Search results for: factor models

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: Iyd Eqqab Maree, Habil Jurgen Bast

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Vibration control of machines and structures incorporating viscoelastic materials in suitable arrangement is an important aspect of investigation. The use of viscoelastic layers constrained between elastic layers is known to be effective for damping of flexural vibrations of structures over a wide range of frequencies. The energy dissipated in these arrangements is due to shear deformation in the viscoelastic layers, which occurs due to flexural vibration of the structures. Multilayered cantilever sandwich beam like structures can be used in aircrafts and other applications such as robot arms for effective vibration control. These members may experience parametric instability when subjected to time dependant forces. The theory of dynamic stability of elastic systems deals with the study of vibrations induced by pulsating loads that are parametric with respect to certain forms of deformation. The purpose of the present work is to investigate the dynamic stability of a three layered symmetric sandwich beam (Drone Aircraft wings ) subjected to an end periodic axial force . Equations of motion are derived using finite element method (MATLAB software). It is observed that with increase in core thickness parameter fundamental buckling load increases. The fundamental resonant frequency and second mode frequency parameter also increase with increase in core thickness parameter. Fundamental loss factor and second mode loss factor also increase with increase in core thickness parameter. Increase in core thickness parameter enhances the stability of the beam. With increase in core loss factor also the stability of the beam enhances. There is a very good agreement of the experimental results with the theoretical findings.

Keywords: steel cantilever beam, viscoelastic material core, loss factor, transition region, MATLAB R2011a

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Authors: Xiaoyu Shen, Fang Fang, Chujun Qiu

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Herewith we present a Fourier method for credit risk quantification and allocation in the factor-copula model framework. The key insight is that, compared to directly computing the cumulative distribution function of the portfolio loss via Monte Carlo simulation, it is, in fact, more efficient to calculate the transformation of the distribution function in the Fourier domain instead and inverting back to the real domain can be done in just one step and semi-analytically, thanks to the popular COS method (with some adjustments). We also show that the Euler risk allocation problem can be solved in the same way since it can be transformed into the problem of evaluating a conditional cumulative distribution function. Once the conditional or unconditional cumulative distribution function is known, one can easily calculate various risk metrics. The proposed method not only fills the niche in literature, to the best of our knowledge, of accurate numerical methods for risk allocation but may also serve as a much faster alternative to the Monte Carlo simulation method for risk quantification in general. It can cope with various factor-copula model choices, which we demonstrate via examples of a two-factor Gaussian copula and a two-factor Gaussian-t hybrid copula. The fast error convergence is proved mathematically and then verified by numerical experiments, in which Value-at-Risk, Expected Shortfall, and conditional Expected Shortfall are taken as examples of commonly used risk metrics. The calculation speed and accuracy are tested to be significantly superior to the MC simulation for real-sized portfolios. The computational complexity is, by design, primarily driven by the number of factors instead of the number of obligors, as in the case of Monte Carlo simulation. The limitation of this method lies in the "curse of dimension" that is intrinsic to multi-dimensional numerical integration, which, however, can be relaxed with the help of dimension reduction techniques and/or parallel computing, as we will demonstrate in a separate paper. The potential application of this method has a wide range: from credit derivatives pricing to economic capital calculation of the banking book, default risk charge and incremental risk charge computation of the trading book, and even to other risk types than credit risk.

Keywords: credit portfolio, risk allocation, factor copula model, the COS method, Fourier method

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Authors: Sadiq Sani, Muhammad B. Ibrahim

