Search results for: RGB models

Authors: Fahad Alanazi, Andrew Jones

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Digital forensics seeks to achieve the successful investigation of digital crimes through obtaining acceptable evidence from digital devices that can be presented in a court of law. Thus, the digital forensics investigation is normally performed through a number of phases in order to achieve the required level of accuracy in the investigation processes. Since 1984 there have been a number of models and frameworks developed to support the digital investigation processes. In this paper, we review a number of the investigation processes that have been produced throughout the years and introduce a proposed digital forensic model which is based on the scope of the Saudi Arabia investigation process. The proposed model has been integrated with existing models for the investigation processes and produced a new phase to deal with a situation where there is initially insufficient evidence.

Keywords: digital forensics, process, metadata, Traceback, Sauid Arabia

Procedia PDF Downloads 359

Authors: Martin K. Steiger, Lukas Heisler, Hans-Georg Brachtendorf

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Deep neural networks and their variants form the backbone of many AI applications. Based on the so-called residual networks, a continuous formulation of such models as ordinary differential equations (ODEs) has proven advantageous since different techniques may be applied that significantly increase the learning speed and enable controlled trade-offs with the resulting error at the same time. For the evaluation of such models, high-performance numerical differential equation solvers are used, which also provide the gradients required for training. However, whether classical gradient-based methods are even applicable or which one yields the best results has not been discussed yet. This paper aims to redeem this situation by providing empirical results for different applications.

Keywords: deep neural networks, gradient-based learning, image processing, ordinary differential equation networks

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Authors: Alice Schittek, Isabelle Roskam, Moira Mikolajczak

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Background: Perfectionistic strivings (PS) and perfectionistic concerns (PC) are associated with an increase in parental burnout (PB), and PB causally increases violence towards the offspring. Objective: To our best knowledge, no study has ever investigated whether perfectionism (PS and PC) predicts violence towards the offspring and whether PB could explain this link. We hypothesized that an increase in PS and PC would lead to an increase in violence via an increase in PB. Method: 228 participants responded to an online survey, with three measurement occasions spaced two months apart. Results: Contrary to expectations, cross-lagged path models revealed that violence towards the offspring prospectively predicts an increase in PS and PC. Mediation models showed that PB is not a significant mediator. The results of all models did not change when controlling for social desirability. Conclusion: The present study shows that violence towards the offspring increases the risk of PS and PC in parents, which highlights the importance of understanding the effect of child maltreatment on the whole family system and not just on children. Results are discussed in light of the feeling of guilt experienced by parents. Considering the insignificant mediation effect, PB research should slowly shift towards more (quasi) causal designs, allowing to identify which significant correlations translate into causal effects. Implications: Clinicians should focus on preventing child maltreatment as well as treating parental perfectionism. Researchers should unravel the effects of child maltreatment on the family system.

Keywords: maltreatment, parental burnout, perfectionistic strivings, perfectionistic concerns, perfectionism, violence

Procedia PDF Downloads 72

Authors: Sarah Potter, Michele Laliberte

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As eating disorders are associated with high levels of chronicity, impairment, and distress, it is paramount to evaluate factors that may improve treatment outcomes in this group. Individuals with eating disorders exhibit elevated levels of perfectionism and emotion dysregulation, as well as reduced self-compassion. These variables are related to eating disorder outcomes, including shape/weight concerns and psychosocial impairment. Thus, these factors may be tenable targets for treatment within eating disorder populations. However, the relative contributions of perfectionism, emotion dysregulation, and self-compassion to the severity of shape/weight concerns and psychosocial impairment remain largely unexplored. In the current study, mediation analyses were conducted to clarify how perfectionism, emotion dysregulation, and self-compassion are linked to shape/weight concerns and psychosocial impairment. The sample was comprised of 85 patients from an outpatient eating disorder clinic. The patients completed self-report measures of perfectionism, self-compassion, emotion dysregulation, eating disorder symptoms, and psychosocial impairment. Specifically, emotion dysregulation was assessed as a mediator in the relationships between (1) perfectionism and shape/weight concerns, (2) self-compassion and shape/weight concerns, (3) perfectionism and psychosocial impairment, and (4) self-compassion and psychosocial impairment. It was postulated that emotion dysregulation would significantly mediate relationships in the former two models. An a priori hypothesis was not constructed in reference to the latter models, as these analyses were preliminary and exploratory in nature. The PROCESS macro for SPSS was utilized to perform these analyses. Emotion dysregulation fully mediated the relationships between perfectionism and eating disorder outcomes. In the link between self-compassion and psychosocial impairment, emotion dysregulation partially mediated this relationship. Finally, emotion dysregulation did not significantly mediate the relationship between self-compassion and shape/weight concerns. The results suggest that emotion dysregulation and self-compassion may be suitable targets to decrease the severity of psychosocial impairment and shape/weight concerns in individuals with eating disorders. Further research is required to determine the stability of these models over time, between diagnostic groups, and in nonclinical samples.

