Search results for: multivariate disaggregation rainfall model

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: Zina Benouaret, Djamil Aissani

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In this work, we introduce the qualitative and quantitative concept of the strong stability method in the risk process modeling two lines of business of the same insurance company or an insurance and re-insurance companies that divide between them both claims and premiums with a certain proportion. The approach proposed is based on the identification of the ruin probability associate to the model considered, with a stationary distribution of a Markov random process called a reversed process. Our objective, after clarifying the condition and the perturbation domain of parameters, is to obtain the stability inequality of the ruin probability which is applied to estimate the approximation error of a model with disturbance parameters by the considered model. In the stability bound obtained, all constants are explicitly written.

Keywords: Markov chain, risk models, ruin probabilities, strong stability analysis

Procedia PDF Downloads 249

Authors: E. Channol, O. Collet, N. Kostyuchyk, T. Mesbah, Quoc Hoang Long Nguyen

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In this paper, a pricing model is proposed for co-integrated commodities extending Larsson model. The futures formulae have been derived and tests have been performed with non-constant volatility. The model has been applied to energy commodities (gas, CO2, energy) and soft commodities (corn, wheat). Results show that non-constant volatility leads to more accurate short term prices, which provides better evaluation of value-at-risk and more generally improve the risk management.

Keywords: co-integration, soft commodities, risk management, value-at-risk

Procedia PDF Downloads 547

Authors: Khaled S. Abdallah, Abdel-Aziz M. Mohamed

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Moving industries consume numerous resources and dispose masses of used packaging materials. Proper sorting, recycling and disposing the packaging materials is necessary to avoid a sever pollution disaster. This research paper presents a conceptual model to propose sustainable truck rental operations instead of the regular one. An optimization model was developed to select the locations of truck rental centers, collection sites, maintenance and repair sites, and identify the rental fees to be charged for all routes that maximize the total closed supply chain profits. Fixed costs of vehicle purchasing, costs of constructing collection centers and repair centers, as well as the fixed costs paid to use disposal and recycling centers are considered. Operating costs include the truck maintenance, repair costs as well as the cost of recycling and disposing the packing materials, and the costs of relocating the truck are presented in the model. A mixed integer model is developed followed by a simulation model to examine the factors affecting the operation of the model.

Keywords: modeling, truck rental, supply chains management.

Procedia PDF Downloads 228

Authors: Celina Pestano-Gabino, Concepcion Gonzalez-Concepcion, M. Candelaria Gil-Fariña

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Some estimation methods for VARMA models, and Multivariate Time Series Models in general, rely on the use of a Hankel matrix. It is known that if the data sample is populous enough and the dimension of the Hankel matrix is unnecessarily large, this may result in an unnecessary number of computations as well as in numerical problems. In this sense, the aim of this paper is two-fold. First, we provide some theoretical results for these matrices which translate into a lower dimension for the matrices normally used in the algorithms. This contribution thus serves to improve those methods from a numerical and, presumably, statistical point of view. Second, we have chosen an estimation algorithm to illustrate in practice our improvements. The results we obtained in a simulation of VARMA models show that an increase in the size of the Hankel matrix beyond the theoretical bound proposed as valid does not necessarily lead to improved practical results. Therefore, for future research, we propose conducting similar studies using any of the linear system estimation methods that depend on Hankel matrices.

Keywords: covariances Hankel matrices, Kronecker indices, system identification, VARMA models

Procedia PDF Downloads 243

Authors: Todd Zhou, Mikhail Yurochkin

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Out-of-distribution (OOD) detection is receiving increasing amounts of attention in the machine learning research community, boosted by recent technologies, such as autonomous driving and image processing. This newly-burgeoning field has called for the need for more effective and efficient methods for out-of-distribution generalization methods. Without accessing the label information, deploying machine learning models to out-of-distribution domains becomes extremely challenging since it is impossible to evaluate model performance on unseen domains. To tackle this out-of-distribution detection difficulty, we designed a model selection pipeline algorithm and developed a model selection framework with different impurity and randomness measurements to evaluate and choose the best-performing models for out-of-distribution data. By exploring different randomness scores based on predicted probabilities, we adopted the out-of-distribution entropy and developed a custom-designed score, ”CombinedScore,” as the evaluation criterion. This proposed score was created by adding labeled source information into the judging space of the uncertainty entropy score using harmonic mean. Furthermore, the prediction bias was explored through the equality of opportunity violation measurement. We also improved machine learning model performance through model calibration. The effectiveness of the framework with the proposed evaluation criteria was validated on the Folktables American Community Survey (ACS) datasets.