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Watermelon rinds powder (WRP) and neem-tree leaves powder (NLP) were used as adsorbents for equilibrium adsorption isotherms studies for detoxification of methyl orange dye (MO) from simulated wastewater. The applicability of the process to various isotherm models was tested. All isotherms from the experimental data showed excellent linear reliability (R2: 0.9487-0.9992) but adsorptions onto WRP were more reliable (R2: 0.9724-0.9992) than onto NLP (R2: 0.9487-0.9989) except for Temkin’s Isotherm where reliability was better onto NLP (R2: 0.9937) than onto WRP (R2: 0.9935). Dubinin-Radushkevich’s monolayer adsorption capacities for both WRP and NLP (qD: 20.72 mg/g, 23.09 mg/g) were better than Langmuir’s (qm: 18.62 mg/g, 21.23 mg/g) with both capacities higher for adsorption onto NLP (qD: 23.09 mg/g; qm: 21.23 mg/g) than onto WRP (qD: 20.72 mg/g; qm: 18.62 mg/g). While values for Langmuir’s separation factor (RL) for both adsorbents suggested unfavourable adsorption processes (RL: -0.0461, -0.0250), Freundlich constant (nF) indicated favourable process onto both WRP (nF: 3.78) and NLP (nF: 5.47). Adsorption onto NLP had higher Dubinin-Radushkevich’s mean free energy of adsorption (E: 0.13 kJ/mol) than WRP (E: 0.08 kJ/mol) and Temkin’s heat of adsorption (bT) was better onto NLP (bT: -0.54 kJ/mol) than onto WRP (bT: -0.95 kJ/mol) all of which suggested physical adsorption.

Keywords: adsorption isotherms, methyl orange, neem leaves, watermelon rinds

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Authors: Jeonghwan Jeon

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Recently, the industry and academia have been planning development through industry/university cooperation (IUC), and the government has been promoting alternative methods to achieve successful IUC. Representatively, business cultivation involves the lead university (regarding IUC), research and development (R&D), company support, professional manpower cultivation, and marketing, etc., and the scale of support expands every year. Research is performed by many academic researchers to achieve IUC and although satisfaction of their results is high, expectations are not being met and study of the main factor is insufficient. Therefore, this research improves on theirs by analysing the main factors influencing their satisfaction. Each factor is analysed by AHP, and portfolio analysis is performed on the importance and current satisfaction level. This will help improve satisfaction of business participants and ensure effective IUC in the future.

Keywords: industry/university cooperation, satisfaction, portfolio analysis, business participant

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Authors: Ali Bakhtiari Gharibdosti, Mohammad Hosein Bijeh Keshavarzi, Samira Alijani

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To understand internal characteristics relationships and determine factors which explain under consideration characteristics in rapeseed varieties, 10 rapeseed genotypes were implemented in complete accidental plot with three-time repetitions under drought stress in 2009-2010 in research field of agriculture college, Islamic Azad University, Karaj branch. In this research, 11 characteristics include of characteristics related to growth, production and functions stages was considered. Variance analysis results showed that there is a significant difference among rapeseed varieties characteristics. By calculating simple correlation coefficient under both conditions, normal and drought stress indicate that seed function characteristics in plant and pod number have positive and significant correlation in 1% probable level with seed function and selection on the base of these characteristics was effective for improving this function. Under normal and drought stress, analyzing the main factors showed that numbers of factors which have more than one amount, had five factors under normal conditions which were 82.72% of total variance totally, but under drought stress four factors diagnosed which were 76.78% of total variance. By considering total results of this research and by assessing effective characteristics for factor analysis and selecting different components of these characteristics, they can be used for modifying works to select applicable and tolerant genotypes in drought stress conditions.

Keywords: correlation, drought stress, factor analysis, rapeseed

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Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

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Authors: Hae-Jun Lee, Ji-Sun Shin, Kyung-Tae Lee

