Search results for: foundation models

Authors: Yiannis G. Smirlis

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The classification and the prediction of efficiencies in Data Envelopment Analysis (DEA) is an important issue, especially in large scale problems or when new units frequently enter the under-assessment set. In this paper, we contribute to the subject by proposing a grid structure based on interval segmentations of the range of values for the inputs and outputs. Such intervals combined, define hyper-rectangles that partition the space of the problem. This structure, exploited by Interval DEA models and a dominance relation, acts as a DEA pre-processor, enabling the classification and prediction of efficiency scores, without applying any DEA models.

Keywords: data envelopment analysis, interval DEA, efficiency classification, efficiency prediction

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Authors: Srinidhi. A, Naveed Ahmed, Twinkle Hareendran, Vriksha Prakash

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This work reviews some of the advanced image processing techniques for deep learning applications. Object detection by template matching, image denoising, edge detection, and super-resolution modelling are but a few of the tasks. The paper looks in into great detail, given that such tasks are crucial preprocessing steps that increase the quality and usability of image datasets in subsequent deep learning tasks. We review some of the methods for the assessment of image quality, more specifically sharpness, which is crucial to ensure a robust performance of models. Further, we will discuss the development of deep learning models specific to facial emotion detection, age classification, and gender classification, which essentially includes the preprocessing techniques interrelated with model performance. Conclusions from this study pinpoint the best practices in the preparation of image datasets, targeting the best trade-off between computational efficiency and retaining important image features critical for effective training of deep learning models.

Keywords: image processing, machine learning applications, template matching, emotion detection

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Authors: Solaine Hachem, Frédéric Bourquin, Dominique Siegert

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The brutal collapse of bridges is mainly due to scour. Indeed, the soil erosion in the riverbed around a pier modifies the embedding conditions of the structure, reduces its overall stiffness and threatens its stability. Hence, finding an efficient technique that allows early scour detection becomes mandatory. Vibration analysis is an indirect method for scour detection that relies on real-time monitoring of the bridge. It tends to indicate the presence of a scour based on its consequences on the stability of the structure and its dynamic response. Most of the research in this field has focused on the dynamic behavior of a single pile and has examined the depth of the scour. In this paper, a bridge is fully modeled with all piles and spans and the scour is represented by a reduction in the foundation's stiffnesses. This work aims to identify the vibration modes sensitive to the rigidity’s loss in the foundations so that their variations can be considered as a scour indicator: the decrease in soil-structure interaction rigidity leads to a decrease in the natural frequencies’ values. By using the first-order perturbation method, the expression of sensitivity, which depends only on the selected vibration modes, is established to determine the deficiency of foundations stiffnesses. The solutions are obtained by using the singular value decomposition method for the regularization of the inverse problem. The propagation of uncertainties is also calculated to verify the efficiency of the inverse problem method. Numerical simulations describing different scenarios of scour are investigated on a simplified model of a real composite steel-concrete bridge located in France. The results of the modal analysis show that the modes corresponding to in-plane and out-of-plane piers vibrations are sensitive to the loss of foundation stiffness. While the deck bending modes are not affected by this damage.

Keywords: bridge’s piers, inverse problems, modal sensitivity, scour detection, vibration analysis

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Authors: Jairson Barbosa Rodrigues, Paulo Romero Martins Maciel, Germano Crispim Vasconcelos

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This paper presents an investigation of the performance impacts regarding the variation of five factors (input data size, node number, cores, memory, and disks) when applying a distributed implementation of Naïve Bayes for text classification of a large Corpus on the Spark big data processing framework. Problem: The algorithm's performance depends on multiple factors, and knowing before-hand the effects of each factor becomes especially critical as hardware is priced by time slice in cloud environments. Objectives: To explain the functional relationship between factors and performance and to develop linear predictor models for time and cost. Methods: the solid statistical principles of Design of Experiments (DoE), particularly the randomized two-level fractional factorial design with replications. This research involved 48 real clusters with different hardware arrangements. The metrics were analyzed using linear models for screening, ranking, and measurement of each factor's impact. Results: Our findings include prediction models and show some non-intuitive results about the small influence of cores and the neutrality of memory and disks on total execution time, and the non-significant impact of data input scale on costs, although notably impacts the execution time.

Keywords: big data, design of experiments, distributed machine learning, natural language processing, spark

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Authors: Meenalochana Inguva

