Search results for: leadership models

Authors: Fu Jinyu, Lin Jinguan

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This paper introduces a novel approach that unifies two types of models: one is the continuous-time jump-diffusion used to model high-frequency data, and the other is discrete-time GQARCH employed to model low-frequency financial data by embedding the discrete GQARCH structure with jumps in the instantaneous volatility process. This model is named “GQARCH-It\^{o} -Jumps mode.” We adopt the realized range-based threshold estimation for high-frequency financial data rather than the realized return-based volatility estimators, which entail the loss of intra-day information of the price movement. Meanwhile, a quasi-likelihood function for the low-frequency GQARCH structure with jumps is developed for the parametric estimate. The asymptotic theories are mainly established for the proposed estimators in the case of finite activity jumps. Moreover, simulation studies are implemented to check the finite sample performance of the proposed methodology. Specifically, it is demonstrated that how our proposed approaches can be practically used on some financial data.

Keywords: It\^{o} process, GQARCH, leverage effects, threshold, realized range-based volatility estimator, quasi-maximum likelihood estimate

Procedia PDF Downloads 161

Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Cristina Diego Soroa

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Nowadays, the use of drones has been extended to practically any human activity. One of the main applications is focused on the surveying field. In this regard, software programs that process the images captured by the sensor from the drone in an almost automatic way have been developed and commercialized, but they only allow contrasting the results through control points. This work proposes the contrast of a 3D model obtained from a flight developed by a drone and a non-metric camera (due to its low cost), with a second model that is obtained by means of the historically-endorsed classical methods. In addition to this, the contrast is developed over a certain territory with a significant unevenness, so as to test the model generated with photogrammetry, and considering that photogrammetry with drones finds more difficulties in terms of accuracy in this kind of situations. Distances, heights, surfaces and volumes are measured on the basis of the 3D models generated, and the results are contrasted. The differences are about 0.2% for the measurement of distances and heights, 0.3% for surfaces and 0.6% when measuring volumes. Although they are not important, they do not meet the order of magnitude that is presented by salespeople.

Keywords: accuracy, classical topographic, model tridimensional, photogrammetry, Uav.

Procedia PDF Downloads 139

Authors: Pooya Niksiar, Ali Ashrafizadeh, Mehrzad Shams, Amir Hossein Madani

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There are many computationally demanding applications in science and engineering which need efficient algorithms implemented on high performance computers. Recently, Graphics Processing Units (GPUs) have drawn much attention as compared to the traditional CPU-based hardware and have opened up new improvement venues in scientific computing. One particular application area is Computational Fluid Dynamics (CFD), in which mature CPU-based codes need to be converted to GPU-based algorithms to take advantage of this new technology. In this paper, numerical solutions of two classes of discrete fluid flow models via both CPU and GPU are discussed and compared. Test problems include an Eulerian model of a two-dimensional incompressible laminar flow case and a Lagrangian model of a two phase flow field. The CUDA programming standard is used to employ an NVIDIA GPU with 480 cores and a C++ serial code is run on a single core Intel quad-core CPU. Up to two orders of magnitude speed up is observed on GPU for a certain range of grid resolution or particle numbers. As expected, Lagrangian formulation is better suited for parallel computations on GPU although Eulerian formulation represents significant speed up too.

Keywords: CFD, Eulerian formulation, graphics processing units, Lagrangian formulation

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Authors: N. Manoj

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The aeroelastic behavior of engine nacelle strake when subjected to unsteady aerodynamic flows is investigated in this paper. Geometric nonlinear characteristics and modal parameters of nacelle strake are studied when it is under dynamic loading condition. Here, an N-S based Finite Volume solver is coupled with Finite Element (FE) based nonlinear structural solver to investigate the nonlinear characteristics of nacelle strake over a range of dynamic pressures at various phases of flight like takeoff, climb, and cruise conditions. The combination of high fidelity models for both aerodynamics and structural dynamics is used to predict the nonlinearities of strake (chine). The methodology adopted for present aeroelastic analysis is partitioned-based time domain coupled CFD and CSD solvers and it is validated by the consideration of experimental and numerical comparison of aeroelastic data for a cropped delta wing model which has a proven record. The present strake geometry is derived from theoretical formulation. The amplitude and frequency obtained from the coupled solver at various dynamic pressures is discussed, which gives a better understanding of its impact on aerodynamic design-sizing of strake.

