Search results for: multivariate models.

Authors: Priscilla Eng Lian Murphy

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This study examines the nature of student conceptions of mathematics in higher education using quantitative research methods. This study validates the Short Form of Conception of Mathematics survey as well as reveals the epistemological nature of student conceptions of mathematics. Using a random sample of mathematics students in Australia and New Zealand (N=274), this paper highlighted three key findings, of relevance to lecturers in higher education. Firstly, descriptive data shows that mathematics students in Australia and New Zealand reported that mathematics is about numbers and components, models and life. Secondly, models conceptions of mathematics predicted strong examination performances using regression analyses; and thirdly, there is a positive correlation between high mathematics examination scores and cohesive conceptions of mathematics.

Keywords: higher education, learning mathematics, mathematics performances, student conceptions of mathematics

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Authors: Ahmad R. Zamani, Luigi Sanguigno, Angelo R. Maligno

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A 3D woven composite, designed for automotive applications, is studied using Abaqus Finite Element (FE) software suite. Python scripts were developed to build FE models of the woven composite in Complete Abaqus Environment (CAE). They can read TexGen or WiseTex files and automatically generate consistent meshes of the fabric and the matrix. A user menu is provided to help define parameters for the FE models, such as type and size of the elements in fabric and matrix as well as the type of matrix-fabric interaction. Node-to-node constraints were imposed to guarantee periodicity of the deformed shapes at the boundaries of the representative volume element of the composite. Tensile loads in three axes and biaxial loads in x-y directions have been applied at different Fibre Volume Fractions (FVFs). A simple damage model was implemented via an Abaqus user material (UMAT) subroutine. Existing tools for homogenization were also used, including voxel mesh generation from TexGen as well as Abaqus Micromechanics plugin. Linear relations between homogenised elastic properties and the FVFs are given. The FE models of composite exhibited balanced behaviour with respect to warp and weft directions in terms of both stiffness and strength.

Keywords: 3D woven composite (3DWC), meso-scale finite element model, homogenisation of elastic material properties, Abaqus Python scripting

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Authors: C. C. Kruger, P. Van Tonder

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Concrete deteriorates over time and the deterioration can be escalated due to multiple factors. When deteriorations are beneath the concrete’s surface, they could be unknown, even more so when they are located at high elevations. Establishing the severity of such defects could prove difficult and therefore the need to find efficient, safe and economical methods to find these defects becomes ever more important. Current methods using thermography to find defects require equipment such as scaffolding to reach these higher elevations. This could become time- consuming and costly. The risks involved with personnel scaffold or abseil to such heights are high. Accordingly, by combining the technologies of a thermal camera and a Remotely Piloted Aerial System it could be used to find better diagnostic methods. The data could then be constructed into a 3D thermal model to easy representation of the results

Keywords: concrete, infrared thermography, 3D thermal models, diagnostic

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Authors: Hajer Chaker Ben Hadj Kacem, Thouraya Slama, Néjiba El Yetim Zribi

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This paper analyzes the effects of gender, affiliation, prior work experience, social work, and vicarious learning through family role models on entrepreneurial skills development by students when they have learned through the entrepreneurship method in Tunisia. Authors suggest that these variables enhance the development of students’ entrepreneurial skills when combined with teaching through entrepreneurship. The article assesses the impact of these combinations by comparing their effects on the development of thirteen students’ entrepreneurial competencies, namely entrepreneurial mindset, core self-evaluation, entrepreneurial attitude, entrepreneurial knowledge, creativity, financial literacy, managing ambiguity, marshaling of resources, planning, teaching methods, entrepreneurial teachers, innovative employee, and Entrepreneurial intention. Authors use a two-sample independent t-test to make the comparison, and the results indicate that, when combined with teaching through the entrepreneurship method, students with prior work experience developed better six entrepreneurial skills; students with social work developed better three entrepreneurial skills, men developed better four entrepreneurial skills than women. However, all students developed their entrepreneurial skills through this practical method regardless of their affiliation and their vicarious learning through family role models.

