Search results for: deformable part model

Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

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This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

Procedia PDF Downloads 279

Authors: Mohamed M. A. Abumandour

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The red swamp freshwater crayfish breathe through three types of feather-like trichobranchiate gills; podobranchiae, arthrobranchiae and pleurobranchiae. All gills have the same general structure and appearance; plume-like with single broad setiferous, and single axis. The gill consists of axis with numerous finger-like filaments, having three morphological types; round, pointed and somewhat hooked shaped. The direction of filaments vary according their position; in middle region were nearly perpendicular to gill axis while in the apex were nearly parallel to axis. There were characteristic system of gill spines on; central axis (two types were distinguishable by presence of socket), basal plate, setobranch (long non-branched and short multidenticulate) and on the bilobed epipodal plate. There are four shape of spinated-like distal region of setobranch seta; two pointed processes (longitudinal arrangement and irregular arranged) and two broad processes (transverse triangular and multidenticulate). The bilobed epipodal plate devoid from any filaments and extended from outer side of podobranchiae as triangular basal part then extended between the gills as cord-like middle part then pass under the gill to lies against the thoracic body wall. By SEM, the apical part of bilobed epipodal plate have serrated free border and corrugated surface while the middle part have none serrated free border. There are two methods of gill cleaning mechanism in crayfish; passive and active method. The passive method occurred by; setae of setobranch, branchiostegite, bilobed epipodal plate, setiferous arthrodial lamellae and reversing the respiratory water through a narrow spaced branchial chamber.

Keywords: crayfis, gill spines, setobranch, gill setae, cleaning mechanisms

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Authors: A. El Amri, M. El Yakhloufi Haddou, A. Khamlichi

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The numerical simulation based on the Finite Element Method (FEM) is widely used in academic institutes and in the industry. It is a useful tool to predict many phenomena present in the classical manufacturing forming processes such as fracture. But, the results of such numerical model depend strongly on the parameters of the constitutive behavior model. The influences of thermal and mechanical loads cause damage. The temperature and strain rate dependent materials’ properties and their modelling are discussed. A Johnson-Cook Model of damage has been selected for the numerical simulations. Virtual software called the ABAQUS 6.11 is used for finite element analysis. This model was introduced in order to give information concerning crack initiation during thermal and mechanical loads.

Keywords: thermo-mechanical fatigue, failure, numerical simulation, fracture, damage

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Authors: Kholil, Laksanto Utomo

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The food needs of the Indonesian people will continue increase year to year due to the increase of population growth. For ensuring food securityand and resilience, the government has developed a program food self-resilience village since 2006. Food resilience is a complex system, consisting of subsystem availability, distribution and consumption of the sufficiency of food consumed both in quantity and quality. Low access, and limited assets to food sources is the dominant factor vulnerable of food. Women have a major role in supporting the productive activities of the family to meet food sufficiency and resilience. The purpose of this paper is to discuss the model of food self-resilience village wich gender responsive by using a dynamic system model. Model will be developed into 3 level: family, vilage, and regency in accordance with the concept of village food resilience model wich has been developed by ministry of agriculture. Model development based on the results of experts discussion and field study. By some scenarios and simulation models we will able to develop appropriate policy strategies for family food resilience. The result of study show that food resilience was influenced by many factors: goverment policies, technology, human resource, and in the same time it will be a feed back for goverment policies and number of poor family.