Keywords: aeroelasticity, finite volume, geometric nonlinearity, limit cycle oscillations, strake

Procedia PDF Downloads 285

Authors: Yiğit Gürler, İbrahim Şimşek, Müge Savaştaer, Ayberk Karakuş, Alper Taşdemirci

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316L steel is frequently used in the industry due to its easy formability and accessibility in sheet metal forming processes. Numerical and experimental studies are frequently encountered in the literature to examine the mechanical behavior of 316L stainless steel during the forming process. 316L stainless steel is the most common material used in the production of plate heat exchangers and plate heat exchangers are produced by plastic deformation of the stainless steel. The motivation in this study is to determine the appropriate material model during the simulation of the sheet metal forming process. For this reason, two different material models were examined and Ls-Dyna material cards were created using material test data. These are MAT133_BARLAT_YLD2000 and MAT093_SIMPLIFIED_JOHNSON_COOK. In order to compare results of the tensile test & hydraulic bulge test performed both numerically and experimentally. The obtained results were evaluated comparatively and the most suitable material model was selected for the forming simulation. In future studies, this material model will be used in the numerical modeling of the sheet metal forming process.

Keywords: 316L, mechanical characterization, metal forming, Ls-Dyna

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Authors: Azade Ghorbani-HasanSaraei, Seyed-Ahmad Shahidi, Sakineh Alizadeh, Adeleh Maghsoudlou

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Improvement of color, as a quality attribute of Plum Concentrate, has been made possible by the increase in knowledge of kinetic of color change. Three different heating/evaporation processes were employed for the production of pPlum juice concentrate. The Plum juice was concentrated to a final 55 °Bx from an initial °Bx of 15 by microwave heating, rotary vacuum evaporator and evaporating at atmospheric pressure. The final Plum juice concentration of 55 °Bx was achieved in 17, 24 and 57 min by using the microwave, rotary vacuum and atmospheric heating processes, respectively. The colour change during concentration processes was investigated. Total colour differences, Hunter L, a and b parameters were used to estimate the extent of colour loss. All Hunter colour parameters decreased with time. The zero-order, first-order and a combined kinetics model were applied to the changes in colour parameters. Results indicated that variation in TCD followed both first-order and combined kinetics models, and parameters L, a and b followed only combined model. This model implied that the colour formation and pigment destruction occurred during concentration processes of plum juice.

Keywords: colour, kinetics, concentration, plum juice

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Authors: Yulina E. Riany, Divna Haslam, Matthew Sanders

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This cross-cultural study aims to compare the level of parental depression and stress, parenting style use, and child emotional and behavioural problems between parents in Australia as an example of a Western country and parents in Indonesia as an example of Asian culture. A series of hierarchical regressions were undertaken to determine two models examining the factors that predict child problems residing in Australia (Model 1) and in Indonesia (Model 2). The online survey was completed by 179 parents in Australia and 448 parents in Indonesia. Results indicated that Australian parents reported higher levels of depression, authoritative parenting and higher levels of child misbehaviours compared to Indonesian parents. In comparison, Indonesian parents reported higher authoritarian parenting. Analyses performed to examine Model 1 and 2 revealed that parental negative emotional states and parenting style predicted child emotional and behavioural problems in both countries.

Keywords: cross-cutural study, parental stress, parenting, child misbehaviour

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Authors: Ali Oveysi Sarabi

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The dimensions of nanostructures are in the range of inter-atomic spacing of the structures which makes them impossible to be modeled as a continuum. Nanoscale size-effects on vibration analysis of nanobeams embedded in an elastic medium is investigated using different types of beam theory. To this end, Eringen’s nonlocal elasticity is incorporated to various beam theories namely as Euler-Bernoulli beam theory (EBT), Timoshenko beam theory (TBT), Reddy beam theory (RBT), and Levinson beam theory (LBT). The surrounding elastic medium is simulated with both Winkler and Pasternak foundation models and the difference between them is studies. Explicit formulas are presented to obtain the natural frequencies of nanobeam corresponding to each nonlocal beam theory. Selected numerical results are given for different values of the non-local parameter, Winkler modulus parameter, Pasternak modulus parameter and aspect ratio of the beam that imply the effects of them, separately. It is observed that the values of natural frequency are strongly dependent on the stiffness of elastic medium and the value of the non-local parameter and these dependencies varies with the value of aspect ratio and mode number.

