges, thus avoiding the need to convert tip-times to rainfall depths prior to fitting the models. One advantage of this approach was that the use of maximum likelihood methods enables a more straightforward estimation of parameter uncertainty and comparison of sub-models of interest. Another strand of this approach employed the DSPP model for the arrivals of rain cells and attached a pulse or a cluster of pulses to each rain cell. Different mechanisms for the pattern of the pulse process were used to construct variants of this model. We present the results of these models when they were fitted to hourly and sub-hourly rainfall data. The results of our analysis suggest that the proposed class of stochastic models is capable of reproducing the fine-scale structure of the rainfall process, and hence provides a useful tool in hydrological modelling.

Keywords: fine-scale rainfall, maximum likelihood, point process, stochastic model

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Authors: John Oupa Hlatshwayo

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Background: There seem to be preferred digital business models with varying impacts within hospitality, tourism and catering sub-sectors explored through online commerce, as all are ingrained in the business economics domain. Aim: A study aims to establish if such phenomena (Digital Business Models) exist and to what extent if any, within the hospitality, tourism and catering industries, respectively. Setting: This is a qualitative study conducted by exploring several (Four) institutions globally through Case Studies. Method: This research explored explanatory case studies to answer questions about ‘how’ or ’why’ with little control by a researcher over the occurrence of events. It is qualitative research, deductive, and inductive methods. Hence, a comprehensive approach to analyzing qualitative data was attainable through immersion by reading to understand the information. Findings: The results corroborated the notion that digital business models are applicable, by and large, in business economics. Thus, three sectors wherein enterprises operate in the business economics sphere have been narrowed down i.e. hospitality, tourism and catering, are also referred to as triangular polygons due to the atypical nature of being ‘stand-alone’, yet ‘sub-sectors’, but there are confounding factors to consider. Conclusion: The significance of digital business models and digital transformation shows an inevitable merger between business and technology within Hospitality, Tourism, and Catering. Contribution: Such symbiotic relationship of business and technology, persistent evolution of clients’ interface with end-products, forever changing market, current adaptation as well as adjustment to ‘new world order’ by enterprises must be embraced constantly without fail by Business Practitioners, Academics, Business Students, Organizations and Governments.

Keywords: digital business models, hospitality, tourism, catering, business economics

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Authors: Osayande Pascal Omondiagbe, Sherlock a Licorish

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Stack Overflow is a popular community question and answer portal which is used by practitioners to solve technology-related challenges during software development. Previous studies have shown that this forum is becoming a substitute for official software programming languages documentation. While tools have looked to aid developers by presenting interfaces to explore Stack Overflow, developers often face challenges searching through many possible answers to their questions, and this extends the development time. To this end, researchers have provided ways of predicting acceptable Stack Overflow answers by using various modeling techniques. However, less interest is dedicated to examining the performance and quality of typically used modeling methods, and especially in relation to models’ and features’ complexity. Such insights could be of practical significance to the many practitioners that use Stack Overflow. This study examines the performance and quality of various modeling methods that are used for predicting acceptable answers on Stack Overflow, drawn from 2014, 2015 and 2016. Our findings reveal significant differences in models’ performance and quality given the type of features and complexity of models used. Researchers examining classifiers’ performance and quality and features’ complexity may leverage these findings in selecting suitable techniques when developing prediction models.

Keywords: feature selection, modeling and prediction, neural network, random forest, stack overflow

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Authors: Nieto Bernal Wilson, Carmona Suarez Edgar

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The organizations have structured and unstructured information in different formats, sources, and systems. Part of these come from ERP under OLTP processing that support the information system, however these organizations in OLAP processing level, presented some deficiencies, part of this problematic lies in that does not exist interesting into extract knowledge from their data sources, as also the absence of operational capabilities to tackle with these kind of projects.  Data Warehouse and its applications are considered as non-proprietary tools, which are of great interest to business intelligence, since they are repositories basis for creating models or patterns (behavior of customers, suppliers, products, social networks and genomics) and facilitate corporate decision making and research. The following paper present a structured methodology, simple, inspired from the agile development models as Scrum, XP and AUP. Also the models object relational, spatial data models, and the base line of data modeling under UML and Big data, from this way sought to deliver an agile methodology for the developing of data warehouses, simple and of easy application. The methodology naturally take into account the application of process for the respectively information analysis, visualization and data mining, particularly for patterns generation and derived models from the objects facts structured.