Keywords: model selection, domain generalization, model fairness, randomness measurements, bias index

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Authors: K. Bencherif, M. Bellifa

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The expected climatic changes in North Africa are the increase of both intensity and frequencies of the summer droughts and a reduction in water availability during growing season. The exiting coppices and forest formations in the national park of Tlemcen are dominated by holm oak, zen oak and cork oak. These opened-fragmented structures don’t seem enough strong so to hope durable protection against climate change. According to the observed climatic tendency, the objective is to analyze the climatic context and its evolution taking into account the eventual behaving of the oak species during the next 20-30 years on one side and the landscaped context in relation with the most adequate sylvicultural models to choose and especially in relation with human activities on another side. The study methodology is based on Climatic synthesis and Floristic and spatial analysis. Meteorological data of the decade 1989-2009 are used to characterize the current climate. An another approach, based on dendrochronological analysis of a 120 years sample Aleppo pine stem growing in the park, is used so to analyze the climate evolution during one century. Results on the climate evolution during the 50 years obtained through climatic predictive models are exploited so to predict the climate tendency in the park. Spatially, in each forest unit of the Park, stratified sampling is achieved so to reduce the degree of heterogeneity and to easily delineate different stands using the GPS. Results from precedent study are used to analyze the anthropogenic factor considering the forecasts for the period 2025-2100, the number of warm days with a temperature over 25°C would increase from 30 to 70. The monthly mean temperatures of the maxima’s (M) and the minima’s (m) would pass respectively from 30.5°C to 33°C and from 2.3°C to 4.8°C. With an average drop of 25%, precipitations will be reduced to 411.37 mm. These new data highlight the importance of the risk fire and the water stress witch would affect the vegetation and the regeneration process. Spatial analysis highlights the forest and the agricultural dimensions of the park compared to the urban habitat and bare soils. Maps show both fragmentation state and forest surface regression (50% of total surface). At the level of the park, fires affected already all types of covers creating low structures with various densities. On the silvi cultural plan, Zen oak form in some places pure stands and this invasion must be considered as a natural tendency where Zen oak becomes the structuring specie. Climate-related changes have nothing to do with the real impact that South-Mediterranean forests are undergoing because human constraints they support. Nevertheless, hardwoods stand of oak in the national park of Tlemcen will face up to unexpected climate changes such as changing rainfall regime associated with a lengthening of the period of water stress, to heavy rainfall and/or to sudden cold snaps. Faced with these new conditions, management based on mixed uneven aged high forest method promoting the more dynamic specie could be an appropriate measure.

Keywords: global warming, mediterranean forest, oak shrub-lands, Tlemcen

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Authors: Ghassan Al-Dulaimi

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This paper studied the biochemical parameter (BOD5) and (DO) for the Thames River (Canada-Ontario). Water samples have been collected from Thames River along different points between Chatham to Woodstock and were analysed for various water quality parameters during the low flow season (April). The study involves the application of the stream water quality model QUAL2K model to simulate and predict the dissolved oxygen (DO) and biochemical oxygen demand (BOD5) profiles for Thames River in a stretch of 251 kilometers. The model output showed that DO in the entire river was within the limit of not less than 4 mg/L. For Carbonaceous Biochemical Oxygen Demand CBOD, the entire river may be divided into two main reaches; the first one is extended from Chatham City (0 km) to London (150 km) and has a CBOD concentration of 2 mg/L, and the second reach has CBOD range (2–4) mg/L in which begins from London city and extend to near Woodstock city (73km).

Keywords: biochemical oxygen demand, dissolved oxygen, Thames river, QUAL2K model