Keywords: food availability, food sufficiency, gender, model dynamic, law enfrocement

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Authors: Florina Dutt, Subhajit Das, Matthew Swartz

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Lighting design and its impact on indoor comfort conditions are an integral part of good interior design. Impact of lighting in an interior space is manifold and it involves many sub components like glare, color, tone, luminance, control, energy efficiency, flexibility etc. While other components have been researched and discussed multiple times, this paper discusses the research done to understand the glare component from an artificial lighting source in an indoor space. Consequently, the paper discusses a parametric model to convey real time glare level in an interior space to the designer/ architect. Our end users are architects and likewise for them it is of utmost importance to know what impression the proposed lighting arrangement and proposed furniture layout will have on indoor comfort quality. This involves specially those furniture elements (or surfaces) which strongly reflect light around the space. Essentially, the designer needs to know the ramification of the ‘discomfortable glare’ at the early stage of design cycle, when he still can afford to make changes to his proposed design and consider different routes of solution for his client. Unfortunately, most of the lighting analysis tools that are present, offer rigorous computation and analysis on the back end eventually making it challenging for the designer to analyze and know the glare from interior light quickly. Moreover, many of them do not focus on glare aspect of the artificial light. That is why, in this paper, we explain a novel approach to approximate interior glare data. Adding to that we visualize this data in a color coded format, expressing the implications of their proposed interior design layout. We focus on making this analysis process very fluid and fast computationally, enabling complete user interaction with the capability to vary different ranges of user inputs adding more degrees of freedom for the user. We test our proposed parametric model on a case study, a Computer Lab space in our college facility.

Keywords: computational geometry, glare impact in interior space, info visualization, parametric lighting analysis

Procedia PDF Downloads 350

Authors: Reza Davoodi, Hamid Abbasi, Heidar Norouzi, Gholamabbas Alipourian

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A dynamic model shaping a process of knowledge management (KM) culture change is suggested. It is aimed at providing effective KM of employees for obtaining desired results in an organization. The essential requirements for obtaining KM culture change are determined. The proposed model realizes these requirements. Dynamics of the model are expressed by a change of its parameters. It is adjusted to the dynamic process of KM culture change. Building the model includes elaboration and integration of interconnected components. The “Result” is a central component of the model. This component determines a desired organizational goal and possible directions of its attainment. The “Confront” component engenders constructive confrontation in an organization. For this reason, the employees are prompted toward KM culture change with the purpose of attaining the desired result. The “Assess” component realizes complex assessments of employee proposals by management and peers. The proposals are directed towards attaining the desired result in an organization. The “Reward” component sets the order of assigning rewards to employees based on the assessments of their proposals.

Keywords: knowledge management, organizational culture change, employee, result

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Authors: Thohidul Islam, Md. Hamidul Haque, Robin Kumar Biswas

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Floods are one of the deadliest natural disasters which are very complex to model; however, machine learning is opening the door for more reliable and accurate flood prediction. In this research, a multilayer perceptron neural network (MLP) is developed to model the rainfall-water level relation, in a subtropical monsoon climatic region of the Bangladesh-India border. Our experiments show promising empirical results to forecast the water level for 1 day lead time. Our best performing MLP model achieves 98.7% coefficient of determination with lower model complexity which surpasses previously reported results on similar forecasting problems.

Keywords: flood forecasting, machine learning, multilayer perceptron network, regression

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Authors: Felix Böck

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Nowadays, data about learners and their digital activities are collected, which could help educational institutions to better understand learning processes, improve them and be able to provide better learning assistance. In this research project, custom knowledge- and data-driven recommendation algorithms will be used to offer students in higher education integrated learning assistance. The pre-requisite for this is a learner model that is as comprehensive as possible, which should first be created and then kept up-to-date largely automatically for being able to individualize and personalize the learning experience. In order to create such a learner model, a roadmap is presented that describes the individual phases up to the creation and evaluation of the finished model. The methodological process for the research project is disclosed, and the research question of how learners can be supported in their learning with personalized, customized learning recommendations is explored.