Keywords: nanobeams, free vibration, nonlocal elasticity, winkler foundation model, Pasternak foundation model, beam theories

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Authors: Teklu Urgessa, Wookjae Maeng, Joong Seek Lee

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Application of five implementations of three data mining classification techniques was experimented for extracting important insights from tourism data. The aim was to find out the best performing algorithm among the compared ones for tourism knowledge discovery. Knowledge discovery process from data was used as a process model. 10-fold cross validation method is used for testing purpose. Various data preprocessing activities were performed to get the final dataset for model building. Classification models of the selected algorithms were built with different scenarios on the preprocessed dataset. The outperformed algorithm tourism dataset was Random Forest (76%) before applying information gain based attribute selection and J48 (C4.5) (75%) after selection of top relevant attributes to the class (target) attribute. In terms of time for model building, attribute selection improves the efficiency of all algorithms. Artificial Neural Network (multilayer perceptron) showed the highest improvement (90%). The rules extracted from the decision tree model are presented, which showed intricate, non-trivial knowledge/insight that would otherwise not be discovered by simple statistical analysis with mediocre accuracy of the machine using classification algorithms.

Keywords: classification algorithms, data mining, knowledge discovery, tourism

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Authors: Tatsuya Otoshi, Masayuki Murata

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With the development and diversification of applications on the Internet, applications that require high responsiveness, such as video streaming, are becoming mainstream. Application responsiveness is not only a matter of communication delay but also a matter of time required to grasp changes in network conditions. The tradeoff between accuracy and measurement time is a challenge in network control. We people make countless decisions all the time, and our decisions seem to resolve tradeoffs between time and accuracy. When making decisions, people are known to make appropriate choices based on relatively small samples. Although there have been various studies on models of human decision-making, a model that integrates various cognitive biases, called ”quantum decision-making,” has recently attracted much attention. However, the modeling of small samples has not been examined much so far. In this paper, we extend the model of quantum decision-making to model decision-making with a small sample. In the proposed model, the state is updated by value-based probability amplitude amplification. By analytically obtaining a lower bound on the number of samples required for decision-making, we show that decision-making with a small number of samples is feasible.

Keywords: quantum decision making, small sample, MPEG-DASH, Grover's algorithm

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Authors: Emin Avcı, Çiydem Çatak

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The recent economic crisis have shown that procyclicality, which could threaten the stability and growth of the economy, is a major problem of financial and real sector. The term procyclicality refers here the cyclical behavior of banks that lead them to follow the same patterns as the real economy. In this study, leverage which demonstrate how a bank manage its debt, is chosen as bank specific variable to see the effect of changes in it over the economic cycle. The procyclical behavior of Turkish banking sector (commercial, participation, development-investment banks) is tried to explain with analyzing the relationship between leverage and asset growth. On the basis of theoretical explanations, eight different leverage ratios are utilized in eight different panel data models to demonstrate the procyclicality effect of Turkish banks leverage using monthly data covering the 2005-2014 period. It is tested whether there is an increasing (decreasing) trend in the leverage ratio of Turkish banks when there is an enlargement (contraction) in their balance sheet. The major finding of the study indicates that asset growth has a significant effect on all eight leverage ratios. In other words, the leverage of Turkish banks follow a cyclical pattern, which is in line with those of earlier literature.

Keywords: banking, economic cycles, leverage, procyclicality

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Authors: Abdulrahman R. Alenezi

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This research investigates the effects of facility disruptions on-demand allocation within the context of the Reliable Facility Location Problem (RFLP). We explore two distinct scenarios: one where primary and backup facilities can fail simultaneously and another where such simultaneous failures are not possible. The RFLP model is tailored to reflect these scenarios, incorporating different approaches to transportation cost calculations. Utilizing a Lagrange relaxation method, the model achieves high efficiency, yielding an average optimality gap of 0.1% within 12.2 seconds of CPU time. Findings indicate that primary facilities are typically sited closer to demand points than backup facilities. In cases where simultaneous failures are prohibited, demand points are predominantly assigned to the nearest available facility. Conversely, in scenarios permitting simultaneous failures, demand allocation may prioritize factors beyond mere proximity, such as failure rates. This study highlights the critical influence of facility reliability on strategic location decisions, providing insights for enhancing resilience in supply chain networks.

Keywords: reliable supply chain network, facility location problem, reliable facility location model, LaGrange relaxation

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Authors: Belkacem Chebil Sonia, Bensalem Wacef

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The majority of ball end milling models includes only the influence of cutting parameters (cutting speed, feed rate, depth of cut). Furthermore, this influence is studied in most of works on cutting force. Therefore, this study proposes an accurate ball end milling process modeling which includes also the influence of tool workpiece inclination. In addition, a characterization of residual stresses resulting of thermo mechanical loading in the workpiece was also presented. Moreover, the study of the influence of tool workpiece inclination and cutting parameters was made on residual stresses distribution. In order to achieve the predetermination of cutting forces and residual stresses during a milling operation, a thermo mechanical three-dimensional numerical model of ball end milling was developed. Furthermore, an experimental companion of ball end milling tests was realized on a 5-axis machining center to determine the cutting forces and characterize the residual stresses. The simulation results are compared with the experiment to validate the Finite Element Model and subsequently identify the optimum inclination angle and cutting parameters.

