Search results for: H₂-optimal model reduction

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud Ccomputing, data security, SAAS, PAAS, IAAS, Blowfish

Procedia PDF Downloads 477

Authors: Junling Li, Fang Meng, Yichun Zhang

Abstract:

Image saliency detection has been long studied, while several challenging problems are still unsolved, such as detecting saliency inaccurately in complex scenes or suppressing salient objects in the image borders. In this paper, we propose a new saliency detection algorithm in order to solving these problems. We represent the image as a graph with superixels as nodes. By considering appearance similarity between the boundary and the background, the proposed method chooses non-saliency boundary nodes as background priors to construct the background probability model. The probability that each node belongs to the model is computed, which measures its similarity with backgrounds. Thus we can calculate saliency by the transformed probability as a metric. We compare our algorithm with ten-state-of-the-art salient detection methods on the public database. Experimental results show that our simple and effective approach can attack those challenging problems that had been baffling in image saliency detection.

Keywords: visual saliency, background probability, boundary knowledge, background priors

Procedia PDF Downloads 429

Authors: M. Sumida, S. Morita

Abstract:

In this research, the effect of unsteady flows acting on road vehicles was experimentally investigated, using an advanced and recently introduced wind tunnel. The aims of this study were to extract the characteristics of fluid forces acting on road vehicles under unsteady wind conditions and obtain new information on drag forces in a practical on-road test. We applied pulsating wind as a representative example of the atmospheric fluctuations that vehicles encounter on the road. That is, we considered the case where the vehicles are moving at constant speed in the air, with large wind oscillations. The experimental tests were performed on the Ahmed-type test model, which is a simplified vehicle model. This model was chosen because of its simplicity and the data accumulated under steady wind conditions. The experiments were carried out with a time-averaged Reynolds number of Re = 4.16x10⁵ and a pulsation period of T = 1.5 s, with amplitude of η = 0.235. Unsteady fluid forces of drag and lift were obtained utilizing a multi-component load cell. It was observed that the unsteady aerodynamic forces differ significantly from those under steady wind conditions. They exhibit a phase shift and an enhanced response to the wind oscillations. Furthermore, their behavior depends on the slant angle of the rear shape of the model.

Keywords: Ahmed body, automotive aerodynamics, unsteady wind, wind tunnel test

Procedia PDF Downloads 293

Authors: Kristyna Hrabova, Sabina Hüblova, Tomas Vymazal

Abstract:

Structural design of concrete structure has the result in qualities of structural safety and serviceability, together with durability, robustness, sustainability and resilience. A sustainable approach is at the heart of the research agenda around the world, and the Fibrillation Commission is also working on a new model code 2020. Now it is clear that the effects of mechanical, environmental load and even social coherence need to be reflected and included in the designing and evaluating structures. This study aimed to present the methodology for the sustainability assessment of various concrete mixtures.

Keywords: concrete, cement, sustainability, Model Code 2020

Procedia PDF Downloads 178

Authors: Adeep Hande, Shubham Agarwal

Abstract:

This paper presents a study on identifying sexism in online texts using various state-of-the-art deep learning models based on BERT. We experimented with different feature sets and model architectures and evaluated their performance using precision, recall, F1 score, and accuracy metrics. We also explored the use of pseudolabeling technique to improve model performance. Our experiments show that the best-performing models were based on BERT, and their multilingual model achieved an F1 score of 0.83. Furthermore, the use of pseudolabeling significantly improved the performance of the BERT-based models, with the best results achieved using the pseudolabeling technique. Our findings suggest that BERT-based models with pseudolabeling hold great promise for identifying sexism in online texts with high accuracy.

Keywords: large language models, semi-supervised learning, sexism detection, data sparsity

Procedia PDF Downloads 70

Authors: Taehan Bae

Abstract:

In this paper, a class of length-biased Weibull mixtures is presented to model loss severity data. The proposed model generalizes the Erlang mixtures with the common scale parameter, and it shares many important modelling features, such as flexibility to fit various data distribution shapes and weak-denseness in the class of positive continuous distributions, with the Erlang mixtures. We show that the asymptotic tail estimate of the length-biased Weibull mixture is Weibull-type, which makes the model effective to fit loss severity data with heavy-tailed observations. A method of statistical estimation is discussed with applications on real catastrophic loss data sets.

Keywords: Erlang mixture, length-biased distribution, transformed gamma distribution, asymptotic tail estimate, EM algorithm, expectation-maximization algorithm

Procedia PDF Downloads 224

Authors: Huazhen Lin, Ruihua Xu, Zhibin Jiang

Abstract:

In this real-world case, timetabling the LRT network as a whole is rather challenging for the operator: they are supposed to create a timetable to avoid various route conflicts manually while satisfying a given interval and the number of rolling stocks, but the outcome is not satisfying. Therefore, the operator adopts a computerised timetabling tool, the Train Plan Maker (TPM), to cope with this problem. However, with various constraints in the dual-line network, it is still difficult to find an adequate pairing of turnback time, interval and rolling stocks’ number, which requires extra manual intervention. Aiming at current problems, a one-off model for timetabling is presented in this paper to simplify the procedure of timetabling. Before the timetabling procedure starts, this paper presents how the dual-line system with a ring and several branches is turned into a simpler structure. Then, a non-linear programming model is presented in two stages. In the first stage, the model sets a series of constraints aiming to calculate a proper timing for coordinating two lines by adjusting the turnback time at termini. Then, based on the result of the first stage, the model introduces a series of inequality constraints to avoid various route conflicts. With this model, an analysis is conducted to reveal the relation between the ratio of trains in different directions and the possible minimum interval, observing that the more imbalance the ratio is, the less possible to provide frequent service under such strict constraints.