Procedia PDF Downloads 93

Authors: Bobuchi Ken-Opurum

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The impacts of climate change on urban settlements is growing. In the global south, communities are even more vulnerable and suffer there is an increased vulnerability from due to climate change disasters such as flooding and high temperatures. This is primarily due to high intensity rainfall, low-lying coasts, inadequate infrastructure, and limited resources. According to the Emergency Events Database, floods were the leading cause of disaster -based deaths in the global south between 2006 and 2015. This includes deaths from heat stress related health outcomes. Adapting to climate vulnerabilities is paramount in reducing the significant redevelopment costs from climate disasters. Governments and urban planners provide top-down approaches such as evacuation, and disaster and emergency communication. While they address infrastructure and public services, they are not always able to address the immediate and critical day to day needs of poor and vulnerable populations. There is growing evidence that some bottom-up strategies and grassroots initiatives of self-build housing such as in urban informal settlements are successful in coping and adapting to hydroclimatic impacts. However, these research findings are not consolidated and the evaluation of the resilience outcomes of the bottom-up strategies are limited. Using self-build housing as a model for sustainable and resilient urban planning, this research aimed to consolidate the flood and heat stress resilient design solutions, analyze the effectiveness of these solutions, and develop guidelines and methods for adopting these design solutions into mainstream housing in megathermal climates. The methodological approach comprised of analyses of over 40 ethnographic based peer reviewed literature, white papers, and reports between the years 2000 and 2019 to identify coping strategies and grassroots initiatives that have been applied by occupants and communities of the global south. The results of the research provide a consolidated source and prioritized list of the best bottom-up strategies for communities in megathermal climates to improve the lives of people in some of the most vulnerable places in the world.

Keywords: resilient, design, megathermal, climate change

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Authors: S. Belhour, A. K. Ferouani, C. Azizi

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In recent years, a considerable effort (experience, numerical simulation, and theoretical prediction models) has characterised by high efficiency and low cost. Then an improved physics analytical model for simulating is proposed. The performance of GaAs MESFETs has been developed for use in device design for high frequency. This model is based on mathematical analysis, and a new approach for the standard model is proposed, this approach allowed to conceive applicable model for MESFET’s operating in the turn-one or pinch-off region and valid for the short-channel and the long channel MESFET’s in which the two dimensional potential distribution contributed by the depletion layer under the gate is obtained by conventional approximation. More ever, comparisons between the analytical models with different values of mobility are proposed, and a good agreement is obtained.

Keywords: analytical, gallium arsenide, MESFET, mobility, models

Procedia PDF Downloads 74

Authors: Usiobaifo Agharese Rosemary, Osaseri Roseline Oghogho

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Diabetes is a complex group of disease with a variety of causes; it is a disorder of the body metabolism in the digestion of carbohydrates food. The application of machine learning in the field of medical diagnosis has been the focus of many researchers and the use of recognition and classification model as a decision support tools has help the medical expert in diagnosis of diseases. Considering the large volume of medical data which require special techniques, experience, and high diagnostic skill in the diagnosis of diseases, the application of an artificial intelligent system to assist medical personnel in order to enhance their efficiency and accuracy in diagnosis will be an invaluable tool. In this study will propose a diabetes diagnosis model using rough set and K-nearest Neighbor classifier algorithm. The system consists of two modules: the feature extraction module and predictor module, rough data set is used to preprocess the attributes while K-nearest neighbor classifier is used to classify the given data. The dataset used for this model was taken for University of Benin Teaching Hospital (UBTH) database. Half of the data was used in the training while the other half was used in testing the system. The proposed model was able to achieve over 80% accuracy.

Keywords: classifier algorithm, diabetes, diagnostic model, machine learning

Procedia PDF Downloads 336

Authors: Hyun-Woo Cho

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The monitoring of industrial production quality has to be implemented to alarm early warning for unusual operating conditions. Furthermore, identification of their assignable causes is necessary for a quality control purpose. For such tasks many multivariate statistical techniques have been applied and shown to be quite effective tools. This work presents a process data-based monitoring scheme for production processes. For more reliable results some additional steps of noise filtering and preprocessing are considered. It may lead to enhanced performance by eliminating unwanted variation of the data. The performance evaluation is executed using data sets from test processes. The proposed method is shown to provide reliable quality control results, and thus is more effective in quality monitoring in the example. For practical implementation of the method, an on-line data system must be available to gather historical and on-line data. Recently large amounts of data are collected on-line in most processes and implementation of the current scheme is feasible and does not give additional burdens to users.