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The context: The Center for Preparatory study is one of the strongest and most vibrant academic teaching units of the Sultan Qaboos University (SQU). The Foundation Programme English Language (FPEL) is part of a larger foundation programme which was implemented at SQU in fall 2010. The programme has been designed to prepare the students who have been accepted to study in the university in order to achieve the required educational goals (the learning outcomes) that have been designed according to Oman Academic Standards and published by the Omani Authority for Academic Accreditation (OAAA) for the English language component. The curriculum: At the CPS, the English language curriculum is based on the learning outcomes drafted for each level. These learning outcomes guide the students in meeting what is expected of them by the end of each level. These six levels are progressive in nature and are seen as a continuum. The study: A periodic evaluation of language programmes is necessary to improve the quality of the programmes and to meet the set goals of the programmes. An evaluation may be carried out internally or externally depending on the purpose and context. A self-study programme was initiated at the beginning of spring semester 2015 with a team comprising a total of 11 members who worked with-in the assigned course areas (level and programme specific). Only areas specific to FPEL have been included in the study. The study was divided into smaller tasks and members focused on their assigned courses. The self-study primarily focused on analyzing the programme LOs, curriculum planning, materials used and their relevance against the GFP exit standards. The review team also reflected on the assessment methods and procedures followed to reflect on student learning. The team has paid attention to having standard criteria for assessment and transparency in procedures. A special attention was paid to the staging of LOs across levels to determine students’ language and study skills ability to cope with higher level courses. Findings: The findings showed that most of the LOs are met through the materials used for teaching. Students score low on objective tests and high on subjective tests. Motivated students take advantage of academic support activities others do not utilize the student support activities to their advantage. Reading should get more hours. In listening, the format of the listening materials in CT 2 does not match the test format. Some of the course materials need revision. For e.g. APA citation, referencing etc. No specific time is allotted for teaching grammar Conclusion: The findings resulted in taking actions in bridging gaps. It will also help the center to be better prepared for the external review of its FPEL curriculum. It will also provide a useful base to prepare for the self-study portfolio for GFP standards assessment and future audit.

Keywords: curriculum planning, learning outcomes, reflections, self-evaluation

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Authors: Ning Chang, Zelong Yuan, Yunpeng Wang, Jianchun Wang

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Large eddy simulation (LES) has been extensively used in the investigation of turbulence. LES calculates the grid-resolved large-scale motions and leaves small scales modeled by sublfilterscale (SFS) models. Among the existing SFS models, the deconvolution model has been used successfully in the LES of the engineering flows and geophysical flows. Despite the wide application of deconvolution models, the effects of subfilter scale dynamics and filter anisotropy on the accuracy of SFS modeling have not been investigated in depth. The results of LES are highly sensitive to the selection of filters and the anisotropy of the grid, which has been overlooked in previous research. In the current study, two critical aspects of LES are investigated. Firstly, we analyze the influence of sub-filter scale (SFS) dynamics on the accuracy of direct deconvolution models (DDM) at varying filter-to-grid ratios (FGR) in isotropic turbulence. An array of invertible filters are employed, encompassing Gaussian, Helmholtz I and II, Butterworth, Chebyshev I and II, Cauchy, Pao, and rapidly decaying filters. The significance of FGR becomes evident, as it acts as a pivotal factor in error control for precise SFS stress prediction. When FGR is set to 1, the DDM models cannot accurately reconstruct the SFS stress due to the insufficient resolution of SFS dynamics. Notably, prediction capabilities are enhanced at an FGR of 2, resulting in accurate SFS stress reconstruction, except for cases involving Helmholtz I and II filters. A remarkable precision close to 100% is achieved at an FGR of 4 for all DDM models. Additionally, the further exploration extends to the filter anisotropy to address its impact on the SFS dynamics and LES accuracy. By employing dynamic Smagorinsky model (DSM), dynamic mixed model (DMM), and direct deconvolution model (DDM) with the anisotropic filter, aspect ratios (AR) ranging from 1 to 16 in LES filters are evaluated. The findings highlight the DDM's proficiency in accurately predicting SFS stresses under highly anisotropic filtering conditions. High correlation coefficients exceeding 90% are observed in the a priori study for the DDM's reconstructed SFS stresses, surpassing those of the DSM and DMM models. However, these correlations tend to decrease as lter anisotropy increases. In the a posteriori studies, the DDM model consistently outperforms the DSM and DMM models across various turbulence statistics, encompassing velocity spectra, probability density functions related to vorticity, SFS energy flux, velocity increments, strain-rate tensors, and SFS stress. It is observed that as filter anisotropy intensify, the results of DSM and DMM become worse, while the DDM continues to deliver satisfactory results across all filter-anisotropy scenarios. The findings emphasize the DDM framework's potential as a valuable tool for advancing the development of sophisticated SFS models for LES of turbulence.

Keywords: deconvolution model, large eddy simulation, subfilter scale modeling, turbulence

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Authors: Davies Obaromi, Qin Yongsong, James Ndege, Azeez Adeboye, Akinwumi Odeyemi

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The basic model usually used in disease mapping, is the Besag, York and Mollie (BYM) model and which combines the spatially structured and spatially unstructured priors as random effects. Bayesian Conditional Autoregressive (CAR) model is a disease mapping method that is commonly used for smoothening the relative risk of any disease as used in the Besag, York and Mollie (BYM) model. This model (CAR), which is also usually assigned as a prior to one of the spatial random effects in the BYM model, successfully uses information from adjacent sites to improve estimates for individual sites. To our knowledge, there are some unrealistic or counter-intuitive consequences on the posterior covariance matrix of the CAR prior for the spatial random effects. In the conventional BYM (Besag, York and Mollie) model, the spatially structured and the unstructured random components cannot be seen independently, and which challenges the prior definitions for the hyperparameters of the two random effects. Therefore, the main objective of this study is to construct and utilize an extended Bayesian spatial CAR model for studying tuberculosis patterns in the Eastern Cape Province of South Africa, and then compare for flexibility with some existing CAR models. The results of the study revealed the flexibility and robustness of this alternative extended CAR to the commonly used CAR models by comparison, using the deviance information criteria. The extended Bayesian spatial CAR model is proved to be a useful and robust tool for disease modeling and as a prior for the structured spatial random effects because of the inclusion of an extra hyperparameter.