Keywords: light rail transit (LRT), non-linear programming, railway timetabling, timetable coordination

Procedia PDF Downloads 88

Authors: Pascal Mwenge, Tumisang Seodigeng

Abstract:

The combination of world population and the third industrial revolution led to high demand for fuels. On the other hand, the decrease of global fossil 8fuels deposits and the environmental air pollution caused by these fuels has compounded the challenges the world faces due to its need for energy. Therefore, new forms of environmentally friendly and renewable fuels such as biodiesel are needed. The primary analytical techniques for methanolysis yield monitoring have been chromatography and spectroscopy, these methods have been proven reliable but are more demanding, costly and do not provide real-time monitoring. In this work, the in situ monitoring of biodiesel from sunflower oil using FTIR (Fourier Transform Infrared) has been studied; the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of methanolysis was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. 15 samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centering and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R² value of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor methanol of sunflower oil at industrial and lab scale.

Keywords: biodiesel, calibration, chemometrics, methanolysis, multivariate analysis, transesterification, FTIR

Procedia PDF Downloads 149

Authors: Kwok W. Mui, Ling T. Wong, Chi T. Cheung

Abstract:

Cooling energy consumption in the residential sector, different from shopping mall, office or commercial buildings, is significantly subject to occupant decisions where in-depth investigations are found limited. It shows that energy consumptions could be associated with housing types. Surveys have been conducted in existing Hong Kong public housings to understand the housing characteristics, apartment electricity demands, occupant’s thermal expectations, and air–conditioning usage patterns for further cooling energy-saving assessments. The aim of this study is to develop a hybrid cooling energy prediction model, which integrated by EnergyPlus (EP) and artificial neural network (ANN) to estimate cooling energy consumption in public residential sector. Sensitivity tests are conducted to find out the energy impacts with changing building parameters regarding to external wall and window material selection, window size reduction, shading extension, building orientation and apartment size control respectively. Assessments are performed to investigate the relationships between cooling demands and occupant behavior on thermal environment criteria and air-conditioning operation patterns. The results are summarized into a cooling energy calculator for layman use to enhance the cooling energy saving awareness in their own living environment. The findings can be used as a directory framework for future cooling energy evaluation in residential buildings, especially focus on the occupant behavioral air–conditioning operation and criteria of energy-saving incentives.

Keywords: artificial neural network, cooling energy, occupant behavior, residential buildings, thermal environment

Procedia PDF Downloads 168

Authors: Ma Cecilia Siva

Abstract:

This study introduces a Bidirectional Encoder Representations from Transformers (BERT)-based machine learning model aimed at improving educational counseling by automating the process of recommending academic strands for students. The framework is designed to streamline and enhance the strand selection process by analyzing students' profiles and suggesting suitable academic paths based on their interests, strengths, and goals. Data was gathered from a sample of 200 grade 10 students, which included personal essays and survey responses relevant to strand alignment. After thorough preprocessing, the text data was tokenized, label-encoded, and input into a fine-tuned BERT model set up for multi-label classification. The model was optimized for balanced accuracy and computational efficiency, featuring a multi-category classification layer with sigmoid activation for independent strand predictions. Performance metrics showed an F1 score of 88%, indicating a well-balanced model with precision at 80% and recall at 100%, demonstrating its effectiveness in providing reliable recommendations while reducing irrelevant strand suggestions. To facilitate practical use, the final deployment phase created a recommendation framework that processes new student data through the trained model and generates personalized academic strand suggestions. This automated recommendation system presents a scalable solution for academic guidance, potentially enhancing student satisfaction and alignment with educational objectives. The study's findings indicate that expanding the data set, integrating additional features, and refining the model iteratively could improve the framework's accuracy and broaden its applicability in various educational contexts.

Keywords: tokenized, sigmoid activation, transformer, multi category classification

Procedia PDF Downloads 9

Authors: Miled Amel, Ben Maad Hatem, Askri Faouzi, Ben Nasrallah Sassi

Abstract:

Metal hydride water pumping system uses hydrogen as working fluid to pump water for low head and high discharge. The principal operation of this pump is based on the desorption of hydrogen at high pressure and its absorption at low pressure by a metal hydride. This work is devoted to study a concept of the dynamic behavior of a metal hydride pump using unsteady model and LaNi5 as hydriding alloy. This study shows that with MHP, it is possible to pump 340l/kg-cycle of water in 15 000s using 1 Kg of LaNi5 at a desorption temperature of 360 K, a pumping head equal to 5 m and a desorption gear ratio equal to 33. This study reveals also that the error given by the steady model, using LaNi5 is about 2%.A dimensional mathematical model and the governing equations of the pump were presented to predict the coupled heat and mass transfer within the MHP. Then, a numerical simulation is carried out to present the time evolution of the specific water discharge and to test the effect of different parameters (desorption temperature, absorption temperature, desorption gear ratio) on the performance of the water pumping system (specific water discharge, pumping efficiency and pumping time). In addition, a comparison between results obtained with steady and unsteady model is performed with different hydride mass. Finally, a geometric configuration of the reactor is simulated to optimize the pumping time.