Keywords: ball end milling, cutting forces, cutting parameters, residual stress, tool-workpiece inclination

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Authors: Al-Braa Kashegari, Ali M. El-Halawany, Akram A. Shalabi, Sabrin R. M. Ibrahim, Hossam M. Abdallah

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Chemical investigation of Chrozophora oblongifolia resulted in the isolation of five major compounds that were identified as apeginin-7-O-glucoside (1), quercetin-3-O-glucuronic acid (2), quercetin-3-O-glacturonic acid (3), rutin (4), and 1,3,6-trigalloyl glucose (5). The identity of isolated compounds was assessed by different spectroscopic methods, including one- and two-dimensional NMR. The isolated compounds were tested for their antioxidant activity using different assays viz., DPPH, FRAP, ABTS, ORAC, and metal chelation effects. In addition, the inhibition of target enzymes involved in the metabolic syndrome, such as alpha-glucosidase and pancreatic lipase, were carried out. Moreover, the effect of the compounds on the advanced glycation end-products (AGEs) as one of the major complications of oxidative stress and hyperglycemia in metabolic syndromes were carried out using BSA‐fructose (bovine serum albumin), BSA-methylglyoxal, and arginine methylglyoxal models. The pure isolates showed a protective effect in metabolic syndromes as well as promising antioxidant activity. The results showed potent activity of compound 5 in all measured parameters meanwhile, none of the tested compounds showed activity against pancreatic lipase.

Keywords: Chrozophora oblongifolia, antioxidant, pancreatic lipase, metabolic syndromes

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Authors: Abdulaziz Afandi

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Minimizing the inventory cost, optimizing the inventory quantities, and increasing system operational availability are the main motivations to enhance forecasting demand of spare parts in a major power utility company in Medina. This paper reports in an effort made to optimize the orders quantities of spare parts by improving the method of forecasting the demand. The study focuses on equipment that has frequent spare parts purchase orders with uncertain demand. The pattern of the demand considers a lumpy pattern which makes conventional forecasting methods less effective. A comparison was made by benchmarking various methods of forecasting based on experts’ criteria to select the most suitable method for the case study. Three actual data sets were used to make the forecast in this case study. Two neural networks (NN) approaches were utilized and compared, namely long short-term memory (LSTM) and multilayer perceptron (MLP). The results as expected, showed that the NN models gave better results than traditional forecasting method (judgmental method). In addition, the LSTM model had a higher predictive accuracy than the MLP model.

Keywords: neural network, LSTM, MLP, forecasting demand, inventory management

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Authors: Jiahe Liu, HongyangYu, Feng Qian, Miao Luo

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The aim of this study was to improve the effects of human body 3D reconstruction. The MvP algorithm was adopted to obtain key point information from multiple perspectives. This algorithm allowed the capture of human posture and joint positions from multiple angles, providing more comprehensive and accurate data. The study also incorporated the SMPL-X model, which has been widely used for human body modeling, to achieve more accurate 3D reconstruction results. The use of the MvP algorithm made it possible to observe the reconstructed object from multiple angles, thus reducing the problems of blind spots and missing information. This algorithm was able to effectively capture key point information, including the position and rotation angle of limbs, providing key data for subsequent 3D reconstruction. Compared with traditional single-view methods, the method of multi-view fusion significantly improved the accuracy and stability of reconstruction. By combining the MvP algorithm with the SMPL-X model, we successfully achieved better human body 3D reconstruction effects. The SMPL-X model is highly scalable and can generate highly realistic 3D human body models, thus providing more detail and shape information.

Keywords: 3D human reconstruction, multi-view, joint point, SMPL-X

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Authors: Jiajun Wang, Xiaoge Li

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The purpose of the aspect-level sentiment analysis task is to identify the sentiment polarity of aspects in a sentence. Currently, most methods mainly focus on using neural networks and attention mechanisms to model the relationship between aspects and context, but they ignore the dependence of words in different ranges in the sentence, resulting in deviation when assigning relationship weight to other words other than aspect words. To solve these problems, we propose a new aspect-level sentiment analysis model that combines a multi-channel convolutional network and graph convolutional network (GCN). Firstly, the context and the degree of association between words are characterized by Long Short-Term Memory (LSTM) and self-attention mechanism. Besides, a multi-channel convolutional network is used to extract the features of words in different ranges. Finally, a convolutional graph network is used to associate the node information of the dependency tree structure. We conduct experiments on four benchmark datasets. The experimental results are compared with those of other models, which shows that our model is better and more effective.