Keywords: Besag2, CAR models, disease mapping, INLA, spatial models

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Authors: Azin Zargham, Gholamreza Rouhi, Allahyar Geramy

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One of the most prevalent types of alveolar bone loss is horizontal bone loss (HBL) in which the bone height around teeth is reduced homogenously. In the presence of HBL the magnitudes of forces during orthodontic treatment should be altered according to the degree of HBL, in a way that without further bone loss, desired tooth movement can be obtained. In order to investigate the appropriate orthodontic force system in the presence of HBL, a three-dimensional numerical model capable of the simulation of orthodontic tooth movement was developed. The main goal of this research was to evaluate the effect of different degrees of HBL on a long-term orthodontic tooth movement. Moreover, the effect of different force magnitudes on orthodontic tooth movement in the presence of HBL was studied. Five three-dimensional finite element models of a maxillary lateral incisor with 0 mm, 1.5 mm, 3 mm, 4.5 mm and 6 mm of HBL were constructed. The long-term orthodontic tooth tipping movements were attained during a 4-weeks period in an iterative process through the external remodeling of the alveolar bone based on strains in periodontal ligament as the bone remodeling mechanical stimulus. To obtain long-term orthodontic tooth movement in each iteration, first the strains in periodontal ligament under a 1-N tipping force were calculated using finite element analysis. Then, bone remodeling and the subsequent tooth movement were computed in a post-processing software using a custom written program. Incisal edge, cervical, and apical area displacement in the models with different alveolar bone heights (0, 1.5, 3, 4.5, 6 mm bone loss) in response to a 1-N tipping force were calculated. Maximum tooth displacement was found to be 2.65 mm at the top of the crown of the model with a 6 mm bone loss. Minimum tooth displacement was 0.45 mm at the cervical level of the model with a normal bone support. Tooth tipping degrees of models in response to different tipping force magnitudes were also calculated for models with different degrees of HBL. Degrees of tipping tooth movement increased as force level was increased. This increase was more prominent in the models with smaller degrees of HBL. By using finite element method and bone remodeling theories, this study indicated that in the presence of HBL, under the same load, long-term orthodontic tooth movement will increase. The simulation also revealed that even though tooth movement increases with increasing the force, this increase was only prominent in the models with smaller degrees of HBL, and tooth models with greater degrees of HBL will be less affected by the magnitude of an orthodontic force. Based on our results, the applied force magnitude must be reduced in proportion of degree of HBL.

Keywords: bone remodeling, finite element method, horizontal bone loss, orthodontic tooth movement.

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Authors: Liwiusz Wojciechowski

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Research background: The current knowledge does not give a clear answer to the question of the impact of FDI on productivity. Results of the empirical studies are still inconclusive, no matter how extensive and diverse in terms of research approaches or groups of countries analyzed they are. It should also take into account the possibility that FDI and productivity are linked and that there is a bidirectional relationship between them. This issue is particularly important because on one hand FDI can contribute to changes in productivity in the host country, but on the other hand its level and dynamics may imply that FDI should be undertaken in a given country. As already mentioned, a two-way relationship between the presence of foreign capital and productivity in the host country should be assumed, taking into consideration the endogenous nature of FDI. Purpose of the article: The overall objective of this study is to determine the causality between foreign direct investment and total factor productivity in host county in terms of different relative absorptive capacity across countries. In the classic sense causality among variables is not always obvious and requires for testing, which would facilitate proper specification of FDI models. The aim of this article is to study endogeneity of selected macroeconomic variables commonly being used in FDI models in case of Visegrad countries: main recipients of FDI in CEE. The findings may be helpful in determining the structure of the actual relationship between variables, in appropriate models estimation and in forecasting as well as economic policymaking. Methodology/methods: Panel and time-series data techniques including GMM estimator, VEC models and causality tests were utilized in this study. Findings & Value added: The obtained results allow to confirm the hypothesis states the bi-directional causality between FDI and total factor productivity. Although results differ from among countries and data level of aggregation implications may be useful for policymakers in case of providing foreign capital attracting policy.