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Potentilla species (Rosasease) have been used in traditional medicine to treat different ailment, disease or malady. In this study, we investigated the anti-inflammatory effects of ethanol extracts of NUTT (EPP) in lipopolysaccharide (LPS)-induced Raw 264.7 macrophages and septic mice. EPP suppressed LPS-induced nitric oxide (NO) and prostaglandin E2 (PGE2) production in LPS-induced Raw 264.7 macrophages. Consistent with these observations, EPP reduced the expressions of inducible nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) by downregulation of their promoter activities. EPP inhibited tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) at production and mRNA levels. Molecularly, EPP attenuated the LPS-induced transcriptional activity, and DNA-binding activity of nuclear factor-κB (NF-κB), and this was associated with a decrease of translocation and phosphorylation of p65 NF-κB by inhibiting the inhibitory κB-α (IκB-α) degradation and IκB kinase-α/β (IKK-α/β) phosphorylation. Furthermore, EPP suppressed the LPS-induced activation of activator protein-1 (AP-1) by reducing the expression of c-Fos and c-Jun in nuclear. EPP also reduced the phosphorylation of mitogen-activated protein kinase (MAPK), such as p38 MAPK and c-Jun N-terminal kinase/stress-activated protein kinase (JNK). In a sepsis model, pretreatment with EPP reduced the LPS-induced lethality. Collectively, these results suggest that the anti-inflammatory effects of EPP were associated with the suppression of NF-κB and AP-1 activation, and support its possible therapeutic role for the treatment of sepsis.

Keywords: anti-inflammation, activator protein-1, nuclear factor κB, Potentilla paradoxa Nutt

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Authors: Barbara Rebecca Mutonyi, Chukwuemeka Echebiri, Terje Slåtten, Gudbrand Lien

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The concept of affective commitment to change has been scarcely explored among employees in the higher education literature. The present study addresses this knowledge gap in the literature by examining how various psychological factors, such as psychological empowerment (PsyEmp), and psychological capital (PsyCap), promotes affective commitment to change. As affective commitment to change has been identified by previous studies as an important aspect to implementation behavior, the study examines the correlation of affective commitment to change on employee innovative behavior (EIB) in higher education. The study proposes mediation relationship between PsyEmp, PsyCap, and affective commitment to change. 250 employees in higher education in Norway were sampled for this study. The study employed online survey for data collection, utilizing Stata software to perform Partial least square equation modeling to test the proposed hypotheses of the study. Through bootstrapping, the study was able to test for mediating effects. Findings of the study shows a strong direct relationship between the leadership factor PsyEmp on the individual factor PsyCap ( = 0.453). In addition, the findings of the study reveal that both PsyEmp and PsyCap are related to affective commitment to change ( = 0.28 and  = 0.249, respectively). In total, PsyEmp and PsyCap explains about 10% of the variance in the concept of affective commitment to change. Further, the direct effect of effective commitment to change and EIB is also supported ( = 0.183). The three factors, PsyEmp, PsyCap, and affective commitment to change, explains nearly 40% (R2 = 0.39) of the variance found in EIB. The relationship between PsyEmp, PsyCap, and affective commitment to change are mediated through the individual factor PsyCap. In order to effectively promote affective commitment to change among higher education employees, higher education managers should focus on both the leadership factor, PsyEmp, as well as the individual factor, PsyCap, of their employees. In this regard, higher education managers should strengthen employees EIB through providing autonomy, creating a safe environment that encourages innovation thinking and action, and providing employees in higher education opportunities to be involved in changes occurring at work. This contributes to strengthening employees´ affective commitment to change, that further improves their EIB in their work roles as higher education employees. As such, the results of this study implicate the ambidextrous nature of the concepts of affective commitment to change and EIB that should be considered in future studies of innovation in higher education research.

Keywords: affective commitment to change, psychological capital, innovative behavior, psychological empowerment, higher education

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Authors: O. P. Oladipo, O. A. Falode

