Search results for: Huff's Gravity Model

Authors: Jenny Oliveros Lao Phillips, Arturo E. Osorio, José Alves

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Family business are the dominant form of business in the world, and Chinese family business (CFB) is a unique type of family business that relies on collective action to survive. This paper argues that in CFBs, entrepreneurial actions are transgenerational collective endeavors, and successors are groomed as stewards of the family legacy. Work-life relationship in CFBs is about synergy and not balance because the family identity is the business identity, and vice-versa. Using five in-depth case studies, this research introduces an alternative understanding of CFBs and proposes a model of work-life synergy in transgenerational entrepreneurship based on discussion of five theory-based propositions. This model explains that through emphasizing on the business family’s shared value and entrepreneurial legacy, elements of trust, shared identity and stewardship of family members are enhanced which leads to collective action and goal of the business family, resulting in transgenerational entrepreneurship. Limitations and future research are presented.

Keywords: Chinese family business, family legacy, stewardship, transgenerational entrepreneurship, work-life synergy

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Authors: Ahmed M. Ashteyat

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Artificial Neural Network (ANN) models have been widely used in material modeling, inter-correlations, as well as behavior and trend predictions when the nonlinear relationship between system parameters cannot be quantified explicitly and mathematically. In this paper, ANN was used to predict the residual modulus of elasticity (RME) of self compacted concrete (SCC) damaged by heat. The ANN model was built, trained, tested and validated using a total of 112 experimental data sets, gathered from available literature. The data used in model development included temperature, relative humidity conditions, mix proportions, filler types, and fiber type. The result of ANN training, testing, and validation indicated that the RME of SCC, exposed to different temperature and relative humidity levels, could be predicted accurately with ANN techniques. The reliability between the predicated outputs and the actual experimental data was 99%. This show that ANN has strong potential as a feasible tool for predicting residual elastic modulus of SCC damaged by heat within the range of input parameter. The ANN model could be used to estimate the RME of SCC, as a rapid inexpensive substitute for the much more complicated and time consuming direct measurement of the RME of SCC.

Keywords: residual modulus of elasticity, artificial neural networks, self compacted-concrete, material modeling

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Authors: İsmail Ay

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In this study, it was aimed to determine the relations between need for psychological help and psychological symptoms. The sample of the study consists of 530 university students getting educated in University of Atatürk in 2015-2016 academic years. Need for Psychological Help Scale and Brief Symptom Inventory were used to collect data in the study. In data analysis, correlation analysis and structural equation model with latent variables were used. Normality and homogeneity analyses were used to analyze the basic conditions of parametric tests. The findings obtained from the study show that as the psychological symptoms increase, need for psychological help also increases. The findings obtained through the study were approached according to the literature.

Keywords: psychological symptoms, need for psychological help, structural equation model, correlation

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: Bouabdellah Abed, Mohamed Bouzit, Lakhdar Bouarbi

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The objective of this study is to investigate numerically the effect of roof shaped on wind flow and pollutant dispersion in a street canyon with one row of trees of pore volume, Pvol = 96%. A three-dimensional computational fluid dynamics (CFD) model for evaluating air flow and pollutant dispersion within an urban street canyon using Reynolds-averaged Navier–Stokes (RANS) equations and the k-Epsilon EARSM turbulence model as close of the equation system. The numerical model is performed with ANSYS-CFX code. Vehicle emissions were simulated as double line sources along the street. The numerical model was validated against the wind tunnel experiment. Having established this, the wind flow and pollutant dispersion in urban street canyons of six roof shapes are simulated. The numerical simulation agrees reasonably with the wind tunnel data. The results obtained in this work, indicate that the flow in 3D domain is more complicated, this complexity is increased with presence of tree and variability of the roof shapes. The results also indicated that the largest pollutant concentration level for two walls (leeward and windward wall) is observed with the upwind wedge-shaped roof. But the smallest pollutant concentration level is observed with the dome roof-shaped. The results also indicated that the corners eddies provide additional ventilation and lead to lower traffic pollutant concentrations at the street canyon ends.