Keywords: endogeneity, foreign direct investment, multi-equation models, total factor productivity

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Authors: Svetlana K. Eden

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Movies and TV shows have long become part of modern culture. We all have our preferred genre, story, actors, and actresses. However, can we objectively discern good acting from the bad? As laymen, we are probably not objective, but what about the Oscar academy members? Are their votes based on objective measures? Oscar academy members are probably also biased due to many factors, including their professional affiliations or advertisement exposure. Heavily advertised films bring more publicity to their cast and are likely to have bigger budgets. Because a bigger budget may also help earn a Best Picture (BP) nomination, we hypothesize that best actor/actress (BA) nominees from BP-nominated movies would have higher chances of winning the award than those BA nominees from non-BP-nominated films. To test this hypothesis, three Bayesian hierarchical models are proposed, and their performance is evaluated. The results from all three models largely support our hypothesis. Depending on the proportion of BP nominations among BA nominees, the odds ratios (estimated over expected) of winning the BA award conditional on BP nomination vary from 2.8 [0.8-7.0] to 4.3 [2.0, 15.8] for actors and from 1.5 [0.0, 12.2] to 5.4 [2.7, 14.2] for actresses.

Keywords: Oscar, best picture, best actor/actress, bias

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Authors: Hami Ashraf, Mohammad Heydarnejad

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Introduction: The landscape of cancer treatment has been revolutionized by immunotherapy, offering novel therapeutic avenues for diverse cancer types. Animal models play a pivotal role in the development and elucidation of these therapeutic modalities. Nevertheless, the manifestation of Graft-versus-Host Disease (GVHD) in such models poses significant challenges, muddling the interpretation of experimental data within the ambit of cancer immunotherapy. This study is dedicated to scrutinizing the role of GVHD as a confounding factor in animal models used for cancer immunotherapy, alongside proposing viable strategies to mitigate this complication. Method: Employing a systematic review framework, this study undertakes a comprehensive literature survey including academic journals in PubMed, Embase, and Web of Science databases and conference proceedings to collate pertinent research that delves into the impact of GVHD on animal models in cancer immunotherapy. The acquired studies undergo rigorous analysis and synthesis, aiming to assess the influence of GVHD on experimental results while identifying strategies to alleviate its confounding effects. Results: Findings indicate that GVHD incidence significantly skews the reliability and applicability of experimental outcomes, occasionally leading to erroneous interpretations. The literature surveyed also sheds light on various methodologies under exploration to counteract the GVHD dilemma, thereby bolstering the experimental integrity in this domain. Conclusion: GVHD's presence critically affects both the interpretation and validity of experimental findings, underscoring the imperative for strategies to curtail its confounding impacts. Current research endeavors are oriented towards devising solutions to this issue, aiming to augment the dependability and pertinence of experimental results. It is incumbent upon researchers to diligently consider and adjust for GVHD's effects, thereby enhancing the translational potential of animal model findings to clinical applications and propelling progress in the arena of cancer immunotherapy.

Keywords: graft-versus-host disease, cancer immunotherapy, animal models, preclinical model

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Authors: Rafika Bayu Kusumandari, Istyarini, Ispen Safrel

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Character education will be more meaningful if carried out since early childhood. This is because early childhood education is the foundation of the formation of character. This study intends to find a model of character education in early childhood based on Javanese culture. In keeping with the focus of the study, long-term goals to be achieved through this research is to find once described the development of a model of character education in early childhood Javanese culture based in Semarang are then applied across early childhood education institutions in Semarang City. The specific objective of the study is: Describe the character models and management education in early childhood Java-based culture in Semarang City. The benefits of this research are; Provide an overview of the model and describe the management of character education in early childhood Java-based culture in Semarang City. Referring to the objectives of the research program was designed with a "Research and Development", meaning that a program of research followed by development programs for improvement or refinement. To produce a prototype model of character education in early childhood Java-based culture in the city, taken systematic measures in the form of the action, reflection, evaluation and innovation by applying qualitative research methods, descriptive, development, experimentation, and evaluation. This study aims to gain in-depth description of the model of character education in early childhood Java-based culture in the city of Semarang. The reason for the use of the use of qualitative methods researcher's knowledge, no study results and empirical research specifically about the model of character education in early childhood Java-based culture in the city of Semarang. On the implementation of character education early childhood adapted to the characteristics of each school and the emphasis of each agency arrangements for early childhood education, culture-based Java. Javanese culture should be introduced early in order not to erode the cultural lost outside the entrance as the era of globalization. In addition, Java is promoting a culture of courtesy and manners are very appropriate for the character formation of children of early age.

Keywords: education character, Javanese culture, childhood, character

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Authors: Sarthak Deshpande, Akshay Patil, Pradip Pandhare, Nikhil Wankhede, Rushali Deshmukh

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Among the highly significant duties for any language most effective is the sentiment analysis, which is also a key area of NLP, that recently made impressive strides. There are several models and datasets available for those tasks in popular and commonly used languages like English, Russian, and Spanish. While sentiment analysis research is performed extensively, however it is lagging behind for the regional languages having few resources such as Hindi, Marathi. Marathi is one of the languages that included in the Indian Constitution’s 8th schedule and is the third most widely spoken language in the country and primarily spoken in the Deccan region, which encompasses Maharashtra and Goa. There isn’t sufficient study on sentiment analysis methods based on Marathi text due to lack of available resources, information. Therefore, this project proposes the use of different ML/NLP models for the analysis of Marathi data from the comments below YouTube content, tweets or Instagram posts. We aim to achieve a short and precise analysis and summary of the related data using our dataset (Dates, names, root words) and lexicons to locate exact information.