Keywords: data warehouse, model data, big data, object fact, object relational fact, process developed data warehouse

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Authors: Sudipta Ghorai, Ossama Salem

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Pavement maintenance, repair, and rehabilitation (MRR) processes may have considerable environmental impacts due to traffic disruptions associated with work zones. The simulation models in use to predict the emission of work zones were mostly static emission factor models (SEFD). SEFD calculates emissions based on average operation conditions e.g. average speed and type of vehicles. Although these models produce accurate results for large-scale planning studies, they are not suitable for analyzing driving conditions at the micro level such as acceleration, deceleration, idling, cruising, and queuing in a work zone. The purpose of this study is to prepare a comprehensive work zone environmental assessment (WEA) framework to calculate the emissions caused due to disrupted traffic; by integrating traffic microsimulation tools with emission models. This will help highway officials to assess the benefits of accelerated construction and opt for the most suitable TMP not only economically but also from an environmental point of view.

Keywords: accelerated construction, pavement MRR, traffic microsimulation, congestion, emissions

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Authors: Min Kyung An

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In Wireless Sensor Networks which consist of tiny wireless sensor nodes with limited battery power, one of the most fundamental applications is data aggregation which collects nearby environmental conditions and aggregates the data to a designated destination, called a sink node. Important issues concerning the data aggregation are time efficiency and energy consumption due to its limited energy, and therefore, the related problem, named Minimum Latency Aggregation Scheduling (MLAS), has been the focus of many researchers. Its objective is to compute the minimum latency schedule, that is, to compute a schedule with the minimum number of timeslots, such that the sink node can receive the aggregated data from all the other nodes without any collision or interference. For the problem, the two interference models, the graph model and the more realistic physical interference model known as Signal-to-Interference-Noise-Ratio (SINR), have been adopted with different power models, uniform-power and non-uniform power (with power control or without power control), and different antenna models, omni-directional antenna and directional antenna models. In this survey article, as the problem has proven to be NP-hard, we present and compare several state-of-the-art approximation algorithms in various models on the basis of latency as its performance measure.

Keywords: data aggregation, convergecast, gathering, approximation, interference, omni-directional, directional

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Authors: Hamed K. Esfahani, Bithin Datta

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Transport of reactive chemical contaminant species in groundwater aquifers is a complex and highly non-linear physical and geochemical process especially for real life scenarios. Simulating this transport process involves solving complex nonlinear equations and generally requires huge computational time for a given aquifer study area. Development of optimal remediation strategies in aquifers may require repeated solution of such complex numerical simulation models. To overcome this computational limitation and improve the computational feasibility of large number of repeated simulations, Genetic Programming based trained surrogate models are developed to approximately simulate such complex transport processes. Transport process of acid mine drainage, a hazardous pollutant is first simulated using a numerical simulated model: HYDROGEOCHEM 5.0 for a contaminated aquifer in a historic mine site. Simulation model solution results for an illustrative contaminated aquifer site is then approximated by training and testing a Genetic Programming (GP) based surrogate model. Performance evaluation of the ensemble GP models as surrogate models for the reactive species transport in groundwater demonstrates the feasibility of its use and the associated computational advantages. The results show the efficiency and feasibility of using ensemble GP surrogate models as approximate simulators of complex hydrogeologic and geochemical processes in a contaminated groundwater aquifer incorporating uncertainties in historic mine site.