Keywords: detection, filtering, monitoring, process data

Procedia PDF Downloads 559

Authors: Dana R. Thomson, Catherine Linard, Sabine Vanhuysse, Jessica E. Steele, Michal Shimoni, Jose Siri, Waleska Caiaffa, Megumi Rosenberg, Eleonore Wolff, Tais Grippa, Stefanos Georganos, Helen Elsey

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The Sustainable Development Goals (SDGs) and Urban Health Equity Assessment and Response Tool (Urban HEART) identify dozens of key indicators to help local decision-makers prioritize and track inequalities in health outcomes. However, presentations and discussions at the International Conference on Urban Health (ICUH) 2017 suggested that additional indicators are needed to make decisions and policies. A local decision-maker may realize that malaria or road accidents are a top priority. However, s/he needs additional health determinant indicators, for example about standing water or traffic, to address the priority and reduce inequalities. Health determinants reflect the physical and social environments that influence health outcomes often at community- and societal-levels and include such indicators as access to quality health facilities, access to safe parks, traffic density, location of slum areas, air pollution, social exclusion, and social networks. Indicator identification and disaggregation are necessarily constrained by available datasets – typically collected about households and individuals in surveys, censuses, and administrative records. Continued advancements in earth observation, data storage, computing and mobile technologies mean that new sources of health determinants indicators derived from 'big data' are becoming available at fine geographic scale. Big data includes high-resolution satellite imagery and aggregated, anonymized mobile phone data. While big data are themselves not representative of the population (e.g., satellite images depict the physical environment), they can provide information about population density, wealth, mobility, and social environments with tremendous detail and accuracy when combined with population-representative survey, census, administrative and health system data. The aim of this paper is to (1) flag to data scientists important indicators needed by health decision-makers at the city and sub-city scale - ideally free and publicly available, and (2) summarize for local decision-makers new datasets that can be generated from big data, with layperson descriptions of difficulties in generating them. We include SDGs and Urban HEART indicators, as well as indicators mentioned by decision-makers attending ICUH 2017.

Keywords: health determinant, health outcome, mobile phone, remote sensing, satellite imagery, SDG, urban HEART

Procedia PDF Downloads 209

Authors: Lukasz Grabowski, Tytus Tulwin, Michal Geca, P. Karpinski

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This paper presents the radial aircraft engine model which has been created in AVL Boost software. This model is a one-dimensional physical model of the engine, which enables us to investigate the impact of an ignition system design on engine performance (power, torque, fuel consumption). In addition, this model allows research under variable environmental conditions to reflect varied flight conditions (altitude, humidity, cruising speed). Before the simulation research the identifying parameters and validating of model were studied. In order to verify the feasibility to take off power of gasoline radial aircraft engine model, some validation study was carried out. The first stage of the identification was completed with reference to the technical documentation provided by manufacturer of engine and the experiments on the test stand of the real engine. The second stage involved a comparison of simulation results with the results of the engine stand tests performed on a WSK ’PZL-Kalisz’. The engine was loaded by a propeller in a special test bench. Identifying the model parameters referred to a comparison of the test results to the simulation in terms of: pressure behind the throttles, pressure in the inlet pipe, and time course for pressure in the first inlet pipe, power, and specific fuel consumption. Accordingly, the required coefficients and error of simulation calculation relative to the real-object experiments were determined. Obtained the time course for pressure and its value is compatible with the experimental results. Additionally the engine power and specific fuel consumption tends to be significantly compatible with the bench tests. The mapping error does not exceed 1.5%, which verifies positively the model of combustion and allows us to predict engine performance if the process of combustion will be modified. The next conducted tests verified completely model. The maximum mapping error for the pressure behind the throttles and the inlet pipe pressure is 4 %, which proves the model of the inlet duct in the engine with the charging compressor to be correct.

Keywords: 1D-model, aircraft engine, performance, validation

Procedia PDF Downloads 336

Authors: S. Jursová, P. Pustějovská, S. Brožová, J. Bilík

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The paper deals with possibilities of interpretation of iron ore reducibility tests. It presents a mathematical model developed at Centre ENET, VŠB–Technical University of Ostrava, Czech Republic for an evaluation of metallurgical material of blast furnace feedstock such as iron ore, sinter or pellets. According to the data from the test, the model predicts its usage in blast furnace technology and its effects on production parameters of shaft aggregate. At the beginning, the paper sums up the general concept and experience in mathematical modelling of iron ore reduction. It presents basic equation for the calculation and the main parts of the developed model. In the experimental part, there is an example of usage of the mathematical model. The paper describes the usage of data for some predictive calculation. There are presented material, method of carried test of iron ore reducibility. Then there are graphically interpreted effects of used material on carbon consumption, rate of direct reduction and the whole reduction process.

