Search results for: mixed spin Heisenberg model

Authors: Cagri Mollamahmutoglu, Aykut Levent, Ali Mercan

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Micro-beams are one of the most common components of Nano-Electromechanical Systems (NEMS) and Micro Electromechanical Systems (MEMS). For this reason, static bending, buckling, and free vibration analysis of micro-beams have been the subject of many studies. In addition, micro-beams restrained with elastic type foundations have been of particular interest. In the analysis of microstructures, closed-form solutions are proposed when available, but most of the time solutions are based on numerical methods due to the complex nature of the resulting differential equations. Thus, a robust and efficient solution method has great importance. In this study, a mixed finite element formulation is obtained for a functionally graded Timoshenko micro-beam resting on two-parameter elastic foundation. In the formulation modified couple stress theory is utilized for the micro-scale effects. The equation of motion and boundary conditions are derived according to Hamilton’s principle. A functional, derived through a scientific procedure based on Gateaux Differential, is proposed for the bending and buckling analysis which is equivalent to the governing equations and boundary conditions. Most important advantage of the formulation is that the mixed finite element formulation allows usage of C₀ type continuous shape functions. Thus shear-locking is avoided in a built-in manner. Also, element matrices are sparsely populated and can be easily calculated with closed-form integration. In this framework results concerning the effects of micro-scale length parameter, power-law parameter, aspect ratio and coefficients of partially or fully continuous elastic foundation over the static bending, buckling, and free vibration response of FG-micro-beam under various boundary conditions are presented and compared with existing literature. Performance characteristics of the presented formulation were evaluated concerning other numerical methods such as generalized differential quadrature method (GDQM). It is found that with less computational burden similar convergence characteristics were obtained. Moreover, formulation also includes a direct calculation of the micro-scale related contributions to the structural response as well.

Keywords: micro-beam, functionally graded materials, two-paramater elastic foundation, mixed finite element method

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Authors: A. Seleem, M. Mortada, M. El-Morsi, M. Younan

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Diffusion stills have been effective in water desalination. The present work represents a model of the distillation process by using vertical single-effect diffusion stills. A semi-analytical model has been developed to model the process. A software computer code using Engineering Equation Solver EES software has been developed to solve the equations of the developed model. An experimental setup has been constructed, and used for the validation of the model. The model is also validated against former literature results. The results obtained from the present experimental test rig, and the data from the literature, have been compared with the results of the code to find its best range of validity. In addition, a parametric analysis of the system has been developed using the model to determine the effect of operating conditions on the system's performance. The dominant parameters that affect the productivity of the still are the hot plate temperature that ranges from (55-90 °C) and feed flow rate in range of (0.00694-0.0211 kg/m2-s).

Keywords: analytical model, solar distillation, sustainable water systems, vertical diffusion still

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Authors: Zdeněk Veselý, Milan Honner, Jiří Mach

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The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. The complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from the 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on the temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source

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Authors: David Simpson, Kyle Nash

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There is considerable evidence linking slow, deliberative reasoning (system 2) with utilitarian judgments in dilemmas involving the sacrificing of another person for the greater good (other-sacrificial dilemmas). Joshua Greene has argued, based on this kind of evidence, that system 2 drives utilitarian judgments. However, the evidence on whether system 2 is associated with utilitarian judgments in self-sacrificial dilemmas is more mixed. We employed process dissociation to measure a self-sacrificial utilitarian (SU) parameter and an other-sacrificial (OU) utilitarian parameter. It was initially predicted that contra Greene, the cognitive reflection test (CRT) would only be positively correlated with the OU parameter and not the SU parameter. However, Greene’s hypothesis was corroborated: the CRT positively correlated with both the OU parameter and the SU parameter. By contrast, the CRT did not correlate with the other two moral parameters we extracted (altruism and deontology).

Keywords: dual-process model, utilitarianism, altruism, reason, emotion, process dissociation

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Authors: Mohsen Farshad

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Information and force definition has been intertwined with the concept of entropy for many years. The displacement information of degrees of freedom with Brownian motions at a given temperature in space emerges as an entropic force between species. Here, we use this concept of entropy to understand the underlying physics behind the formation of attractive and repulsive forces by imagining that space is filled with free Brownian degrees of freedom. We incorporate the radius of bodies and the distance between them into entropic force relation systematically. Using this modified gravitational entropic force, we derive the attractive entropic force between bodies without considering their spin. We further hypothesize a possible mechanism for the formation of the repulsive force between two bodies. We visually elaborate that the repulsive entropic force will be manifested through the rotation of degrees of freedom around the spinning particles.