Keywords: research agenda, user model, learner model, higher education, adaptive educational digital learning environments, personalized learning paths, recommendation system, adaptation, personalization

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Authors: Rodolfo Alfonso, David Alonso, Albin Garcia, Jose Luis Alonso

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Recently a new kilovoltage radiotherapy unit model Xstrahl 200 - donated to the INOR´s Department of Radiotherapy (DR-INOR) in the framework of a IAEA's technical cooperation project- has been commissioned. This unit is able to treat shallow and low deep laying lesions, as it provides 8 discrete beam qualities, from 40 to 200 kV. As part of the patient-specific quality assurance program established at DR-INOR for external beam radiotherapy, it has been recommended to implement in vivo dose measurements (IVD), as they allow effectively discovering eventual errors or failures in the radiotherapy process. For that purpose a radio-photoluminescence (RPL) dosimetry system, model XXX, -also donated to DR-INOR by the same IAEA project- has been studied and commissioned. Main dosimetric parameters of the RPL system, such as reproducibility, linearity, and filed size influence were assessed. In a similar way, the response of radiochromic EBT3 type film was investigated for purposes of IVD. Both systems were calibrated in terms of entrance surface dose. Results of the dosimetric commissioning of RPL and EBT3 for IVD, and their pre-clinical implementation through end-to-end test cases are presented. The RPL dosimetry seems more recommendable for hyper-fractionated schemes with larger fields and curved patient contours, as those in chest wall irradiations, where the use of more than one dosimeter could be required. The radiochromic system involves smaller corrections with field size, but it sensibility is lower; hence it is more adequate for hypo-fractionated treatments with smaller fields.

Keywords: glass dosimetry, in vivo dosimetry, kilovotage radiotherapy, radiochromic dosimetry

Procedia PDF Downloads 398

Authors: Anusha P. Wijesundara, Dulap I. Rathnayake, Nihal D. Perera

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Bathymetric information is fundamental importance to coastal and marine planning and management, nautical navigation, and scientific studies of marine environments. Satellite-derived bathymetry data provide detailed information in areas where conventional sounding data is lacking and conventional surveys are inaccessible. The two empirical approaches of log-linear bathymetric inversion model and non-linear bathymetric inversion model are applied for deriving bathymetry from high-resolution multispectral satellite imagery. This study compares these two approaches by means of geographical error analysis for the site Kankesanturai using WorldView-2 satellite imagery. Based on the Levenberg-Marquardt method calibrated the parameters of non-linear inversion model and the multiple-linear regression model was applied to calibrate the log-linear inversion model. In order to calibrate both models, Single Beam Echo Sounding (SBES) data in this study area were used as reference points. Residuals were calculated as the difference between the derived depth values and the validation echo sounder bathymetry data and the geographical distribution of model residuals was mapped. The spatial autocorrelation was calculated by comparing the performance of the bathymetric models and the results showing the geographic errors for both models. A spatial error model was constructed from the initial bathymetry estimates and the estimates of autocorrelation. This spatial error model is used to generate more reliable estimates of bathymetry by quantifying autocorrelation of model error and incorporating this into an improved regression model. Log-linear model (R²=0.846) performs better than the non- linear model (R²=0.692). Finally, the spatial error models improved bathymetric estimates derived from linear and non-linear models up to R²=0.854 and R²=0.704 respectively. The Root Mean Square Error (RMSE) was calculated for all reference points in various depth ranges. The magnitude of the prediction error increases with depth for both the log-linear and the non-linear inversion models. Overall RMSE for log-linear and the non-linear inversion models were ±1.532 m and ±2.089 m, respectively.

Keywords: log-linear model, multi spectral, residuals, spatial error model

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Authors: Nana Adjoah Mbroh, Suares Clovis Oukouomi Noutchie

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Singularly perturbed problems are parameter dependent problems, and they play major roles in the modelling of real-life situational problems in applied sciences. Thus, designing efficient numerical schemes to solve these problems is of much interest since the exact solutions of such problems may not even exist. Generally, singularly perturbed problems are identified by a small parameter multiplying at least the highest derivative in the equation. The presence of this parameter causes the solution of these problems to be characterized by rapid oscillations. This unique feature renders classical numerical schemes inefficient since they are unable to capture the behaviour of the exact solution in the part of the domain where the rapid oscillations are present. In this paper, a numerical scheme is proposed to solve a singularly perturbed Volterra Integro-differential equation. The scheme is based on the midpoint rule and employs the non-standard finite difference scheme to solve the differential part whilst the composite trapezoidal rule is used for the integral part. A fully fledged error estimate is performed, and Richardson extrapolation is applied to accelerate the convergence of the scheme. Numerical simulations are conducted to confirm the theoretical findings before and after extrapolation.

