Search results for: statistical model

Authors: Haikal Achmad Thaha, Pujo Laksono, Dhamma Nibbana Putra

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Customer service is one of the core interest in a service sector of a company, whether as the core business or as service part of the operation. Most of the time, the people and the previous research in service industry is focused on finding the best business model solution for the service sector, usually to decide between total in house customer service, outsourcing, or something in between. Conventionally, to take this decision is some important part of the management job, and this is a process that usually takes some time and staff effort, meanwhile market condition and overall company needs may change and cause loss of income and temporary disturbance in the companies operation . However, in this paper we have offer a new concept model to assist decision making process in service industry. This model will featured information platform as central tool to integrate service industry operation. The result is service information model which would ideally increase response time and effectivity of the decision making. it will also help service industry in switching the service solution system quickly through machine learning when the companies growth and the service solution needed are changing.

Keywords: service industry, customer service, machine learning, decision making, information platform

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Authors: Jason West

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Low profitability in agriculture production along with increasing scrutiny over environmental effects is limiting food production at scale. In contrast, the mining sector offers access to resources including energy, water, transport and chemicals for food production at low marginal cost. Scalable agricultural production can benefit from the nexus of resources (water, energy, transport) offered by mining activity in remote locations. A decision support bioeconomic model for controlled environment vertical farms was used. Four submodels were used: crop structure, nutrient requirements, resource-crop integration, and economic. They escalate to a macro mathematical model. A demonstrable dynamic systems framework is needed to prove productive outcomes are feasible. We demonstrate a generalized bioeconomic macro model for controlled environment production systems in minesites using systems dynamics modeling methodology. Despite the complexity of bioeconomic modelling of resource-agricultural dynamic processes and interactions, the economic potential greater than general economic models would assume. Scalability of production as an input becomes a key success feature.

Keywords: crop production systems, mathematical model, mining, agriculture, dynamic systems

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Authors: Dino Carpentras, Alejandro Dinkelberg, Michael Quayle

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Opinion dynamics models use an agent-based modeling approach to model people’s opinions. Model's properties are usually explored by testing the two 'degrees of freedom': the interaction rule and the network topology. The latter defines the connection, and thus the possible interaction, among agents. The interaction rule, instead, determines how agents select each other and update their own opinion. Here we show the existence of the third degree of freedom. This can be used for turning one model into each other or to change the model’s output up to 100% of its initial value. Opinion dynamics models represent the evolution of real-world opinions parsimoniously. Thus, it is fundamental to know how real-world opinion (e.g., supporting a candidate) could be turned into a number. Specifically, we want to know if, by choosing a different opinion-to-number transformation, the model’s dynamics would be preserved. This transformation is typically not addressed in opinion dynamics literature. However, it has already been studied in psychometrics, a branch of psychology. In this field, real-world opinions are converted into numbers using abstract objects called 'scales.' These scales can be converted one into the other, in the same way as we convert meters to feet. Thus, in our work, we analyze how this scale transformation may affect opinion dynamics models. We perform our analysis both using mathematical modeling and validating it via agent-based simulations. To distinguish between scale transformation and measurement error, we first analyze the case of perfect scales (i.e., no error or noise). Here we show that a scale transformation may change the model’s dynamics up to a qualitative level. Meaning that a researcher may reach a totally different conclusion, even using the same dataset just by slightly changing the way data are pre-processed. Indeed, we quantify that this effect may alter the model’s output by 100%. By using two models from the standard literature, we show that a scale transformation can transform one model into the other. This transformation is exact, and it holds for every result. Lastly, we also test the case of using real-world data (i.e., finite precision). We perform this test using a 7-points Likert scale, showing how even a small scale change may result in different predictions or a number of opinion clusters. Because of this, we think that scale transformation should be considered as a third-degree of freedom for opinion dynamics. Indeed, its properties have a strong impact both on theoretical models and for their application to real-world data.