Keywords: entropy, information, force, Brownian Motions

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Authors: Roaa Sait, Richard Cross

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The synthesis and characterization of one dimensional nanostructure such as nanowires has received considerable attention. Much effort has concentrated on TiN material especially in the biological field due to its useful and unique properties in this field. Therefore, for the purpose of this project, synthesis of Titanium Nitride (TiN) nanowires (NWs) will be presented. They will be synthesised by growing titanium dioxide (Ti) NWs in an aqueous solution at low temperatures under atmospheric pressure. Then the grown nanowires will undergo a 'Nitrodation process' in which results in the formation of TiN NWs. The structure, morphology and composition of the grown nanowires will be characterized using Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD) and Cyclic Voltammetry (CV). Obtaining TiN NWs is a challenging task since it has not been formulated before, as far as we acknowledge. This might be due to the fact that nitriding Ti NWs can be difficult in terms of optimizing experimental parameters.

Keywords: nanowires, dissolution-growth, nucleation, PECVD, deposition, spin coating, scanning electron microscopic analysis, cyclic voltammetry analysis

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Authors: Fuchun Li, Hong Xiao

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We propose a new early warning model for predicting financial stress events for a given future time. In this model, we examine whether credit conditions play an important role as a nonlinear propagator of shocks when predicting the likelihood of occurrence of financial stress events for a given future time. This propagation takes the form of a threshold regression in which a regime change occurs if credit conditions cross a critical threshold. Given the new early warning model for financial stress events, we evaluate the performance of this model and currently available alternatives, such as the model from signal extraction approach, and linear regression model. In-sample forecasting results indicate that the three types of models are useful tools for predicting financial stress events while none of them outperforms others across all criteria considered. The out-of-sample forecasting results suggest that the credit-regime switching model performs better than the two others across all criteria and all forecasting horizons considered.

Keywords: cut-off probability, early warning model, financial crisis, financial stress, regime-switching model, forecasting horizons

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Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Martin Búda

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The paper deals with possibilities of increase train capacity by using a new type of railway wagon. In the first part is created a mathematical model to calculate the capacity of the train. The model is based on the main limiting parameters of the train - maximum number of axles per train, the maximum gross weight of the train, the maximum length of train and number of TEUs per one wagon. In the second part is the model applied to four different model trains with different composition of the train set and three different average weights of TEU and a train consisting of a new type of wagons. The result is to identify where the carrying capacity of the original trains is higher, respectively less than a capacity of the train consisting of a new type of wagons.

Keywords: loading units, theoretical capacity model, train capacity, wagon for intermodal transport

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Authors: Anna Dabrowska

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Taking Daniel Goleman’s (1994) belief that success in life depends on IQ in 20% and in 80% on emotional intelligence, and that it is worth considering emotional intelligence as an important factor in human performance and development potential, the aim of the paper is to explore the range of emotions experienced by university students who represent Society 5.0. This quantitative and qualitative study is meant to explore not only the list of the most and least experienced emotions by the students, but also the main reasons behind these feelings. The database of the study consists of 115 respondents out of 129 students of the 1st and 5th year of Applied Linguistics at Maria Curie-Skłodowska University, which constitutes 89% of those being surveyed. The data is extracted from the anonymous questionnaire, which comprises young people’s answers and discourse concerning the causes of their most experienced emotions. Following Robert Plutchik’s theory of eight primary emotions, i.e. anger, fear, sadness, disgust, surprise, anticipation, trust, and joy, we adopt his argument for the primacy of these emotions by showing each to be the trigger of behaviour with high survival value. In fact, all other emotions are mixed or derivative states; that is, they occur as combinations, mixtures, or compounds of the primary emotions. Accordingly, the eight primary emotions, and their mixed states, are checked in the study on the students.

Keywords: emotions, intelligence, students, discourse study, emotional intelligence

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Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,

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This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.

Keywords: model based design (MBD), MATLAB, Simulink, stateflow, plant model, real time model, real-time workshop (RTW), target language compiler (TLC)

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Authors: Mohd Asrul Affendi Bi Abdullah, Nyi Nyi Naing

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The purpose of this study was to identify comparable manner between negative binomial death rate (NBDR) and zero inflated negative binomial death rate (ZINBDR) with died patients with (HIV + T B+) and (HIV + T B−). HIV and TB is a serious world wide problem in the developing country. Data were analyzed with applying NBDR and ZINBDR to make comparison which a favorable model is better to used. The ZINBDR model is able to account for the disproportionately large number of zero within the data and is shown to be a consistently better fit than the NBDR model. Hence, as a results ZINBDR model is a superior fit to the data than the NBDR model and provides additional information regarding the died mechanisms HIV+TB. The ZINBDR model is shown to be a use tool for analysis death rate according age categorical.