Keywords: blast furnace technology, iron ore reduction, mathematical model, prediction of iron ore reduction

Procedia PDF Downloads 674

Authors: Jose Francisco Ferreira Ribeiro, Alexandre Bevilacqua Leoneti, Andre Lucirton Costa

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This paper presents a mathematical model in binary variables 0/1 to make the assignment of surgical procedures to the operating rooms in a hospital. The proposed mathematical model is based on the generalized assignment problem, which maximizes the sum of preferences for the use of the operating rooms by doctors, respecting the time available in each room. The corresponding program was written in Visual Basic of Microsoft Excel, and tested to schedule surgeries at St. Lydia Hospital in Ribeirao Preto, Brazil.

Keywords: generalized assignment problem, logistics, optimization, scheduling

Procedia PDF Downloads 292

Authors: Abhijeet Ostawal, Parmjit Lall

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The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant.

Keywords: model run time, demand model, parallelisation, python scripting

Procedia PDF Downloads 118

Authors: F. A. Al-Awadhi, D. Al-Hulail

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In this study, we applied the Bayesian hierarchical model to detect single and multiple change points for daily earthquake body wave magnitude. The change point analysis is used in both backward (off-line) and forward (on-line) statistical research. In this study, it is used with the backward approach. Different types of change parameters are considered (mean, variance or both). The posterior model and the conditional distributions for single and multiple change points are derived and implemented using BUGS software. The model is applicable for any set of data. The sensitivity of the model is tested using different prior and likelihood functions. Using Mb data, we concluded that during January 2002 and December 2003, three changes occurred in the mean magnitude of Mb in Kuwait and its vicinity.

Keywords: multiple change points, Markov Chain Monte Carlo, earthquake magnitude, hierarchical Bayesian mode

Procedia PDF Downloads 456

Authors: Siffat Ullah Khan, Rahmat Ullah Khan, Rafiq Ahmad Khan, Habibullah Khan

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Green IT or green computing has emerged as a fast growing business paradigm in recent years in order to develop energy-efficient Software and peripheral devices. With the constant evolution of technology and the world critical environmental status, all private and public information technology (IT) businesses are moving towards sustainability. We identified, through systematic literature review and questionnaire survey, 9 motivators, in total, faced by vendors in IT-Outsourcing relationship. Amongst these motivators 7 were ranked as critical motivators. We also identified 21, in total, practices for addressing these critical motivators. Based on these inputs we have developed Green IT-Outsourcing Assurance Model (GITAM) for IT-Outsourcing vendors. The model comprises four different levels. i.e. Initial, White, Green and Grey. Each level comprises different critical motivators and their relevant practices. We conclude that our model, GITAM, will assist IT-Outsourcing vendors in gauging their level in order to manage IT-Outsourcing activities in a green and sustainable fashion to assist the environment and to reduce the carbon emission. The model will assist vendors in improving their current level by suggesting various practices. The model will contribute to the body of knowledge in the field of Green IT.

Keywords: Green IT-outsourcing Assurance Model (GITAM), Systematic Literature Review, Empirical Study, Case Study

Procedia PDF Downloads 252

Authors: Areej Al-Khabbaz, Swapna Goerge, Majedah Abdul-Rasoul

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Introduction: The most prevalent periodontal disease among children is gingivitis, and it usually becomes more severe in adolescence. A number of intervention studies suggested that resolution of periodontal inflammation can improve metabolic control in patients diagnosed with diabetes mellitus. Aim: to assess the effect of non-surgical periodontal therapy on glycemic control of children diagnosed with diabetes mellitus. Method: Twenty-eight children diagnosed with diabetes mellitus were recruited with established diagnosis diabetes for at least 1 year. Informed consent and child assent form were obtained from children and parents prior to enrolment. The dental examination for the participants was performed on the same week directly following their annual medical assessment. All patients had their glycosylated hemoglobin (HbA1c%) test one week prior to their annual medical and dental visit and 3 months following non-surgical periodontal therapy. All patients received a comprehensive periodontal examination The periodontal assessment included clinical attachment loss, bleeding on probing, plaque score, plaque index and gingival index. All patients were referred for non-surgical periodontal therapy, which included oral hygiene instruction and motivation followed by supra-gingival and subg-ingival scaling using ultrasonic and hand instruments. Statistical Analysis: Data were entered and analyzed using the Statistical Package for Social Science software (SPSS, Chicago, USA), version 18. Statistical analysis of clinical findings was performed to detect differences between the two groups in term of periodontal findings and HbA1c%. Binary logistic regression analysis was performed in order to examine which factors were significant in multivariate analysis after adjusting for confounding between effects. The regression model used the dependent variable ‘Improved glycemic control’, and the independent variables entered in the model were plaque index, gingival index, bleeding %, plaque Statistical significance was set at p < 0.05. Result: A total of 28 children. The mean age of the participants was 13.3±1.92 years. The study participants were divided into two groups; Compliant group (received dental scaling) and non-complaints group (received oral hygiene instructions only). No statistical difference was found between compliant and non-compliant group in age, gender distribution, oral hygiene practice and the level of diabetes control. There was a significant difference between compliant and non-compliant group in term of improvement of HBa1c before and after periodontal therapy. Mean gingival index was the only significant variable associated with improved glycemic control level. In conclusion, this study has demonstrated that non-surgical mechanical periodontal therapy can improve HbA1c% control. The result of this study confirmed that children with diabetes mellitus who are compliant to dental care and have routine professional scaling may have better metabolic control compared to diabetic children who are erratic with dental care.