Keywords: multilingual sentiment analysis, Marathi, natural language processing, text summarization, lexicon-based approaches

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Authors: Yamina Boughari, Ruxandra Mihaela Botez, Florian Theel, Georges Ghazi

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Clearance of flight control laws of a civil aircraft is a long and expensive process in the Aerospace industry. Thousands of flight combinations in terms of speeds, altitudes, gross weights, centers of gravity and angles of attack have to be investigated, and proved to be safe. Nonetheless, in this method, a worst flight condition can be easily missed, and its missing would lead to a critical situation. Definitively, it would be impossible to analyze a model because of the infinite number of cases contained within its flight envelope, that might require more time, and therefore more design cost. Therefore, in industry, the technique of the flight envelope mesh is commonly used. For each point of the flight envelope, the simulation of the associated model ensures the satisfaction or not of specifications. In order to perform fast, comprehensive and effective analysis, other varying parameters models were developed by incorporating variations, or uncertainties in the nominal models, known as Linear Fractional Representation LFR models; these LFR models were able to describe the aircraft dynamics by taking into account uncertainties over the flight envelope. In this paper, the LFRs models are developed using the speeds and altitudes as varying parameters; The LFR models were built using several flying conditions expressed in terms of speeds and altitudes. The use of such a method has gained a great interest by the aeronautical companies that have seen a promising future in the modeling, and particularly in the design and certification of control laws. In this research paper, we will focus on the Cessna Citation X open loop stability analysis. The data are provided by a Research Aircraft Flight Simulator of Level D, that corresponds to the highest level flight dynamics certification; this simulator was developed by CAE Inc. and its development was based on the requirements of research at the LARCASE laboratory. The acquisition of these data was used to develop a linear model of the airplane in its longitudinal and lateral motions, and was further used to create the LFR’s models for 12 XCG /weights conditions, and thus the whole flight envelope using a friendly Graphical User Interface developed during this study. Then, the LFR’s models are analyzed using Interval Analysis method based upon Lyapunov function, and also the ‘stability and robustness analysis’ toolbox. The results were presented under the form of graphs, thus they have offered good readability, and were easily exploitable. The weakness of this method stays in a relatively long calculation, equal to about four hours for the entire flight envelope.

Keywords: flight control clearance, LFR, stability analysis, robustness analysis

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Authors: Nicola Rubino

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This paper presents an analysis of a group of commodity exporting countries' nominal exchange rate movements in relationship to the US dollar. Using a series of Unrestricted Self-exciting Threshold Autoregressive models (SETAR), we model and evaluate sixteen national CPI price differentials relative to the US dollar CPI. Out-of-sample forecast accuracy is evaluated through calculation of mean absolute error measures on the basis of two-hundred and fifty-three months rolling window forecasts and extended to three additional models, namely a logistic smooth transition regression (LSTAR), an additive non linear autoregressive model (AAR) and a simple linear Neural Network model (NNET). Our preliminary results confirm presence of some form of TAR non linearity in the majority of the countries analyzed, with a relatively higher goodness of fit, with respect to the linear AR(1) benchmark, in five countries out of sixteen considered. Although no model appears to statistically prevail over the other, our final out-of-sample forecast exercise shows that SETAR models tend to have quite poor relative forecasting performance, especially when compared to alternative non-linear specifications. Finally, by analyzing the implied half-lives of the > coefficients, our results confirms the presence, in the spirit of arbitrage band adjustment, of band convergence with an inner unit root behaviour in five of the sixteen countries analyzed.

Keywords: transition regression model, real exchange rate, nonlinearities, price differentials, PPP, commodity points

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Authors: Teh Raihana Nazirah Roslan, Siti Zulaiha Ibrahim, Sharmila Karim

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A warrant is a financial contract that confers the right but not the obligation, to buy or sell a security at a certain price before expiration. The standard procedure to value equity warrants using call option pricing models such as the Black–Scholes model had been proven to contain many flaws, such as the assumption of constant interest rate and constant volatility. In fact, existing alternative models were found focusing more on demonstrating techniques for pricing, rather than empirical testing. Therefore, a mathematical model for pricing and analyzing equity warrants which comprises stochastic interest rate and stochastic volatility is essential to incorporate the dynamic relationships between the identified variables and illustrate the real market. Here, the aim is to develop dynamic pricing formulations for hybrid equity warrants by incorporating stochastic interest rates from the Cox-Ingersoll-Ross (CIR) model, along with stochastic volatility from the Heston model. The development of the model involves the derivations of stochastic differential equations that govern the model dynamics. The resulting equations which involve Cauchy problem and heat equations are then solved using partial differential equation approaches. The analytical pricing formulas obtained in this study comply with the form of analytical expressions embedded in the Black-Scholes model and other existing pricing models for equity warrants. This facilitates the practicality of this proposed formula for comparison purposes and further empirical study.