Keywords: street canyon, pollutant dispersion, trees, building configuration, numerical simulation, k-Epsilon EARSM

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Authors: S. Curtin, A. Trace

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Introduction: As patients can often be ambivalent about or resistant to any change in their smoking behavior the traditional ‘5 A’ model may be limited as it assumes that patients are ready and motivated to change. However, there is a stage model that is helpful to give guidance for dental students: the Transtheoretical Model (TTM). This model allows students to understand the tasks and goals for the pre-contemplation stage. The TTM was introduced in early stages as a core component of a smoking cessation programme that was integrated into a Behavioral Science programme as applied to dentistry. The aim of the present study is to evaluate and illustrate the students’ current level of knowledge from the questions the students generated in order to engage patients in the tasks and goals of the pre-contemplation stage. Method: N=47 responses of fifth-year undergraduate dental students. These responses were the data set for this study and related to their knowledge base of appropriate questions for a dentist to ask at the pre-contemplation stage of change. A deductive -descriptive analysis was conducted on the data. The goals and tasks of the pre-contemplation stage of the TTM provided a template for this deductive analysis. Results: 51% of students generated relevant, open, exploratory questions for the pre-contemplation stage, whilst 100% of students generated closed questions. With regard to those questions appropriate for the pre-contemplation stage, 19% were open and exploratory, while 66% were closed questions. A deductive analysis of the open exploratory questions revealed that 53% of the questions addressed increased concern about the current pattern of behavior, 38% of the questions concerned increased awareness of a need for change and only 8% of the questions dealt with the envisioning of the possibility of change. Conclusion: All students formulated relevant questions for the pre-contemplation stage, and half of the students generated the open, exploratory questions that increased patients’ awareness of the need to change. More training is required to facilitate a shift in the formulation from closed to open questioning, especially given that, traditionally, smoking cessation was modeled on the ‘5 As’, and that the general training for dentists supports an advisory and directive approach.

Keywords: behaviour change, pre-contemplation stage, trans-theoretical model, undergraduate dentistry students

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Authors: Ubaidillah Zuhdi, Shunsuke Mori, Kazuhisa Kamegai

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The purpose of this study is to forecast the influences of Information and Communication Technology (ICT) on the structural changes of Japanese economies based on Leontief Input-Output (IO) coefficients. This study establishes a statistical analysis to predict the future interrelationships among industries. We employ the Constrained Multivariate Regression (CMR) model to analyze the historical changes of input-output coefficients. Statistical significance of the model is then tested by Likelihood Ratio Test (LRT). In our model, ICT is represented by two explanatory variables, i.e. computers (including main parts and accessories) and telecommunications equipment. A previous study, which analyzed the influences of these variables on the structural changes of Japanese industrial sectors from 1985-2005, concluded that these variables had significant influences on the changes in the business circumstances of Japanese commerce, business services and office supplies, and personal services sectors. The projected future Japanese economic structure based on the above forecast generates the differentiated direct and indirect outcomes of ICT penetration.

Keywords: forecast, ICT, industrial structural changes, statistical analysis

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Authors: M. Bartal

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A large empirical evidence points to sizable lifetime earnings losses associated with the displacement of tenured workers. The causes of these losses are still not well-understood. Existing explanations are heavily based on human capital depreciation during non-employment spells. In this paper, a new avenue is explored. Evidence on the role of household liquidity constraints in accounting for the persistence of post-displacement earning losses is provided based on SIPP data. Then, a directed search and matching model with endogenous human capital and wealth accumulation is introduced. The model is computationally tractable thanks to its block-recursive structure and highlights a non-trivial, yet intuitive, interaction between wealth and human capital. Constrained workers tend to accept jobs with low firm-sponsored training because the latter are (endogenously) easier to find. This new channel provides a plausible explanation for why young (highly constrained) workers suffer persistent scars after displacement. Finally, the model is calibrated on US data to show that the interplay between wealth and human capital is crucial to replicate the observed lifecycle pattern of earning losses. JEL— E21, E24, J24, J63.

Keywords: directed search, human capital accumulation, job displacement, wealth accumulation

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Authors: Abdelkader Hachemi & Boualem Remini

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Seawater intrusion is a significant challenge faced by coastal aquifers in the Mediterranean basin. This study aims to determine the position of the sharp interface between seawater and freshwater in the aquifer of Wadi Nador, located in the Wilaya of Tipaza, Algeria. A numerical areal sharp interface model using the finite element method is developed to investigate the spatial and temporal behavior of seawater intrusion. The aquifer is assumed to be homogeneous and isotropic. The simulation results are compared with geophysical prospection data obtained through electrical methods in 2011 to validate the model. The simulation results demonstrate a good agreement with the geophysical prospection data, confirming the accuracy of the sharp interface model. The position of the sharp interface in the aquifer is found to be approximately 1617 meters from the sea. Two scenarios are proposed to predict the interface position for the year 2024: one without pumping and the other with pumping. The results indicate a noticeable retreat of the sharp interface position in the first scenario, while a slight decline is observed in the second scenario. The findings of this study provide valuable insights into the dynamics of seawater intrusion in the Wadi Nador aquifer. The predicted changes in the sharp interface position highlight the potential impact of pumping activities on the aquifer's vulnerability to seawater intrusion. This study emphasizes the importance of implementing measures to manage and mitigate seawater intrusion in coastal aquifers. The sharp interface model developed in this research can serve as a valuable tool for assessing and monitoring the vulnerability of aquifers to seawater intrusion.