Keywords: children, diabetes, metabolic control, periodontal therapy

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Authors: Bahram Fathi, Karim Alizadeh, Azam Mohammadbagheri

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The aim of this paper is to investigate the role of oil price shocks in explaining business cycles in Iran using a dynamic stochastic general equilibrium approach. This model incorporates both productivity and oil revenue shocks. The results indicate that productivity shocks are relatively more important to business cycles than oil shocks. The model with two shocks produces different values for volatility, but these values have the same ranking as that of the actual data for most variables. In addition, the actual data are close to the ratio of standard deviations to the output obtained from the model with two shocks. The results indicate that productivity shocks are relatively more important to business cycles than the oil shocks. The model with only a productivity shock produces the most similar figures in term of volatility magnitude to that of the actual data. Next, we use the Impulse Response Functions (IRF) to evaluate the capability of the model. The IRF shows no effect of an oil shock on the capital stocks and on labor hours, which is a feature of the model. When the log-linearized system of equations is solved numerically, investment and labor hours were not found to be functions of the oil shock. This research recommends using different techniques to compare the model’s robustness. One method by which to do this is to have all decision variables as a function of the oil shock by inducing the stationary to the model differently. Another method is to impose a bond adjustment cost. This study intends to fill that gap. To achieve this objective, we derive a DSGE model that allows for the world oil price and productivity shocks. Second, we calibrate the model to the Iran economy. Next, we compare the moments from the theoretical model with both single and multiple shocks with that obtained from the actual data to see the extent to which business cycles in Iran can be explained by total oil revenue shock. Then, we use an impulse response function to evaluate the role of world oil price shocks. Finally, I present implications of the findings and interpretations in accordance with economic theory.

Keywords: oil price, shocks, dynamic stochastic general equilibrium, Iran

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Authors: Ram Narayan Khare, Aradhna Shrivastava, Adhyatma Khare

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This paper focuses on the damage that has been occurred in the Ancient structures due to various factors such as rainfall, climate, insects, lifespan and also most important lack of technologies in the era of its construction. The structure is of lime surkhi masonry and is made a century ago. It has crossed its durability but is of historical importance for the area, that is the reason why it needs utmost importance for its Rehabilitation. The paper deals with the damage that has been occurred in the structure and how to repair and renovate the same keeping in mind that the material deviation could not take place because it shows how in ancient era structures are made of. The building has used lime surkhi mortar along with wood apple as fibrous material for providing adhesiveness in masonry binding. The paper helps in sustainable retrofitting of the structure without changing the integrity of the structure. This helps in maintaining the originality of structure in present era and also help in providing information to the upcoming generation how ancient civil construction has been carried out that withstand even more than a century.

Keywords: Lime Surkhi masonry, rehabilitation, sustainable development, historical building

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Authors: Greg Turner, Bin Lu, Cheer-Sun Yang

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As computing technology advances, smartphone applications can assist in student learning in a pervasive way. For example, the idea of using a mobile apps for the PA Common Trees, Pests, Pathogens, in the field as a reference tool allows middle school students to learn about trees and associated pests/pathogens without bringing a textbook. In the past, some researches study the mobile software Mobile Application Software Development Life Cycle (MADLC) including traditional models such as the waterfall model, or more recent Agile Methods. Others study the issues related to the software development process. Very little research is on the development of three heterogenous mobile systems simultaneously in a small university where the availability of developers is an issue. In this paper, we propose to use a hybride model of Waterfall Model and the Agile Model, known as the Relay Race Methodology (RRM) in practice, to reflect the concept of racing and relaying for scheduling. Based on the development project, we observe that the modeling of the transition between any two phases is manifested naturally. Thus, we claim that the RRM model can provide a de fecto rather than a de jure basis for the core concept in the MADLC. In this paper, the background of the project is introduced first. Then, the challenges are pointed out followed by our solutions. Finally, the experiences learned and the future work are presented.