Keywords: Cox-Ingersoll-Ross model, equity warrants, Heston model, hybrid models, stochastic

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Authors: Mohammad Abu-Taleb

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The final report of the Royal Commission into Australian financial services misconduct, released in February 2019, has had a significant impact on the financial advice industry. The recommendations released in the Commissioner’s final report include changes to ongoing fee arrangements, a new disciplinary system for financial advisers, and mandatory reporting of compliance concerns. This thesis aims to explore the impact of the Royal Commission’s recommendations on the operating model of financial advice firms in terms of advice products, processes, delivery models, and customer segments. Also, this research seeks to investigate whether the Royal Commission’s outcome has accelerated the use of enhanced technology solutions within the operating model of financial advice firms. And to identify the key challenges confronting financial advice firms whilst implementing the Commissioner’s recommendations across their operating models. In order to achieve the objectives of this thesis, a qualitative research design has been adopted through semi-structured in-depth interviews with 24 financial advisers and managers who are engaged in the operation of financial advice services. The study used the thematic analysis approach to interpret the qualitative data collected from the interviews. The findings of this thesis reveal that customer-centric operating models will become more prominent across the financial advice industry in response to the Commissioner’s final report. And the Royal Commission’s outcome has accelerated the use of advice technology solutions within the operating model of financial advice firms. In addition, financial advice firms have started more than before using simpler and more automated web-based advice services, which enable financial advisers to provide simple advice in a greater scale, and also to accelerate the use of robo-advice models and digital delivery to mass customers in the long term. Furthermore, the study identifies process and technology changes as, long with technical and interpersonal skills development, as the key challenges encountered financial advice firms whilst implementing the Commissioner’s recommendations across their operating models.

Keywords: hayne royal commission, financial planning advice, operating model, advice products, advice processes, delivery models, customer segments, digital advice solutions

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Authors: Solopova Olga

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The present paper briefly recalls theoretical preconditions for investigating cognitive-discursive models of future in political discourse. The author reviews theories and methods used for strengthening a future focus in this discourse working out two main tools – a model of future and a metaphorical scenario. The paper examines the implications of metaphorical analogies for modeling future in mass media. It argues that metaphor is not merely a rhetorical ornament in the political discourse of media regulation but a conceptual model that legislates and regulates our understanding of future.

Keywords: cognitive approach, future research, political discourse, model, scenario, metaphor

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Authors: K. Sridhar Reddy, M. Amaranatha Reddy, Nilanjan Mitra

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Short paneled concrete pavement (SPCP) with shorter panel size can be an alternative to the conventional jointed plain concrete pavements (JPCP) at the same cost as the asphalt pavements with all the advantages of concrete pavement with reduced thickness, less chance of mid-slab cracking and or dowel bar locking so common in JPCP. Cast-in-situ short concrete panels (short slabs) laid on a strong foundation consisting of a dry lean concrete base (DLC), and cement treated subbase (CTSB) will reduce the thickness of the concrete slab to the order of 180 mm to 220 mm, whereas JPCP was with 280 mm for the same traffic. During the construction of SPCP test sections on two Indian National Highways (NH), it was observed that the joints remain uncracked after a year of traffic. The undoweled and uncracked joints load transfer variability and joint behavior are of interest with anticipation on its long-term performance of the SPCP. To investigate the effects of undoweled and uncracked joints on short slabs, the present study was conducted. A multilayer linear elastic analysis using 3D finite element package for different panel sizes with different thicknesses resting on different types of solid elastic foundation with and without temperature gradient was developed. Surface deflections were obtained from 3D FE model and validated with measured field deflections from falling weight deflectometer (FWD) test. Stress analysis indicates that flexural stresses in short slabs are decreased with a decrease in panel size and increase in thickness. Detailed evaluation of stress analysis with the effects of curling behavior, the stiffness of the base layer and a variable degree of load transfer, is underway.

Keywords: joint behavior, short slabs, uncracked joints, undoweled joints, 3D numerical simulation

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Authors: R. Ramesh, M. Y. M. Yunus, K. Ramesh

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The study conducted in this research are Viscosities, η, and Densities ,ρ, of 1, 4-dioxane with Bromobenzene at different mole fractions and various temperatures in the atmospheric pressure condition. From experimentations excess volumes, VE, and deviations in viscosities, Δη, of mixtures at infinite dilutions have been obtained. The measured systems exhibited positive values of VmE and negative values of Δη. The binary mixture 1, 4 dioxane + Bromobenzene show positive VE and negative Δη with increasing temperatures. The outcomes clearly indicate that weak interactions present in mixture. It is mainly because of number and position of methyl groups exist in these aromatic hydrocarbons. These measured data tailored to the nonlinear models to derive the binary coefficients. Standard deviations have been considered between the fitted outcomes and the calculated data is helpful deliberate mixing behavior of the binary mixtures. It can conclude that in our cases, the data found with the values correlated by the corresponding models very well. The molecular interactions existing between the components and comparison of liquid mixtures were also discussed.