Keywords: geochemical transport simulation, acid mine drainage, surrogate models, ensemble genetic programming, contaminated aquifers, mine sites

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Authors: Michalis Linardakis, Vasilis Grammatikopoulos, Athanasios Gregoriadis, Kalliopi Trouli

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Discrete choice models belong to the family of Conjoint analysis that are applied on the preferences of the respondents towards a set of scenarios that describe alternative choices. The scenarios have been pre-designed to cover all the attributes of the alternatives that may affect the choices. In this study, we examine how preschool educators integrate physical activities into their everyday teaching practices through the use of discrete choice models. One of the advantages of discrete choice models compared to other more traditional data collection methods (e.g. questionnaires and interviews that use ratings) is that the respondent is called to select among competitive and realistic alternatives, rather than objectively rate each attribute that the alternatives may have. We present the effort to construct and choose representative attributes that would cover all possible choices of the respondents, and the scenarios that have arisen. For the purposes of the study, we used a sample of 50 preschool educators in Greece that responded to 4 scenarios (from the total of 16 scenarios that the orthogonal design resulted), with each scenario having three alternative teaching practices. Seven attributes of the alternatives were used in the scenarios. For the analysis of the data, we used multinomial logit model with random effects, multinomial probit model and generalized mixed logit model. The conclusions drawn from the estimated parameters of the models are discussed.

Keywords: conjoint analysis, discrete choice models, educational data, multivariate statistical analysis

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Authors: N. Sopipan

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In this paper, we study of rainfall time series of weather stations in Nakhon Ratchasima province in Thailand using various statistical methods enabled to analyse the behaviour of rainfall in the study areas. Time-series analysis is an important tool in modelling and forecasting rainfall. ARIMA and Holt-Winter models based on exponential smoothing were built. All the models proved to be adequate. Therefore, could give information that can help decision makers establish strategies for proper planning of agriculture, drainage system and other water resource applications in Nakhon Ratchasima province. We found the best perform for forecasting is ARIMA(1,0,1)(1,0,1)12.

Keywords: ARIMA Models, exponential smoothing, Holt-Winter model

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Authors: Muhammad Nur Haniff Mohd Noor, Rokiah Kadir, Suriyani Muhamad

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The National Forestry Act (NFA) 1984 is the primary forest law that regulates forest-related activities in Peninsular Malaysia. In the 1990s, abundance of illegal logging cases have called for legislative reform of the NFA 1984. As a result, NFA 1984 was amended in 1993 with the principal goal of controlling illegal forest encroachment in the forms of illegal logging, unauthorized harvesting, unlicensed forest settlement and other forms of unlawful activities. At a conceptual level, this paper discusses the policies and strategies implemented under the NFA 1984 (Amendment 1993) that are dedicated to overcome illegal logging. Then, the policies and strategies employed are reviewed and evaluated. Next, this paper conceptually discusses the loopholes of NFA 1984 (Amendment 1993) in relation to aspects where the regulation is considered insufficient to curb illegal logging. In the final section, vital actions and suggested improvements to improve the overall effectiveness of NFA 1984 (Amendment 1993) are examined.

Keywords: forest law and regulation, illegal logging, National Forestry Act 1984, NFA 1984, Amendment 1993, Peninsular Malaysia

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Authors: G. Stamatopoulou, M. Symeonaki, C. Michalopoulou

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In this work, we study the intergenerational social mobility in Greece, in order to provide up-to-date evidence on the changes in the mobility patterns throughout the years. An analysis for both men and women aged between 25-64 years old is carried out. Three main research objectives are addressed. First, we aim to examine the relationship between the socio-economic status of parents and their children. Secondly, we investigate the evolution of the mobility patterns between different birth cohorts. Finally, the role of education is explored in shaping the mobility patterns. For the analysis, we draw data on both parental and individuals' social outcomes from different national databases. The social class of origins and destination is measured according to the European Socio-Economic Classification (ESeC), while the respondents' educational attainment is coded into categories based on the International Standard Classification of Education (ISCED). Applying the Markov transition probability theory, and a range of measures and models, this work focuses on the magnitude and the direction of the movements that take place in the Greek labour market, as well as the level of social fluidity. Three-way mobility tables are presented, where the transition probabilities between the classes of destination and origins are calculated for different cohorts. Additionally, a range of absolute and relative mobility rates, as well as distance measures, are presented. The study covers a large time span beginning in 1940 until 1995, shedding light on the effects of the national institutional processes on the social movements of individuals. Given the evidence on the mobility patterns of the most recent birth cohorts, we also investigate the possible effects of the 2008 economic crisis.