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The determination of Recovery Factor is of great importance to the reservoir engineer since it relates reserves to the initial oil in place. Reserves are the producible portion of reservoirs and give an indication of the profitability of a field Development. The core objective of this project is to develop an artificial neural network model using selected reservoir data to predict Recovery Factors (RF) of hydrocarbon reservoirs and compare the model with a couple of the existing correlations. The type of Artificial Neural Network model developed was the Single Layer Feed Forward Network. MATLAB was used as the network simulator and the network was trained using the supervised learning method, Afterwards, the network was tested with input data never seen by the network. The results of the predicted values of the recovery factors of the Artificial Neural Network Model, API Correlation for water drive reservoirs (Sands and Sandstones) and Guthrie and Greenberger Correlation Equation were obtained and compared. It was noted that the coefficient of correlation of the Artificial Neural Network Model was higher than the coefficient of correlations of the other two correlation equations, thus making it a more accurate prediction tool. The Artificial Neural Network, because of its accurate prediction ability is helpful in the correct prediction of hydrocarbon reservoir factors. Artificial Neural Network could be applied in the prediction of other Petroleum Engineering parameters because it is able to recognise complex patterns of data set and establish a relationship between them.

Keywords: recovery factor, reservoir, reserves, artificial neural network, hydrocarbon, MATLAB, API, Guthrie, Greenberger

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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: Emilienne Lardy, Eric Ballot, Mariam Lafkihi

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Efficient urban logistics requires a comprehensive understanding of traffic dynamics, particularly as it pertains to kinetic parameters influencing energy consumption and trip duration estimations. While real-time traffic information is increasingly accessible, current high-precision forecasting services embedded in route planning often function as opaque 'black boxes' for users. These services, typically relying on AI-processed counting data, fall short in accommodating open design parameters essential for management studies, notably within Supply Chain Management. This work revisits the modelling of traffic conditions in the context of city logistics, emphasizing its significance from the user’s point of view, with two focuses. Firstly, the focus is not on the vehicle flow but on the vehicles themselves and the impact of the traffic conditions on their driving behaviour. This means opening the range of studied indicators beyond vehicle speed, to describe extensively the kinetic and dynamic aspects of the driving behaviour. To achieve this, we leverage the Art. Kinema parameters are designed to characterize driving cycles. Secondly, this study examines how the driving context (i.e., exogenous factors to the traffic flow) determines the mentioned driving behaviour. Specifically, we explore how accurately the kinetic behaviour of a vehicle can be predicted based on a limited set of exogenous factors, such as time, day, road type, orientation, slope, and weather conditions. To answer this question, statistical analysis was conducted on real-world driving data, which includes high-frequency measurements of vehicle speed. A Factor Analysis and a Generalized Linear Model have been established to link kinetic parameters with independent categorical contextual variables. The results include an assessment of the adjustment quality and the robustness of the models, as well as an overview of the model’s outputs.

Keywords: factor analysis, generalised linear model, real world driving data, traffic congestion, urban logistics, vehicle kinematics

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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: 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: 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: Anton Grobler

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Background: Psychological capital (PsyCap), consisting of Hope, Optimism, Resilience, and Self-efficacy, is a popular positive organisational behaviour construct utilised in the studying employee work and behavioral attitudes. Various scholars believe however that further validity research should be conducted on the PsyCap questionnaire (PCQ), outside of the founding research team and in more diverse settings, for the purpose of this paper, within the diverse South African (SA) context. Aim: The purpose of this study was to investigate the construct validity of the PCQ with specific reference to its psychometric properties within the diverse SA context. Setting: The sample includes a total of 1 749 respondents, ± 60 each from 30 organisations in South Africa. Method: This study utilised a cross-sectional design and quantitative analysis. The sample is relatively representative (in terms of race, gender) of the South African workforce. A multi-factorial model was statistically explored and confirmed (with exploratory factor analysis [EFA] and confirmatory factor analysis [CFA] respectively). Results: The study yielded a three-factor solution, with Hope and Optimism as a combined factor and Resilience and Self-efficacy made up of a reconfigured set of substantively justifiable items. Three items of the original 24 items were found not to be suitable. The three factors showed good psychometric properties, good fit (in support of construct validity) and acceptable levels of convergent and discriminant validity. Conclusion: The results support the original conceptualisation of PsyCap, although with a unique structural configuration. This resonates with the notion of scholars that further research should be conducted within diverse settings. This is necessary to ensure the valid measurement of the construct, which is considered to be one of the four criteria for a construct to be categorised as a positive organisational behaviour construct.