Keywords: seawater, intrusion, sharp interface, Algeria

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Authors: Moustafa Osman Mohammed

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This paper will explore formation of HCl aerosol at atmospheric boundary layers and encourages the uptake of environmental modeling systems (EMSs) as a practice evaluation of gaseous emissions (“framework measures”) from small and medium-sized enterprises (SMEs). The conceptual model predicts greenhouse gas emissions to ecological points beyond landfill site operations. It focuses on incorporation traditional knowledge into baseline information for both measurement data and the mathematical results, regarding parameters influence model variable inputs. The paper has simplified parameters of aerosol processes based on the more complex aerosol process computations. The simple model can be implemented to both Gaussian and Eulerian rural dispersion models. Aerosol processes considered in this study were (i) the coagulation of particles, (ii) the condensation and evaporation of organic vapors, and (iii) dry deposition. The chemical transformation of gas-phase compounds is taken into account photochemical formulation with exposure effects according to HCl concentrations as starting point of risk assessment. The discussion set out distinctly aspect of sustainability in reflection inputs, outputs, and modes of impact on the environment. Thereby, models incorporate abiotic and biotic species to broaden the scope of integration for both quantification impact and assessment risks. The later environmental obligations suggest either a recommendation or a decision of what is a legislative should be achieved for mitigation measures of landfill gas (LFG) ultimately.

Keywords: air pollution, landfill emission, environmental management, monitoring/methods and impact assessment

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Authors: Ali Maksum

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In a number of countries, including Indonesia, the tendency for non-communicable diseases is increasing. As a result, health costs must be paid by the state continues to increase as well. People's lifestyles, including due to lack of physical activity, are thought to have contributed significantly to the problem. This study aims to examine the impact of participation in sports on quality of life, which is reflected in three main indicators, namely health, psychological, and social aspects. The study was conducted in the city of Surabaya and its surroundings, with a total of 490 participants, consisting of 245 men and 245 women with an average age of 45.4 years. Data on physical activity and quality of life were collected by questionnaire and analyzed using structural equation modeling. The test results of the model prove that the value of chi-square = 8,259 with p = .409, RMSEA = .008, NFI = .992, and CFI = 1. This means that the model is compatible with the data. The model explains that physical activity has a significant effect on quality of life. People who exercise regularly are better able to cope with stress, have a lower risk of illness, and have higher pro-social behavior. Therefore, it needs serious efforts from stakeholders, especially the government, to create an ecosystem that allows the growth of movement culture in the community.

Keywords: participation, physical activity, quality of life, structural equation modelling

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Authors: Muhammed Ordu, Eren Demir, Chris Tofallis

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Over the past decade, the non-elective admissions in the UK have increased significantly. Taking into account limited resources (i.e. beds), the related service managers are obliged to manage their resources effectively due to the non-elective admissions which are mostly admitted to inpatient specialities via A&E departments. Geriatric medicine is one of specialities that have long length of stay for the non-elective admissions. This study aims to develop a discrete event simulation model to understand how possible increases on non-elective demand over the next 12 months affect the bed occupancy rate and to determine required number of beds in a geriatric medicine speciality in a UK hospital. In our validated simulation model, we take into account observed frequency distributions which are derived from a big data covering the period April, 2009 to January, 2013, for the non-elective admission and the length of stay. An experimental analysis, which consists of 16 experiments, is carried out to better understand possible effects of case studies and scenarios related to increase on demand and number of bed. As a result, the speciality does not achieve the target level in the base model although the bed occupancy rate decreases from 125.94% to 96.41% by increasing the number of beds by 30%. In addition, the number of required beds is more than the number of beds considered in the scenario analysis in order to meet the bed requirement. This paper sheds light on bed management for service managers in geriatric medicine specialities.

Keywords: bed management, bed occupancy rate, discrete event simulation, geriatric medicine, non-elective admission

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Authors: Madaki Umar Yusuf, Mohd Rizam B. Abubakar

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The survival censored data with incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With model when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights. The survival outcome for the class of generalized linear model is applied and this method requires the estimation of the parameters of the distribution of the covariates. In this paper, we propose some clinical trials with ve covariates, four of which have some missing values which clearly show that they were fully censored data.