Keywords: degrees of freedom, empirical validation, opinion scale, opinion dynamics

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Authors: Yousef M. Alammari, Mahmoud A. Gaddoury, Reem A. Almohaini, Sara A. Alharbi, Lena S. Alsaleem, Lujain H. Allowaihiq, Maha H. Alrashid, Abdullah H. Alghamdi, Abdullah A. Alaryni

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Objective: The goal of this study was to establish the prevalence of neuropsychiatric symptoms in systemic lupus erythematosus (NPSLE) patients in Saudi Arabia and the variables that are linked to it. Methods: During June 2021, this cross-sectional study was carried out among SLE patients in Saudi Arabia. The Saudi Rheumatism Association exploited social media platforms to provide a self-administered online questionnaire to SLE patients. All data analyses were performed using the Statistical Packages for Social Sciences (SPSS) version 26. Results: Two hundred and five SLE patients participated in the study (females 91.3 % vs. males 8.7 %). In addition, 13.5 % of patients had a family history of SLE, and 26% had SLE for one to three years. Alteration or loss of sensation (53.4%), Fear (52.4%), and headache (48.1%) were the most prevalent signs of neuropsychiatric symptoms in systemic lupus erythematosus (NPSLE) patients. The prevalence of patients with NPSLE was 40%. In a multivariate regression model, fear, altered sensations, cerebrovascular illness, sleep disruption, and diminished interest in routine activities were identified as independent risk variables for NPSLE. Conclusion: Nearly half of SLE patients demonstrated NP manifestations, with significant symptoms including fear, alteration of sensation, cerebrovascular disease, sleep disturbance, and reduced interest in normal activities. To detect the pathophysiology of NPSLE, it is necessary to understand the relationship between neuropsychiatric morbidity and other relevant rheumatic disorders in the SLE population.

Keywords: neuropsychiatric, systemic lupus erythematosus, NPSLE, prevalence, SLE patients

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Authors: Tooraj Karimi, Mohammadreza Sadeghi Moghadam

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Grey set theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for system study rather than traditional statistical regression which require massive data, normal distribution in the data and few variant factors. So, in this paper grey clustering and entropy of coefficient vector of grey evaluations are used to analyze energy consumption in buildings of the Oil Ministry in Tehran. In fact, this article intends to analyze the results of energy audit reports and defines most favorable characteristics of system, which is energy consumption of buildings, and most favorable factors affecting these characteristics in order to modify and improve them. According to the results of the model, ‘the real Building Load Coefficient’ has been selected as the most important system characteristic and ‘uncontrolled area of the building’ has been diagnosed as the most favorable factor which has the greatest effect on energy consumption of building. Grey clustering in this study has been used for two purposes: First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, grey clustering with variable weights has been used to classify all buildings in three categories named ‘no standard deviation’, ‘low standard deviation’ and ‘non- standard’. Entropy of coefficient vector of Grey evaluations is calculated to investigate greyness of results. It shows that among the 38 buildings surveyed in terms of energy consumption, 3 cases are in standard group, 24 cases are in ‘low standard deviation’ group and 11 buildings are completely non-standard. In addition, clustering greyness of 13 buildings is less than 0.5 and average uncertainly of clustering results is 66%.

Keywords: energy audit, grey set theory, grey incidence matrixes, grey clustering, Iran oil ministry

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Authors: Tauha Hussain Ali, Shabir Hussain Khahro, Nafees Ahmed Memon

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Accurate prediction of project time for planning and bid preparation stage should contain realistic dates. Constructors use their experience to estimate the project duration for the new projects, which is based on intuitions. It has been a constant concern to both researchers and constructors to analyze the accurate prediction of project duration for bid preparation stage. In Pakistan, such study for time cost relationship has been lacked to predict duration performance for the construction projects. This study is an attempt to explore the time cost relationship that would conclude with a mathematical model to predict the time for the drainage rehabilitation projects in the province of Sindh, Pakistan. The data has been collected from National Engineering Services (NESPAK), Pakistan and regression analysis has been carried out for the analysis of results. Significant relationship has been found between time and cost of the construction projects in Sindh and the generated mathematical model can be used by the constructors to predict the project duration for the upcoming projects of same nature. This study also provides the professionals with a requisite knowledge to make decisions regarding project duration, which is significantly important to win the projects at the bid stage.