Keywords: zero inflated negative binomial death rate, HIV and TB, AIC and BIC, death rate

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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: Elizabeth Valenti

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Objective: To date, there remains an absence of literature examining perceptions of mindfulness and mindful practices among college students, particularly among Christian students. The purpose of this mixed-methods, exploratory study was to gain a better understanding of students’ perception of mindfulness and assess current mindful practices. Methods: The mixed-methods, exploratory study examined data from freshmen undergraduate college students (N=107) enrolled in an introductory psychology course at a private, non-profit Christian university. Students completed a researcher-developed questionnaire containing both Likert and opened ended questions to assess knowledge about and perceptions of mindfulness, as well as current mindful practices. Results: Results of the thematic analysis revealed approximately half of the students had a limited understanding of mindfulness, with several reporting disadvantages. Most students listed prayer as a consistent practice, with a much smaller percentage of students consistently engaging in other mindful activities. Discussion: Implications for mindfulness education and the promotion of evidence-based methods, particularly in Christian communities, are discussed.

Keywords: mindfulness, mindful practices, perception, Christian, university students, mental health

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Authors: Shiwei Deng, Yang Bao

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In this paper, we present a model-based regression test suite reducing approach that uses EFSM model dependence analysis and probability-driven greedy algorithm to reduce software regression test suites. The approach automatically identifies the difference between the original model and the modified model as a set of elementary model modifications. The EFSM dependence analysis is performed for each elementary modification to reduce the regression test suite, and then the probability-driven greedy algorithm is adopted to select the minimum set of test cases from the reduced regression test suite that cover all interaction patterns. Our initial experience shows that the approach may significantly reduce the size of regression test suites.

Keywords: dependence analysis, EFSM model, greedy algorithm, regression test

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Authors: Mashael AlSalem

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While research into language assessment has expanded in recent years, few if any studies to date have targeted the nature of thought processes used by teachers when constructing classroom-based assessment. This study reports on teachers’ conceptions of English grammar assessment and their classroom assessment practices in their Saudi higher educational facilities. A mixed-method approach using both qualitative and quantitative research instruments was employed to elicit teachers’ perceptions of English grammar assessment and their relationship to their current practices. Participants of the study included EFL teachers from 4 different educational facilities: King Saudi University, Princess Noura University, Imam Mouhamed Islamic University, and Institute of Public Administration. Data collection involved questionnaire (N=100), semi-structured interviews (N=30), retrospective thinking (N=20), and document analysis (N=20). Activity theory is used as an interpretive framework to explore and investigate the entire system of constructing classroom-based assessment. Preliminary findings reveal several similarities and differences between the participants’ stated beliefs and their current practices of assessing English grammar. Findings also showed that teacher participant’s beliefs about how English grammar should be assessed are influenced mostly by prior learning experience as well as their teaching instruction practices. Their practices, on the other hand, was more guided by educational policies and lack of teacher training in the field of assessment, among other factors. This research makes a significant contribution to knowledge in three different areas: it enriches the literature on language teacher cognition; it builds on the body of research on language classroom assessment, and it expands on the possibilities to use AC to investigate the relationship between teachers’ beliefs and practices.

Keywords: activity theory, classroom-based assessment, language teacher cognition, mixed method approach

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Authors: Abhishek Kumar, Nilam

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As we know that, time delay exists almost in every biological phenomenon. Therefore, in the present study, we propose a susceptible–infected–recovered (SIR) epidemic model along with time delay, modulated incidence rate of infection, and Holling Type II nonlinear treatment rate. The present model aims to provide a strategy to control the spread of epidemics. In the mathematical study of the model, it has been shown that the model has two equilibriums which are named as disease-free equilibrium (DFE) and endemic equilibrium (EE). Further, stability analysis of the model is discussed. To prove the stability of the model at DFE, we derived basic reproduction number, denoted by (R₀). With the help of basic reproduction number (R₀), we showed that the model is locally asymptotically stable at DFE when the basic reproduction number (R₀) less than unity and unstable when the basic reproduction number (R₀) is greater than unity. Furthermore, stability analysis of the model at endemic equilibrium has also been discussed. Finally, numerical simulations have been done using MATLAB 2012b to exemplify the theoretical results.