Keywords: midpoint rule, non-standard finite difference schemes, Richardson extrapolation, singularly perturbed problems, trapezoidal rule, uniform convergence

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Authors: Nadish Anand, Richard D. Gould

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A simplistic model is introduced for determining the thermal characteristics of a Low-rise Residential (LRR) building and then predicts the energy usage by its Heating Ventilation & Air Conditioning (HVAC) system according to changes in weather conditions which are reflected in the Ambient Temperature (Outside Air Temperature). The LRR buildings are treated as a simple lump for solving the heat transfer problem and the model is derived using the lumped capacitance model of transient conduction heat transfer from bodies. Since most contemporary HVAC systems have a thermostat control which will have an offset temperature and user defined set point temperatures which define when the HVAC system will switch on and off. The aim is to predict without any error the Body Temperature (i.e. the Inside Air Temperature) which will estimate the switching on and off of the HVAC system. To validate the mathematical model derived from lumped capacitance we have used EnergyPlus simulation engine, which simulates Buildings with considerable accuracy. We have predicted through the low order model the Inside Air Temperature of a single house kept in three different climate zones (Detroit, Raleigh & Austin) and different orientations for summer and winter seasons. The prediction error from the model for the same day as that of model parameter calculation has showed an error of < 10% in winter for almost all the orientations and climate zones. Whereas the prediction error is only <10% for all the orientations in the summer season for climate zone at higher latitudes (Raleigh & Detroit). Possible factors responsible for the large variations are also noted in the work, paving way for future research.

Keywords: building energy, energy consumption, energy+, HVAC, low order model, lumped capacitance

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Authors: Zainab Fadhil Al Toki, Nader Ghareeb

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This study investigates how lightweight a fire resistance door will perform with under types of insulation materials. Data is initially collected from various websites, scientific books and research papers. Results show that different layers of insulation in a single door can perform better than one insulator. Furthermore, insulation materials that are lightweight, high strength and low thermal conductivity are the most preferred for fire-rated doors. Whereas heavy weight, low strength, and high thermal conductivity are least preferred for fire resistance doors. Fire-rated door specifications, theoretical test methodology, structural analysis, and comparison between five different models with diverse layers insulations are presented. Five different door models are being investigated with different insulation materials and arrangements. Model 1 contains an air gap between door layers. Model 2 includes phenolic foam, mild steel and polyurethane. Model 3 includes phenolic foam and glass wool. Model 4 includes polyurethane and glass wool. Model 5 includes only rock wool between the door layers. It is noticed that model 5 is the most efficient model, and its design is simple compared to other models. For this model, numerical calculations are performed to check its efficiency and the results are compared to data from experiments for validation. Good agreement was noticed.

Keywords: fire resistance, insulation, strength, thermal conductivity, lightweight, layers

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Authors: Hamed Hedayatnia, Nathan Van Den Bossche