Keywords: positive organisational behaviour, psychological capital, hope, optimism, resilience, self-efficacy, construct validity

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Authors: Ludmila A. Gavriliuc, Jerry McLarty, Heather E. Kleiner, J. Michael Mathis

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Abstract -- Background: The citrus coumarine Auraptene (Aur) is an effective chemopreventive agent, as manifested in many models of diseases and cancer. Nuclear factor erythroid 2-related factor (Nrf2) is an important regulator of genes induced by oxidative stress, such as glutathione S-transferases, heme oxygenase-1, and peroxiredoxin 1, by activating the antioxidant response element (ARE). Genetic and biochemical evidence has demonstrated that glutathione (GSH) and glutathione-dependent enzymes, glutathione reductase (GR), glutathione peroxidases (GPs), glutathione S-transferases (GSTs) are responsible for the control of intracellular reduction-oxidation status and participate in cellular adaptation to oxidative stress. The effect of Aur on the activity of GR, GPs (Se-GP and Se-iGP), and content of GSH in the liver, kidney, and spleen is insufficiently explored. Aim: Our goal was the examination of the Aur influence on the redox-system of GSH in Nrf2 wild type and Nrf2 knockout mice via activation of Nrf2 and ARE. Methods: Twenty female mice, 10 Nrf2 wild-type (WT) and 10 Nrf2 (-/-) knockout (KO), were bred and genotyped for our study. The activity of GR, Se-GP, Se-iGP, GST, G6PD, CytP450 reductase, catalase (Cat), and content of GSH were analyzed in the liver, kidney, and spleen using Spectrophotometry methods. The results of the specific activity of enzymes and the amount of GSH were analyzed with ANOVA and Spearman statistical methods. Results: Aur (200 mg/kg) treatment induced hepatic GST, GR, Se-GP activity and inhibited their activity in the spleen of mice, most likely via activation of the ARE through Nrf2. Activation in kidney Se-GP and G6PD by Aur is also controlled, apparently through Nrf2. Results of the non-parametric Spearman correlation analysis indicated the strong positive correlation between GR and G6PD only in the liver in WT control mice (r=+0.972; p < 0.005) and in the kidney KO control mice (r=+0.958; p < 0.005). The observed low content of GSH in the liver of KO mice indicated an increase in its participation in the neutralization of toxic substances with the absence of induction of GSH-dependent enzymes, such as GST, GR, Se-GP, and Se-iGP. Activation of CytP450 in kidney and spleen and Cat in the liver in KO mice probably revealed another regulatory mechanism for these enzymes. Conclusion: Thereby, obtained results testify that Aur can modulate the activity of genes and antioxidant enzymatic redox-system of GSH, responsible for the control of intracellular reduction-oxidation status.

Keywords: auraptene, glutathione, GST, Nrf2

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Authors: Chonlada Choedchun, Ni-on Saelim, Panupong Chuntanalerg, Thanyalak Chaisuwan, Sujitra Wongkasemjit

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Bioethanol is one of the candidates to replace fossil fuels. Membrane technique is one of the attractive processes to produce high purity of ethanol. In this work, polybenzoxazine (PBZ) membrane successfully synthesized from bisphenol-A (BPA), formaldehyde, and two different types of multifunctionalamines: tetraethylenepentamine (tepa), and diethylenetriamine (deta), was evaluated for water-ethanol separation. The membrane thickness was determined by scanning electron microscopy (SEM). Pervaporation technique was carried out to find separation performance. It was found that the optimum PBZ concentration for the preparation of the membranes is 25%. The dipping cycles of PBZ-tepa and PBZ-deta was found to be 4 and 5, giving the total permeation flux of 28.97 and 14.75 g/m2.h, respectively. The separation factor of both membranes was higher than 10,000.