Keywords: cohort analysis, education, Greece, intergenerational mobility, social class

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Authors: Keneilwe Maremi, Marlien Herselman, Adele Botha

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The main purpose and focus of this paper are to determine the Interoperability Maturity Models to consider when using School Management Systems (SMS). The importance of this is to inform and help schools with knowing which Interoperability Maturity Model is best suited for their SMS. To address the purpose, this paper will apply a scoping review to ensure that all aspects are provided. The scoping review will include papers written from 2012-2019 and a comparison of the different types of Interoperability Maturity Models will be discussed in detail, which includes the background information, the levels of interoperability, and area for consideration in each Maturity Model. The literature was obtained from the following databases: IEEE Xplore and Scopus, the following search engines were used: Harzings, and Google Scholar. The topic of the paper was used as a search term for the literature and the term ‘Interoperability Maturity Models’ was used as a keyword. The data were analyzed in terms of the definition of Interoperability, Interoperability Maturity Models, and levels of interoperability. The results provide a table that shows the focus area of concern for each Maturity Model (based on the scoping review where only 24 papers were found to be best suited for the paper out of 740 publications initially identified in the field). This resulted in the most discussed Interoperability Maturity Model for consideration (Information Systems Interoperability Maturity Model (ISIMM) and Organizational Interoperability Maturity Model for C2 (OIM)).

Keywords: interoperability, interoperability maturity model, school management system, scoping review

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Authors: Anjali Dewi Krishnan

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This paper attempts to explore the factors causing student loan defaults among NHEFC borrower besides measuring the enforcement actions that have been took by NHEFC to improve repayment rate. It starts by reviewing the causes of student loan default from the perspective of the loan borrowers besides finding out about the effectiveness of approaches taken by NHEFC (National Higher Education Fund Corporation) until now in order to increase the repayment rate and recover student loan default. The results gathered from the research used to investigate or identify the relationship between job statuses, gender, and ethnicity of the borrowers with repayment status, enforcement from the NHEFC side in the sense of student loan repayment; and respondent's opinion about enforcement in encouraging repayment of student loan and recover loan default. A combination of unemployment, financial constraint, inefficient repayment method and some other reasons of student loan defaults were discovered through this research. It finishes by presenting the reality whereby a student loan default is a result of inability to pay back and not about willingness to pay back.

Keywords: loan default, loan recovery, loan repayment, national higher education fund corporation

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Authors: Ivan Župan

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Critical infrastructure is essential for the functioning of a country and is designated for special protection by governments worldwide. Due to the increase in smart technology usage in every facet of the industry, including critical infrastructure, the exposure to malicious cyber-physical attacks has grown in the last few years. Proper security measures must be undertaken in order to defend against cyber-physical threats that can disrupt the normal functioning of critical infrastructure and, consequently the functioning of the country. This paper provides a review of the scientific literature of models, methods and technologies used to protect from cyber-physical threats in industries. The focus of the literature was observed from three aspects. The first aspect, resilience, concerns itself with the robustness of the system’s defense against threats, as well as preparation and education about potential future threats. The second aspect concerns security risk management for systems with cyber-physical aspects, and the third aspect investigates available testbed environments for testing developed models on scaled models of vulnerable infrastructure.

Keywords: critical infrastructure, cyber-physical security, smart industry, security methodology, security technology

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Authors: Nighat Bibi

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In recent years, there has been a significant increase in the use of AI models in healthcare. These models have been demonstrated to produce high accuracy in disease diagnosis and classification; however, they do not reveal the reasoning behind their predictions. Their black-box nature makes them untrustworthy for medical diagnosis. However, eXplainable Artificial Intelligence (XAI) techniques help determine the basis on which AI models make predictions. This review paper provides an overview of research conducted in the field of XAI for diagnosing, detecting, and classifying brain diseases such as brain tumours, Alzheimer’s disease, dementia, Parkinson’s disease, stroke, epilepsy, and autism spectrum disorder (ASD). It also highlights the importance of XAI techniques and the significance of the research being conducted in this field. Finally, we discuss the limitations of current XAI techniques and future research directions. This study can help doctors, researchers, and policymakers interested in the interpretability and explainability of AI models in diagnosing brain diseases.