Keywords: 1, 4 dioxane, bromobenzene, density, excess molar volume

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Authors: Rajendra Kumar Dubey

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Einstein’s field equations with variable cosmological term Λ are considered in the presence of viscous fluid for Bianchi type I space time. Exact solutions of Einstein’s field equations are obtained by assuming cosmological term Λ Proportional to (R is a scale factor and m is constant). We observed that the shear viscosity is found to be responsible for faster removal of initial anisotropy in the universe. The physical significance of the cosmological models has also been discussed.

Keywords: bianchi type, I cosmological model, viscous fluid, cosmological constant Λ

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Authors: Mounia El Hafyani, Khalid El Himdi

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Precipitation is one of the key variables in water resource planning. The importance of modeling wet and dry durations is a crucial pointer in engineering hydrology. The objective of this study is to model and analyze the distribution of wet and dry durations. For this purpose, the daily rainfall data from 1967 to 2017 of the Moroccan city of Kenitra’s station are used. Three models are implemented for the distribution of wet and dry durations, namely the first-order Markov chain, the second-order Markov chain, and the truncated negative binomial law. The adherence of the data to the proposed models is evaluated using Chi-square and Kolmogorov-Smirnov tests. The Akaike information criterion is applied to assess the most effective model distribution. We go further and study the law of the number of wet and dry days among k consecutive days. The calculation of this law is done through an algorithm that we have implemented based on conditional laws. We complete our work by comparing the observed moments of the numbers of wet/dry days among k consecutive days to the calculated moment of the three estimated models. The study shows the effectiveness of our approach in modeling wet and dry durations of daily precipitation.

Keywords: Markov chain, rainfall, truncated negative binomial law, wet and dry durations

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Authors: Jamal A. Hassan, Ali Q. Abdulrazzaq, Sadiq J. Abass

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In this study, both the photoelastic, as well as the finite element methods, are used to study the stress distribution within human vertebra (L4) under forces similar to those that occur during normal life. Two & three dimensional models of vertebra were created by the software AutoCAD. The coordinates obtained were fed into a computer numerical control (CNC) tensile machine to fabricate the models from photoelastic sheets. Completed models were placed in a transmission polariscope and loaded with static force (up to 1500N). Stresses can be quantified and localized by counting the number of fringes. In both methods the Principle stresses were calculated at different regions. The results noticed that the maximum von-mises stress on the area of the extreme superior vertebral body surface and the facet surface with high normal stress (σ) and shear stress (τ). The facets and other posterior elements have a load-bearing function to help support the weight of the upper body and anything that it carries, and are also acted upon by spinal muscle forces. The numerical FE results have been compared with the experimental method using photoelasticity which shows good agreement between experimental and simulation results.

Keywords: photoelasticity, stress, load, finite element

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Authors: Zukhrof Romadhon, Nani Kurniati

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Availability of Spare parts is critical to support maintenance tasks and the production system. Managing spare part inventory deals with some parameters and objective functions, as well as the tradeoff between inventory costs and spare parts availability. Several mathematical models and methods have been developed to optimize the spare part policy. Many researchers who proposed optimization models need to be considered to identify other potential models. This work presents a review of several pertinent literature on spare part inventory optimization and analyzes the gaps for future research. Initial investigation on scholars and many journal database systems under specific keywords related to spare parts found about 17K papers. Filtering was conducted based on five main aspects, i.e., replenishment policy, objective function, echelon network, lead time, model solving, and additional aspects of part classification. Future topics could be identified based on the number of papers that haven’t addressed specific aspects, including joint optimization of spare part inventory and maintenance.

Keywords: spare part, spare part inventory, inventory model, optimization, maintenance

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Authors: Yoonsuh Jung

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As DNA microarray data contain relatively small sample size compared to the number of genes, high dimensional models are often employed. In high dimensional models, the selection of tuning parameter (or, penalty parameter) is often one of the crucial parts of the modeling. Cross-validation is one of the most common methods for the tuning parameter selection, which selects a parameter value with the smallest cross-validated score. However, selecting a single value as an "optimal" value for the parameter can be very unstable due to the sampling variation since the sample sizes of microarray data are often small. Our approach is to choose multiple candidates of tuning parameter first, then average the candidates with different weights depending on their performance. The additional step of estimating the weights and averaging the candidates rarely increase the computational cost, while it can considerably improve the traditional cross-validation. We show that the selected value from the suggested methods often lead to stable parameter selection as well as improved detection of significant genetic variables compared to the tradition cross-validation via real data and simulated data sets.

Keywords: cross validation, parameter averaging, parameter selection, regularization parameter search

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Authors: Zhaoan Wang

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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.

Keywords: automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation

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Authors: Yungtai Lo

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Two-part random effects models have been used to fit semi-continuous longitudinal data where the response variable has a point mass at 0 and a continuous right-skewed distribution for positive values. We review methods proposed in the literature for analyzing data with excess zeros. A two-part logit-log-normal random effects model, a two-part logit-truncated normal random effects model, a two-part logit-gamma random effects model, and a two-part logit-skew normal random effects model were used to examine effects of a bottle-weaning intervention on reducing bottle use and daily milk intake from bottles in toddlers aged 11 to 13 months in a randomized controlled trial. We show in all four two-part models that the intervention promoted bottle-weaning and reduced daily milk intake from bottles in toddlers drinking from a bottle. We also show that there are no differences in model fit using either the logit link function or the probit link function for modeling the probability of bottle-weaning in all four models. Furthermore, prediction accuracy of the logit or probit link function is not sensitive to the distribution assumption on daily milk intake from bottles in toddlers not off bottles.