Keywords: affiliation, entrepreneurial skills, gender, role models, social work, teaching through entrepreneurship, vicarious learning, work experience

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Authors: Mahesh K. Chudasama, Harit K. Raval

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3-roller conical bending process is widely used in the industries for manufacturing of conical sections and shells. It involves static as well dynamic bending stages. Analytical models for prediction of bending force during static as well as dynamic bending stage are available in the literature. In this paper, bending forces required for static bending stage and dynamic bending stages have been compared using the analytical models. It is concluded that force required for dynamic bending is very less as compared to the bending force required during the static bending stage.

Keywords: analytical modeling, cone frustum, dynamic bending, static bending

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Authors: William J. Crowther, Conor Marsh

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Object-based flow simulation allows fast computation of arbitrarily complex aerodynamic models made up of simple objects with limited flow interactions. The proposed approach is universally applicable to objects made from arbitrarily scaled ellipsoid primitives at arbitrary aerodynamic attitude and angular rate. The use of a component-based aerodynamic modelling approach increases efficiency by allowing selective inclusion of different physics models at run-time and allows extensibility through the development of new models. Insight into the numerical stability of the model under first order fixed-time step integration schemes is provided by stability analysis of the drag component. The compute cost of model components and functions is evaluated and compared against numerical benchmarks. Model static outputs are verified against theoretical expectations and dynamic behaviour using falling plate data from the literature. The model is applied to a range of case studies to demonstrate the efficacy of its application in extensibility, ease of use, and low computational cost. Dynamically complex multi-body systems can be implemented in a transparent and efficient manner, and we successfully demonstrate large scenes with hundreds of objects interacting with diverse flow fields.

Keywords: aerodynamics, real-time simulation, low-order model, flight dynamics

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Authors: Mustapha Babatunde, Bassam Tawabini, Ole John Nielson

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Air dispersion (AD) models such as AERMOD are important tools for estimating the environmental impacts of air pollutant emissions into the atmosphere from anthropogenic sources. The outcome of these models is significantly linked to the climate condition like air temperature, which is expected to differ in the future due to the global warming phenomenon. With projections from scientific sources of impending changes to the future climate of Saudi Arabia, especially anticipated temperature rise, there is a potential direct impact on the dispersion patterns of air pollutants results from AD models. To our knowledge, no similar studies were carried out in Saudi Arabia to investigate such impact. Therefore, this research investigates the effects of climate temperature change on air quality in the Dammam Metropolitan area, Saudi Arabia, using AERMOD coupled with Station data using Sulphur dioxide (SO₂) – as a model air pollutant. The research uses AERMOD model to predict the SO₂ dispersion trends in the surrounding area. Emissions from five (5) industrial stacks on twenty-eight (28) receptors in the study area were considered for the climate period (2010-2019) and future period of mid-century (2040-2060) under different scenarios of elevated temperature profiles (+1ᵒC, + 3ᵒC and + 5ᵒC) across averaging time periods of 1hr, 4hr and 8hr. Results showed that levels of SO₂ at the receiving sites under current and simulated future climactic condition fall within the allowable limit of WHO and KSA air quality standards. Results also revealed that the projected rise in temperature would only have mild increment on the SO₂ concentration levels. The average increase of SO₂ levels was 0.04%, 0.14%, and 0.23% due to the temperature increase of 1, 3, and 5 degrees, respectively. In conclusion, the outcome of this work elucidates the degree of the effects of global warming and climate changes phenomena on air quality and can help the policymakers in their decision-making, given the significant health challenges associated with ambient air pollution in Saudi Arabia.