Keywords: eating disorders, emotion dysregulation, perfectionism, self-compassion

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Authors: Arunas Burinskas, Manuela Tvaronavičienė

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Although the new trade theories, unlike the theories of an industrial organisation, see the structure of the market and competition between enterprises through their heterogeneity according to various parameters, they do not pay any particular attention to the analysis of the market structure and its development. In this article, although we relied mainly on models developed by the scholars of new trade theory, we proposed a different approach. In our simulation model, we model market demand according to normal distribution function, while on the supply side (as it is in the new trade theory models), productivity is modeled with the Pareto distribution function. The results of the simulation show that companies with higher productivity (lower marginal costs) do not pass on all the benefits of such economies to buyers. However, even with higher marginal costs, firms can choose to offer higher value-added goods to stay in the market. In general, the structure of the market is formed quickly enough and depends on the skills available to firms.

Keywords: market, structure, simulation, heterogenous firms

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Authors: D. S. Fardhyanti, Megawati, W. B. Sediawan

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Coal tar is a liquid by-product of the process of coal gasification and carbonation. This liquid oil mixture contains various kinds of useful compounds such as aromatic compounds and phenolic compounds. These compounds are widely used as raw material for insecticides, dyes, medicines, perfumes, coloring matters, and many others. This research investigates thermodynamic modelling of liquid-liquid equilibria (LLE) in the separation of phenol from the coal tar by solvent extraction. The equilibria are modeled by ternary components of Wohl, Van Laar, and Three-Suffix Margules models. The values of the parameters involved are obtained by curve-fitting to the experimental data. Based on the comparison between calculated and experimental data, it turns out that among the three models studied, the Three-Suffix Margules seems to be the best to predict the LLE of p-Cresol mixtures for those system.

Keywords: coal tar, phenol, Wohl, Van Laar, Three-Suffix Margules

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Authors: Massimo Miccoli, Luca Marangoni, Alberto Aniello Scaringi, Alessandro Marceddu, Alessandro Amicone

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The susceptibility of deep neural networks (DNNs) to adversarial manipulations is a recognized challenge within the computer vision domain. Adversarial examples, crafted by adding subtle yet malicious alterations to benign images, exploit this vulnerability. Various defense strategies have been proposed to safeguard DNNs against such attacks, stemming from diverse research hypotheses. Building upon prior work, our approach involves the utilization of autoencoder models. Autoencoders, a type of neural network, are trained to learn representations of training data and reconstruct inputs from these representations, typically minimizing reconstruction errors like mean squared error (MSE). Our autoencoder was trained on a dataset of benign examples; learning features specific to them. Consequently, when presented with significantly perturbed adversarial examples, the autoencoder exhibited high reconstruction errors. The architecture of the autoencoder was tailored to the dimensions of the images under evaluation. We considered various image sizes, constructing models differently for 256x256 and 512x512 images. Moreover, the choice of the computer vision model is crucial, as most adversarial attacks are designed with specific AI structures in mind. To mitigate this, we proposed a method to replace image-specific dimensions with a structure independent of both dimensions and neural network models, thereby enhancing robustness. Our multi-modal autoencoder reconstructs the spectral representation of images across the red-green-blue (RGB) color channels. To validate our approach, we conducted experiments using diverse datasets and subjected them to adversarial attacks using models such as ResNet50 and ViT_L_16 from the torch vision library. The autoencoder extracted features used in a classification model, resulting in an MSE (RGB) of 0.014, a classification accuracy of 97.33%, and a precision of 99%.

Keywords: adversarial attacks, malicious images detector, binary classifier, multimodal transformer autoencoder

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Authors: Ahmad Aslizadeh, Farid Ghaderi

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Mapping organizational knowledge is an innovative concept and useful instrument of representation, capturing and visualization of implicit and explicit knowledge. There are a diversity of methods, instruments and techniques presented by different researchers following mapping organizational knowledge to reach determined goals. Implicating of these methods, it is necessary to know their exigencies and conditions in which those can be used. Integrating identified methods of knowledge mapping and comparing them would help knowledge managers to select the appropriate methods. This research conducted to presenting a model and framework to map organizational knowledge. At first, knowledge maps, their applications and necessity are introduced because of extracting comparative framework and detection of their structure. At the next step techniques of researchers such as Eppler, Kim, Egbu, Tandukar and Ebner as knowledge mapping models are presented and surveyed. Finally, they compare and a superior model would be introduced.