Keywords: EM algorithm, incomplete categorical covariates, ignorable missing data, missing at random (MAR), Weibull Distribution

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Authors: Sergey A. Lurie, Yury O. Solyaev, Dmitry B. Volkov-Bogorodsky, Alexander V. Volkov

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The media with voids is considered and the method of the analytical estimation of the effective mechanical properties in the theory of elastic materials with voids is proposed. The variational model of the porous media is discussed, which is based on the model of the media with fields of conserved dislocations. It is shown that this model is fully consistent with the known model of the linear elastic materials with voids. In the present work, the generalized model of the porous media is proposed in which the specific surface properties are associated with the field of defects-pores in the volume of the deformed body. Unlike typical surface elasticity model, the strain energy density of the considered model includes the special part of the surface energy with the quadratic form of the free distortion tensor. In the result, the non-classical boundary conditions take modified form of the balance equations of volume and surface stresses. The analytical approach is proposed in the present work which allows to receive the simple enough engineering estimations for effective characteristics of the media with free dilatation. In particular, the effective flexural modulus and Poisson's ratio are determined for the problem of a beam pure bending. Here, the known voids elasticity solution was expanded on the generalized model with the surface effects. Received results allow us to compare the deformed state of the porous beam with the equivalent classic beam to introduce effective bending rigidity. Obtained analytical expressions for the effective properties depend on the thickness of the beam as a parameter. It is shown that the flexural modulus of the porous beam is decreased with an increasing of its thickness and the effective Poisson's ratio of the porous beams can take negative values for the certain values of the model parameters. On the other hand, the effective shear modulus is constant under variation of all values of the non-classical model parameters. Solutions received for a beam pure bending and the hydrostatic loading of the porous media are compared. It is shown that an analytical estimation for the bulk modulus of the porous material under hydrostatic compression gives an asymptotic value for the effective bulk modulus of the porous beam in the case of beam thickness increasing. Additionally, it is shown that the scale effects appear due to the surface properties of the porous media. Obtained results allow us to offer the procedure of an experimental identification of the non-classical parameters in the theory of the linear elastic materials with voids based on the bending tests for samples with different thickness. Finally, the problem of implementation of the Saint-Venant hypothesis for the transverse stresses in the porous beam are discussed. These stresses are different from zero in the solution of the voids elasticity theory, but satisfy the integral equilibrium equations. In this work, the exact value of the introduced surface parameter was found, which provides the vanishing of the transverse stresses on the free surfaces of a beam.

Keywords: effective properties, scale effects, surface defects, voids elasticity

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Authors: Arshia Khan, Hans-Dietrich Haasis

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Different tools of the supply chain should be managed very efficiently in mass customization. In the automobile industry, there are different strategies to manage these tools. We need to investigate which strategies among the different ones are successful and which are not. There is lack in literature regarding such analysis. Keeping this in view, the purpose of this paper is to construct a framework and model which can help to analyze the supply chain of mass customized automobiles quantitatively for future studies. Furthermore, we will also consider that which type of data can be used for the suggested model and where it can be taken from. Such framework can help to bring insight for future analysis.

Keywords: mass customization, supply chain, inventory, distribution, automobile industry

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Authors: Christian Louis Kühner, Florian Pfeffel, Valentin Nickolai

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Taking care of children, dependents, or pets can be a difficult and time-consuming task. Especially for part- and full-time employees, it can feel exhausting and overwhelming to meet these obligations besides working a job. Thus, working mostly at home and not having to drive to the company can save valuable time and stress. This study aims to show the influence that the working model has on the job satisfaction of employees with care responsibilities in comparison to employees who do not have such obligations. Using structural equation modeling (SEM), the three work models, “work from home”, “working remotely”, and a hybrid model, have been analyzed based on 13 influencing constructs on job satisfaction. These 13 factors have been further summarized into three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, an online survey was conducted with n = 684 employees from the service sector. Here, Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. In addition, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that among the employees with care responsibilities, the higher the proportion of working from home in comparison to working from the office, the more satisfied the employees are with their job. Since the work models that meet the requirements of comprehensive care led to higher job satisfaction amongst employees with such obligations, adapting as a company to such private obligations by employees can be crucial to sustained success. Conversely, the satisfaction level of the working model where employees work at the office is higher for workers without caregiving responsibilities.