Keywords: air quality, sulfur dioxide, dispersion models, global warming, KSA

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Authors: Chinmayee Choudhury

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Human Melanocortin 4 Receptor (HMC4R) is one of the most potential drug targets for the treatment of obesity which controls the appetite. A deletion of the residues 88-92 in HMC4R is sometimes the cause of severe obesity in the humans. In this study, two homology models are constructed for the normal as well as mutated HMC4Rs and some phytochemicals present in Green Tea, Honey and Cinnamon have been docked to them to study their differential binding to the normal and mutated HMC4R as compared to the natural agonist α- MSH. Two homology models have been constructed for the normal as well as mutated HMC4Rs using the Modeller9v7. Some of the phytochemicals present in Green Tea, Honey, and Cinnamon, which have appetite suppressant activities are constructed, minimized and docked to these normal and mutated HMC4R models using ArgusLab 4.0.1. The mode of binding of the phytochemicals with the Normal and Mutated HMC4Rs have been compared. Further, the mode of binding of these phytochemicals with that of the natural agonist α- Melanocyte Stimulating Hormone(α-MSH) to both normal and mutated HMC4Rs have also been studied. It is observed that the phytochemicals Kaempherol, Epigallocatechin-3-gallate (EGCG) present in Green Tea and Honey, Isorhamnetin, Chlorogenic acid, Chrysin, Galangin, Pinocambrin present in Honey, Cinnamaldehyde, Cinnamyl acetate and Cinnamyl alcohol present in Cinnamon have capacity to form more stable complexes with the Mutated HMC4R as compared to α- MSH. So they may be potential agonists of HMC4R to suppress the appetite.

Keywords: HMC4R, α-MSH, docking, photochemical, appetite suppressant, homology modelling

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Authors: Rong Wang, Sandra Hasanefendic, Elizabeth von Hauff, Bart Bossink

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Technological learning and learning curve models have been continuously used to estimate the photovoltaics (PV) cost development over time for the climate mitigation targets. They can integrate a number of technological learning sources which influence the learning process. Yet the accuracy and realistic predictions for cost estimations of PV development are still difficult to achieve. This paper develops four hypothetical-alternative learning curve models by proposing different combinations of technological learning sources, including both local and global technology experience and the knowledge stock. This paper specifically focuses on the non-linear relationship between the costs and technological learning source and their dynamic interaction and uses the system dynamics approach to predict a more accurate PV cost estimation for future development. As the case study, the data from China is gathered and drawn to illustrate that the learning curve model that incorporates both the global and local experience is more accurate and realistic than the other three models for PV cost estimation. Further, absorbing and integrating the global experience into the local industry has a positive impact on PV cost reduction. Although the learning curve model incorporating knowledge stock is not realistic for current PV cost deployment in China, it still plays an effective positive role in future PV cost reduction.

Keywords: photovoltaic, system dynamics, technological learning, learning curve

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Authors: Mazura Mokhtar, Adibah Shuib, Daud Mohamad

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Portfolio optimization problem has received a lot of attention from both researchers and practitioners over the last six decades. This paper provides an overview of the current state of research in portfolio optimization with the support of mathematical programming techniques. On top of that, this paper also surveys the solution algorithms for solving portfolio optimization models classifying them according to their nature in heuristic and exact methods. To serve these purposes, 40 related articles appearing in the international journal from 2003 to 2013 have been gathered and analyzed. Based on the literature review, it has been observed that stochastic programming and goal programming constitute the highest number of mathematical programming techniques employed to tackle the portfolio optimization problem. It is hoped that the paper can meet the needs of researchers and practitioners for easy references of portfolio optimization.

Keywords: portfolio optimization, mathematical programming, multi-objective programming, solution approaches

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Authors: Abdolghader Pourali, Mohammad V. Malakooti, Muhammad Hussein Yektaie

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A mobile payment system in mobile e-commerce generally have high security so that the user can trust it for doing business deals, sales, paying financial transactions, etc. in the mobile payment system. Since an architecture or payment model in e-commerce only shows the way of interaction and collaboration among users and mortgagers and does not present any evaluation of effectiveness and confidence about financial transactions to stakeholders. In this paper, we try to present a detailed assessment of the reliability of a mobile payment model in the mobile e-commerce using formal models and colored Petri nets. Finally, we demonstrate that the reliability of this system has high value (case study: a secure payment model in mobile commerce.