Keywords: knowledge mapping, knowledge management, comparative study, business and management

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Authors: Simone Leonardi, Luca Ardito

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Micro-influencers are effective elements in the marketing strategies of companies and institutions because of their capability to create an hyper-engaged audience around a specific topic of interest. In recent years, many scientific approaches and commercial tools have handled the task of detecting this type of social media users. These strategies adopt solutions ranging from rule based machine learning models to deep neural networks and graph analysis on text, images, and account information. This work compares the existing solutions and proposes an ensemble method to generalize them with different input data and social media platforms. The deployed solution combines deep learning models on unstructured data with statistical machine learning models on structured data. We retrieve both social media accounts information and multimedia posts on Twitter and Instagram. These data are mapped into feature vectors for an eXtreme Gradient Boosting (XGBoost) classifier. Sixty different topics have been analyzed to build a rule based gold standard dataset and to compare the performances of our approach against baseline classifiers. We prove the effectiveness of our work by comparing the accuracy, precision, recall, and f1 score of our model with different configurations and architectures. We obtained an accuracy of 0.91 with our best performing model.

Keywords: deep learning, gradient boosting, image processing, micro-influencers, NLP, social media

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Authors: M. Varin, A. M. Dubois, R. Gadbois-Langevin, B. Chalghaf

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Good knowledge of the physical environment is essential for an integrated forest planning. This information enables better forecasting of operating costs, determination of cutting volumes, and preservation of ecologically sensitive areas. The use of satellite images in stereoscopic pairs gives the capacity to generate high precision 3D models, which are scale-adapted for harvesting operations. These models could represent an alternative to 3D LiDAR data, thanks to their advantageous cost of acquisition. The objective of the study was to assess the quality of stereo-derived canopy height models (CHM) in comparison to a traditional LiDAR CHM and ground tree-height samples. Two study sites harboring two different forest stand types (broadleaf and conifer) were analyzed using stereo pairs and tri-stereo images from the WorldView-3 satellite to calculate CHM. Acquisition of multispectral images from an Unmanned Aerial Vehicle (UAV) was also realized on a smaller part of the broadleaf study site. Different algorithms using two softwares (PCI Geomatica and Correlator3D) with various spatial resolutions and band selections were tested to select the 3D modeling technique, which offered the best performance when compared with LiDAR. In the conifer study site, the CHM produced with Corelator3D using only the 50-cm resolution panchromatic band was the one with the smallest Root-mean-square deviation (RMSE: 1.31 m). In the broadleaf study site, the tri-stereo model provided slightly better performance, with an RMSE of 1.2 m. The tri-stereo model was also compared to the UAV, which resulted in an RMSE of 1.3 m. At individual tree level, when ground samples were compared to satellite, lidar, and UAV CHM, RMSE were 2.8, 2.0, and 2.0 m, respectively. Advanced analysis was done for all of these cases, and it has been noted that RMSE is reduced when the canopy cover is higher when shadow and slopes are lower and when clouds are distant from the analyzed site.

Keywords: very high spatial resolution, satellite imagery, WorlView-3, canopy height models, CHM, LiDAR, unmanned aerial vehicle, UAV

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Authors: Ofosuhene O. Apenteng, Noor Azina Ismail

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The human immunodeficiency virus (HIV) that causes acquired immune deficiency syndrome (AIDS) remains a global cause of morbidity and mortality. It has caused panic since its emergence. Relationships between migration and HIV/AIDS have become complex. In the absence of prospectively designed studies, dynamic mathematical models that take into account the migration movement which will give very useful information. We have explored the utility of mathematical models in understanding transmission dynamics of HIV and AIDS and in assessing the magnitude of how migration has impact on the disease. The model was calibrated to HIV and AIDS incidence data from Malaysia Ministry of Health from the period of 1986 to 2011 using Bayesian analysis with combination of Markov chain Monte Carlo method (MCMC) approach to estimate the model parameters. From the estimated parameters, the estimated basic reproduction number was 22.5812. The rate at which the susceptible individual moved to HIV compartment has the highest sensitivity value which is more significant as compared to the remaining parameters. Thus, the disease becomes unstable. This is a big concern and not good indicator from the public health point of view since the aim is to stabilize the epidemic at the disease-free equilibrium. However, these results suggest that the government as a policy maker should make further efforts to curb illegal activities performed by migrants. It is shown that our models reflect considerably the dynamic behavior of the HIV/AIDS epidemic in Malaysia and eventually could be used strategically for other countries.