Keywords: care responsibilities, home office, job satisfaction, structural equation modeling

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Authors: Shayan Mohajer Hamidi

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Federated learning has emerged as a promising approach for distributed model training while preserving data privacy. However, the challenges of communication overhead, limited network resources, and slow convergence hinder its widespread adoption. On the other hand, knowledge distillation has shown great potential in compressing large models into smaller ones without significant loss in performance. In this paper, we propose an innovative framework that combines federated learning and knowledge distillation to address these challenges and enhance the efficiency of distributed learning. Our approach, called Federated Knowledge Distillation (FKD), enables multiple clients in a federated learning setting to collaboratively distill knowledge from a teacher model. By leveraging the collaborative nature of federated learning, FKD aims to improve model compression while maintaining privacy. The proposed framework utilizes a coded teacher model that acts as a reference for distilling knowledge to the client models. To demonstrate the effectiveness of FKD, we conduct extensive experiments on various datasets and models. We compare FKD with baseline federated learning methods and standalone knowledge distillation techniques. The results show that FKD achieves superior model compression, faster convergence, and improved performance compared to traditional federated learning approaches. Furthermore, FKD effectively preserves privacy by ensuring that sensitive data remains on the client devices and only distilled knowledge is shared during the training process. In our experiments, we explore different knowledge transfer methods within the FKD framework, including Fine-Tuning (FT), FitNet, Correlation Congruence (CC), Similarity-Preserving (SP), and Relational Knowledge Distillation (RKD). We analyze the impact of these methods on model compression and convergence speed, shedding light on the trade-offs between size reduction and performance. Moreover, we address the challenges of communication efficiency and network resource utilization in federated learning by leveraging the knowledge distillation process. FKD reduces the amount of data transmitted across the network, minimizing communication overhead and improving resource utilization. This makes FKD particularly suitable for resource-constrained environments such as edge computing and IoT devices. The proposed FKD framework opens up new avenues for collaborative and privacy-preserving distributed learning. By combining the strengths of federated learning and knowledge distillation, it offers an efficient solution for model compression and convergence speed enhancement. Future research can explore further extensions and optimizations of FKD, as well as its applications in domains such as healthcare, finance, and smart cities, where privacy and distributed learning are of paramount importance.

Keywords: federated learning, knowledge distillation, knowledge transfer, deep learning

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Authors: Mohsen Farhadloo, Majid Farhadloo

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Aspect-level opinion mining that aims at discovering aspects (aspect identification) and their corresponding ratings (sentiment identification) from customer reviews have increasingly attracted attention of researchers and practitioners as it provides valuable insights about products/services from customer's points of view. Instead of addressing aspect identification and sentiment identification in two separate steps, it is possible to simultaneously identify both aspects and sentiments. In recent years many graphical models based on Latent Dirichlet Allocation (LDA) have been proposed to solve both aspect and sentiment identifications in a single step. Although LDA models have been effective tools for the statistical analysis of document collections, they also have shortcomings in addressing some unique characteristics of opinion mining. Our goal in this paper is to address one of the limitations of topic models to date; that is, they fail to directly model the associations among topics. Indeed in many text corpora, it is natural to expect that subsets of the latent topics have higher probabilities. We propose a probabilistic graphical model called focus-LDA, to better capture the associations among topics when applied to aspect-level opinion mining. Our experiments on real-life data sets demonstrate the improved effectiveness of the focus-LDA model in terms of the accuracy of the predictive distributions over held out documents. Furthermore, we demonstrate qualitatively that the focus-LDA topic model provides a natural way of visualizing and exploring unstructured collection of textual data.

Keywords: aspect-level opinion mining, document modeling, Latent Dirichlet Allocation, LDA, sentiment analysis

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Authors: Sajed Sarabandi, Mostafa Rostampour Vajari

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Breast cancer is the most frequent form of cancer among women and the fifth-leading cause of cancer-related deaths. A common feature of cancer cells is their ability to survive and evade apoptosis. Understanding the mechanisms of these pathways and their regulatory factors can lead to the development of effective treatment strategies. In this study, we aim to model the effect of key miRNAs, which are significant regulatory factors in breast cancer. We designed a Petri net focusing on two crucial pathways, proliferation, and apoptosis, and identified the role of miRNAs in these pathways. Our analysis indicates that the upregulation of miRNAs 99a and 372 can effectively increase apoptosis and decrease proliferation. Moreover, we demonstrate that miRNA-600, previously reported as a potential candidate for treatment, may not be a suitable target due to its dual activity in proliferation. Therefore, further research is required to investigate the potential of this miRNA in cancer treatment. Our model shows that a combination of miRNA upregulation and knockdown can efficiently influence key genes such as MDM2 and PTEN, leading to the activation of apoptosis in cancer cells. Ultimately, our model successfully simulates the connection between regulatory miRNAs and key genes in breast cancer.