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Understanding the ways in which climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the conservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like freeze-thaw cycles and wind erosion is also a key parameter when considering mitigating actions. Due to the vulnerability of cultural heritage to climate change, the impact of this phenomenon on material degradation criteria with the focus on brick masonry walls in Timurid heritage, located in Iran, was studied. The Timurids were the final great dynasty to emerge from the Central Asian steppe. Through their patronage, the eastern Islamic world in northwestern of Iran, especially in Mashhad and Herat, became a prominent cultural center. Goharshad Mosque is a mosque in Mashhad of the Razavi Khorasan Province, Iran. It was built by order of Empress Goharshad, the wife of Shah Rukh of the Timurid dynasty in 1418 CE. Choosing an appropriate regional climate model was the first step. The outputs of two different climate model: the 'ALARO-0' and 'REMO,' were analyzed to find out which model is more adopted to the area. For validating the quality of the models, a comparison between model data and observations was done in 4 different climate zones in Iran for a period of 30 years. The impacts of the projected climate change were evaluated until 2100. To determine the material specification of Timurid bricks, standard brick samples from a Timurid mosque were studied. Determination of water absorption coefficient, defining the diffusion properties and determination of real density, and total porosity tests were performed to characterize the specifications of brick masonry walls, which is needed for running HAM-simulations. Results from the analysis showed that the threatening factors in each climate zone are almost different, but the most effective factor around Iran is the extreme temperature increase and erosion. In the north-western region of Iran, one of the key factors is wind erosion. In the north, rainfall erosion and mold growth risk are the key factors. In the north-eastern part, in which our case study is located, the important parameter is wind erosion.

Keywords: brick, climate change, degradation criteria, heritage, Timurid period

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Authors: Kolesnik Nadezda A.

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The research aims to elaborate inter-organizational network relationships management model to maximize value co-creation. We propose a network management framework that requires evaluation of network partners with respect to their position and role in network; and elaboration of appropriate relationship development strategy with partners in network. Empirical research and approval is based on the case study method, including structured in-depth interviews with the companies from b2b market.

Keywords: inter-organizational networks, value co-creation, model, B2B market

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Authors: Phanida Phukoetphim, Asaad Y. Shamseldin

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In this study, the novel Stochastic Gradient Boosting (SGB) combination method is addressed for producing daily river flows from four different rain-runoff models of Ohinemuri catchment, New Zealand. The selected rainfall-runoff models are two empirical black-box models: linear perturbation model and linear varying gain factor model, two conceptual models: soil moisture accounting and routing model and Nedbør-Afrstrømnings model. In this study, the simple average combination method and the weighted average combination method were used as a benchmark for comparing the results of the novel SGB combination method. The models and combination results are evaluated using statistical and graphical criteria. Overall results of this study show that the use of combination technique can certainly improve the simulated river flows of four selected models for Ohinemuri catchment, New Zealand. The results also indicate that the novel SGB combination method is capable of accurate prediction when used in a combination method of the simulated river flows in New Zealand.

Keywords: multi-model combination, rainfall-runoff modeling, stochastic gradient boosting, bioinformatics

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

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Authors: Khaled Mammar

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This paper presents an application of adaptive neuro-fuzzy controller for PEM fuel cell system. The model proposed for control include a fuel cell stack model, reformer model and DC/AC inverter model. Furthermore, a Fuzzy Logic (FLC) and adaptive neuro-fuzzy controllers are used to control the active power of PEM fuel cell system. The controllers modify the hydrogen flow feedback from the terminal load. The validity of the controller is verified when the fuel cell system model is used in conjunction with the ANFIS controller to predict the response of the active power. Simulation results confirmed the high-performance capability of the neuo-fuzzy to control power generation.

Keywords: fuel cell, PEMFC, modeling, simulation, Fuzzy Logic Controller, FLC, adaptive neuro-fuzzy controller, ANFIS

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Authors: A. Ascenso, C. Silveira, B. Augusto, S. Rafael, S. Coelho, J. Ferreira, A. Monteiro, P. Roebeling, A. I. Miranda