Keywords: epidemic model, reproduction number, HIV, MCMC, parameter estimation

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Authors: Caroline E. Mendes, Alberto C. Badino

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Pneumatic reactors have been widely employed in various sectors of the chemical industry, especially where are required high heat and mass transfer rates. This study aimed to obtain correlations that allow the prediction of gas hold-up (Ԑ) and volumetric oxygen transfer coefficient (kLa), and compare these values, for three models of pneumatic reactors on two scales utilizing Newtonian fluids. Values of kLa were obtained using the dynamic pressure-step method, while  was used for a new proposed measure. Comparing the three models of reactors studied, it was observed that the mass transfer was superior to draft-tube airlift, reaching  of 0.173 and kLa of 0.00904s-1. All correlations showed good fit to the experimental data (R2≥94%), and comparisons with correlations from the literature demonstrate the need for further similar studies due to shortage of data available, mainly for airlift reactors and high viscosity fluids.

Keywords: bubble column, internal loop airlift, gas hold-up, kLa

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Authors: Khandoker Akib Mohammad

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While analyzing time-to-event data, it is possible that a certain fraction of subjects will never experience the event of interest, and they are said to be cured. When this feature of survival models is taken into account, the models are commonly referred to as cure models. In the presence of covariates, the conditional survival function of the population can be modelled by using the cure model, which depends on the probability of being uncured (incidence) and the conditional survival function of the uncured subjects (latency), and a combination of logistic regression and Cox proportional hazards (PH) regression is used to model the incidence and latency respectively. In this paper, we have shown the asymptotic normality of the profile likelihood estimator via asymptotic expansion of the profile likelihood and obtain the explicit form of the variance estimator with an implicit function in the profile likelihood. We have also shown the efficient score function based on projection theory and the profile likelihood score function are equal. Our contribution in this paper is that we have expressed the efficient information matrix as the variance of the profile likelihood score function. A simulation study suggests that the estimated standard errors from bootstrap samples (SMCURE package) and the profile likelihood score function (our approach) are providing similar and comparable results. The numerical result of our proposed method is also shown by using the melanoma data from SMCURE R-package, and we compare the results with the output obtained from the SMCURE package.

Keywords: Cox PH model, cure model, efficient score function, EM algorithm, implicit function, profile likelihood

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Authors: Endang Jati Mat Sahid, Hussain Ali Bekhet

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Ability to supply reliable and secure electricity has been one of the crucial components of economic development for any country. Forecasting of electricity production is therefore very important for accurate investment planning of generation power plants. In this study, we aim to examine and analyze the factors that affect electricity generation. Multiple regression models were used to find the relationship between various variables and electricity production. The models will simultaneously determine the effects of the variables on electricity generation. Many variables influencing electricity generation, i.e. natural gas (NG), coal (CO), fuel oil (FO), renewable energy (RE), gross domestic product (GDP) and fuel prices (FP), were examined for Malaysia. The results demonstrate that NG, CO, and FO were the main factors influencing electricity generation growth. This study then identified a number of policy implications resulting from the empirical results.

Keywords: energy policy, energy security, electricity production, Malaysia, the regression model

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Authors: Navid Zarif Karimi, Hossein Heidary, Giangiacomo Minak, Mehdi Ahmadi

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In this paper analytical model based on the mechanics of oblique cutting, linear elastic fracture mechanics (LEFM) and bending plate theory has been presented to determine the critical feed rate causing delamination in drilling of composite materials. Most of the models in this area used LEFM and bending plate theory; hence, they can only determine the critical thrust force which is an incorporable parameter. In this model by adding cutting oblique mechanics to previous models, critical feed rate has been determined. Also instead of simplification in loading condition, actual thrust force induced by chisel edge and cutting lips on composite plate is modeled.