Keywords: reliability, colored Petri net, assessment, payment models, m-commerce

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Authors: Ghaleb Y. Abbasi, Israa Abu Rumman

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This paper modeled sales history archived from 2012 to 2015 bulked in monthly bins for five products for a medical supply company in Jordan. The sales forecasts and extracted consistent patterns in the sales demand history from the Enterprise Resource Planning (ERP) system were used to predict future forecasting and generate sales demand forecasting using time series analysis statistical technique called Auto Regressive Integrated Moving Average (ARIMA). This was used to model and estimate realistic sales demand patterns and predict future forecasting to decide the best models for five products. Analysis revealed that the current replenishment system indicated inventory overstocking.

Keywords: ARIMA models, sales demand forecasting, time series, R code

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Authors: Terefe Fuge, George Tsourtos , Emma Miller

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Objectives: Maintaining optimal adherence and viral suppression in people living with HIV (PLWHA) is essential to ensure both preventative and therapeutic benefits of antiretroviral therapy (ART). Prisoners bear a particularly high burden of HIV infection and are highly likely to transmit to others during and after incarceration. However, the level of adherence and viral suppression, as well as its associated factors in incarcerated populations in low-income countries is unknown. This study aimed to determine the prevalence of non-adherence and viral failure, and contributing factors to this amongst prisoners in South Ethiopia. Methods: A prospective cohort study was conducted between June 1, 2019 and July 31, 2020 to compare the level of adherence and viral suppression between incarcerated and non-incarcerated PLWHA. The study involved 74 inmates living with HIV (ILWHA) and 296 non-incarcerated PLWHA. Background information including sociodemographic, socioeconomic, psychosocial, behavioural, and incarceration-related characteristics was collected using a structured questionnaire. Adherence was determined based on participants’ self-report and pharmacy refill records, and plasma viral load measurements which were undertaken within the study period were prospectively extracted to determine viral suppression. Various univariate and multivariate regression models were used to analyse data. Results: Self-reported dose adherence was approximately similar between ILWHA and non-incarcerated PLWHA (81% and 83% respectively), but ILWHA had a significantly higher medication possession ratio (MPR) (89% vs 75%). The prevalence of viral failure (VF) was slightly higher (6%) in ILWHA compared to non-incarcerated PLWHA (4.4%). The overall dose non-adherence (NA) was significantly associated with missing ART appointments, level of satisfaction with ART services, patient’s ability to comply with a specified medication schedule and types of methods used to monitor the schedule. In ILWHA specifically, accessing ART services from a hospital compared to a health centre, an inability to always attend clinic appointments, experience of depression and a lack of social support predicted NA. VF was significantly higher in males, people of age 31-35 years and in those who experienced social stigma, regardless of their incarceration status. Conclusions: This study revealed that HIV-infected prisoners in South Ethiopia were more likely to be non-adherent to doses and so to develop viral failure compared to their non-incarcerated counterparts. A multitude of factors was found to be responsible for this requiring multilevel intervention strategies focusing on the specific needs of prisoners.

Keywords: Adherence , Antiretroviral therapy, Incarceration, South Ethiopia, Viral suppression

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Authors: Artemis Louppis, Michalis Constantinou, Ioanna Kosma, Federica Blando, Michael Kontominas, Anastasia Badeka

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The aim of the present study was to differentiate yellow prickly pear according to geographical origin based on the combination of mineral content, physicochemical parameters, vitamins and antioxidants. A total of 240 yellow prickly pear samples from Cyprus, Spain, Italy and Greece were analyzed for pH, titratable acidity, electrical conductivity, protein, moisture, ash, fat, antioxidant activity, individual antioxidants, sugars and vitamins by UPLC-MS/MS as well as minerals by ICP-MS. Statistical treatment of the data included multivariate analysis of variance followed by linear discriminant analysis. Based on results, a correct classification of 66.7% was achieved using the cross validation by mineral content while 86.1% was achieved using the cross validation method by combination of all analytical parameters.