Keywords: two-part model, semi-continuous variable, truncated normal, gamma regression, skew normal, Pearson residual, receiver operating characteristic curve

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Authors: Sebastian Kohlstädt, Michael Vynnycky, Stephan Goeke, Jan Jäckel, Andreas Gebauer-Teichmann

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This paper summarizes the progress in the latest computational fluid dynamics research towards the modeling in of lost core viability in high-pressure die casting. High-pressure die casting is a process that is widely employed in the automotive and neighboring industries due to its advantages in casting quality and cost efficiency. The degrees of freedom are however somewhat limited as it has been so far difficult to use lost cores in the process. This is right now changing and the deployment of lost cores is considered a future growth potential for high-pressure die casting companies. The use of this technology itself is difficult though. The strength of the core material, as chiefly salt is used, is limited and experiments have shown that the cores will not hold under all circumstances and process designs. For this purpose, the publicly available CFD library foam-extend (OpenFOAM) is used, and two additional fluid models for incompressible and compressible two-phase flow are implemented as fluid solver models into the FSI library. For this purpose, the volume-of-fluid (VOF) methodology is used. The necessity for the fluid-structure interaction (FSI) approach is shown by a simple CFD model geometry. The model is benchmarked against analytical models and experimental data. Sufficient agreement is found with the analytical models and good agreement with the experimental data. An outlook on future developments concludes the paper.

Keywords: CFD, fluid-structure interaction, high-pressure die casting, multiphase flow

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Authors: Ameer A. Jebur, William Atherton, Rafid M. Alkhaddar, Edward Loffill

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Superstructures like offshore platforms, tall buildings, transition towers, skyscrapers and bridges are normally designed to resist compression, uplift and lateral forces from wind waves, negative skin friction, ship impact and other applied loads. Better understanding and the precise simulation of the response of batter piles under the action of independent uplift loads is a vital topic and an area of active research in the field of geotechnical engineering. This paper investigates the use of finite element code (FEC) to examine the behaviour of model batter piles penetrated in dense sand, subjected to pull-out pressure by means of numerical modelling. The concept of the Winkler Model (beam on elastic foundation) has been used in which the interaction between the pile embedded depth and adjacent soil in the bearing zone is simulated by nonlinear p-y curves. The analysis was conducted on different pile slenderness ratios (lc⁄d) ranging from 7.5, 15.22 and 30 respectively. In addition, the optimum batter angle for a model steel pile penetrated in dense sand has been chosen to be 20° as this is the best angle for this simulation as demonstrated by other researcher published in literature. In this numerical analysis, the soil response is idealized as elasto-plastic and the model piles are described as elastic materials for the purpose of simulation. The results revealed that the applied loads affect the pullout pile capacity as well as the lateral pile response for dense sand together with varying shear strength parameters linked to the pile critical depth. Furthermore, the pile pull-out capacity increases with increasing the pile aspect ratios.

Keywords: slenderness ratio, soil-pile interaction, winkler model (beam on elastic foundation), pull-out capacity

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Authors: Bikis Muhammed, Sehra Sedigh Sarvestani, Ali R. Hurson, Lasanthi Gamage

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Vehicular traffic events have overly complex spatial correlations and temporal interdependencies and are also influenced by environmental events such as weather conditions. To capture these spatial and temporal interdependencies and make more realistic vehicular traffic predictions, graph neural networks (GNN) based traffic prediction models have been extensively utilized due to their capability of capturing non-Euclidean spatial correlation very effectively. However, most of the already existing GNN-based traffic prediction models have some limitations during learning complex and dynamic spatial and temporal patterns due to the following missing factors. First, most GNN-based traffic prediction models have used static distance or sometimes haversine distance mechanisms between spatially separated traffic observations to estimate spatial correlation. Secondly, most GNN-based traffic prediction models have not incorporated environmental events that have a major impact on the normal traffic states. Finally, most of the GNN-based models did not use an attention mechanism to focus on only important traffic observations. The objective of this paper is to study and make real-time vehicular traffic predictions while incorporating the effect of weather conditions. To fill the previously mentioned gaps, our prediction model uses a real-time driving distance between sensors to build a distance matrix or spatial adjacency matrix and capture spatial correlation. In addition, our prediction model considers the effect of six types of weather conditions and has an attention mechanism in both spatial and temporal data aggregation. Our prediction model efficiently captures the spatial and temporal correlation between traffic events, and it relies on the graph attention network (GAT) and Bidirectional bidirectional long short-term memory (Bi-LSTM) plus attention layers and is called GAT-BILSTMA.

Keywords: deep learning, real time prediction, GAT, Bi-LSTM, attention

Procedia PDF Downloads 70