Keywords: aspect-level sentiment analysis, attention, multi-channel convolution network, graph convolution network, dependency tree

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Authors: Sajid Hussain

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The complex domain approach for image segmentation based on active contour has been designed, which deforms step by step to partition an image into numerous expedient regions. A novel region-based trigonometric complex pressure force function is proposed, which propagates around the region of interest using image forces. The signed trigonometric force function controls the propagation of the active contour and the active contour stops on the exact edges of the object accurately. The proposed model makes the level set function binary and uses Gaussian smoothing kernel to adjust and escape the re-initialization procedure. The working principle of the proposed model is as follows: The real image data is transformed into complex data by iota (i) times of image data and the average iota (i) times of horizontal and vertical components of the gradient of image data is inserted in the proposed model to catch complex gradient of the image data. A simple finite difference mathematical technique has been used to implement the proposed model. The efficiency and robustness of the proposed model have been verified and compared with other state-of-the-art models.

Keywords: image segmentation, active contour, level set, Mumford and Shah model

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Authors: K. Nasir, S. Ahmad, A. Khan, H. Benkreira

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The topic of the research is to develop sustainable fire-resistant materials for vibration and acoustic damping of structure and airborne noises from sustainable recycled materials and biodegradable binders. The paper reports, methods and techniques of enhancing fire resistive, vibration and acoustic properties of building insulation materials made from natural resources like wood and recycled materials like rubber and textile waste. The structures are designed to optimize the number, size and stratification of closed (heat insulating) and open (noise insulating) pores. The samples produced are tested for their heat and noise insulating properties, including vibration damping and their structural properties (airflow resistivity, porosity, tortuosity and elastic modulus). The structural properties are then used in theoretical models to check the acoustic insulation measurements. Initial data indicate that one layer of such material can yield as much as 18 times more damping, increasing the loss factor by 18%.

Keywords: fire resistant, vibration damping, acoustic material, vibro-acoustic, thermal insulation, sustainable material, low cost materials, recycled materials, construction material

Procedia PDF Downloads 135

Authors: Innocent C. Ezenwa, Takashi Yoshino

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Knowledge of the transport properties of Fe and its alloys at extreme high pressure (P), temperature (T) conditions are essential for understanding the generation and sustainability of the magnetic field of the rocky planets with a metallic core. Since Pt, an unfilled d-band late transition metal with an electronic structure of Xe4f¹⁴5d⁹6s¹, is paramagnetic and remains close-packed structure at ambient conditions and high P-T, it is expected that its transport properties at these conditions would be similar to those of ε-Fe. We investigated the T-dependent electrical resistivity of solid and liquid Pt up to 8 GPa and found it constant along its melting curve both on the liquid and solid sides in agreement with theoretical prediction and experimental results estimated from thermal conductivity measurements. Our results suggest that the T-dependent resistivity of ε-Fe is linear and would not saturate at high P, T conditions. This, in turn, suggests that the thermal conductivity of liquid Fe at Earth’s core conditions may not be as high as previously suggested by models employing saturation resistivity. Hence, thermal convection could have powered the geodynamo before the birth of the inner core. The electrical resistivity and thermal conductivity on the liquid and solid sides of the inner core boundary of the Earth would be significantly different in values.

Keywords: electrical resistivity, thermal conductivity, transport properties, geodynamo and geomagnetic field

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Authors: Zhen Sun

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The study adopts the method of visual social semiotics to analyze a sample of fashion photos that were recently published in Chinese fashion magazines that target towards both male and female readers. It identifies a new visual trend in fashion photography, which is characterized by two features. First, the photos represent young, confident, and stylish female models with lower-class sloppy old men. The visual inharmony between the sexually desirable women and the aged men has suggested an impossibly accomplished sexuality and eroticism. Though the women are still under the male gaze, they are depicted as unreachable objects of voyeurism other than sexual objects subordinated to men. Second, the represented people are usually put in the backdrop of tasteless or vulgar Chinese town life, which is congruent with the images of men but makes the modern city girls out of place. The photographers intentionally contrast the images of women with that of men and with the background, which implies an imaginary binary division of modern Orientalism and the photographers’ self-orientalization strategy. Under the theoretical umbrella of neoliberal postfeminism, this study defines a new kind of gynocentric stereotype in Chinese fashion photography, which challenges the previous observations on gender portrayals in fashion magazines.