Keywords: polybenzoxazine, pervaporation, permeation flux, separation factor

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Authors: Xiaohua Jing

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Efficient extraction for separation of V and Cr in the leaching/aqueous solution is essential to the reuse of V and Cr in the V-Cr slag. Trioctylamine, a common tertiary amine extractant, with some good characters (e.g., weak base, insoluble in water and good stability) different from N1923, was investigated in this paper. The separation factor of Cr and V can be reached to 230.71 when initial pH of the aqueous solution is 0.5, so trioctylamine can be used for extracting Cr from the leaching/aqueous solution contained V and Cr. The highest extraction percentages of Cr and V were 98.73% and 90.22% when the initial pH values were 0.5 and 1.5, respectively. Via FT-IR spectra of loaded organic phase and trioctylamine, the hydrogen bond association mechanism of extracting V and Cr was investigated, which was the same with the way of extracting the two metals with primary amine N1923.

Keywords: selective extraction, trioctylamine, V and Cr, separation factor, hydrogen bond association

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Authors: Mirnawati, Gita Ciptaan, Ferawati

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Background and Objective: Palm kernel cake (PKC) is a waste of the palm oil industry. Indonesia, as the largest palm oil producer in the world, produced 45-46% palm kernel cake. Palm kernel cake can potentially be used as animal ration but its utilization for poultry is limited. Thus, fermentation process was done in order to increase the utilization PKC in poultry ration. An experiment was conducted to study the effect between Inoculum Doses with Bacillus subtilis and fermentation time to improve the quality and nutrient content of fermented Palm Kernel Cake. Material and Methods: 1) Palm kernel cake derived from Palm Kernel Processing Manufacture of Andalas Agro Industry in Pasaman, West Sumatra. 2) Bacillus subtilis obtained from The Research Center of Applied Chemistry LIPI, Bogor. 3) Preparations nutrient agar medium (NA) produced by Difoo - Becton Dickinson. 4) Rice bran 5) Aquades and mineral standard. The experiment used completely randomize design (CRD) with 3 x 3 factorial and 3 replications. The first factors were three doses of inoculum Bacillus subtilis: (3%), (5%), and (7%). The second factor was fermentation time: (1) 2 day, (2) 4 day, and (3) 6 day. The parameters were crude protein, crude fiber, nitrogen retention, and crude fiber digestibility of fermented palm kernel cake (FPKC). Results: The result of the study showed that there was significant interaction (P<0.01) between factor A and factor B and each factor A and B also showed significant effect (P<0.01) on crude protein, crude fiber, nitrogen retention, and crude fiber digestibility. Conclusion: From this study, it can be concluded that fermented PKC with 7% doses of Bacillus subtilis and 6 days fermentation time provides the best result as seen from 24.65% crude protein, 17.35% crude fiber, 68.47% nitrogen retention, 53.25% crude fiber digestibility of fermented palm kernel cake (FPKC).

Keywords: fermentation, Bacillus Subtilis, inoculum, palm kernel cake, quality, nutrient

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Authors: Firat Arslan, Hasan Degirmenci, Serife Tulin Akkaya Aslan

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The aim of the current experiment was to determine the relationship among shape indexes which are used by the researchers in many fields to evaluate parcel shapes which is very important for farming even if these indexes are controversial. In the current study, land consolidation project of Halitaga village in Mersin province in Turkey which has 278 parcel and cover 894.4 ha, was taken as a material. Commonly used indicators such as fractal dimension (FD), shape index (SI), form factor (FORM), areal form factor (AFF) and two distinct area-perimeter ratio (APR-1 and APR2) in land consolidation are used to measure agricultural plot’s shape. FD was positively correlated with SI, APR-1 and APR-2 whereas it was negatively correlated with FORM and AFF. SI was positively correlated with APR-1 and APR-2 whereas it was negatively correlated with FORM and AFF. As a conclusion, it is likely that these indexes involved may be used interchangeably due to high correlations among them.

Keywords: GIS, land consolidation, parcel shape, shape index

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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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