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Innovative nature-based solutions (NBSs) can provide answers to the challenges that urban areas are currently facing due to urban densification and extreme weather conditions. The effects of NBSs are recognized and include improved quality of life, mental and physical health and improvement of air quality, among others. Part of the work developed in the scope of the UNaLab project, which aims to guide cities in developing and implementing their own co-creative NBSs, intends to assess the impacts of NBSs on air quality, using Eindhoven city as a case study. The state-of-the-art online air quality modelling system WRF-CHEM was applied to simulate meteorological and concentration fields over the study area with a spatial resolution of 1 km2 for the year 2015. The baseline simulation (without NBSs) was validated by comparing the model results with monitored data retrieved from the Eindhoven air quality database, showing an adequate model performance. In addition, land use changes were applied in a set of simulations to assess the effects of different types of NBSs. Finally, these simulations were compared with the baseline scenario and the impacts of the NBSs were assessed. Reductions on pollutant concentrations, namely for NOx and PM, were found after the application of the NBSs in the Eindhoven study area. The present work is particularly important to support public planners and decision makers in understanding the effects of their actions and planning more sustainable cities for the future.

Keywords: air quality, modelling approach, nature based solutions, urban area

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Authors: Seyed-Mohammad-Kazem Emami, Behrang Saki, Majid Mohammadian

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The wastewater flow field inside a sewage network including pipe and ‎manhole was investigated using a Computational Fluid Dynamics ‎‎(CFD) model. The numerical model is developed by incorporating a ‎rheological model to calculate the viscosity of wastewater fluid by ‎means of open source toolbox OpenFOAM. The rheological ‎properties of prepared wastewater fluid suspensions are first measured ‎using a BrookField LVDVII Pro+ viscometer with an enhanced UL ‎adapter and then correlated the suitable rheological viscosity model ‎values from the measured rheological properties. The results show the ‎significant effects of rheological characteristics of wastewater fluid on ‎the flow domain of sewer system. Results were compared and ‎discussed with the commonly used Newtonian model to evaluate the ‎differences for velocity profile, pressure and shear stress. ‎

Keywords: Non-Newtonian flows, Wastewater, Numerical simulation, Rheology, Sewage Network

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Authors: Taher M. Abou-deif, Esmail M. El-Bialy, Essam E. Khalil

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The paper is devoted to numerically investigating the influence of the air supply outlets geometry on human comfort inside living looms. A computational fluid dynamics model is developed to examine the air flow characteristics of a room with different supply air diffusers. The work focuses on air flow patterns, thermal behavior in the room with few number of occupants. As an input to the full-scale 3-D room model, a 2-D air supply diffuser model that supplies direction and magnitude of air flow into the room is developed. Air distribution effect on thermal comfort parameters was investigated depending on changing the air supply diffusers type, angles and velocity. Air supply diffusers locations and numbers were also investigated. The pre-processor Gambit is used to create the geometric model with parametric features. Commercially available simulation software “Fluent 6.3” is incorporated to solve the differential equations governing the conservation of mass, three momentum and energy in the processing of air flow distribution. Turbulence effects of the flow are represented by the well-developed two equation turbulence model. In this work, the so-called standard k-ε turbulence model, one of the most widespread turbulence models for industrial applications, was utilized. Basic parameters included in this work are air dry bulb temperature, air velocity, relative humidity and turbulence parameters are used for numerical predictions of indoor air distribution and thermal comfort. The thermal comfort predictions through this work were based on ADPI (Air Diffusion Performance Index),the PMV (Predicted Mean Vote) model and the PPD (Percentage People Dissatisfied) model, the PMV and PPD were estimated using Fanger’s model.