Keywords: autism spectrum disorder, brain tumour, computer-aided diagnosis, dementia, epilepsy, explainability, explainable AI, interpretability, Parkinson’s disease, stroke, transparency

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Authors: Ali Hesari, Arezoo Esmaeeli

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Regarding to dramatic changes of fertility and higher order births during recent decades in Iran, access to knowledge about affecting factors on different birth orders has crucial importance. In this study, According to hierarchical structure of many of social sciences data and the effect of variables of different levels of social phenomena that determine different birth orders in 365 days ending to 1390 census have been explored by multilevel approach. In this paper, 2% individual row data for 1390 census is analyzed by HLM software. Three different hierarchical linear regression models are estimated for data analysis of the first and second, third, fourth and more birth order. Research results displays different outcomes for three models. Individual level variables entered in equation are; region of residence (rural/urban), age, educational level and labor participation status and province level variable is GDP per capita. Results show that individual level variables have different effects in these three models and in second level we have different random and fixed effects in these models.

Keywords: fertility, birth order, hierarchical approach, fixe effects, random effects

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Authors: Ehsan Eshtehardian, Saeed Khodaverdi

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This paper surveys the studies on construction change and reveals some of the potential future works. A full-scale investigation of change literature, including change definitions, types, causes and effects, and change management systems, is accomplished to explore some of the coming change trends. It is tried to pick up the critical works in each section to deduct a true timeline of construction changes. The findings show that leaping from best practice guides in late 1990s and generic process models in the early 2000s to very advanced modeling environments in the mid-2000s and the early 2010s have made gaps along with opportunities for change researchers in order to develop some more easy and applicable models. Another finding is that there is a compelling similarity between the change and risk prediction models. Therefore, integrating these two concepts, specifically from proactive management point of view, may lead to a synergy and help project teams avoid rework. Also, the findings show that exploitation of cause-effect relationship models, in order to facilitate the dispute resolutions, seems to be an interesting field for future works.

Keywords: construction change, change management systems, dispute resolutions, change literature

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Authors: Suren Chilingaryan

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We study two models describing a single two-level system coupled to two boson field modes in either a parallel or orthogonal setup. Both models may be feasible for experimental realization through Raman adiabatic driving in cavity QED. We study their ground state configurations; that is, we find the quantum precursors of the corresponding semi-classical phase transitions. We found that the ground state configurations of both models present the same critical coupling as the quantum Rabi model. Around this critical coupling, the ground state goes from the so-called normal configuration with no excitation, the qubit in the ground state and the fields in the quantum vacuum state, to a ground state with excitations, the qubit in a superposition of ground and excited state, while the fields are not in the vacuum anymore, for the first model. The second model shows a more complex ground state configuration landscape where we find the normal configuration mentioned above, two single-mode configurations, where just one of the fields and the qubit are excited, and a dual-mode configuration, where both fields and the qubit are excited.

Keywords: quantum optics, quantum phase transition, cavity QED, circuit QED

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Authors: Salah Alrabeei, Mohammad Yousuf

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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. However, most of the option pricing models have no analytical solution. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, we solve the American option under jump diffusion models by using efficient time-dependent numerical methods. several techniques are integrated to reduced the overcome the computational complexity. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). Partial fraction decomposition technique is applied to rational approximation schemes to overcome the complexity of inverting polynomial of matrices. The proposed method is easy to implement on serial or parallel versions. Numerical results are presented to prove the accuracy and efficiency of the proposed method.