Keywords: breast cancer, microRNAs, bio-modeling, Petri net

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Authors: Roghayyeh Motallebzadeh, Shahin Hajizadeh, Mohammad Reza Ghasemi

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Laminar mixed convection heat transfer of a nanofluid with prescribed constant heat flux on the inner wall of horizontal annular tube has been studied numerically based on two-phase mixture model in different Rayleigh numbers and Azimuth angles. Effects of applying of different volume fractions of Al2O3 nanoparticles in water as a base fluid on hydrodynamic and thermal behaviours of the fluid flow such as axial velocity, secondary flow, temperature, heat transfer coefficient and friction coefficient at the inner and outer wall region, has been investigated. Conservation equations in elliptical form has been utilized and solved in three dimensions for a steady flow. It is observed that, there is a good agreement between results in this work and previously published experimental and numerical works on mixed convection in horizontal annulus. These particles cause to increase convection heat transfer coefficient of the fluid, meanwhile there is no considerable effect on friction coefficient.

Keywords: buoyancy force, laminar mixed convection, mixture model, nano-fluid, two-phase

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Authors: Sandrine Andriantsimietry, Hantanirina Ravaosendrasoa

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Madagascar, in 2018, set up the first best available technology, autoclave, to treat the health care waste in public hospitals according the best environmental practices in health care waste management. Incineration of health care waste, frequently through open burning is the most common practice of treatment and elimination of health care waste across the country. Autoclave is a best available technology for non-incineration of health care waste that permits recycling of treated waste and prevents harm in environment through the reduction of unintended persistent organic pollutants from the health sector. A Global Environment Fund project supported the introduction of the non-incineration treatment of health care waste to help countries in Africa to move towards Stockholm Convention objectives in the health sector. Two teaching hospitals in Antananarivo and one district hospital in Manjakandriana were equipped respectively with 1300L, 250L and 80L autoclaves. The capacity of these model hospitals was strengthened by the donation of equipment and materials and the training of the health workers in best environmental practices in health care waste management. Proper segregation of waste in the wards to collect the infectious waste that was treated in the autoclave was the main step guaranteeing a cost-efficient non-incineration of health care waste. Therefore, the start-up of the switch of incineration into non-incineration treatment was carried out progressively in each ward with close supervision of hygienist. Emissions avoided of unintended persistent organic pollutants during these four months of autoclaves use is 9.4 g Toxic Equivalent per year. Public hospitals in low income countries can be model in best environmental practices in health care waste management but efforts must be made internally for sustainment.

Keywords: autoclave, health care waste management, model hospitals, non-incineration

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Authors: Merouane Salhi, Toufik Zebbiche

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When the stagnation pressure of perfect gas increases, the specific heat and their ratio do not remain constant anymore and start to vary with this pressure. The gas doesn’t remain perfect. Its state equation change and it becomes for a real gas. In this case, the effects of molecular size and intermolecular attraction forces intervene to correct the state equation. The aim of this work is to show and discuss the effect of stagnation pressure on supersonic thermodynamical, physical and geometrical flow parameters, to find a general case for real gas. With the assumptions that Berthelot’s state equation accounts for the molecular size and intermolecular force effects, expressions are developed for analyzing supersonic flow for thermally and calorically imperfect gas lower than the dissociation molecules threshold. The designs parameters for supersonic nozzle like thrust coefficient depend directly on stagnation parameters of the combustion chamber. The application is for air. A computation of error is made in this case to give a limit of perfect gas model compared to real gas model.

Keywords: supersonic flow, real gas model, Berthelot’s state equation, Simpson’s method, condensation function, stagnation pressure

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Authors: Badli Shah Mohd Yusoff, Khairur Rijal Jamaludin, Rozetta Dollah

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The emerging of reverse logistics and product recovery management is an important concept in reconciling economic and environmental objectives through recapturing values of the end of life product returns. End of life products contains valuable modules, parts, residues and materials that can create value if recovered efficiently. The main objective of this study is to explore and develop a model to recover as much of the economic value as reasonably possible to find the optimality of return acquisition and sorting to meet demand and maximize profits over time. In this study, the benefits that can be obtained for remanufacturer is to develop demand forecasting of used products in the future with uncertainty of returns and quality of products. Formulated based on a generic disassembly tree, the proposed model focused on three reverse logistics activity, namely refurbish, remanufacture and disposal incorporating all plausible means quality levels of the returns. While stricter sorting policy, constitute to the decrease amount of products to be refurbished or remanufactured and increases the level of discarded products. Numerical experiments carried out to investigate the characteristics and behaviour of the proposed model with mathematical programming model using Lingo 16.0 for medium-term planning of return acquisition, disassembly (refurbish or remanufacture) and disposal activities. Moreover, the model seeks an analysis a number of decisions relating to trade off management system to maximize revenue from the collection of use products reverse logistics services through refurbish and remanufacture recovery options. The results showed that full utilization in the sorting process leads the system to obtain less quantity from acquisition with minimal overall cost. Further, sensitivity analysis provides a range of possible scenarios to consider in optimizing the overall cost of refurbished and remanufactured products.