Keywords: BTC Model, project time, relationship of time cost, regression

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Authors: Cafer Görkem Pınar, İlker Coşar, Serkan Uzun, Atahan Çelebi, Mehmet Ali Ersoy, Ali Pınarbaşı

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In this study, it was numerically investigated that a 1:1 scale model of the Renault Clio MK4 SW brand vehicle aerodynamic analysis was performed in the commercial computational fluid dynamics (CFD) package program of ANSYS CFX 2021 R1 under steady, subsonic, and 3-D conditions. The model of vehicle used for the analysis was made independent of the number of mesh elements, and the k-epsilon turbulence model was applied during the analysis. Results were interpreted as streamlines, pressure gradient, and turbulent kinetic energy contours around the vehicle at 50 km/h and 100 km/h speeds. In addition, the validity of the analysis was decided by comparing the drag coefficient of the vehicle with the values in the literature. As a result, the pressure gradient contours of the taillight of the Renault Clio MK4 SW vehicle were examined, and the behavior of the total force at speeds of 50 km/h and 100 km/h was interpreted.

Keywords: CFD, k-epsilon, aerodynamics, drag coefficient, taillight

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Authors: Arnab Mondal, Sanjeev Kumar Sharma, Ranjit Kumar Upadhyay

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We study the spatiotemporal dynamics of a neuronal cable. The processes of one- dimensional (1D) and 2D diffusion are considered for a single variable, which is the membrane voltage, i.e., membrane voltage diffusively interacts for spatiotemporal pattern formalism. The recovery and other variables interact through the membrane voltage. A 3D Leech-Heart (LH) model is introduced to investigate the nonlinear responses of an excitable neuronal cable. The deterministic LH model shows different types of firing properties. We explore the parameter space of the uncoupled LH model and based on the bifurcation diagram, considering v_k2_ashift as a bifurcation parameter, we analyze the 1D diffusion dynamics in three regimes: bursting, regular spiking, and a quiescent state. Depending on parameters, it is shown that the diffusive system may generate regular and irregular bursting or spiking behavior. Further, it is explored a 2D diffusion acting on the membrane voltage, where different types of patterns can be observed. The results show that the LH neurons with different firing characteristics depending on the control parameters participate in a collective behavior of an information processing system that depends on the overall network.

Keywords: bifurcation, pattern formation, spatio-temporal dynamics, stability analysis

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Authors: Marine Segui, Ruxandra Mihaela Botez

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OpenVSP is an aerodynamic solver developed by National Aeronautics and Space Administration (NASA) that allows building a reliable model of an aircraft. This software performs an aerodynamic simulation according to the angle of attack of the aircraft makes between the incoming airstream, and its speed. A reliable aerodynamic model of the Cessna Citation X was designed but it required a lot of computation time. As a consequence, a prediction method was established that allowed predicting lift and drag coefficients for all Mach numbers and for all angles of attack, exclusively for stall conditions, from a computation of three angles of attack and only one Mach number. Aerodynamic coefficients given by the prediction method for a Cessna Citation X model were finally compared with aerodynamics coefficients obtained using a complete OpenVSP study.

Keywords: aerodynamic, coefficient, cruise, improving, longitudinal, openVSP, solver, time

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Authors: Mark Watson, J.-F. Bousquet, Adam Forget

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A magnetic induction based underwater communication link is evaluated using an analytical model and a custom Finite-Difference Time-Domain (FDTD) simulation tool. The analytical model is based on the Sommerfeld integral, and a full-wave simulation tool evaluates Maxwell’s equations using the FDTD method in cylindrical coordinates. The analytical model and FDTD simulation tool are then compared and used to predict the system performance for various transmitter depths and optimum frequencies of operation. To this end, the system bandwidth, signal to noise ratio, and the magnitude of the induced voltage are used to estimate the expected channel capacity. The models show that in seawater, a relatively low-power and small coils may be capable of obtaining a throughput of 40 to 300 kbps, for the case where a transmitter is at depths of 1 to 3 m and a receiver is at a height of 1 m.

Keywords: magnetic induction, FDTD, underwater communication, Sommerfeld

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Authors: Elizabeth Adebomi Akinlotan, Olukemi Odukoya