Keywords: geographical differentiation, prickly pear, chemometrics, analytical techniques

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Authors: Nancy Bartekian, Christine Reyna

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Republicans and Democrats are often polarized when it comes to important topics, but the portrayal of polarization of key issues might be distorted and exaggerated. We examined Republicans' and Democrats’ attitudes about police reform policy during the 2020 racial justice protests and calls to ‘defund the police’. We hypothesized that a) Republicans and Democrats will be polarized on the “defund police'' question; however, b) they will have similar overall attitudes towards specific police reform policies (will be on the same side of the scale--disagree vs. agree), but c) will differ in their extent of agreement or disagreement (main effect of political party ID, but located on the same side of the scale). Using one-way, Multivariate analysis of covariance (MANCOVA) controlling for race, education, and income, we found an overall effect of political party ID. Six out of the nine policies studied were, in fact, not polarizing; both groups were in consensus on whether they disagreed or agreed with the policy, including “defund police''. Results suggest that polarization might be exaggerated.

Keywords: political psychology, social, ideology, polarization

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Authors: Ivana Tadic, Snjezana Pivac

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Although human resources are recognized as the crucial companies’ resources and their positive influence on companies’ performances has been confirmed through different researches, scientists are still debating it. In order to contribute this debate, this paper firstly discusses the most important human resource management elements and practices and its influence on companies’ success. Afterwards it defines human resource “bundles” – interrelated and internally consistent human resource practices, complementary to each other, or the most important human resource practices and elements regarding Croatian companies and its human resource management activities. Finally, the paper provides empirical results; more precisely it reveals the relation of the level of development of human resource management function (“bundles”) and companies’ financial performances (using profitability ratios, liquidity ratios, solvency ratios and a group of additional ratios related to employees’ indicators).

Keywords: companies’ performances, human resource bundles, multivariate statistical analysis, marketing

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Authors: Andrew J. Zacharias

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The forest garden approach (FGA) was established by Trees for the Future (TREES) over the organization’s 30 years of agroforestry projects in Sub-Saharan Africa. This method transforms traditional agricultural systems into highly managed gardens that produce food and marketable products year-round. The effects of the FGA on food security, dietary diversity, and economic resilience have been measured closely, and TREES has begun to closely monitor the environmental impacts through the use of sensors mounted on unmanned aerial vehicles, commonly known as 'drones'. These drones collect thousands of pictures to create 3-D models in both the visible and the near-infrared wavelengths. Analysis of these models provides TREES with quantitative and qualitative evidence of improvements to the annual above-ground biomass and leaf area indices, as measured in-situ using NDVI calculations.

Keywords: agroforestry, biomass, drones, NDVI

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Authors: Christopher Godwin Udomboso, Angela Unna Chukwu, Isaac Kwame Dontwi

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In selecting a Statistical Neural Network model, the Network Information Criterion (NIC) has been observed to be sample biased, because it does not account for sample sizes. The selection of a model from a set of fitted candidate models requires objective data-driven criteria. In this paper, we derived and investigated the Adjusted Network Information Criterion (ANIC), based on Kullback’s symmetric divergence, which has been designed to be an asymptotically unbiased estimator of the expected Kullback-Leibler information of a fitted model. The analyses show that on a general note, the ANIC improves model selection in more sample sizes than does the NIC.

Keywords: statistical neural network, network information criterion, adjusted network, information criterion, transfer function

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Authors: Asmae Tafraouti, Yasmina Layouni, Pascal Kleimann