Keywords: integral differential equations, jump–diffusion model, American options, rational approximation

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Authors: Hany Mohamed Abdu, Mohamed Hassan Gadallah, El-Giushi Mokhtar, Yehia Mahmoud Ismail

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Laser beam cutting is one nontraditional machining process. This paper optimizes the parameters of Laser beam cutting machining parameters of Stainless steel (316L) by considering the effect of input parameters viz. power, oxygen pressure, frequency and cutting speed. Statistical design of experiments are carried in three different levels and process responses such as 'Average kerf taper (Ta)' and 'Surface Roughness (Ra)' are measured accordingly. A quadratic mathematical model (RSM) for each of the responses is developed as a function of the process parameters. Responses predicted by the models (as per Taguchi’s L27 OA) are employed to search for an optimal parametric combination to achieve desired yield of the process. RSM models are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective problem subject to process constraints. Models are formulated based on Analysis of Variance (ANOVA) using MATLAB environment. Optimum solutions are compared with Taguchi Methodology results.

Keywords: optimization, laser cutting, robust design, kerf width, Taguchi method, RSM and DOE

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Authors: D. S. C. Soares, D. G. Costa, J. T. S., A. K. S. Abud, T. P. Nunes, A. M. Oliveira Júnior

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Mathematical models of drying are used for the purpose of understanding the drying process in order to determine important parameters for design and operation of the dryer. The jackfruit is a fruit with high consumption in the Northeast and perishability. It is necessary to apply techniques to improve their conservation for longer in order to diffuse it by regions with low consumption. This study aimed to analyse several mathematical models (Page, Lewis, and Midilli) to indicate one that best fits the conditions of convective drying process using performance indicators associated with each model: accuracy (Af) and noise factors (Bf), mean square error (RMSE) and standard error of prediction (% SEP). Jackfruit drying was carried out in convective type tray dryer at a temperature of 50°C for 9 hours. It is observed that the model Midili was more accurate with Af: 1.39, Bf: 1.33, RMSE: 0.01%, and SEP: 5.34. However, the use of the Model Midilli is not appropriate for purposes of control process due to need four tuning parameters. With the performance indicators used in this paper, the Page model showed similar results with only two parameters. It is concluded that the best correlation between the experimental and estimated data is given by the Page’s model.

Keywords: drying, models, jackfruit, biotechnology

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Authors: Abdellatif Chebboub

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Agricultural production is sensitive to weather and thus directly affected by climate change. Plausible estimates of these climate change impacts require combined use of climate, crop, and economic models. Results from previous studies vary substantially due to differences in models, scenarios, and data. This paper is part of a collective effort to systematically integrate these three types of models. We focus on the economic component of the assessment, investigating how nine global economic models of agriculture represent endogenous responses to seven standardized climate change scenarios produced by two climate and five crop models. These responses include adjustments in yields, area, consumption, and international trade. We apply biophysical shocks derived from the Intergovernmental Panel on Climate Change’s representative concentration pathway with end-of-century radiative forcing of 8.5 W/m2. The mean biophysical yield effect with no incremental CO2 fertilization is a 17% reduction globally by 2050 relative to a scenario with unchanging climate. Endogenous economic responses reduce yield loss to 11%, increase area of major crops by 11%, and reduce consumption by 3%. Agricultural production, cropland area, trade, and prices show the greatest degree of variability in response to climate change, and consumption the lowest. The sources of these differences include model structure and specification; in particular, model assumptions about ease of land use conversion, intensification, and trade. This study identifies where models disagree on the relative responses to climate shocks and highlights research activities needed to improve the representation of agricultural adaptation responses to climate change.

Keywords: climate change, agriculture, weather change, danger of climate change

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

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Authors: Sabry A. El Azazy

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Tourism plays an essential role in supporting the National Economy. Egypt was ranked as one of the most attractive touristic destinations worldwide. Tourism as a service sector affects political events and unstable conditions. Within the revolution of January 25th, 2011, tourism became below standards, and the archeological heritage sites were subject to threat. Because of the political tension and social instability, Egypt's tourism sector has drastically dropped. Currently, Egypt is working on overcoming the crisis caused by political unrest. However, it is expected to take a long time to get back to where it was, especially in terms of regaining the confidence of travelers in the country's ability to guarantee and maintain security and stability. Recently, many great projects have been done, such as; New Administrative Cairo Capital, New Suez Canal logistic project, New City of Al Alamin, New Grand Egyptian Museum, as well as other great projects that reflect positively on the tourism industry and archaeological heritage development in Egypt.