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INTRODUCTION: Physical Activity is defined as activity that involves bodily movement which is done as a part of daily activity in the form of working, playing, active transportation such as walking and also as a form of recreational activity. Physical inactivity has been identified as the fourth leading risk factor for global mortality and morbidity causing an estimated 3.2 million deaths globally and 5.5% of total deaths and it remains a pressing public health issue. There is a shift in the major causes of death from communicable to non-communicable diseases in many developed countries and this is fast becoming the case in developing countries. Physical activity is an important determinant of health and has been associated with lower mortality rates as it reduces the risk of developing chronic diseases such as diabetes mellitus, hypertension, stroke, cancer and osteoporosis. It improves musculoskeletal health, controls weight and reduces symptoms of depression. AIM: The aim is to study the knowledge, attitude and practices of physical activity among adults in Alimosho local government area. METHODOLOGY: This was a descriptive cross sectional survey designed to study the knowledge, attitude and practice of physical activity among adults in Alimosho Local Government Area. The study population were 250 adults aged 18-65 who were residents of the area of more than 6 months duration and had no chronic disease condition or physical disability. A multistage sampling method was used to select the respondents and data was collected using interviewer administered questionnaires. The data was analyzed with the use of EPI-info 2007 statistical software. Chi Square was thereafter used to test the association between selected variables. The level of statistical significance was set at 5% (p<0.05). RESULTS: In general, majority (61.6%) of the respondents had a good knowledge of what physical activity entails, 34.0% had fair knowledge and 4.4% had poor knowledge. There was a favorable attitude towards physical activity among the respondents with 82.4% having an overall positive attitude. Below a third of the respondents (26.4%) reported having a high physical activity (METS > 3001) while 40.0% had moderate (601-3000 METS) levels of activity and 33.6% were inactive (<600METS). There is statistical significance between the gender of the respondent and the levels of physical activity (p=0.0007); 75.2% males reached the minimum recommendations while 24.8% were inactive and 55.0% females reached the minimum recommendations while 45.0% were inactive. Results also showed that of 95 respondents who were satisfied with their levels of physical activity, 33.7% were insufficiently active while 66.3% were either minimally active or highly active and of 110 who were unsatisfied with their levels of physical activity, 72.0% were above the minimum recommendations while 38.0% were insufficiently active. CONCLUSION: In contrast to the high level of knowledge and favorable attitude towards physical activity, there was a lower level of practice of high or moderate physical activities. It is recommended that more awareness should be created on the recommended levels of physical activity especially for the vigorous intensity and moderate intensity physical activity.

Keywords: METS, physical activity, physical inactivity, public health

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Authors: Anna Ouskova Leonteva, Michel Risser, Anne Jeannin-Girardon, Pierre Parrend, Pierre Collet

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This paper proposes an efficient optimization tool for an active magnetic regenerator (AMR) model, operating in two modes: magnetic refrigeration system (MRS) and thermo-magnetic generator (TMG). The aim of this optimizer is to improve the design of the AMR by applying a multi-physics multi-scales numerical model as a core of evaluation functions to achieve industrial requirements for refrigeration and energy conservation systems. Based on the multi-objective non-dominated sorting genetic algorithm 3 (NSGA3), it maximizes four different objectives: efficiency and power density for MRS and TMG. The main contribution of this work is in the simultaneously application of a CPU-parallel NSGA3 version to the AMR model in both modes for studying impact of control and design parameters on the performance. The parametric study of the optimization results are presented. The main conclusion is that the common (for TMG and MRS modes) optimal parameters can be found by the proposed tool.

Keywords: ecological refrigeration systems, active magnetic regenerator, thermo-magnetic generator, multi-objective evolutionary optimization, industrial optimization problem, real-world application

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Authors: Abdisalam Hassan Muse, Samuel Mwalili, Oscar Ngesa

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A generalized log-logistic distribution with variable shapes of the hazard rate was introduced and studied, extending the log-logistic distribution by adding an extra parameter to the classical distribution, leading to greater flexibility in analysing and modeling various data types. The proposed distribution has a large number of well-known lifetime special sub-models such as; Weibull, log-logistic, exponential, and Burr XII distributions. Its basic mathematical and statistical properties were derived. The method of maximum likelihood was adopted for estimating the unknown parameters of the proposed distribution, and a Monte Carlo simulation study is carried out to assess the behavior of the estimators. The importance of this distribution is that its tendency to model both monotone (increasing and decreasing) and non-monotone (unimodal and bathtub shape) or reversed “bathtub” shape hazard rate functions which are quite common in survival and reliability data analysis. Furthermore, the flexibility and usefulness of the proposed distribution are illustrated in a real-life data set and compared to its sub-models; Weibull, log-logistic, and BurrXII distributions and other parametric survival distributions with 3-parmaeters; like the exponentiated Weibull distribution, the 3-parameter lognormal distribution, the 3- parameter gamma distribution, the 3-parameter Weibull distribution, and the 3-parameter log-logistic (also known as shifted log-logistic) distribution. The proposed distribution provided a better fit than all of the competitive distributions based on the goodness-of-fit tests, the log-likelihood, and information criterion values. Finally, Bayesian analysis and performance of Gibbs sampling for the data set are also carried out.