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The growing market for Microsystems (MST) and Micro-Electromechanical Systems (MEMS) is driving the research for alternative manufacturing techniques to microelectronics-based technologies, which are generally expensive and time-consuming. Hot-embossing and micro-injection modeling of thermoplastics appear to be industrially viable processes. However, both require the use of master models, usually made in hard materials such as steel. These master models cannot be fabricated using standard microelectronics processes. Thus, other micromachining processes are used, such as laser machining or micro-electrical discharge machining (µEDM). In this work, µEDM has been used. The principle of µEDM is based on the use of a thin cylindrical micro-tool that erodes the workpiece surface. The two electrodes are immersed in a dielectric with a distance of a few micrometers (gap). When an electrical voltage is applied between the two electrodes, electrical discharges are generated, which cause material machining. In order to produce master models with high resolution and smooth surfaces, it is necessary to well control the discharge mechanism. However, several problems are encountered, such as a random electrical discharge process, the fluctuation of the discharge energy, the electrodes' polarity inversion, and the wear of the micro-tool. The effect of different parameters, such as the applied voltage, the working capacitor, the micro-tool diameter, and the initial gap, has been studied. This analysis helps to improve the machining performances, such as the workpiece surface condition and the lateral crater's gap.

Keywords: craters, electrical discharges, micro-electrical discharge machining, microsystems

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Authors: Bader Alkandari, Jamal Y. Madouh, Ahmad M. Alkandari, Anwar A. Alnaqi

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A new formulation of fuzzy linear estimation problem is presented. It is formulated as a linear programming problem. The objective is to minimize the spread of the data points, taking into consideration the type of the membership function of the fuzzy parameters to satisfy the constraints on each measurement point and to insure that the original membership is included in the estimated membership. Different models are developed for a fuzzy triangular membership. The proposed models are applied to different examples from the area of fuzzy linear regression and finally to different examples for estimating the electrical load on a busbar. It had been found that the proposed technique is more suited for electrical load estimation, since the nature of the load is characterized by the uncertainty and vagueness.

Keywords: fuzzy regression, load estimation, fuzzy linear parameters, electrical load estimation

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Authors: N. P. Bhandary, R. C. Tiwari, R. Yatabe

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The research employs finite element method to evaluate the stability of roadside settlements slopes from Barpak to Yamagaon through Laprak village of Gorkha, Nepal after the 7.8Mw 2015 Barpak, Gorkha, Nepal earthquake. It includes three major villages of Gorkha, i.e., Barpak, Laprak and Yamagaun that were devastated by 2015 Gorkhas’ earthquake. The road head distance from the Barpak to Laprak and Laprak to Yamagaun are about 14 and 29km respectively. The epicentral distance of main shock of magnitude 7.8 and aftershock of magnitude 6.6 were respectively 7 and 11 kilometers (South-East) far from the Barpak village nearer to Laprak and Yamagaon. It is also believed that the epicenter of the main shock as said until now was not in the Barpak village, it was somewhere near to the Yamagaun village. The chaos that they had experienced during the earthquake in the Yamagaun was much more higher than the Barpak. In this context, we have carried out a detailed study to investigate the stability of Yamagaun settlements slope as a case study, where ground fissures, ground settlement, multiple cracks and toe failures are the most severe. In this regard, the stability issues of existing settlements and proposed road alignment, on the Yamagaon village slope are addressed, which is surrounded by many newly activated landslides. Looking at the importance of this issue, field survey is carried out to understand the behavior of ground fissures and multiple failure characteristics of the slopes. The results suggest that the Yamgaun slope in Profile 2-2, 3-3 and 4-4 are not safe enough for infrastructure development even in the normal soil slope conditions as per 2, 3 and 4 material models; however, the slope seems quite safe for at Profile 1-1 for all 4 material models. The result also indicates that the first three profiles are marginally safe for 2, 3 and 4 material models respectively. The Profile 4-4 is not safe enough for all 4 material models. Thus, Profile 4-4 needs a special care to make the slope stable.

Keywords: earthquake, finite element method, landslide, stability

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Authors: Eduardo C. Guardia, Jose W. M. Lima, Afonso H. M. Santos

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This paper presents a nonparametric method to obtain the hazard rate “Bathtub curve” for power system components. The model is a mixture of the three known phases of a component life, the decreasing failure rate (DFR), the constant failure rate (CFR) and the increasing failure rate (IFR) represented by three parametric Weibull models. The parameters are obtained from a simultaneous fitting process of the model to the Kernel nonparametric hazard rate curve. From the Weibull parameters and failure rate curves the useful lifetime and the characteristic lifetime were defined. To demonstrate the model the historic time-to-failure of distribution transformers were used as an example. The resulted “Bathtub curve” shows the failure rate for the equipment lifetime which can be applied in economic and replacement decision models.