Keywords: thermal comfort, Fanger's model, ADPI, energy effeciency

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Authors: Victor Toom

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Albeit it is never possible to anticipate the full range of difficulties after a catastrophe, efforts to identify victims of mass casualty events have become institutionalized and standardized with the aim of effectively and efficiently addressing the many challenges and contingencies. Such ‘disaster victim identification’ (DVI) practices are dependent on the forensic sciences, are subject of national legislation, and are reliant on technical and organizational protocols to mitigate the many complexities in the wake of catastrophe. Apart from such technological, legal and bureaucratic elements constituting a DVI operation, victims’ families and their emotions are also part and parcel of any effort to identify casualties of mass human fatality incidents. Take for example the fact that forensic experts require (antemortem) information from the group of relatives to make identification possible. An identified body or body part is also repatriated to kin. Relatives are thus main stakeholders in DVI operations. Much has been achieved in years past regarding facilitating victims’ families’ issues and their emotions. Yet, how families are dealt with by experts and authorities is still considered a difficult topic. Due to sensitivities and required emphatic interaction with families on the one hand, and the rationalized DVI efforts, on the other hand, there is still scope for improving communication, providing information and meaningful inclusion of relatives in the DVI effort. This paper aims to bridge the standardized world of DVI efforts and families’ experienced realities and makes suggestions to further improve DVI efforts through inclusion of victims’ families. Based on qualitative interviews, the paper narrates involvement and experiences of inter alia DVI practitioners, victims’ families, advocates and clergy in the wake of the 1995 Srebrenica genocide which killed approximately 8,000 men, and the 9/11 in New York City with 2,750 victims. The paper shows that there are several models of including victims’ families into a DVI operation, and it argues for a model of where victims’ families become a partner in DVI operations.

Keywords: disaster victim identification (DVI), victims’ families, social science (qualitative), 9/11 attacks, Srebrenica genocide

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Authors: Arian Ebneyamini, Hoda Azimi, Jules Thibaults, F. Handan Tezel

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In this study, a modification of Hennepe model for pervaporation separation of butanol from aqueous solutions using Polydimethylsiloxane (PDMS) mixed matrix membranes has been introduced and validated by experimental data. The model was compared to the original Hennepe model and few other models which are applicable for membrane gas separation processes such as Maxwell, Lewis Nielson and Pal. Theoretical modifications for non-ideal interface morphology have been offered to predict the permeability in case of interface void, interface rigidification and pore-blockage. The model was in a good agreement with experimental data.

Keywords: butanol, PDMS, modeling, pervaporation, mixed matrix membranes

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Authors: Fethi Bouksila, Magnus Persson, Ronny Berndtsson, Akissa Bahri

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Under salinity conditions, we evaluate the performance of Hilhost (2000) model to predict pore electrical conductivity ECp from dielectric permittivity and bulk electrical conductivity (ECa) using Time and Frequency Domain Reflectometry sensors (TDR, FDR). Using FDR_WET sensor, RMSE of ECp was 4.15 dS m-1. By replacing the standard soil parameter (K0) in Hilhost model by K0-ECa relationship, the RMSE of ECp decreased to 0.68 dS m-1. WET sensor could give similar accuracy to estimate ECp than TDR if calibrated values of K0 were used instead of standard values in Hilhost model.

Keywords: hilhost model, soil salinity, time domain reflectometry, frequency domain reflectometry, dielectric methods

Procedia PDF Downloads 135

Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

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Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Suchitra Sivakumar, Hajime Shingyouchi, Toshinori Okajima, Kyohei Yamaguchi, Jin Kusaka

Abstract:

The progressing need for powertrain electrification calls for more accurate and reliable simulation models. A battery pack serves as the most vital component for energy storage in an electrified powertrain. Hybrid electric vehicles (HEV) do not behave the same way as they age, and there are several environmental factors that account for the degradation of the battery on a system level. Therefore, in this work, a battery model was proposed to study the state of charge (SOC) variation and the internal dynamic changes that contribute to aging and performance degradation in HEV batteries. An equivalent circuit battery model (ECM) is built using MATLAB Simulink to investigate the output characteristics of the lithium-ion battery. The ECM comprises of circuit elements like a voltage source, a series resistor and a parallel RC network connected in series. A parameter estimation study is conducted on the ECM to study the dependencies of the circuit elements with the state of charge (SOC) and the terminal voltage of the battery. The battery model is extended to simulate the temperature dependence of the individual battery cell and the battery pack with the environment. The temperature dependence model accounts for the heat loss due to internal resistance build up in the battery pack during charging, discharging, and due to atmospheric temperature. The model was validated for a lithium-ion battery pack with an independent drive cycle showing a voltage accuracy of 4% and SOC accuracy of about 2%.