Keywords: fashion photography, gynocentrism, neoliberal postfeminism, self-orientalization

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Authors: E. Accomando, L. Delle Rose, S. Moretti, E. Olaiya, C. Shepherd-Themistocleous

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Heavy sterile neutrinos are almost ubiquitous in the class of Beyond Standard Model scenarios aimed at addressing the puzzle that emerged from the discovery of neutrino flavour oscillations, hence the need to explain their masses. In particular, they are necessary in a U(1)’ enlarged Standard Model (SM). We show that these heavy neutrinos can be rather long-lived producing distinctive displaced vertices and tracks. Indeed, depending on the actual decay length, they can decay inside a Large Hadron Collider (LHC) detector far from the main interaction point and can be identified in the inner tracking system or the muon chambers, emulated here through the Compact Muon Solenoid (CMS) detector parameters. Among the possible production modes of such heavy neutrino, we focus on their pair production mechanism in the SM Higgs decay, eventually yielding displaced lepton signatures following the heavy neutrino decays into weak gauge bosons. By employing well-established triggers available for the CMS detector and using the data collected by the end of the LHC Run 2, these signatures would prove to be accessible with negligibly small background. Finally, we highlight the importance that the exploitation of new triggers, specifically, displaced tri-lepton ones, could have for this displaced vertex search.

Keywords: beyond the standard model, displaced vertex, Higgs physics, neutrino physics

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Authors: Belalia Douma Omar, Bakhta Boukhatem, Mohamed Ghrici

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Self-compacting concrete (SCC) developed in Japan in the late 80s has enabled the construction industry to reduce demand on the resources, improve the work condition and also reduce the impact of environment by elimination of the need for compaction. Fuzzy logic (FL) approaches has recently been used to model some of the human activities in many areas of civil engineering applications. Especially from these systems in the model experimental studies, very good results have been obtained. In the present study, a model for predicting compressive strength of SCC containing various proportions of fly ash, as partial replacement of cement has been developed by using Adaptive Neuro-Fuzzy Inference System (ANFIS). For the purpose of building this model, a database of experimental data were gathered from the literature and used for training and testing the model. The used data as the inputs of fuzzy logic models are arranged in a format of five parameters that cover the total binder content, fly ash replacement percentage, water content, super plasticizer and age of specimens. The training and testing results in the fuzzy logic model have shown a strong potential for predicting the compressive strength of SCC containing fly ash in the considered range.

Keywords: self-compacting concrete, fly ash, strength prediction, fuzzy logic

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Authors: Yuanxiang Miao

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Couchsurfing is a free homestay and social networking service accessible via the website and mobile app. Couchsurfers can directly request free accommodations from others and receive offers from each other. However, it is typically difficult for people to make a decision that accepts or declines a request when they receive it from Couchsurfers because they do not know each other at all. People are expected to meet up with some Couchsurfers who are kind, generous, and interesting while it is unavoidable to meet up with someone unfriendly. This paper utilized classification algorithms of Machine Learning to help people to find out the Good Couchsurfers and Not Good Couchsurfers on the Couchsurfing website. By knowing the prior experience, like Couchsurfer’s profiles, the latest references, and other factors, it became possible to recognize what kind of the Couchsurfers, and furthermore, it helps people to make a decision that whether to host the Couchsurfers or not. The value of this research lies in a case study in Kyoto, Japan in where the author has hosted 54 Couchsurfers, and the author collected relevant data from the 54 Couchsurfers, finally build a model based on classification algorithms for people to predict Couchsurfers. Lastly, the author offered some feasible suggestions for future research.

Keywords: Couchsurfing, Couchsurfers prediction, classification algorithm, hospitality tourism platform, hospitality sciences, machine learning

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Authors: M. Shahab Uddin, Pennung Warnitchai