Keywords: agile methods, mobile apps, software process model, waterfall model

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Authors: G. Scremin, I. Y. Suh, S. Doukas

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Spectators follow their favorite sports teams for different reasons. While some attend a sporting event simply for its entertainment value, others do so because of the personal sense of achievement and accomplishment their connection with a sports team creates. Moreover, the level of identity spectators feel toward their favorite sports team falls in a broad continuum. Some are mere spectators. For those spectators, their association to a sports team has little impact on their self-image. Others are die-hard fans who are proud of their association with their team and whose connection with that team is an important reflection of who they are. Several motives for sports consumption can be used to explain the level of spectator support in a variety of sports. Those motives can also be used to explain the variance in the identification, attachment, and loyalty spectators feel toward their favorite sports team. Motives for sports consumption can be used to discriminate the degree of identification spectators have with their favorite sports team. In this study, motives for sports consumption was used to discriminate the level of identity spectators feel toward their sports team. It was hypothesized that spectators with a strong level of team identity would report higher rates of interest in player, interest in sports, and interest in team than spectators with a low level of team identity. And spectators with a low level of team identity would report higher rates for entertainment value, bonding with friends or family, and wholesome environment. Football spectators in the United States and England were surveyed about their motives for football consumption and their level of identification with their favorite football team. To assess if the motives of sports fans differed by level of team identity and allegiance to an American or English football team, a Multivariate Analysis of Variance (MANOVA) under the General Linear Model (GLM) procedure found in SPSS was performed. The independent variables were level of team identity and allegiance to an American or English football team, and the dependent variables were the sport fan motives. A tripartite split (low, moderate, high) was used on a composite measure for team identity. Preliminary results show that effect of team identity is statistically significant (p < .001) for at least nine of the 17 motives for sports consumption assessed in this investigation. These results indicate that the motives of spectators with a strong level of team identity differ significantly from spectators with a low level of team identity. Those differences can be used to discriminate the degree of identification spectators have with their favorite sports team. Sports marketers can use these methods and results to develop identity profiles of spectators and create marketing strategies specifically designed to attract those spectators based on their unique motives for consumption and their level of team identification.

Keywords: fan identification, market segmentation of sports fans, motives for sports consumption, team identity

Procedia PDF Downloads 167

Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

Abstract:

This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

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Authors: Abdel Rahman Khider Hassan

Abstract:

This paper describes a multi-criteria geospatial model for prediction of landslide hazard zonation (LHZ) for Lake Naivasha catchment (Kenya), based on spatial analysis of integrated datasets of location intrinsic parameters (slope stability factors) and external landslides triggering factors (natural and man-made factors). The intrinsic dataset included: lithology, geometry of slope (slope inclination, aspect, elevation, and curvature) and land use/land cover. The landslides triggering factors included: rainfall as the climatic factor, in addition to the destructive effects reflected by proximity of roads and drainage network to areas that are susceptible to landslides. No published study on landslides has been obtained for this area. Thus, digital datasets of the above spatial parameters were conveniently acquired, stored, manipulated and analyzed in a Geographical Information System (GIS) using a multi-criteria grid overlay technique (in ArcGIS 10.2.2 environment). Deduction of landslide hazard zonation is done by applying weights based on relative contribution of each parameter to the slope instability, and finally, the weighted parameters grids were overlaid together to generate a map of the potential landslide hazard zonation (LHZ) for the lake catchment. From the total surface of 3200 km² of the lake catchment, most of the region (78.7 %; 2518.4 km²) is susceptible to moderate landslide hazards, whilst about 13% (416 km²) is occurring under high hazards. Only 1.0% (32 km²) of the catchment is displaying very high landslide hazards, and the remaining area (7.3 %; 233.6 km²) displays low probability of landslide hazards. This result confirms the importance of steep slope angles, lithology, vegetation land cover and slope orientation (aspect) as the major determining factors of slope failures. The information provided by the produced map of landslide hazard zonation (LHZ) could lay the basis for decision making as well as mitigation and applications in avoiding potential losses caused by landslides in the Lake Naivasha catchment in the Kenya Highlands.