Keywords: time delayed SIR epidemic model, modulated incidence rate, Holling type II nonlinear treatment rate, stability

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Authors: Mehrdad Shahrbanozadeh, Gholam Abbas Barani, Saeed Shojaee

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In this study, a finite element (Seep3D model) and an artificial neural network (ANN) model were developed to simulate flow through dam foundation. Seep3D model is capable of simulating three-dimensional flow through a heterogeneous and anisotropic, saturated and unsaturated porous media. Flow through the Shahid Abbaspour dam foundation has been used as a case study. The FEM with 24960 triangular elements and 28707 nodes applied to model flow through foundation of this dam. The FEM being made denser in the neighborhood of the curtain screen. The ANN model developed for Shahid Abbaspour dam is a feedforward four layer network employing the sigmoid function as an activator and the back-propagation algorithm for the network learning. The water level elevations of the upstream and downstream of the dam have been used as input variables and the piezometric heads as the target outputs in the ANN model. The two models are calibrated and verified using the Shahid Abbaspour’s dam piezometric data. Results of the models were compared with those measured by the piezometers which are in good agreement. The model results also revealed that the ANN model performed as good as and in some cases better than the FEM.

Keywords: seepage, dam foundation, finite element method, neural network, seep 3D model

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Authors: Hanna Gulema, Meaza Demissie, Alemayehu Worku, Tesfaye Assebe Yadeta, Yemane Berhane

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Background: In patriarchal societies, female caregivers decide on food allocation within a family based on prevailing gender and age norms, which may lead to inequality that does not favor young adolescent girls. This study evaluated the effect of a community-based social norm intervention involving female caregivers in West Hararghe, Ethiopia. The intervention was engaging female caregivers along with other adult influential community members to deliberate and act on food allocation social norms in a process referred to as Social Analysis and Action (SAA). Method: We used data from a large quasi-experimental study to compare family eating practices between those who participated in the Social Analyses and Action intervention and those who did not. The respondents were female caregivers in households with young adolescent girls (ages 13 and 14 years). The study’s outcome was the practice of family eating together from the same dish. The difference in difference (DID) analysis with the Mixed effect logistic regression model was used to examine the effect of the intervention. Result: The results showed improved family eating practices in both groups, but the improvement was greater in the intervention group. The DID analysis showed an 11.99 percentage points greater improvement in the intervention arm than in the control arm. The mixed-effect regression produced an adjusted odds ratio of 2.08 (95% CI [1.06–4.09]) after controlling selected covariates, p-value 0.033. Conclusions: The involvement of influential adult community members significantly improves the family practice of eating together in households where adolescent girls are present in our study. The intervention has great potential to minimize household food allocation inequalities and thus improve the nutritional status of young adolescents. Further studies are necessary to evaluate the effectiveness of the intervention in different social norm contexts to formulate policy and guidelines for scale-up.

Keywords: family eating practice, social norm intervention, adolescence girls, caregiver

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Authors: D. Mohammadzadeh S., J. Bolouri Bazaz

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This paper presents a new prediction model for compression index of fine-grained soils using multi-gene genetic programming (MGGP) technique. The proposed model relates the soil compression index to its liquid limit, plastic limit and void ratio. Several laboratory test results for fine-grained were used to develop the models. Various criteria were considered to check the validity of the model. The parametric and sensitivity analyses were performed and discussed. The MGGP method was found to be very effective for predicting the soil compression index. A comparative study was further performed to prove the superiority of the MGGP model to the existing soft computing and traditional empirical equations.

Keywords: new prediction model, compression index soil, multi-gene genetic programming, MGGP

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Authors: Elena V. Syurina, Sophie Renckens, Martina Valente

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Objective: The objective of this study was to investigate the nature of the conversation around orthorexia nervosa (ON) on Instagram. Methods: The present study was conducted using mixed methods, combining a concurrent triangulation and sequential explanatory design. First, 3027 pictures posted on Instagram using #Orthorexia were analyzed. Then, a questionnaire about Instagram use related to ON was completed entirely by 185 respondents. These two quantitative data sources were statistically analyzed and triangulated afterwards. Finally, 9 interviews were conducted, to more deeply investigate what is being said about ON on Instagram and what the motivations to post about it are. Results: Four main categories of pictures were found to be represented in Instagram posts about ON: ‘food’, ‘people’, ‘text’, and ‘other.’ Savory and unprocessed food was most highly represented within the food category, and pictures of people were mostly pictures of the account holder. People who self-identify as having ON were more likely to post about ON, and they were significantly more likely to post about ‘food’, ‘people’ and ‘text.’ The goal of the posts was to raise awareness around ON, as well as to provide support for people who believe to be suffering from it. Conclusion: Since the conversation around ON on Instagram is supportive, it could be beneficial to consider Instagram use in the treatment of ON. However, more research is needed on a larger scale.