Keywords: hazard rate function, log-logistic distribution, maximum likelihood estimation, generalized log-logistic distribution, survival data, Monte Carlo simulation

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Authors: Fazlul Karim, Esa Al-Islam

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Many problems in oceanography and environmental sciences require the solution of shallow water equations on physical domains having curvilinear coastlines and abrupt changes of ocean depth near the shore. Finite-difference technique for the shallow water equations representing the boundary as stair step may give inaccurate results near the coastline where results are of greatest interest for various applications. This suggests the use of methods which are capable of incorporating the irregular boundary in coastal belts. At the same time, large velocity gradient is expected near the beach and islands as water depth vary abruptly near the coast. A nested numerical scheme with fine resolution is the best resort to enhance the numerical accuracy with the least grid numbers for the region of interests where the velocity changes rapidly and which is unnecessary for the away of the region. This paper describes the development of a boundary fitted nested grid (BFNG) model to compute tsunami propagation of 2004 Indonesian tsunami in Southern Thailand coastal waters. In this paper, we develop a numerical model employing the shallow water nested model and an orthogonal boundary fitted grid to investigate the tsunami impact on the Southern Thailand due to the Indonesian tsunami of 2004. Comparisons of water surface elevation obtained from numerical simulations and field measurements are made.

Keywords: Indonesian tsunami of 2004, Boundary-fitted nested grid model, Southern Thailand, finite difference method

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Authors: Juan Harold Sosa-Arnao, Daniel José de Oliveira Ferreira, Caice Guarato Santos, Justo Emílio Alvarez, Leonardo Paes Rangel, Song Won Park

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A comprehensive CFD model is developed to represent heterogeneous combustion and two burner designs of supply sugar-cane bagasse into a furnace. The objective of this work is to compare the insertion and burning of a Brazilian south-eastern sugar-cane bagasse using a new swirl burner design against an actual geometry under operation. The new design allows control the particles penetration and scattering inside furnace by adjustment of axial/tangential contributions of air feed without change their mass flow. The model considers turbulence using RNG k-, combustion using EDM, radiation heat transfer using DTM with 16 ray directions and bagasse particle tracking represented by Schiller-Naumann model. The obtained results are favorable to use of new design swirl burner because its axial/tangential control promotes more penetration or more scattering than actual design and allows reproduce the actual design operation without change the overall mass flow supply.

Keywords: comprehensive CFD model, sugar-cane bagasse combustion, swirl burner, contributions

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Authors: Sawsan Eissa, Momen Gharib, Omnia Kabbany

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A flushing numerical study has been performed for intended artificial islands on the Persian Gulf coast in Abu Dhabi, UAE. The island masterplan was tested for flushing using the DELFT 3D hydrodynamic model, and it was found that its residence time exceeds the acceptable PIANC flushing Criteria. Therefore, a number of mitigation measures were applied and tested one by one using the flushing model. Namely, changing the location of the entrance opening, dredging, removing part of the mangrove existing in the near vicinity to create a channel, removing the mangrove altogether, using culverts of different numbers and locations, and pumping at selected points. The pumping option gave the best solution, but it was disregarded due to high capital and running costs. Therefore, it opted for a combination of other solutions, including removing mangroves, introducing culverts, and adjusting island boundaries and types of protection.

Keywords: hydrodynamics, flushing, delft 3d, Persian Gulf, artificial islands.

Procedia PDF Downloads 50

Authors: Jingwei Du

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The need of optimizing air conditioning systems for existing buildings calls for control methods designed with energy-efficiency as a primary goal. The majority of current control methods boil down to two categories: empirical and model-based. To be effective, the former heavily relies on engineering expertise and the latter requires extensive historical data. Reinforcement Learning (RL), on the other hand, is a model-free approach that explores the environment to obtain an optimal control strategy often referred to as “policy”. This research adopts Proximal Policy Optimization (PPO) to improve chiller plant control, and enable the RL agent to collaborate with experienced engineers. It exploits the fact that while the industry lacks historical data, abundant operational data is available and allows the agent to learn and evolve safely under human supervision. Thanks to the development of language models, renewed interest in RL has led to modern, online, policy-based RL algorithms such as the PPO. This research took inspiration from “alignment”, a process that utilizes human feedback to finetune the pretrained model in case of unsafe content. The methodology can be summarized into three steps. First, an initial policy model is generated based on minimal prior knowledge. Next, the prepared PPO agent is deployed so feedback from both critic model and human experts can be collected for future finetuning. Finally, the agent learns and adapts itself to the specific chiller plant, updates the policy model and is ready for the next iteration. Besides the proposed approach, this study also used traditional RL methods to optimize the same simulated chiller plants for comparison, and it turns out that the proposed method is safe and effective at the same time and needs less to no historical data to start up.