Keywords: decision making, geospatial, landslide, multi-criteria, Naivasha

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Authors: Nelson Nenuwe

Abstract:

The behavior of interacting electrons in one dimension was studied by calculating correlation functions and critical exponents at zero and external magnetic fields for arbitrary band filling. The technique employed in this study is based on the conformal field theory (CFT). The charge and spin degrees of freedom are separated, and described by two independent conformal theories. A detailed comparison of the t-J model with the repulsive Hubbard model was then undertaken with emphasis on their Tomonaga-Luttinger (TL) liquid properties. Near half-filling the exponents of the t-J model take the values of the strong-correlation limit of the Hubbard model, and in the low-density limit the exponents are those of a non-interacting system. The critical exponents obtained in this study belong to the repulsive TL liquid (conducting phase) and attractive TL liquid (superconducting phase). The theoretical results from this study find applications in one-dimensional organic conductors (TTF-TCNQ), organic superconductors (Bechgaard salts) and carbon nanotubes (SWCNTs, DWCNTs and MWCNTs). For instance, the critical exponent at from this study is consistent with the experimental result from optical and photoemission evidence of TL liquid in one-dimensional metallic Bechgaard salt- (TMTSF)2PF6.

Keywords: critical exponents, conformal field theory, Hubbard model, t-J model

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Authors: Chadi Azoury, Assad Kallassy, Pierre Rahme

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In this paper, we consider the modal analysis of small frames. Firstly, we construct the 3D model using H8 elements and find the natural frequencies of the frame focusing our attention on the modes in the XY plane. Secondly, we construct the 2D model (plane stress model) using Q4 elements. We concluded that the results of both models are very close to each other’s. Then we formulate the stiffness matrix and the mass matrix of the 3-noded Timoshenko beam that is well suited for thick and short beams like in our case. Finally, we model the corners where the horizontal and vertical bar meet with a special matrix. The results of our new model (3-noded Timoshenko beam for the horizontal and vertical bars and a special element for the corners based on the Q4 elements) are very satisfying when performing the modal analysis.

Keywords: corner element, high-order Timoshenko beam, Guyan reduction, modal analysis of frames, rigid link, shear locking, and short beams

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Authors: Sana Dridi, Jalel Aouissi, Rafla Attia, Taoufik Hermassi, Thouraya Sahli

Abstract:

Soil erosion is an increasing issue in Mediterranean countries. In Tunisia, the capacity of dam reservoirs continues to decrease as a consequence of soil erosion. This study aims to predict sediment yield to enrich soil management practices using Soil and Water Assessment Tools model (SWAT) in the Siliana watershed (1041.6 km²), located in the northwest of Tunisia. A database was constructed using remote sensing and Geographical Information System. Climatic and flow data were collected from water resources directorates in Tunisia. The SWAT model was built to simulate hydrological processes and sediment transport. A sensitivity analysis, calibration, and validation were performed using SWAT-CUP software. The model calibration of stream flow simulations shows a good performance with NSE and R² values of 0.77 and 0.79, respectively. The model validation shows a very good performance with values of NSE and R² for 0.8 and 0.88, respectively. After calibration and validation of stream flow simulation, the model was used to simulate the soil erosion and sediment load transport. The spatial distributions of soil loss rate for determining the critical sediment source areas show that 63 % of the study area has a low soil loss rate less than 7 t ha⁻¹y⁻¹. The annual average soil loss rate simulated with the SWAT model in the Siliana watershed is 4.62 t ha⁻¹y⁻¹.

Keywords: water erosion, SWAT model, streamflow, SWATCUP, sediment yield

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Authors: Anyia Nduka, Aslan Bin Amad Senin, Ayu Azrin Bte Abdul Aziz

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A management practice characterised by a value chain as its relatively flexible culture is replacing the old bureaucratic model of organisational practice that was built on dominance. Using a management practice fruition paradigm, the study delves into the implications of organisational culture and leadership. Developing a theory of leadership called the “cultural model” of organisational leadership by explaining how the shift from bureaucracy to management practises altered the roles and interactions of leaders. This model is well-grounded in leadership theory, considering the concept's adaptability to different leadership ideologies. In organisations where operational procedures and borders are not clearly defined, hierarchies are flattened, and work collaborations are sometimes based on contracts rather than employment. This cultural model of organizational leadership is intended to be a useful tool for predicting how effectively a leader will perform.

Keywords: leadership, organizational culture, management practices, efficiency

Procedia PDF Downloads 84