Keywords: dynamic behavior, LaNi5, performance of water pumping system, unsteady model

Procedia PDF Downloads 205

Authors: Maria Laura Alzua, Maria Adelaida Lopera

Abstract:

This paper measures the relative importance of conditional cooperation and unconditional cooperation in a large public goods experiment conducted in Mali. We use expectations about total public goods provision to estimate a structural choice model with heterogeneous preferences. While unconditional cooperation can be captured by common preferences shared by all participants, conditional cooperation is much more heterogeneous and depends on unobserved individual factors. This structural model, in combination with two experimental treatments, suggests that leadership and group communication incentivize public goods provision through different channels. First, We find that participation of local leaders effectively changes individual choices through unconditional cooperation. A simulation exercise predicts that even in the most pessimistic scenario in which all participants expect zero public good provision, 60% would still choose to cooperate. Second, allowing participants to communicate fosters conditional cooperation. The simulations suggest that expectations are responsible for around 24% of the observed public good provision and that group communication does not necessarily ameliorate public good provision. In fact, communication may even worsen the outcome when expectations are low.

Keywords: conditional cooperation, discrete choice model, expectations, public goods game, random coefficients model

Procedia PDF Downloads 306

Authors: Aguasanta M. Sarmiento, Jose Miguel Davila, Juan Carlos Fortes, Maria Luisa de la Torre

Abstract:

Acid mine drainage (AMD) is an acidic leachate with high levels of metals and sulphates in solution, which seriously affects the durability and strength of metallic materials used in the construction of structural and mechanical components. This paper presents the results of the evolution over time of the reduction in tensile strength and defects in AISI 304 stainless steel in contact with acid mine drainage. For this purpose, a total of 30 bars with a diameter of 8 mm and a length of 14 cm were placed transversely in the course of a stream contaminated by AMD from the sulphide mines of the Iberian Pyritic Belt (SW Spain). This stream has average pH values of 2.6, a potential of 660 mV and average concentrations of 12 g/L of sulphates, 1.2 g/L of Fe, 191 mg/L of Zn, etc. Every two months of exposure, 6 stainless steel bars were extracted from the acid stream. They were subjected to surface roughness analysis carried out with the help of Mitutoyo Surftest SJ-210 surface roughness tester. The analysis was carried out at three different points on 5 specimens from each series. The average reading of each parameter is calculated in order to ensure the accuracy of the measurements and the surface coverage. Arithmetic mean roughness value (Ra), mean roughness depth (Rz) and root mean square roughness (Rq) were measured. Five specimens from each series were statically tensile tested using universal equipment (Servosis ME 403 of 200kN). The specimens were clamped at their ends with two grips for cylindrical sections, and the tensile force was applied at a constant speed of 0.5 kN/s, according to the requirements of standard UNE-EN ISO 6892-1: 2020. To determine the modulus of elasticity, limits close to 15% and 55% of the maximum load were used, depending on the course of each test. Field Emission Scanning Electron Microscopy (FESEM) was used to observe corrosion products and defects generated by exposure to AMD. Energy dispersive X-ray spectrometry (EDS) was used to analyze the chemical composition of the corrosion products formed. For this purpose, small pieces were cut from the resulting specimens, cleaned and embedded in epoxy resin. The results show that after only 5 months of exposure of AISI 304 stainless steel to the mining environment, the surface roughness increases significantly, with average depths almost 6 times greater than the initial one. Cracks are observed on the surface of the material, which increases in size with the time of exposure. A large number of grains with a composition of more than 57% Pb and 16% Sn can be observed inside these cracks. Tensile tests show a reduction in the resistance of this material after only two months of exposure. The results show the serious problems that would result from the use of this material for the use of mechanical components in a sulphide mining environment, not only because of the significant reduction in the lifetime of such components but also because of the implications for human safety.

Keywords: Acid mine drainage, Corrosion, Mechanical properties, Stainless steel

Procedia PDF Downloads 9

Authors: Alexander Buhr, Klaus Ehrenfried

Abstract:

Trackside induced airflow velocities, also known as slipstream velocities, are an important criterion for the design of high-speed trains. The maximum permitted values are given by the Technical Specifications for Interoperability (TSI) and have to be checked in the approval process. For train manufactures it is of great interest to know in advance, how new train geometries would perform in TSI tests. The Reynolds number in moving model experiments is lower compared to full-scale. Especially the limited model length leads to a thinner boundary layer at the rear end. The hypothesis is that the boundary layer rolls up to characteristic flow structures in the train wake, in which the maximum flow velocities can be observed. The idea is to enlarge the boundary layer using roughness elements at the train model head so that the ratio between the boundary layer thickness and the car width at the rear end is comparable to a full-scale train. This may lead to similar flow structures in the wake and better prediction accuracy for TSI tests. In this case, the design of the roughness elements is limited by the moving model rig. Small rectangular roughness shapes are used to get a sufficient effect on the boundary layer, while the elements are robust enough to withstand the high accelerating and decelerating forces during the test runs. For this investigation, High-Speed Particle Image Velocimetry (HS-PIV) measurements on an ICE3 train model have been realized in the moving model rig of the DLR in Göttingen, the so called tunnel simulation facility Göttingen (TSG). The flow velocities within the boundary layer are analysed in a plain parallel to the ground. The height of the plane corresponds to a test position in the EN standard (TSI). Three different shapes of roughness elements are tested. The boundary layer thickness and displacement thickness as well as the momentum thickness and the form factor are calculated along the train model. Conditional sampling is used to analyse the size and dynamics of the flow structures at the time of maximum velocity in the train wake behind the train. As expected, larger roughness elements increase the boundary layer thickness and lead to larger flow velocities in the boundary layer and in the wake flow structures. The boundary layer thickness, displacement thickness and momentum thickness are increased by using larger roughness especially when applied in the height close to the measuring plane. The roughness elements also cause high fluctuations in the form factors of the boundary layer. Behind the roughness elements, the form factors rapidly are approaching toward constant values. This indicates that the boundary layer, while growing slowly along the second half of the train model, has reached a state of equilibrium.

Keywords: boundary layer, high-speed PIV, ICE3, moving train model, roughness elements

Procedia PDF Downloads 306

Authors: Safaa S. Hassan, Mohammed H. Elbakry, Safwat A. Mangoura, Zainab M. Omar

Abstract:

Background: Liver fibrosis is the main reason for increased mortality in chronic liver disease. It has no standard treatment. Antioxidants from a variety of sources are capable of slowing or preventing oxidation of other molecules. Aim: to evaluate the hepatoprotective effect of vit. C, vit. E and gallic acid in comparison to silymarin in the rat model of carbon tetrachloride induced liver fibrosis and their possible mechanisms of action. Material& Methods: A total number of 60 adult male albino rats 160-200gm were divided into six equal groups; received subcutaneous (s.c) injection for 8 weeks. Group I: as control. Group II: received 1.5 mL/kg of CCL4 .Group III: CCL4 and co- treatment with silymarin 100mg/kg p.o. daily. Group IV: CCL4 and co-treatment with vit. C 50mg/kg p.o. daily. Group V: CCL4 and co-treatment with vit. E 200mg/kg. p.o. Group VI: CCL4 and co-treatment with Gallic acid 100mg/kg. p.o. daily. Liver was processed for histological and immunohistochemical examination. Levels of AST, ALT, ALP, reduced GSH, MDA, SOD and hydroxyproline concentration were measured and evaluated statistically. Results: Light and electron microscopic examination of liver of group II exhibited foci of altered cells with dense nuclei and vacuolated, granular cytoplasm, mononuclear cell infiltration in portal areas, profuse collagen fiber deposits were found around portal tract, more intense staining α-SMA-positive cells occupied most of the liver fibrosis tissue, electron lucent areas in the cytoplasm of the hepatocytes, margination of nuclear chromatin. Treatment by any of the antioxidants variably reduced the hepatic structural changes induced by CCL4. Biochemical analysis showed that carbon tetrachloride significantly increased the levels of serum AST, ALT, ALP, hepatic malondialdehyde and hydroxyproline content. Moreover, it decreased the activities of superoxide dismutase and glutathione. Treatment with silymarin, gallic acid, vit. C and vit. E decreased significantly the AST, ALT, and ALP levels in plasma, MDA and hydroxyproline and increased the activities of SOD and glutathione in liver tissue. The effect of administration of CCl4 was improved with the used antioxidants in variable degrees. The most efficient antioxidant was silymarin followed by gallic acid and vit. C then vit. E. It is possibly due to their antioxidant effect, free radical scavenging properties and the reduction of oxidant dependent activation and proliferation of HSCs. Conclusion: So these antioxidants can be a promising drugs candidate for ameliorating liver fibrosis better than the use of the drugs and their side effects.

Keywords: antioxidant, ccl4, gallic acid, liver fibrosis

Procedia PDF Downloads 272

Authors: Karthiyayini Nagarajan, P. V. Ramakrishna

Abstract:

Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar (SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System (Lab Bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench, imaging engineering

Procedia PDF Downloads 498

Authors: Chang-Hui Shen, Paulina Konarzewska

Abstract:

Cell homeostasis is regulated by vacuolar activity and it has been shown that lipid composition of the vacuole plays an important role in vacuolar function. The major phosphoinositide species present in the vacuolar membrane include phosphatidylinositol 3,5-biphosphate (PI(3,5)P₂) which is generated from PI(3)P controlled by Fab1p. Deletion of FAB1 gene reduce the synthesis of PI(3,5)P₂ and thus result in enlarged or fragmented vacuoles, with neutral vacuolar pH due to reduced vacuolar H⁺-ATPase activity. These mutants also exhibited poor growth at high extracellular pH and in the presence of CaCl₂. Conversely, VPS34 regulates the synthesis of PI(3)P from phosphatidylinositol (PI), and the lack of Vps34p results in the reduction of vacuolar activity. Although the cellular observations are clear, it is still unknown about the molecular mechanism between the phospholipid biosynthesis pathway and vacuolar activity. Since both VPS34 and FAB1 are important in vacuolar activity, we hypothesize that the molecular mechanism of vacuolar function might be regulated by the transcriptional regulators of phospholipid biosynthesis. In this study, we study the role of the major phospholipid biosynthesis transcription factor, INO2, in the regulation of vacuolar activity. We first performed qRT-PCR to examine the effect of Ino2p on the expression of VPS34 and FAB1. Our results showed that VPS34 was upregulated in the presence of inositol for both WT and ino2Δ cells. However, FAB1 was only upregulated significantly in ino2Δ cells. This indicated that Ino2p might be the negative regulator for FAB1 expression. Next, growth sensitivity experiment showed that WT, vma3Δ, and ino2Δ grew well in growth medium buffered to pH 5.5 containing 10 mM CaCl₂. As cells were switched to growth medium buffered to pH 7 containing CaCl₂ WT, ino2Δ and opi1Δ showed growth reduction, whereas vma3Δ was completely nonviable. As the concentration of CaCl₂ was increased to 60 mM, ino2Δ cells showed moderate growth reduction compared to WT. This result suggests that ino2Δ cells have better vacuolar activity. Microscopic analysis and vacuolar acidification were employed to further elucidate the importance of INO2 in vacuolar homeostasis. Analysis of vacuolar morphology indicated that WT and vma3Δ cells displayed vacuoles that occupied a small area of the cell when grown in media buffered to pH 5.5. Whereas, ino2Δ displayed fragmented vacuoles. On the other hand, all strains grown in media buffered to pH 7, exhibited enlarged vacuoles that occupied most of the cell’s surface. This indicated that the presence of INO2 may play negative effect in vacuolar morphology when cells are grown in media buffered to pH 5.5. Furthermore, vacuolar acidification assay showed that only vma3Δ cells displayed notably less acidic vacuoles as cells were grown in media buffered to pH 5.5 and pH 7. Whereas, ino2Δ cells displayed more acidic pH compared to WT at pH7. Taken together, our results demonstrated the molecular mechanism of the vacuolar activity regulated by the phospholipid biosynthesis transcription factors Ino2p. Ino2p negatively regulates vacuolar activity through the expression of FAB1.

Keywords: vacuole, phospholipid, homeostasis, Ino2p, FAB1

Procedia PDF Downloads 127

Authors: Ammatu Alhassan

Abstract:

Quality healthcare delivery is a crucial indicator in assessing the overall developmental status of a country. There are many limitations in the Ghanaian healthcare supply chain due to the lack of studies about the correlation between quality health service and the healthcare supply chain. Patients who visit various healthcare providers face unpleasant experiences such as delays in the availability of their medications. In this study, an assessment of the quality of services provided to Ghanaian outpatients who visit public healthcare providers was investigated to establish its effect on the healthcare supply chain using a conceptual model. The Donabedian’s structure, process, and outcome theory for service quality evaluation were used to analyse 20 Ghanaian hospitals. The data obtained was tested using the structural equation model (SEM). The findings from this research will help us to improve the overall quality of the Ghanaian healthcare supply chain. The model which will be developed will help us to understand better the linkage between quality healthcare and the healthcare supply chain as well as serving as a reference tool for future healthcare research in Ghana.

Keywords: Ghana, healthcare, outpatients, supply chain

Procedia PDF Downloads 186

Authors: Sunday B. Alabi, Edikan P. Felix, Aniediong M. Umo

Abstract:

Crystal size distribution is of great importance in the sugar factories. It determines the market value of granulated sugar and also influences the cost of production of sugar crystals. Typically, sugar is produced using fed-batch vacuum evaporative crystallizer. The crystallization quality is examined by crystal size distribution at the end of the process which is quantified by two parameters: the average crystal size of the distribution in the mean aperture (MA) and the width of the distribution of the coefficient of variation (CV). Lack of real-time measurement of the sugar crystal size hinders its feedback control and eventual optimisation of the crystallization process. An attractive alternative is to use a soft sensor (model-based method) for online estimation of the sugar crystal size. Unfortunately, the available models for sugar crystallization process are not suitable as they do not contain variables that can be measured easily online. The main contribution of this paper is the development of a regression model for estimating the sugar crystal size as a function of input variables which are easy to measure online. This has the potential to provide real-time estimates of crystal size for its effective feedback control. Using 7 input variables namely: initial crystal size (Lo), temperature (T), vacuum pressure (P), feed flowrate (Ff), steam flowrate (Fs), initial super-saturation (S0) and crystallization time (t), preliminary studies were carried out using Minitab 14 statistical software. Based on the existing sugar crystallizer models, and the typical ranges of these 7 input variables, 128 datasets were obtained from a 2-level factorial experimental design. These datasets were used to obtain a simple but online-implementable 6-input crystal size model. It seems the initial crystal size (Lₒ) does not play a significant role. The goodness of the resulting regression model was evaluated. The coefficient of determination, R² was obtained as 0.994, and the maximum absolute relative error (MARE) was obtained as 4.6%. The high R² (~1.0) and the reasonably low MARE values are an indication that the model is able to predict sugar crystal size accurately as a function of the 6 easy-to-measure online variables. Thus, the model can be used as a soft sensor to provide real-time estimates of sugar crystal size during sugar crystallization process in a fed-batch vacuum evaporative crystallizer.