Keywords: composite material, delamination, drilling, thrust force

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Authors: Yazan M. Alatrash, Han-ok Kang, Hyun-gi Yoon, Shen Zhang, Juhyeon Yoon

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Flow coastdown phenomena are very important to secure nuclear fuel integrity during loss of off-site power accidents. In this study, primary coolant flow coastdown phenomena are investigated for the Jordan Research and Training Reactor (JRTR) using a simulation software package, Modular Modelling System (MMS). Two MMS models are built. The first one is a simple model to investigate the characteristics of the primary coolant pump only. The second one is a model for a simulation of the Primary Coolant System (PCS) loop, in which all the detailed design data of the JRTR PCS system are modelled, including the geometrical arrangement data. The same design data for a PCS pump are used for both models. Coastdown curves obtained from the two models are compared to study the PCS loop coolant inertia effect on a flow coastdown. Results showed that the loop coolant inertia effect is found to be small in the JRTR PCS loop, i.e., about one second increases in a coastdown half time required to halve the coolant flow rate. The effects of different flywheel inertia on the flow coastdown are also investigated. It is demonstrated that the coastdown half time increases with the flywheel inertia linearly. The designed coastdown half time is proved to be well above the design requirement for the fuel integrity.

Keywords: flow coastdown, loop inertia, modelling, research reactor

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Authors: B. H. Aitchanov, Sh. K. Aitchanova, O. A. Baimuratov

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This paper is focused on dynamic pulse-frequency modulation (DPFM) control systems. Currently, the control law based on DPFM control signals is widely used in direct digital control subsystems introduced in the automated control systems of technological processes. Statistical analysis of automatic control systems is reduced to its construction of functional relationships between the statistical characteristics of the errors processes and input processes. Structural and dynamic Volterra models of digital pulse-frequency control systems can be used to develop methods for generating the dependencies, differing accuracy, requiring the amount of information about the statistical characteristics of input processes and computing labor intensity of their use.

Keywords: digital dynamic pulse-frequency control systems, dynamic pulse-frequency modulation, control object, discrete filter, impulse device, microcontroller

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Authors: Yasser Mahmoudi, Nader Karimi

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The present work investigates numerically the effect of thermal radiation from the solid phase on the rate of heat transfer inside a porous medium. Forced convection heat transfer process within a pipe filled with a porous media is considered. The Darcy-Brinkman-Forchheimer model is utilized to represent the fluid transport within the porous medium. A local thermal non-equilibrium (LTNE), two-equation model is used to represent the energy transport for the solid and fluid phases. The radiative heat transfer equation is solved by discrete ordinate method (DOM) to compute the radiative heat flux in the porous medium. Two primary approaches (models A and B) are used to represent the boundary conditions for constant wall heat flux. The effects of radiative heat transfer on the Nusselt numbers of the two phases are examined by comparing the results obtained by the application of models A and B. The fluid Nusselt numbers calculated by the application of models A and B show that the Nusselt number obtained by model A for the radiative case is higher than those predicted for the non-radiative case. However, for model B the fluid Nusselt numbers obtained for the radiative and non-radiative cases are similar.

Keywords: porous media, local thermal non-equilibrium, forced convection heat transfer, thermal radiation, Discrete Ordinate Method (DOM)

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Authors: Julia Desiree Velastegui Caceres, Luis Alejandro Velastegui Caceres, Oswaldo Padilla, Eduardo Kirby, Francisco Guerrero, Theofilos Toulkeridis

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It is fundamental to conserve sites of natural and cultural heritage with any available technique or existing methodology of preservation in order to sustain them for the following generations. We propose a further skill to protect the actual view of such sites, in which with high technology instrumentation we are able to digitally preserve natural and cultural heritages applied in Ecuador. In this project the use of laser technology is presented for three-dimensional models, with high accuracy in a relatively short period of time. In Ecuador so far, there are not any records on the use and processing of data obtained by this new technological trend. The importance of the project is the description of the methodology of the laser scanner system using the Faro Laser Scanner Focus 3D 120, the method for 3D modeling of geospatial data and the development of virtual environments in the areas of Cultural and Natural Heritage. In order to inform users this trend in technology in which three-dimensional models are generated, the use of such tools has been developed to be able to be displayed in all kinds of digitally formats. The results of the obtained 3D models allows to demonstrate that this technology is extremely useful in these areas, but also indicating that each data campaign needs an individual slightly different proceeding starting with the data capture and processing to obtain finally the chosen virtual environments.