Keywords: chiller plant, control methods, energy efficiency, proximal policy optimization, reinforcement learning

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Authors: Zhou Shangcheng, Yi Sicen

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Objective: To understand the mortality patterns of Zhangwan District in 2010 and provide the basis for the development of scientific and rational health policy. Methods: Data are collected from the Sixth Census of Zhangwan District and disease surveillance system. The statistical analysis include death difference between age, gender, region and time and the related factors. Methods developed for the Global Burden of Disease (GBD) Study by the World Bank and World Health Organization (WHO) were adapted and applied to Zhangwan District population health data. DALY rate per 1,000 was calculated for varied causes of death. SPSS 16 is used by statistic analysis. Results: From the data of death population of Zhangwan District we know the crude mortality rate was 6.03 ‰. There are significant differences of mortality rate in male and female population which was respectively 7.37 ‰ and 4.68 ‰. 0 age group population life expectancy in Zhangwan District in 2010 was 78.40 years old(Male 75.93, Female 81.03). The five leading causes of YLL in descending order were: cardiovascular diseases(42.63DALY/1000), malignant neoplasm (23.73DALY/1000), unintentional injuries (5.84DALY/1000), Respiratory diseases(5.43 DALY/1000), Respiratory infections (2.44DALY/1000). In addition, there are strong relation between the marital status , educational level and mortality in some to a certain extend. Conclusion Zhangwan District, as city level, is at lower mortality levels. The mortality of the total population of Zhangwan District has a downward trend and life expectancy is rising.

Keywords: sixth census, Zhangwan district, death level differences, influencing factors, cause of death

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Authors: V. Diaz, B. Pardo , D. Villegas

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In premature births most babies have complications at birth, these complications can be reduced, if an atmosphere of relaxation is provided and is also similar to intrauterine life, for this, there are programs where their mothers lull and sway them; however, the conditions in which they do so and the way in they do it may not be the indicated. Here we describe an investigation based on the biomimics of the kinematics of human fetal movement, which consists of determining the movements that the fetus experiences and the deformations of the components that surround the fetus during a gentle walk at week 32 of the gestation stage. This research is based on a 3D model that has the anatomical structure of the pelvis, fetus, muscles, uterus and its most important supporting elements (ligaments). Normal load conditions are applied to this model according to the stage of gestation and the kinematics of a gentle walk of a pregnant mother, which focuses on the pelvic bone, this allows to receive a response from the other elements of the model. To accomplish this modeling and subsequent simulation Solidworks software was used. From this analysis, the curves that describe the movement of the fetus at three different points were obtained. Additionally, we could found the deformation of the uterus and the ligaments that support it, showing the characteristics that these tissues can have in the face of the support of the fetus. These data can be used for the construction of artifacts that help the normal development of premature infants.

Keywords: simulation, biomimic, uterine model, fetal movement study

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Authors: Soyon Kim, Edward Kim