Keywords: crystal size, regression model, soft sensor, sugar, vacuum evaporative crystallizer

Procedia PDF Downloads 208

Authors: José M Martín-Moreno, Rafaela Pérez, Jesús Ruiz

Abstract:

In this paper we use a small open economy Dynamic Stochastic General Equilibrium Model (DSGE) for the Spanish economy to search for a deeper characterization of the determinants of Spain’s macroeconomic fluctuations throughout the period 1970-2008. In order to do this, we distinguish between tradable and non-tradable goods to take into account the fact that the presence of non-tradable goods in this economy is one of the largest in the world. We estimate a DSGE model with supply and demand shocks (sectorial productivity, public spending, international real interest rate and preferences) using Kalman Filter techniques. We find the following results. First of all, our variance decomposition analysis suggests that 1) the preference shock basically accounts for private consumption volatility, 2) the idiosyncratic productivity shock accounts for non-tradable output volatility, and 3) the sectorial productivity shock along with the international interest rate both greatly account for tradable output. Secondly, the model closely replicates the time path observed in the data for the Spanish economy and finally, the model captures the main cyclical qualitative features of this economy reasonably well.

Keywords: business cycle, DSGE models, Kalman filter estimation, small open economy

Procedia PDF Downloads 416

Authors: Shen Jian, Hu Jie, Qi Jin, Liu Wei Jie, Chen Ji Yi, Peng Ying Hong

Abstract:

In order to settle the problem of acquiring case in biological related to design problems, a biometrics instance acquisition method based on text mining is presented. Through the construction of corpus text vector space and knowledge mining, the feature selection, similarity measure and case retrieval method of text in the field of biology are studied. First, we establish a vector space model of the corpus in the biological field and complete the preprocessing steps. Then, the corpus is retrieved by using the vector space model combined with the functional keywords to obtain the biological domain examples related to the design problems. Finally, we verify the validity of this method by taking the example of text.

Keywords: text mining, vector space model, feature selection, biologically inspired design

Procedia PDF Downloads 262

Authors: Ayelet Siman-Tov, Shlomo Kaniel

Abstract:

Objectives: The research validates a multivariate model that predicts parental adjustment to coping successfully with an autistic child. The model comprises four elements: parental stress, parental resources, parental adjustment and the child's autism symptoms. Background and aims: The purpose of the current study is the construction and validation of a model for the adjustment of parents and a child with autism. The suggested model is based on theoretical views on stress and links personal resources, stress, perception, parental mental health and quality of marriage and child adjustment with autism. The family stress approach focuses on the family as a system made up of a dynamic interaction between its members, who constitute interdependent parts of the system, and thus, a change in one family member brings about changes in the processes of the entire family system. From this perspective, a rise of new demands in the family and stress in the role of one family member affects the family system as a whole. Materials and methods: 176 parents of children aged between 6 to 16 diagnosed with ASD answered several questionnaires measuring parental stress, personal resources (sense of coherence, locus of control, social support), adjustment (mental health and marriage quality) and the child's autism symptoms. Results: Path analysis showed that a sense of coherence, internal locus of control, social support and quality of marriage increase the ability to cope with the stress of parenting an autistic child. Directions for further research are suggested.

Keywords: stress, adjustment, resources, Autism, parents, coherence

Procedia PDF Downloads 140

Authors: Jyoti Sahu, Vinay A. Juvekar

Abstract:

Electrolytes are often used to bring about salting-in and salting-out of organic molecules and polymers (e.g. polyethylene glycols/proteins) from the aqueous solutions. For quantification of these phenomena, a thermodynamic model which can accurately predict activity coefficient of electrolyte as a function of temperature is needed. The thermodynamics models available in the literature contain a large number of empirical parameters. These parameters are estimated using lower/upper critical solution temperature of the solution in the electrolyte/organic molecule at different temperatures. Since the number of parameters is large, inaccuracy can bethe creep in during their estimation, which can affect the reliability of prediction beyond the range in which these parameters are estimated. Cloud point of solution is related to its free energy through temperature and composition derivative. Hence, the Cloud point measurement can be used for accurate estimation of the temperature and composition dependence of parameters in the model for free energy. Hence, if we use a two pronged procedure in which we first use cloud point of solution to estimate some of the parameters of the thermodynamic model and determine the rest using osmotic coefficient data, we gain on two counts. First, since the parameters, estimated in each of the two steps, are fewer, we achieve higher accuracy of estimation. The second and more important gain is that the resulting model parameters are more sensitive to temperature. This is crucial when we wish to use the model outside temperatures window within which the parameter estimation is sought. The focus of the present work is to prove this proposition. We have used electrolyte (NaCl/Na2CO3)-water-organic molecule (Iso-propanol/ethanol) as the model system. The model of Robinson-Stokes-Glukauf is modified by incorporating the temperature dependent Flory-Huggins interaction parameters. The Helmholtz free energy expression contains, in addition to electrostatic and translational entropic contributions, three Flory-Huggins pairwise interaction contributions viz., and (w-water, p-polymer, s-salt). These parameters depend both on temperature and concentrations. The concentration dependence is expressed in the form of a quadratic expression involving the volume fractions of the interacting species. The temperature dependence is expressed in the form .To obtain the temperature-dependent interaction parameters for organic molecule-water and electrolyte-water systems, Critical solution temperature of electrolyte -water-organic molecules is measured using cloud point measuring apparatus The temperature and composition dependent interaction parameters for electrolyte-water-organic molecule are estimated through measurement of cloud point of solution. The model is used to estimate critical solution temperature (CST) of electrolyte water-organic molecules solution. We have experimentally determined the critical solution temperature of different compositions of electrolyte-water-organic molecule solution and compared the results with the estimates based on our model. The two sets of values show good agreement. On the other hand when only osmotic coefficients are used for estimation of the free energy model, CST predicted using the resulting model show poor agreement with the experiments. Thus, the importance of the CST data in the estimation of parameters of the thermodynamic model is confirmed through this work.