Keywords: laser scanner system, 3D model, cultural heritage, natural heritage

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Authors: Mohadeseh Shojaei Shahrokhabadi, Ding-Geng (Din) Chen

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Positive continuous outcomes with a substantial number of zero values and incomplete longitudinal follow-up are quite common in medical cost data. To jointly model semi-continuous longitudinal cost data and survival data and to provide marginalized covariate effect estimates, a marginalized two-part joint model (MTJM) has been developed for outcome variables with lognormal distributions. In this paper, we propose MTJM models for outcome variables from a generalized gamma (GG) family of distributions. The GG distribution constitutes a general family that includes approximately all of the most frequently used distributions like the Gamma, Exponential, Weibull, and Log Normal. In the proposed MTJM-GG model, the conditional mean from a conventional two-part model with a three-parameter GG distribution is parameterized to provide the marginal interpretation for regression coefficients. In addition, MTJM-gamma and MTJM-Weibull are developed as special cases of MTJM-GG. To illustrate the applicability of the MTJM-GG, we applied the model to a set of real electronic health record data recently collected in Iran, and we provided SAS code for application. The simulation results showed that when the outcome distribution is unknown or misspecified, which is usually the case in real data sets, the MTJM-GG consistently outperforms other models. The GG family of distribution facilitates estimating a model with improved fit over the MTJM-gamma, standard Weibull, or Log-Normal distributions.

Keywords: marginalized two-part model, zero-inflated, right-skewed, semi-continuous, generalized gamma

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Authors: Yasser Mahmoudi, Nader Karimi

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The present work examines analytically the effect internal heat generation on temperature fields in a channel partially-filled with a porous under local thermal non-equilibrium condition. The Darcy-Brinkman model is used to represent the fluid transport through the porous material. Two fundamental models (models A and B) represent the thermal boundary conditions at the interface between the porous medium and the clear region. The governing equations of the problem are manipulated, and for each interface model, exact solutions for the solid and fluid temperature fields are developed. These solutions incorporate the porous material thickness, Biot number, fluid to solid thermal conductivity ratio Darcy number, as the non-dimensional energy terms in fluid and solid as parameters. Results show that considering any of the two models and under zero or negative heat generation (heat sink) and for any Darcy number, an increase in the porous thickness increases the amount of heat flux transferred to the porous region. The obtained results are applicable to the analysis of complex porous media incorporating internal heat generation, such as heat transfer enhancement (THE), tumor ablation in biological tissues and porous radiant burners (PRBs).

Keywords: porous media, local thermal non-equilibrium, forced convection, heat transfer, exact solution, internal heat generation

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Authors: Carlos Caro, Ernest Blade, Nestor Rojas

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This study determined the relationship between basic geo-technical parameters and parameters of the hydro logical model Thomas for water balance of rural watersheds, as a methodological calibration application, applicable in distributed models as IBER model, which represents a distributed system simulation models for unsteady flow numerical free surface. There was an exploration in 25 points (on 15 sub) basin of Rio Piedras (Boy.) obtaining soil samples, to which geo-technical characterization was performed by laboratory tests. Thomas model has a physical characterization of the input area by only four parameters (a, b, c, d). Achieve measurable relationship between geo technical parameters and 4 values of hydro logical parameters helps to determine subsurface, underground and surface flow more agile manner. It is intended in this way to reach some solutions regarding limits initial model parameters on the basis of Thomas geo-technical characterization. In hydro geological models of rural watersheds, calibration is an important process in the characterization of the study area. This step can require a significant computational cost and time, especially if the initial values or parameters before calibration are outside of the geo-technical reality. A better approach in these initial values means optimization of these process through a geo-technical materials area, where is obtained an important approach to the study as in the starting range of variation for the calibration parameters.

Keywords: distributed hydrology, hydrological and geotechnical characterization, Iber model

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Authors: Anastasia K. Eleftheriadou, Athanasios Sfetsos, Nikolaos Gounaris

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The present work examines the suitability of a seasonal forecasting model downscaled with a very high spatial resolution in order to assess the energy performance and requirements of buildings. The application of the developed model is applied on Greece for a period and with a forecast horizon of 5 months in the future. Greece, as a country in the middle of a financial crisis and facing serious societal challenges, is also very sensitive to climate changes. The commonly used method for the correlation of climate change with the buildings energy consumption is the concept of Degree Days (DD). This method can be applied to heating and cooling systems for a better management of environmental, economic and energy crisis, and can be used as medium (3-6 months) planning tools in order to predict the building needs and country’s requirements for residential energy use.

Keywords: downscaled seasonal models, degree days, energy performance

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Authors: J. García-Pérez

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An approach to compute optimum seismic design parameters is presented. It is based on the optimization of the expected present value of the total cost, which includes the initial cost of structures as well as the cost due to earthquakes. Different types of seismicity models are considered, including one for characteristic earthquakes. Uncertainties are included in some variables to observe the influence on optimum values. Optimum seismic design coefficients are computed for three different structural types representing high, medium and low rise buildings, located near and far from the seismic sources. Ordinary and important structures are considered in the analysis. The results of optimum values show an important influence of seismicity models as well as of uncertainties on the variables.