Keywords: orthorexia nervosa, Instagram, social media, disordered eating

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Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

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Authors: Gang Liu, Can Wang, Runnan Zhang, Quan Wang, Huimin Song, Shaomin Ji

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Biba model can protect information integrity but might deny various non-malicious access requests of the subjects, thereby decreasing the availability in the system. Therefore, a mechanism that allows exceptional access control is needed. Break the Glass (BTG) strategies refer an efficient means for extending the access rights of users in exceptional cases. These strategies help to prevent a system from stagnation. An approach is presented in this work for integrating Break the Glass strategies into the Biba model. This research proposes a model, BTG-Biba, which provides both an original Biba model used in normal situations and a mechanism used in emergency situations. The proposed model is context aware, can implement a fine-grained type of access control and primarily solves cross-domain access problems. Finally, the flexibility and availability improvement with the use of the proposed model is illustrated.

Keywords: Biba model, break the glass, context, cross-domain, fine-grained

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Authors: Ferhat Demir

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Even if strategic management is highly critical for all types of organizations, only a few maturity models have been proposed in business literature for the area of strategic management activities. This paper updates previous studies and presents a new conceptual model for assessing the maturity of strategic management in any organization. Strategic management maturity model (S-3M) is basically composed of 6 maturity levels with 7 dimensions. The biggest contribution of S-3M is to put innovation into agenda of strategic management. The main objective of this study is to propose a model to align innovation with business strategies. This paper suggests that innovation (breakthrough new products/services and business models) is the only way of creating sustainable growth and strategy studies cannot ignore this aspect. Maturity models should embrace innovation to respond dynamic business environment and rapidly changing customer behaviours.

Keywords: strategic management, innovation, business model, maturity model

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Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

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Authors: A.Zitouni, S.Bentata, B.Bouadjemi, T.Lantri, W. Benstaali, Z.Aziz, S.Cherid, A. Sefir

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Using the first-principles method, we investigate the structural, electronic, and magnetic properties of the diluted magnetic semiconductors CdCoTe and CdMnTe in the zinc blende phase with 12.5% of Cr. The calculations are performed by a developed full potential augmented plane wave (FP-L/APW) method within the spin density functional theory (DFT). As exchange–correlation potential, we used the new generalized gradient approximation GGA. Structural properties are determined from the total energy calculations and we found that these compounds are stable in the ferromagnetic phase. We discuss the electronic structures, total and partial densities of states and local moments. Finally, CdCoTe and CdMnTe in the zinc-blend phase show the half-metallic ferromagnetic nature and are expected to be potential materials for spintronic devices.

Keywords: DFT, GGA, band structures, half-metallic, spintronics

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Authors: Dereje Ferede, Solomon Negash

Abstract:

Artificial Intelligence (AI) is a key enabler and driver to transform and revolutionize the healthcare industries. However, utilizing AI and achieving these benefits is challenging for different sectors in wide-ranging, more difficult for developing economy healthcare. Due to this, real-world clinical execution and implementation of AI have not yet aged. We believe that examining the determinants is key to addressing these challenges. Furthermore, the literature does not yet particularize determinants of AI capabilities and ways of empowering the healthcare ecosystem to develop AI capabilities in a developing economy. Thus, this study aims to position AI as a digital transformation weapon for the healthcare ecosystem by examining AI capability determinants and providing insights on better empowering the healthcare industry to develop AI capabilities. To do so, we base on the technology-organization-environment (TOE) model and will apply a mixed research approach. We will conclude with recommendations based on findings for future practitioners and researchers.