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In order to retrieve information from the massive stream of songs in the music industry, music search by title, lyrics, artist, mood, and genre has become more important. Despite the subjectivity and controversy over the definition of music genres across different nations and cultures, automatic genre classification systems that facilitate the process of music categorization have been developed. Manual genre selection by music producers is being provided as statistical data for designing automatic genre classification systems. In this paper, an automatic music genre classification system utilizing non-negative matrix factorization (NMF) is proposed. Short-term characteristics of the music signal can be captured based on the timbre features such as mel-frequency cepstral coefficient (MFCC), decorrelated filter bank (DFB), octave-based spectral contrast (OSC), and octave band sum (OBS). Long-term time-varying characteristics of the music signal can be summarized with (1) the statistical features such as mean, variance, minimum, and maximum of the timbre features and (2) the modulation spectrum features such as spectral flatness measure, spectral crest measure, spectral peak, spectral valley, and spectral contrast of the timbre features. Not only these conventional basic long-term feature vectors, but also NMF based feature vectors are proposed to be used together for genre classification. In the training stage, NMF basis vectors were extracted for each genre class. The NMF features were calculated in the log spectral magnitude domain (NMF-LSM) as well as in the basic feature vector domain (NMF-BFV). For NMF-LSM, an entire full band spectrum was used. However, for NMF-BFV, only low band spectrum was used since high frequency modulation spectrum of the basic feature vectors did not contain important information for genre classification. In the test stage, using the set of pre-trained NMF basis vectors, the genre classification system extracted the NMF weighting values of each genre as the NMF feature vectors. A support vector machine (SVM) was used as a classifier. The GTZAN multi-genre music database was used for training and testing. It is composed of 10 genres and 100 songs for each genre. To increase the reliability of the experiments, 10-fold cross validation was used. For a given input song, an extracted NMF-LSM feature vector was composed of 10 weighting values that corresponded to the classification probabilities for 10 genres. An NMF-BFV feature vector also had a dimensionality of 10. Combined with the basic long-term features such as statistical features and modulation spectrum features, the NMF features provided the increased accuracy with a slight increase in feature dimensionality. The conventional basic features by themselves yielded 84.0% accuracy, but the basic features with NMF-LSM and NMF-BFV provided 85.1% and 84.2% accuracy, respectively. The basic features required dimensionality of 460, but NMF-LSM and NMF-BFV required dimensionalities of 10 and 10, respectively. Combining the basic features, NMF-LSM and NMF-BFV together with the SVM with a radial basis function (RBF) kernel produced the significantly higher classification accuracy of 88.3% with a feature dimensionality of 480.

Keywords: mel-frequency cepstral coefficient (MFCC), music genre classification, non-negative matrix factorization (NMF), support vector machine (SVM)

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Authors: Giovanni Masala, Stefania Marica

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

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

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Authors: Hamish Love, Navjot Bhullar, Nicola Schutte

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

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

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Authors: Yuyang Cheng, Marcos Escobar-Anel

Abstract:

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

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

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Authors: Nino Paresashvili, Nino Abesadze

Abstract:

The modern world faces huge challenges. Globalization changed the socio-economic conditions of many countries. The current processes in the global environment have a different impact on countries with different cultures. However, an alleviation of poverty and improvement of living conditions is still the basic challenge for the majority of countries, because much of the population still lives under the official threshold of poverty. It is very important to stimulate youth employment. In order to prepare young people for the labour market, it is essential to provide them with the appropriate professional skills and knowledge. It is necessary to plan efficient activities for decreasing an unemployment rate and for developing the perfect mechanisms for regulation of a labour market. Such planning requires thorough study and analysis of existing reality, as well as development of corresponding mechanisms. Statistical analysis of unemployment is one of the main platforms for regulation of the labour market key mechanisms. The corresponding statistical methods should be used in the study process. Such methods are observation, gathering, grouping, and calculation of the generalized indicators. Unemployment is one of the most severe socioeconomic problems in Georgia. According to the past as well as the current statistics, unemployment rates always have been the most problematic issue to resolve for policy makers. Analytical works towards to the above-mentioned problem will be the basis for the next sustainable steps to solve the main problem. The results of the study showed that the choice of young people is not often due to their inclinations, their interests and the labour market demand. That is why the wrong professional orientation of young people in most cases leads to their unemployment. At the same time, it was shown that there are a number of professions in the labour market with a high demand because of the deficit the appropriate specialties. To achieve healthy competitiveness in youth employment, it is necessary to formulate regional employment programs with taking into account the regional infrastructure specifications.

Keywords: unemployment, analysis, methods, tendencies, regulation mechanisms

Procedia PDF Downloads 374

Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

Abstract:

Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

Procedia PDF Downloads 248

Authors: Yi-Hung Ho, Chih-Wei Wang, Chih-Hsien Chen, Chih-Han Chang

Abstract:

Unilateral laminotomy and bilateral laminotomies were successful decompressions methods for managing spinal stenosis that numerous studies have reported. Thus, unilateral laminotomy was rated technically much more demanding than bilateral laminotomies, whereas the bilateral laminotomies were associated with a positive benefit to reduce more complications. There were including incidental durotomy, increased radicular deficit, and epidural hematoma. However, no relative biomechanical analysis for evaluating spinal instability treated with unilateral and bilateral laminotomies. Therefore, the purpose of this study was to compare the outcomes of different decompressions methods by experimental and finite element analysis. Three porcine lumbar spines were biomechanically evaluated for their range of motion, and the results were compared following unilateral or bilateral laminotomies. The experimental protocol included flexion and extension in the following procedures: intact, unilateral, and bilateral laminotomies (L2–L5). The specimens in this study were tested in flexion (8 Nm) and extension (6 Nm) of pure moment. Spinal segment kinematic data was captured by using the motion tracking system. A 3D finite element lumbar spine model (L1-S1) containing vertebral body, discs, and ligaments were constructed. This model was used to simulate the situation of treating unilateral and bilateral laminotomies at L3-L4 and L4-L5. The bottom surface of S1 vertebral body was fully geometrically constrained in this study. A 10 Nm pure moment also applied on the top surface of L1 vertebral body to drive lumbar doing different motion, such as flexion and extension. The experimental results showed that in the flexion, the ROMs (±standard deviation) of L3–L4 were 1.35±0.23, 1.34±0.67, and 1.66±0.07 degrees of the intact, unilateral, and bilateral laminotomies, respectively. The ROMs of L4–L5 were 4.35±0.29, 4.06±0.87, and 4.2±0.32 degrees, respectively. No statistical significance was observed in these three groups (P>0.05). In the extension, the ROMs of L3–L4 were 0.89±0.16, 1.69±0.08, and 1.73±0.13 degrees, respectively. In the L4-L5, the ROMs were 1.4±0.12, 2.44±0.26, and 2.5±0.29 degrees, respectively. Significant differences were observed among all trials, except between the unilateral and bilateral laminotomy groups. At the simulation results portion, the similar results were discovered with the experiment. No significant differences were found at L4-L5 both flexion and extension in each group. Only 0.02 and 0.04 degrees variation were observed during flexion and extension between the unilateral and bilateral laminotomy groups. In conclusions, the present results by finite element analysis and experimental reveal that no significant differences were observed during flexion and extension between unilateral and bilateral laminotomies in short-term follow-up. From a biomechanical point of view, bilateral laminotomies seem to exhibit a similar stability as unilateral laminotomy. In clinical practice, the bilateral laminotomies are likely to reduce technical difficulties and prevent perioperative complications; this study proved this benefit through biomechanical analysis. The results may provide some recommendations for surgeons to make the final decision.

Keywords: unilateral laminotomy, bilateral laminotomies, spinal stenosis, finite element analysis

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Authors: Tomasz L. Nawrocki, Danuta Szwajca

Abstract:

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

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

Procedia PDF Downloads 242

Authors: A. Porshnev, A. Zaporozhtchuk

Abstract:

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

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

Procedia PDF Downloads 172

Authors: C. Xavier Mendieta, J. J McArthur

Abstract:

Governments are playing an increasingly active role in reducing carbon emissions, and a key strategy has been the introduction of mandatory energy disclosure policies. These policies have resulted in a significant amount of publicly available data, providing researchers with a unique opportunity to develop location-specific energy and carbon emission benchmarks from this data set, which can then be used to develop building archetypes and used to inform urban energy models. This study presents the development of such a benchmark using the public reporting data. The data from Ontario’s Ministry of Energy for Post-Secondary Educational Institutions are being used to develop a series of building archetype dynamic building loads and energy benchmarks to fill a gap in the currently available building database. This paper presents the development of a benchmark for college and university residences within ASHRAE climate zone 6 areas in Ontario using the mandatory disclosure energy and greenhouse gas emissions data. The methodology presented includes data cleaning, statistical analysis, and benchmark development, and lessons learned from this investigation are presented and discussed to inform the development of future energy benchmarks from this larger data set. The key findings from this initial benchmarking study are: (1) the importance of careful data screening and outlier identification to develop a valid dataset; (2) the key features used to develop a model of the data are building age, size, and occupancy schedules and these can be used to estimate energy consumption; and (3) policy changes affecting the primary energy generation significantly affected greenhouse gas emissions, and consideration of these factors was critical to evaluate the validity of the reported data.

Keywords: building archetypes, data analysis, energy benchmarks, GHG emissions

Procedia PDF Downloads 300

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

Abstract:

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

Keywords: collaborative research, developing country, computerization, model

Procedia PDF Downloads 329