Keywords: importance factors, optimum parameters, seismic losses, seismic risk, total cost

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Authors: Castells Pau, Poetsch Christophe

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The effect of gust and turbulence encounters on aircraft is a wide field of study which allows different approaches, from high-fidelity multidisciplinary simulations to more simplified models adapted to industrial applications. The typical main goal is to predict the gust loads on the aircraft in order to ensure a safe design and achieve certification. Another topic widely studied is the gust loads reduction through an active control law. The impact of gusts on aircraft handling qualities is of interest as well in the analysis of in-service events so as to evaluate the aircraft response and the performance of the flight control laws. Traditionally, gust loads and handling qualities are addressed separately with different models adapted to the specific needs of each discipline. In this paper, an assessment of the differences between both models is presented and a strategy to better account for the physics of gust encounters in a typical flight dynamics model is proposed based on the model used for gust loads analysis. The applied corrections aim to capture the gust unsteady aerodynamics and propagation as well as the effect of dynamic flexibility at low frequencies. Results from the gust loads model at different flight conditions and measures from real events are used for validation. An assessment of a possible extension of steady aerodynamic nonlinearities to low frequency range is also addressed. The proposed corrections provide meaningful means to evaluate the performance and possible adjustments of the flight control laws.

Keywords: flight dynamics, gust loads, handling qualities, unsteady aerodynamics

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Authors: Nisarg A. Patel, Hiren B. Patel

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Quantum cryptography is described as a point-to-point secure key generation technology that has emerged in recent times in providing absolute security. Researchers have started studying new innovative approaches to exploit the security of Quantum Key Distribution (QKD) for a large-scale communication system. A number of approaches and models for utilization of QKD for secure communication have been developed. The uncertainty principle in quantum mechanics created a new paradigm for QKD. One of the approaches for use of QKD involved network fashioned security. The main goal was point-to-point Quantum network that exploited QKD technology for end-to-end network security via high speed QKD. Other approaches and models equipped with QKD in network fashion are introduced in the literature as. A different approach that this paper deals with is using QKD in existing protocols, which are widely used on the Internet to enhance security with main objective of unconditional security. Our work is towards the analysis of the QKD in Mobile ad-hoc network (MANET).

Keywords: cryptography, networking, quantum, encryption and decryption

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Authors: S. K. Ashiquer Rahman

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the paper concentrations on the importance of hourly compensation, emphasizing the significance of the unemployment rate. There are the two most important factors of a nation these are its unemployment rate and hourly compensation. These are not merely statistics but they have profound effects on individual, families, and the economy. They are inversely related to one another. When we consider the unemployment rate that will probably decline as hourly compensations in manufacturing rise. But when we reduced the unemployment rates and increased job prospects could result from higher compensation. That’s why, the increased hourly compensation in the manufacturing sector that could have a favorable effect on job changing issues. Moreover, the relationship between hourly compensation and unemployment is complex and influenced by broader economic factors. In this paper, we use panel data regression models to evaluate the expected link between hourly compensation and unemployment rate in order to determine the effect of hourly compensation on unemployment rate. We estimate the fixed effects model, evaluate the error components, and determine which model (the FEM or ECM) is better by pooling all 60 observations. We then analysis and review the data by comparing 3 several countries (United States, Canada and the United Kingdom) using panel data regression models. Finally, we provide result, analysis and a summary of the extensive research on how the hourly compensation effects on the unemployment rate. Additionally, this paper offers relevant and useful informational to help the government and academic community use an econometrics and social approach to lessen on the effect of the hourly compensation on Unemployment rate to eliminate the problem.

Keywords: hourly compensation, Unemployment rate, panel data regression models, dummy variables, random effects model, fixed effects model, the linear regression model

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Authors: Sally Hosny, Mona G. Ibrahim, N. K. Hassan

Abstract:

Fiber reinforced polymers (FRP) is one of the most environmentally method for strengthening and retrofitting steel structure buildings. The behaviour of flexural strengthened steel I-beams using FRP was investigated. The finite element (FE) models were developed using ANSYS® as verification cases to simulate the experimental behaviour of using FRP strips to flexure strengthen steel I-beam. Two experimental studies were selected for verification; first examined the effect of different thicknesses and modulus of elasticity while the second studied the effect of applying different carbon fiber reinforced polymers (CFRP) bond lengths. The proposed FE models were in good agreement with the experimental results in terms of failure modes, load bearing capacities and strain distribution on CFRP strips. The verified FE models can be utilized to conduct a parametric study where various widths (40, 50, 60, 70 and 80 mm), thickness (1.2, 2 and 4 mm) and lengths (1500, 1700 and 1800 mm) of CFRP were analyzed. The results presented clearly revealed that the load bearing capacity was significantly increased (+7%) when the width and thickness were increased. However, load bearing capacity was slightly affected using longer CFRP strips. Moreover, applying another glass fiber reinforced polymers (GFRP) of 1500 mm in length, 50 mm in width and thicknesses of 1.2, 2 and 4 mm were investigated. Load bearing capacity of strengthened I-beams using GFRP is less than CFRP by average 8%. Statistical analysis has been conducted using Minitab®.