Keywords: core acquisition, end of life, reverse logistics, quality uncertainty

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Authors: Rajesh Singh, Kailash Kale

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In this paper, the Binomial process type occurrence of software failures is considered and failure intensity has been characterized by one parameter Rayleigh class Software Reliability Growth Model (SRGM). The proposed SRGM is mathematical function of parameters namely; total number of failures i.e. η-0 and scale parameter i.e. η-1. It is assumed that very little or no information is available about both these parameters and then considering non-informative priors for both these parameters, the Bayes estimators for the parameters η-0 and η-1 have been obtained under square error loss function. The proposed Bayes estimators are compared with their corresponding maximum likelihood estimators on the basis of risk efficiencies obtained by Monte Carlo simulation technique. It is concluded that both the proposed Bayes estimators of total number of failures and scale parameter perform well for proper choice of execution time.

Keywords: binomial process, non-informative prior, maximum likelihood estimator (MLE), rayleigh class, software reliability growth model (SRGM)

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Authors: Paula C. Ferreira, Ana Margarida Veiga Simão, Nádia Pereira, Aristides Ferreira, Alexandra Marques Pinto, Alexandra Barros, Vitor Martinho

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Cyberbullying is a phenomenon of worldwide concern regarding children and adolescents’ mental health and risk behavior. Bystanders of this phenomenon can help diminish the incidence of this phenomenon if they engage in pro-social behavior. However, different social-cognitive and affective bystander reactions may surface because of the lack of contextual information and emotional cues in cyberbullying situations. Hence, this study investigated how cyberbullying bystanders’ unpleasant emotions could be related to their personal moral beliefs and their behavioral intentions to cyberbully or defend the victim. It also proposed to investigate how their normative beliefs of perceived severity about cyberbullying behavior could be related to their personal moral beliefs and their behavioral intentions. Three groups of adolescents participated in this study, namely a first of group 402 students (5th – 12th graders; Mage = 13.12; SD = 2.19; 55.7% girls) to compute explorative factorial analyses of the instruments used; a second group of 676 students (5th – 12th graders; Mage = 14.10; SD = 2.74; 55.5% were boys) to run confirmatory factor analyses; and a third group (N = 397; 5th – 12th graders; Mage = 13.88 years; SD = 1.45; 55.5% girls) to perform the main analyses to test the research hypotheses. Self-report measures were used, such as the Personal moral beliefs about cyberbullying behavior questionnaire, the Normative beliefs of perceived severity about cyberbullying behavior questionnaire, the Unpleasant emotions about cyberbullying incidents questionnaires, and the Bystanders’ behavioral intentions in cyberbullying situations questionnaires. Path analysis results revealed that unpleasant emotions were mediators of the relationship between adolescent cyberbullying bystanders’ personal moral beliefs and their intentions to help the victims in cyberbullying situations. Moreover, adolescent cyberbullying bystanders’ normative beliefs of gravity were mediators of the relationship between their personal moral beliefs and their intentions to cyberbully others. These findings provide insights for the development of prevention and intervention programs that promote social and emotional learning strategies as a means to prevent and intervene in cyberbullying.

Keywords: cyberbullying, normative beliefs of perceived severity, personal moral beliefs, unpleasant emotions

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Authors: Muthana A. M. Jameel Al-Jaboori

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In this paper, we will present a mathematical model to design a system able to generate electricity from ocean-sea waves. We will use the basic principles of the transfer of the energy potential of waves in a chamber to force the air inside a vertical or inclined cylindrical column, which is topped by a wind turbine to rotate the electric generator. The present mathematical model included a high number of variables such as the wave, height, width, length, velocity, and frequency, as well as others for the energy cylindrical column, like varying diameters and heights, and the wave chamber shape diameter and height. While for the wells wind turbine the variables included the number of blades, length, width, and clearance, as well as the rotor and tip radius. Additionally, the turbine rotor and blades must be made from the light and strong material for a smooth blade surface. The variables were too vast and high in number. Then the program was run successfully within the MATLAB and presented very good modeling results.