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Currently more than half of the world’s populations are living in cities, and the number and sizes of cities are growing faster than ever. Cities rely on the effective functioning of complex and interdependent critical infrastructures networks to provide public services, enhance the quality of life, and save the community from hazards and disasters. In contrast, complex connectivity and interdependency among the urban critical infrastructures bring management challenges and make the urban system prone to the domino effect. Unplanned rapid growth, increased connectivity, and interdependency among the infrastructures, resource scarcity, and many other socio-political factors are affecting the typical state of an urban system and making it susceptible to numerous sorts of diversion. In addition to internal vulnerabilities, urban systems are consistently facing external threats from natural and manmade hazards. Cities are not just complex, interdependent system, but also makeup hubs of the economy, politics, culture, education, etc. For survival and sustainability, complex urban systems in the current world need to manage their vulnerabilities and hazardous incidents more wisely and more interactively. Coordinated management in such systems makes for huge potential when it comes to absorbing negative effects in case some of its components were to function improperly. On the other hand, ineffective management during a similar situation of overall disorder from hazards devastation may make the system more fragile and push the system to an ultimate collapse. Following the quantum, the current research hypothesizes that a hazardous event starts its journey as an emergency, and the system’s internal vulnerability and response capacity determine its destination. Connectivity and interdependency among the urban critical infrastructures during this stage may transform its vulnerabilities into dynamic damaging force. An emergency may turn into a disaster in the absence of effective management; similarly, mismanagement or lack of management may lead the situation towards a catastrophe. Situation awareness and factual decision-making is the key to win a battle. The current research proposed a contextual decision support system for an urban critical infrastructure system while integrating three different models: 1) Damage cascade model which demonstrates damage propagation among the infrastructures through their connectivity and interdependency, 2) Restoration model, a dynamic restoration process of individual infrastructure, which is based on facility damage state and overall disruptions in surrounding support environment, and 3) Optimization model that ensures optimized utilization and distribution of available resources in and among the facilities. All three models are tightly connected, mutually interdependent, and together can assess the situation and forecast the dynamic outputs of every input. Moreover, this integrated model will hold disaster managers and decision makers responsible when it comes to checking all the alternative decision before any implementation, and support to produce maximum possible outputs from the available limited inputs. This proposed model will not only support to reduce the extent of damage cascade but will ensure priority restoration and optimize resource utilization through adaptive and collaborative management. Complex systems predictably fail but in unpredictable ways. System understanding, situation awareness, and factual decisions may significantly help urban system to survive and sustain.

Keywords: disaster prevention, decision support system, emergency response, urban critical infrastructure system

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Authors: Tsafi Timor

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The research focuses on the exploration of the unique journey that novice teachers experience in their first year of teaching, among graduates of re-training programs into teaching. The study explores the experiences of success and failure and the factors that underpin positive experiences, as well as the journey (process) of this year with reference to the comparison between novice teachers and new immigrants. The content analysis that was adopted in the study was conducted on texts that were written by the teachers and detailed their first year of teaching. The findings indicate that experiences of success are featured by personal satisfaction, constant need of feedback, high motivation in challenging situations, and emotions. Failure experiences are featured by frustration, helplessness, sense of humiliation, feeling of rejection, and lack of efficacy. Factors that promote and inhibit positive experiences relate to personal, personality, professional and organizational levels. Most teachers reported feeling like new immigrants, and demonstrated different models of the process of the first year of teaching. Further research is recommended on the factors that promote and inhibit positive experiences, and on 'The Missing Link' of the relationship between Teacher Education Programs and the practices in schools.

Keywords: first-year teaching, novice teachers, school practice, teacher education programs

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Authors: Kyere Vincent Nartey, Klaus Greve, Atiemo Sampson

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E-waste is discarded electrical electronic equipment inclusive of all components, sub-assemblies and consumables which are part of the product at the time of discarding and known to contain both hazardous and valuable fractions. E-waste is recycled within the proposed ecological restoration of the Agbogbloshie enclave using crude and rudimental recycling procedures such as open burning and manual dismantling which result in pollution and contamination of soil, water and air. Using GIS, this study was conducted to examine the spatial distribution and extent of soil contamination by heavy metals from the e-waste recycling site in Agbogbloshie. From the month of August to November 2013, 146 soil samples were collected in addition to their coordinates using GPS. Elemental analysis performed on the collected soil samples using X-Ray fluorescence revealed over 30 elements including, Ni, Cr, Zn, Cu, Pb and Mn. Using geostatistical techniques in ArcGIS 10.1 spatial assessment and distribution maps were generated. Mathematical models or equations were used to estimate the degree of contamination and pollution index. Results from soil analysis from the Agbogbloshie enclave showed that levels of measured or observed elements were significantly higher than the Canadian EPA and Dutch environmental standards.