Keywords: artificial intelligence, capability, digital transformation, developing economies, healthcare

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Authors: Athmane Bakhta, Sebastien Leclaire, David Vidal, Francois Bertrand, Mohamed Cheriet

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This work presents a new three-dimensional variational model proposed for the simulation of ink seepage into paper sheets at the fiber level. The model, inspired by the Hising model, takes into account a finite volume of ink and describes the system state through gravity, cohesion, and adhesion force interactions. At the mesoscopic scale, the paper substrate is modeled using a discretized fiber structure generated using a numerical deposition procedure. A modified Monte Carlo method is introduced for the simulation of the ink dynamics. Besides, a multiphase lattice Boltzmann method is suggested to fine-tune the mesoscopic variational model parameters, and it is shown that the ink seepage behaviors predicted by the proposed model can resemble those predicted by a method relying on first principles.

Keywords: fibrous media, lattice Boltzmann, modelling and simulation, Monte Carlo, variational model

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Authors: Suparman

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Piecewise polynomial regression model is very flexible model for modeling the data. If the piecewise polynomial regression model is matched against the data, its parameters are not generally known. This paper studies the parameter estimation problem of piecewise polynomial regression model. The method which is used to estimate the parameters of the piecewise polynomial regression model is Bayesian method. Unfortunately, the Bayes estimator cannot be found analytically. Reversible jump MCMC algorithm is proposed to solve this problem. Reversible jump MCMC algorithm generates the Markov chain that converges to the limit distribution of the posterior distribution of piecewise polynomial regression model parameter. The resulting Markov chain is used to calculate the Bayes estimator for the parameters of piecewise polynomial regression model.

Keywords: piecewise regression, bayesian, reversible jump MCMC, segmentation

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Authors: Luqman Shah

Abstract:

The myopic gender discrimination is now a well-documented and recognized fact. However, gender is only one facet of an individual’s multiple identities. The aim of this work is to investigate gender discrimination highlighted in print media in the subcontinent with a specific focus on Pakistan and India. In this study, an approach is adopted by using the James Paul Gee model for the identification of gender discrimination. As a matter of fact, gender discrimination is not consistent in its nature and intensity across global societies and varies as social, geographical, and cultural background change. The World has been changed enormously in every aspect of life, and there are also obvious changes towards gender discrimination, prejudices, and biases, but still, the world has a long way to go to recognize women as equal as men in every sphere of life. The history of the world is full of gender-based incidents and violence. Now the time came that this issue must be seriously addressed and to eradicate this evil, which will lead to harmonize society and consequently heading towards peace and prosperity. The study was carried out by a mixed model research method. The data was extracted from the contents of five Pakistani English newspapers out of a total of 23 daily English newspapers, and likewise, five Indian daily English newspapers out of 52 those were published 2018-2019. Two news stories from each of these newspapers, in total, twenty news stories were taken as sampling for this research. Content and semiotic analysis techniques were used to analyze through James Paul Gee's seven building tasks of language. The resources of renowned e-papers are utilized, and the highlighted cases in Pakistani newspapers of Indian gender-based stories and vice versa are scrutinized as per the requirement of this research paper. For analysis of the written stretches of discourse taken from e-papers and processing of data for the focused problem, James Paul Gee 'Seven Building Tasks of Language' is used. Tabulation of findings is carried to pinpoint the issue with certainty. Findings after processing the data showed that there is a gross human rights violation on the basis of gender discrimination. The print media needs a more realistic representation of what is what not what seems to be. The study recommends the equality and parity of genders.

Keywords: gender discrimination, print media, Paul Gee model, subcontinent

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Authors: Batuhan Kocaoglu

Abstract:

Although using powerful systems like ERP (Enterprise Resource Planning), companies still cannot benchmark their processes and measure their process performance easily based on predefined SCOR (Supply Chain Operation References) terms. The purpose of this research is to identify common and corresponding processes to present a conceptual model to model and measure the purchasing process of an organization. The main steps for the research study are: Literature review related to 'procure to pay' process in ERP system; Literature review related to 'sourcing' process in SCOR model; To develop a conceptual model integrating 'sourcing' of SCOR model and 'procure to pay' of ERP model. In this study, we examined the similarities and differences between these two models. The proposed framework is based on the assumptions that are drawn from (1) the body of literature, (2) the authors’ experience by working in the field of enterprise and logistics information systems. The modeling framework provides a structured and systematic way to model and decompose necessary information from conceptual representation to process element specification. This conceptual model will help the organizations to make quality purchasing system measurement instruments and tools. And offered adaptation issues for ERP systems and SCOR model will provide a more benchmarkable and worldwide standard business process.

Keywords: SCOR, ERP, procure to pay, sourcing, reference model

Procedia PDF Downloads 356