Keywords: water wave, models, Wells turbine, MATLAB program

Procedia PDF Downloads 363

Authors: Jonathan Heng, Yoong Cheah Huei

Abstract:

A strategic model that does not trigger any false alarms to detect anomalies in Secure Water Treatment (SWaT) test bed is presented. This model uses machine learning invariants formulated from streamlining the general form of Auto-Regressive models with eXogenous input. A creative generalized CUSUM algorithm to integrate the invariants and the detection strategy technique is successfully developed and tested in the SWaT Programmable Logic Controllers (PLCs). Three steps to fine-tune parameters, b and τ in the generalized algorithm are stated and an example used to demonstrate the tuning process is discussed. This approach can swiftly and effectively detect various scopes of cyber-attacks such as multiple points single stage and multiple points multiple stages in SWaT. This technique can be applied in water treatment plants and other cyber physical systems like power and gas plants too.

Keywords: machine learning invariants, generalized CUSUM algorithm with invariants and detection strategy, scope of cyber attacks, strategic model, tuning parameters

Procedia PDF Downloads 181

Authors: Fahad Alsharari, Mohd Salmi Md. Noorani

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A Motzkin shift is a mathematical model for constraints on genetic sequences. In terms of the theory of symbolic dynamics, the Motzkin shift is nonsofic, and therefore, we cannot use the Perron-Frobenius theory to calculate its topological entropy. The Motzkin shift M(M,N) which comes from language theory, is defined to be the shift system over an alphabet A that consists of N negative symbols, N positive symbols and M neutral symbols. For an x in the full shift AZ, x is in M(M,N) if and only if every finite block appearing in x has a non-zero reduced form. Therefore, the constraint for x cannot be bounded in length. K. Inoue has shown that the entropy of the Motzkin shift M(M,N) is log(M + N + 1). In this paper, we find a new method of calculating the topological entropy of the Motzkin shift M(M,N) without any measure theoretical discussion.

Keywords: entropy, Motzkin shift, mathematical model, theory

Procedia PDF Downloads 476

Authors: Rahma Fitriani, Eni Sumarminingsih, Suci Astutik

Abstract:

In a fast growing region, conversion of agricultural lands which are surrounded by some new development sites will occur sooner than expected. This phenomenon has been experienced by many regions in Indonesia, especially the fringe of Jakarta (BoDeTaBek). Being Indonesia’s capital city, rapid conversion of land in this area is an unavoidable process. The land conversion expands spatially into the fringe regions, which were initially dominated by agricultural land or conservation sites. Without proper control or growth management, this activity will invite greater costs than benefits. The current land use is the use which maximizes its value. In order to maintain land for agricultural activity or conservation, some efforts are needed to keep the land value of this activity as high as possible. In this case, the knowledge regarding the functional relationship between land value and its driving forces is necessary. In a fast growing region, development externalities are the assumed dominant driving force. Land value is the product of the past decision of its use leading to its value. It is also affected by the local characteristics and the observed surrounded land use (externalities) from the previous period. The effect of each factor on land value has dynamic and spatial virtues; an empirical spatial dynamic land value model will be more useful to capture them. The model will be useful to test and to estimate the extent of land use externalities on land value in the short run as well as in the long run. It serves as a basis to formulate an effective urban growth management’s policy. This study will apply the model to the case of land value in the fringe of Jakarta Metropolitan. The model will be used further to predict the effect of externalities on land value, in the form of prediction map. For the case of Jakarta’s fringe, there is some evidence about the significance of neighborhood urban activity – negative externalities, the previous land value and local accessibility on land value. The effects are accumulated dynamically over years, but they will fully affect the land value after six years.

Keywords: growth management, land use externalities, land value, spatial panel dynamic

Procedia PDF Downloads 256

Authors: Terence Soule, Tami Al Ghamdi

Abstract:

To study how the partial knowledge transfer may affect the Genetic Algorithm (GA) performance, we model the Transfer Learning (TL) process using GA as the model solver. The objective of the TL is to transfer the knowledge from one problem to another related problem. This process imitates how humans think in their daily life. In this paper, we proposed to study a case where the knowledge transferred from the S problem has less information than what the T problem needs. We sampled the transferred population using different strategies of TL. The results showed transfer part of the knowledge is helpful and speeds the GA process of finding a solution to the problem.

Keywords: transfer learning, partial transfer, evolutionary computation, genetic algorithm

Procedia PDF Downloads 132