Keywords: concentrated electrolytes, Debye-Hückel theory, interaction parameters, Robinson-Stokes-Glueckauf model, Flory-Huggins model, critical solution temperature

Procedia PDF Downloads 392

Authors: Mohamed Boullouz, Mohamed Louay Metougui

Abstract:

Accurate modeling of greenhouse gas (GHG) emissions, crop growth, soil productivity, and biochemical processes is crucial considering escalating global concerns about climate change and the urgent need to improve agricultural sustainability. The application of the denitrification-disintegration (DNDC) model in the context of Morocco's unique agro-climate is thoroughly investigated in this study. Our main research hypothesis is that the DNDC model offers an effective and powerful tool for precisely simulating a wide range of significant parameters, including greenhouse gas emissions, crop growth, yield potential, and complex soil biogeochemical processes, all consistent with the intricate features of environmental Moroccan agriculture. In order to verify these hypotheses, a vast amount of field data covering Morocco's various agricultural regions and encompassing a range of soil types, climatic factors, and crop varieties had to be gathered. These experimental data sets will serve as the foundation for careful model calibration and subsequent validation, ensuring the accuracy of simulation results. In conclusion, the prospective research findings add to the global conversation on climate-resilient agricultural practices while encouraging the promotion of sustainable agricultural models in Morocco. A policy architect's and an agricultural actor's ability to make informed decisions that not only advance food security but also environmental stability may be strengthened by the impending recognition of the DNDC model as a potent simulation tool tailored to Moroccan conditions.

Keywords: greenhouse gas emissions, DNDC model, sustainable agriculture, Moroccan cropping systems

Procedia PDF Downloads 65

Authors: Karthiyayini Nagarajan, P. V. RamaKrishna

Abstract:

Radar Imaging techniques provides extensive applications in the field of remote sensing, majorly Synthetic Aperture Radar(SAR) that provide high resolution target images. This paper work puts forward the effective and realizable signal generation and processing for SAR images. The major units in the system include camera, signal generation unit, signal processing unit and display screen. The real radio channel is replaced by its mathematical model based on optical image to calculate a reflected signal model in real time. Signal generation realizes the algorithm and forms the radar reflection model. Signal processing unit provides range and azimuth resolution through matched filtering and spectrum analysis procedure to form radar image on the display screen. The restored image has the same quality as that of the optical image. This SAR imaging system has been designed and implemented using MATLAB and Quartus II tools on Stratix III device as a System(lab bench) that works in real time to study/investigate on radar imaging rudiments and signal processing scheme for educational and research purposes.

Keywords: synthetic aperture radar, radio reflection model, lab bench

Procedia PDF Downloads 468

Authors: Lei Chen, Jian Jiao, Tingdi Zhao

Abstract:

Failures of automotive electric/electronic systems, which are universally considered to be safety-critical and software-intensive, may cause catastrophic accidents. Analysis and verification of failures in these kinds of systems is a big challenge with increasing system complexity. Model-checking is often employed to allow formal verification by ensuring that the system model conforms to specified safety properties. The system-level effects of failures are established, and the effects on system behavior are observed through the formal verification. A hazard analysis technique, called Systems-Theoretic Process Analysis, is capable of identifying design flaws which may cause potential failure hazardous, including software and system design errors and unsafe interactions among multiple system components. This paper provides a concept on how to use model-checking integrated with Systems-Theoretic Process Analysis to perform failure analysis and verification of automotive electric/electronic systems. As a result, safety requirements are optimized, and failure propagation paths are found. Finally, an automotive electric/electronic system case study is used to verify the effectiveness and practicability of the method.

Keywords: failure analysis and verification, model checking, system-theoretic process analysis, automotive electric/electronic system

Procedia PDF Downloads 122

Authors: Amit Saraswat, Ruchi Tewari

Abstract:

Purpose: The research paper aims at understanding the alignment of business and IT in the Indian context and the business value attached to such an alignment. Methodology: The study is conducted in two stages. Stage one: Bibliographic research was conducted to evolve the parameters for defining alignment. Stage two: Evolving a model for strategic alignment to conduct an empirical study. The model is defined in terms of four fundamental domains of strategic management choice – business strategy, information strategy, organizational structure, and information technology structure. A survey through a questionnaire was conducted across organizations from 4 different industries and Structure Equation Modelling (SEM) technique is used for validating the model. Findings: In the Indian scenario all the subscales of alignment could not be validated. It could be validated that organizational strategy impacts information strategy and information technology structure. Research Limitations: The study is limited to the Indian context. Business IT alignment may be culture dependent so further research is required to validate the model in other cultures. Originality/Value: In the western world several models of alignment of business strategy and information systems is available but they do not measure the extent of alignment which the current study in the Indian context. Findings of the study can be used by managers in strategizing and understanding their business and information systems needs holistically and cohesively leading to efficient use of resources and output.