Keywords: bathtub curve, failure analysis, lifetime estimation, parameter estimation, Weibull distribution

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Authors: Aniket Kumar, Jacob Peedicayil

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Major depressive disorder (MDD) is a common and important psychiatric disorder. Several clinical features of MDD suggest an epigenetic basis for its pathogenesis. Since epigenetics (heritable changes in gene expression not involving changes in DNA sequence) may underlie the pathogenesis of MDD, epigenetic drugs such as DNA methyltransferase inhibitors (DNMTi) and histone deactylase inhibitors (HDACi) may be useful for treating MDD. The available literature indexed in Pubmed on preclinical drug trials of epigenetic drugs for the treatment of MDD was investigated. The search terms we used were ‘depression’ or ‘depressive’ and ‘HDACi’ or ‘DNMTi’. Among epigenetic drugs, it was found that there were 3 preclinical trials using HDACi and 3 using DNMTi for the treatment of MDD. All the trials were conducted on rodents (mice or rats). The animal models of depression that were used were: learned helplessness-induced animal model, forced swim test, open field test, and the tail suspension test. One study used a genetic rat model of depression (the Flinders Sensitive Line). The HDACi that were tested were: sodium butyrate, compound 60 (Cpd-60), and valproic acid. The DNMTi that were tested were: 5-azacytidine and decitabine. Among the three preclinical trials using HDACi, all showed an antidepressant effect in animal models of depression. Among the 3 preclinical trials using DNMTi also, all showed an antidepressant effect in animal models of depression. Thus, epigenetic drugs, namely, HDACi and DNMTi, may prove to be useful in the treatment of MDD and merit further investigation for the treatment of this disorder.

Keywords: DNA methylation, drug discovery, epigenetics, major depressive disorder

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Authors: Mayank Raj, V. G. Narendra

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Ever since the DARPA challenge on autonomous vehicles in 2005, there has been a lot of buzz about ‘Autonomous Vehicles’ amongst the major tech giants such as Google, Uber, and Tesla. Numerous approaches have been adopted to solve this problem, which can have a long-lasting impact on mankind. In this paper, we have used Deep Learning techniques and TensorFlow framework with the goal of building a neural network model to predict (speed, acceleration, steering angle, and brake) features needed for navigation of autonomous vehicles. The Deep Neural Network has been trained on images and sensor data obtained from the comma.ai dataset. A heatmap was used to check for correlation among the features, and finally, four important features were selected. This was a multivariate regression problem. The final model had five convolutional layers, followed by five dense layers. Finally, the calculated values were tested against the labeled data, where the mean squared error was used as a performance metric.

Keywords: autonomous vehicles, deep learning, computer vision, artificial intelligence

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Authors: Joao Fialho

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The mathematical modelling of idiopathic scoliosis has been studied throughout the years. The models presented on those papers are based on the orthotic stabilization of the idiopathic scoliosis, which are based on a transversal force being applied to the human spine on a continuous form. When considering the ATT (Antalgic-Trak Technology) device, the existent models cannot be used, as the type of forces applied are no longer transversal nor applied in a continuous manner. In this device, vertical traction is applied. In this study we propose to model the idiopathic scoliosis, using the ATT (Antalgic-Trak Technology) device, and with the parameters obtained from the mathematical modeling, set up a case-by-case individualized therapy plan, for each patient.