Keywords: archaeology, archaeological heritage, attractions, national economy, political events, touristic destinations, tourism industry

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Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: Ilma Ulfatul Janah, Ibnu Rizky Briwantara, Muhammad Afif

Abstract:

The agricultural sector is one of the sectors that contribute to national development. The benefit of the agricultural sector can be felt directly by the majority of Indonesian people. Indonesia is one of the agricultural countries and most of the people working in the agricultural sector. Hence, the agricultural sector’s become the second sector which has contributed greatly to the growth of Gross Domestic Product (GDP) after the manufacture sector. Based on the National Medium Term Development Plan (RPJMN) from 2015 to 2019, one of the targets to be achieved by the Indonesian government is rice’s self-sufficient. Rice is the main food commodities which as most people in Indonesia, and it is making Indonesian government attempt self-sufficient in rice. Indonesia as an agricultural country becomes one of the countries that have a lower percentage of food security than other ASEAN countries. Rice self-sufficiency can be created through agricultural productivity and the availability of a market for the output. There are some problems still to be faced by the farmers such as farmer exchange rate is low. The low exchange rate of farmers showed that the level of the welfare’s Indonesian farmers is still low. The aims of this paper are to resolve problems related to food security and improve the welfare of the national rice farmers. The method by using materials obtained from the analysis of secondary data with the descriptive approach and conceptual framework. Integrated Farmers barn raising rice production is integrated and managed by the government coupled with the implementation of technology in the form of systems connected and accessible to farmers, namely 'SIBUNGTAN'.

Keywords: agriculture, self-sufficiency, technology, productivity

Procedia PDF Downloads 248

Authors: Dev Ras Pandey, Bharat Mishra, S. K. Tripathi

Abstract:

Cloud computing is ready to transform the structure of businesses and learning through supplying the real-time applications and provide an immediate help for small to medium sized businesses. The ability to run a hypervisor inside a virtual machine is important feature of virtualization and it is called nested virtualization. In today’s growing field of information technology, many of the virtualization models are available, that provide a convenient approach to implement, but decision for a single model selection is difficult. This paper explains the applications of operating system based virtualization in cloud computing with an appropriate/suitable model with their different specifications and user’s requirements. In the present paper, most popular models are selected, and the selection was based on container and hypervisor based virtualization. Selected models were compared with a wide range of user’s requirements as number of CPUs, memory size, nested virtualization supports, live migration and commercial supports, etc. and we identified a most suitable model of virtualization.

Keywords: virtualization, OS based virtualization, container based virtualization, hypervisor based virtualization

Procedia PDF Downloads 326

Authors: Geoffrey J. Blanford, Christoph Weissbart

Abstract:

The prospects for the European power sector indicate that it has to almost fully decarbonize in order to reach the economy-wide target of CO₂-emission reduction. We apply the EU-REGEN model to explain the penetration of RES from an economic perspective, their spatial distribution, and the complementary role of conventional generation technologies. Furthermore, we identify economic consequences of national energy and climate targets. Our study shows that onshore wind power will be the most crucial generation technology for the future European power sector. Its geographic distribution is driven by resource quality. Gas power will be the major conventional generation technology for backing-up wind power. Moreover, a complete phase out of coal power proves to be not economically optimal. The paper demonstrates that existing national targets have a negative impact, especially on the German region with higher prices and lower revenues. The remaining regions profit are hardly affected. We encourage an EU-wide coordination on the expansion of wind power with harmonized policies. Yet, this requires profitable market structures for both, RES and conventional generation technologies.

Keywords: European, policy evaluation, power sector investment, technology choices

Procedia PDF Downloads 283