Keywords: FRP, strengthened steel I-beams, flexural, FEM, ANSYS

Procedia PDF Downloads 279

Authors: Abderrahmane Soufi

Abstract:

The building sector is the largest consumer of energy in France, accounting for 44% of French consumption. To reduce energy consumption and improve energy efficiency, France implemented an energy transition law targeting 40% energy savings by 2030 in the tertiary building sector. Building simulation tools are used to predict the energy performance of buildings but the reliability of these tools is hampered by discrepancies between the real and simulated energy performance of a building. This performance gap lies in the simplified assumptions of certain factors, such as the behavior of occupants on air conditioning and heating, which is considered deterministic when setting a fixed operating schedule and a fixed interior comfort temperature. However, the behavior of occupants on air conditioning and heating is stochastic, diverse, and complex because it can be affected by many factors. Probabilistic models are an alternative to deterministic models. These models are usually derived from statistical data and express occupant behavior by assuming a probabilistic relationship to one or more variables. In the literature, logistic regression has been used to model the behavior of occupants with regard to heating and air conditioning systems by considering univariate logistic models in residential buildings; however, few studies have developed multivariate models for higher education and vocational training buildings in a Mediterranean climate. Therefore, in this study, occupant behavior on heating and air conditioning systems was modeled using logistic regression. Occupant behavior related to the turn-on heating and air conditioning systems was studied through experimental measurements collected over a period of one year (June 2023–June 2024) in three classrooms occupied by several groups of students in engineering schools and professional training. Instrumentation was provided to collect indoor temperature and indoor relative humidity in 10-min intervals. Furthermore, the state of the heating/air conditioning system (off or on) and the set point were determined. The outdoor air temperature, relative humidity, and wind speed were collected as weather data. The number of occupants, age, and sex were also considered. Logistic regression was used for modeling an occupant turning on the heating and air conditioning systems. The results yielded a proposed model that can be used in building simulation tools to predict the energy performance of teaching buildings. Based on the first months (summer and early autumn) of the investigations, the results illustrate that the occupant behavior of the air conditioning systems is affected by the indoor relative humidity and temperature in June, July, and August and by the indoor relative humidity, temperature, and number of occupants in September and October. Occupant behavior was analyzed monthly, and univariate and multivariate models were developed.

Keywords: occupant behavior, logistic regression, behavior model, mediterranean climate, air conditioning, heating

Procedia PDF Downloads 62

Authors: Trevor E. Davis, Isaac Cassar, Yi-Kai Lo, Wentai Liu

Abstract:

This study models the use of transcutaneous electrical nerve stimulation on skin with a disk electrode in order to simulate tissue damage. The current density distribution above a disk electrode is known to be a dynamic and non-uniform quantity that is intensified at the edges of the disk. The non-uniformity is subject to change through using various electrode geometries or stimulation methods. One of these methods known as edge-retarded stimulation has shown to reduce this edge enhancement. Though progress has been made in modeling the behavior of a disk electrode, little has been done to test the validity of these models in simulating the actual heat transfer from the electrode. This simulation uses finite element software to couple the injection of current from a disk electrode to heat transfer described by the Pennesbioheat transfer equation. An example application of this model is studying an experimental form of stimulation, known as edge-retarded stimulation. The edge-retarded stimulation method will reduce the current density at the edges of the electrode. It is hypothesized that reducing the current density edge enhancement effect will, in turn, reduce temperature change and tissue damage at the edges of these electrodes. This study tests this hypothesis as a demonstration of the capabilities of this model. The edge-retarded stimulation proved to be safer after this simulation. It is shown that temperature change and the fraction of tissue necrosis is much greater in the square wave stimulation. These results bring implications for changes of procedures in transcutaneous electrical nerve stimulation and transcutaneous spinal cord stimulation as well.

Keywords: bioheat transfer, electrode, neuroprosthetics, TENS, transcutaneous stimulation

Procedia PDF Downloads 240