Keywords: idiopathic scoliosis, mathematical modelling, human spine, Antalgic-Trak technology

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Authors: Shahram Jamali, Samira Hamed

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One of the open issues in Random Early Detection (RED) algorithm is how to set its parameters to reach high performance for the dynamic conditions of the network. Although original RED uses fixed values for its parameters, this paper follows a model-based approach to upgrade performance of the RED algorithm. It models the routers queue behavior by using the Markov model and uses this model to predict future conditions of the queue. This prediction helps the proposed algorithm to make some tunings over RED's parameters and provide efficiency and better performance. Widespread packet level simulations confirm that the proposed algorithm, called Markov-RED, outperforms RED and FARED in terms of queue stability, bottleneck utilization and dropped packets count.

Keywords: active queue management, RED, Markov model, random early detection algorithm

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Authors: Sofia Stoica

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In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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Authors: S. H. Arnaud Kanga, O. Hili, S. Dabo-Niang

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Spatial prediction is an issue appealing and attracting several fields such as agriculture, environmental sciences, ecology, econometrics, and many others. Although multiple non-parametric prediction methods exist for spatial data, those are based on the conditional expectation. This paper took a different approach by examining a non-parametric spatial predictor of the conditional quantile. The study especially observes the stationary multidimensional spatial process over a rectangular domain. Indeed, the proposed quantile is obtained by inverting the conditional distribution function. Furthermore, the proposed estimator of the conditional distribution function depends on three kernels, where one of them controls the distance between spatial locations, while the other two control the distance between observations. In addition, the almost complete convergence and the convergence in mean order q of the kernel predictor are obtained when the sample considered is alpha-mixing. Such approach of the prediction method gives the advantage of accuracy as it overcomes sensitivity to extreme and outliers values.

Keywords: conditional quantile, kernel, nonparametric, stationary

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Authors: Elinor Bull, Faye Horsley

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Abstract Objective: The current study investigated if there was a difference in personality factors in prisoners who had a recorded history of firesetting and who had no recorded history of firesetting. Participants: Participants were 64 male prisoners in a Category B male prison. Participants who had set a fire were identified through the prisons data base, and prisoners who had not set a fire were selected at random. Method: The study used the International Personality Item Pool-50 to measure personality factors, and prisoners who had set a fire were identified through a range of sources accessible to the prison. Analytical evaluation was done by the Multivariate Kruskal Wallis and Mann-Whitney tests. Findings: There was a significant difference between the the firesetting and non-firesetting group in the scores of the personality factor of Contentiousness. Contentiousness was significantly lower in the firesetting sample compared to the non-firesetting sample. Conclusions: Implications for clinical practice and future research are discussed.

Keywords: firesetting, personality, arson, prison, prisoners

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Authors: Farzam Fatolazadeh, Kalifa Goita, Mehdi Eshagh, Shusen Wang

Abstract:

The Gravity Recovery and Climate Experiment (GRACE) is a satellite mission with twin satellites for the precise determination of spatial and temporal variations in the Earth’s gravity field. The products of this mission are monthly global gravity models containing the spherical harmonic coefficients and their errors. These GRACE models can be used for estimating terrestrial water storage (TWS) variations across the globe at large scales, thereby offering an opportunity for surface and groundwater storage (GWS) assessments. Yet, the ability of GRACE to monitor changes at smaller scales is too limited for local water management authorities. This is largely due to the low spatial and temporal resolutions of its models (~200,000 km2 and one month, respectively). High-resolution GRACE data products would substantially enrich the information that is needed by local-scale decision-makers while offering the data for the regions that lack adequate in situ monitoring networks, including northern parts of Canada. Such products could eventually be obtained through downscaling. In this study, we extended the spectral combination theory to simultaneously downscale spatiotemporally the 3o spatial coarse resolution of GRACE to 0.25o degrees resolution and monthly coarse resolution to daily resolution. This method combines the monthly gravity field solution of GRACE and daily hydrological model products in the form of both low and high-frequency signals to produce high spatiotemporal resolution TWSA and GWSA products. The main contribution and originality of this study are to comprehensively and simultaneously consider GRACE and hydrological variables and their uncertainties to form the estimator in the spectral domain. Therefore, it is predicted that we reach downscale products with an acceptable accuracy.

Keywords: GRACE satellite, groundwater storage, spectral combination, terrestrial water storage

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