Keywords: e-waste, geostatistics, soil contamination, spatial distribution

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Authors: H. Bouaziz, M. Sefi, J. de Lapuente, M. Borras, N. Zeghal

Abstract:

Although arsenic trioxide has been the subject of toxicological research, in vitro cytotoxicity and genotoxicity studies using relevant cell models and uniform methodology are not well elucidated. Hence, the aim of the present study was to evaluate the cytotoxicity and genotoxicity induced by arsenic trioxide in human keratinocytes (HaCaT) using the MTT [3-(4, 5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide] and alkaline single cell gel electrophoresis (Comet) assays, respectively. Human keratinocytes were treated with different doses of arsenic trioxide for 4 h prior to cytogenetic assessment. Data obtained from the MTT assay indicated that arsenic trioxide significantly reduced the viability of HaCaT cells in a dose-dependent manner, showing a IC50 value of 34.18 ± 0.6 µM. Data generated from the comet assay also indicated a significant dose-dependent increase in DNA damage in HaCaT cells associated with arsenic trioxide exposure. We observed a significant increase in comet tail length and tail moment, showing an evidence of arsenic trioxide -induced genotoxic damage in HaCaT cells. This study confirms that the comet assay is a sensitive and effective method to detect DNA damage caused by arsenic.

Keywords: arsenic trioxide, cytotoxixity, genotoxicity, HaCaT

Procedia PDF Downloads 257

Authors: David Oyewumi Oyekunle, David Preston, Florence Ibeh

Abstract:

The paper provides an overview of the impacts of the human dimension in project management and team management on projects, which is increasingly affecting the performance of organizations. Recognizing its crucial significance, the research focuses on analyzing the psychological and interpersonal dynamics within project teams. This research is highly significant in the dynamic field of project management, as it addresses important gaps and offers vital insights that align with the constantly changing demands of the profession. A case study was conducted at the University of Salford to examine how human activity affects project management and performance. The study employed a mixed methodology to gain a deeper understanding of the real-world experiences of the subjects and project teams. Data analysis procedures to address the research objectives included the deductive approach, which involves testing a clear hypothesis or theory, as well as descriptive analysis and visualization. The survey comprised a sample size of 40 participants out of 110 project management professionals, including staff and final students in the Salford Business School, using a purposeful sampling method. To mitigate bias, the study ensured diversity in the sample by including both staff and final students. A smaller sample size allowed for more in-depth analysis and a focused exploration of the research objective. Conflicts, for example, are intricate occurrences shaped by a multitude of psychological stimuli and social interactions and may have either a deterrent perspective or a positive perspective on project performance and project management productivity. The study identified conflict elements, including culture, environment, personality, attitude, individual project knowledge, team relationships, leadership, and team dynamics among team members, as crucial human activities to minimize conflict. The findings are highly significant in the dynamic field of project management, as they address important gaps and offer vital insights that align with the constantly changing demands of the profession. It provided project professionals with valuable insights that can help them create a collaborative and high-performing project environment. Uncovering human influence on project performance, effective communication, optimal team synergy, and a keen understanding of project scope are necessary for the management of projects to attain exceptional performance and efficiency. For the research to achieve the aims of this study, it was acknowledged that the productive dynamics of teams and strong group cohesiveness are crucial for effectively managing conflicts in a beneficial and forward-thinking manner. Addressing the identified human influence will contribute to a more sustainable project management approach and offer opportunities for exploration and potential contributions to both academia and practical project management.

Keywords: human dimension, project management, team dynamics, conflict resolution

Procedia PDF Downloads 108

Authors: Hamid Goharnejad, Milad Sadeghpoor Moalem, Mahmood Zakeri Niri, Leili Sadeghi Khalegh Abadi

Abstract:

While there are many benefits to using reservoir dams, their break leads to destructive effects. From the viewpoint of International Committee of Large Dams (ICOLD), dam break means the collapse of whole or some parts of a dam; thereby the dam will be unable to hold water. Therefore, studying dam break phenomenon and prediction of its behavior and effects reduces losses and damages of the mentioned phenomenon. One of the most common types of reservoir dams is embankment dam. Overtopping in embankment dams occurs because of flood discharge system inability in release inflows to reservoir. One of the most important issues among managers and engineers to evaluate the performance of the reservoir dam rim when sliding into the storage, creating waves is large and long. In this study, the effects of floods which caused the overtopping of the dam have been investigated. It was assumed that spillway is unable to release the inflow. To determine outflow hydrograph resulting from dam break, numerical model using Flow-3D software and empirical equations was used. Results of numerical models and their comparison with empirical equations show that numerical model and empirical equations can be used to study the flood resulting from dam break.

Keywords: embankment dam break, empirical equations, Taleghan dam, Flow-3D numerical model

Procedia PDF Downloads 321