Keywords: battery model, hybrid electric vehicle, lithium-ion battery, thermal model

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Authors: Nataliya Venelinova

Abstract:

The paper proposes a new interdisciplinary model of reconsidering the role of mass communication effects by coverage of terrorism. The idea of 4P model is based on the synergy, created by the information strategy of threat, predominantly used by terrorist groups, the effects of mediating the symbolic action of the terrorist attacks or the taking of responsibility of any attacks, and the reshaped public perception for security after the attacks being mass communicated. The paper defines the mass communication cycle of terrorism, which leads not only to re-agenda setting of the societies, but also spirally amplifying the effect of propagating fears by over-informing on terrorism attacks. This finally results in the outlining of the so called 4P-model of information terrorism: mass propaganda, panic, paranoia and pandemic.

Keywords: information terrorism, mass communication cycle, public perception, security

Procedia PDF Downloads 174

Authors: M. A. Ahmed, Sidra A. Shaik

Abstract:

Global and diffuse solar radiation on horizontal surface over seven cities of Sindh namely Karachi, Hyderabad, Chore, Padidan, Nawabshah, Rohri and Jacobabad were carried out using sunshine hour data of the area to assess the feasibility of solar energy utilization at Sindh province. The result obtained shows a variation of direct and diffuse component of solar radiation in summer and winter months in southern Sindh (50% direct and 50% diffuse for Karachi, and Hyderabad) where there is a large variation in direct and diffuse component of solar radiation in summer and winter months in northern region (80% direct and 20% diffuse for Rohri and Jacobabad). In southern Sindh, the contribution of diffuse solar radiation is higher during the monsoon months (July and August). The sky remains clear during September to June. In northern Sindh (Rohri and Jacobabad) the contribution of diffuse solar radiation is low even in monsoon months i,e in July and August. The Kt value for northern Sindh indicates a clear sky. In northern part of the Sindh percentage of diffuse radiation does not exceed more than 20%. The appearance of cloud is rare. From the point of view of power generation, the estimated values indicate that northern part of Sindh has high solar potential while the southern part has low solar potential.

Keywords: global and diffuse solar radiation, solar potential, Province of Sindh, solar radiation studies for power generation

Procedia PDF Downloads 319

Authors: Hung-Chi Chang

Abstract:

For an extended EPQ model with random yield, the existent study revealed that both the disaggregating and consolidating shipment policies for the imperfect quality items are independent of holding cost, and recommended a model with economic benefit by comparing the least total cost for each of the three models investigated. To better capture the real situation, we generalize the existent study to include different holding costs for perfect and imperfect quality items. Through analysis, we show that the above shipment policies are dependent on holding costs. Furthermore, we derive a simple decision rule solely based on the thresholds of problem parameters to select a superior model. The results are illustrated analytically and numerically.

Keywords: consolidating shipments, disaggregating shipments, EPQ, imperfect quality, inventory

Procedia PDF Downloads 376

Authors: Watchareeporn Chaimongkol

Abstract:

In this paper, we compare the statistical measures accuracy of composite forecasting model to estimate automobile customer demand in Thailand. A modified simple exponential smoothing and autoregressive integrate moving average (ARIMA) forecasting model is built to estimate customer demand of passenger cars, instead of using information of historical sales data. Our model takes into account special characteristic of the Thai automobile market such as sales promotion, advertising and publicity, petrol price, and interest rate for loan. We evaluate our forecasting model by comparing forecasts with actual data using six accuracy measurements, mean absolute percentage error (MAPE), geometric mean absolute error (GMAE), symmetric mean absolute percentage error (sMAPE), mean absolute scaled error (MASE), median relative absolute error (MdRAE), and geometric mean relative absolute error (GMRAE).

Keywords: composite forecasting, simple exponential smoothing model, autoregressive integrate moving average model selection, accuracy measurements

Procedia PDF Downloads 362