Keywords: business strategy, information technology (IT), business IT alignment, SEM

Procedia PDF Downloads 388

Authors: Gak-Gyu Kim, Won Il Jung

Abstract:

According to a remarkable development of science and technology, function and role of the system of engineering fields has recently been diversified. The system has become increasingly more complex and precise, and thus, system designers intended to maximize reliability concentrate more effort at the design stage. This study deals with the reliability redundancy optimization problem (RROP) for k-out-of-n: G system configuration with cold standby and warm standby components. This paper further intends to present the optimal mathematical model through which the following three elements of (i) multiple components choices, (ii) redundant components quantity and (iii) the choice of redundancy strategies may be combined in order to maximize the reliability of the system. Therefore, we focus on the following three issues. First, we consider RROP that there exists warm standby state as well as cold standby state of the component. Second, as eliminating an approximation approach of the previous RROP studies, we construct a precise model for system reliability. Third, given transition time when the state of components changes, we present not simply a workable solution but the advanced method. For the wide applicability of RROPs, moreover, we use absorbing continuous time Markov chain and matrix analytic methods in the suggested mathematical model.

Keywords: RROP, matrix analytic methods, k-out-of-n: G system, MTTF, absorbing continuous time Markov Chain

Procedia PDF Downloads 254

Authors: Thanh N. Do

Abstract:

This paper addresses the modeling of two critical behaviors of concrete material in reinforced concrete components: (1) the increase in strength and ductility due to confining stresses from surrounding transverse steel reinforcements, and (2) the progressive deterioration in strength and stiffness due to high strain and/or cyclic loading. To improve the state-of-the-art, the author presents a new 3D constitutive model of concrete material based on plasticity and continuum damage mechanics theory to simulate both the confinement effect and the strength deterioration in reinforced concrete components. The model defines a yield function of the stress invariants and a compressive damage threshold based on the level of confining stresses to automatically capture the increase in strength and ductility when subjected to high compressive stresses. The model introduces two damage variables to describe the strength and stiffness deterioration under tensile and compressive stress states. The damage formulation characterizes well the degrading behavior of concrete material, including the nonsymmetric strength softening in tension and compression, as well as the progressive strength and stiffness degradation under primary and follower load cycles. The proposed damage model is implemented in a general purpose finite element analysis program allowing an extensive set of numerical simulations to assess its ability to capture the confinement effect and the degradation of the load-carrying capacity and stiffness of structural elements. It is validated against a collection of experimental data of the hysteretic behavior of reinforced concrete columns and shear walls under different load histories. These correlation studies demonstrate the ability of the model to describe vastly different hysteretic behaviors with a relatively consistent set of parameters. The model shows excellent consistency in response determination with very good accuracy. Its numerical robustness and computational efficiency are also very good and will be further assessed with large-scale simulations of structural systems.

Keywords: concrete, damage-plasticity, shear wall, confinement

Procedia PDF Downloads 169

Authors: Ella Tyuryumina, Alexey Neznanov

Abstract:

This paper is devoted to mathematical modelling of the progression and stages of breast cancer. We propose Consolidated mathematical growth model of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases (CoM-III) as a new research tool. We are interested in: 1) modelling the whole natural history of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; 2) developing adequate and precise CoM-III which reflects relations between primary tumor and secondary distant metastases; 3) analyzing the CoM-III scope of application; 4) implementing the model as a software tool. Firstly, the CoM-III includes exponential tumor growth model as a system of determinate nonlinear and linear equations. Secondly, mathematical model corresponds to TNM classification. It allows to calculate different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases: 1) ‘non-visible period’ for primary tumor; 2) ‘non-visible period’ for secondary distant metastases growth in patients with lymph nodes metastases; 3) ‘visible period’ for secondary distant metastases growth in patients with lymph nodes metastases. The new predictive tool: 1) is a solid foundation to develop future studies of breast cancer models; 2) does not require any expensive diagnostic tests; 3) is the first predictor which makes forecast using only current patient data, the others are based on the additional statistical data. Thus, the CoM-III model and predictive software: a) detect different growth periods of primary tumor and secondary distant metastases growth in patients with lymph nodes metastases; b) make forecast of the period of the distant metastases appearance in patients with lymph nodes metastases; c) have higher average prediction accuracy than the other tools; d) can improve forecasts on survival of breast cancer and facilitate optimization of diagnostic tests. The following are calculated by CoM-III: the number of doublings for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases; tumor volume doubling time (days) for ‘non-visible’ and ‘visible’ growth period of secondary distant metastases. The CoM-III enables, for the first time, to predict the whole natural history of primary tumor and secondary distant metastases growth on each stage (pT1, pT2, pT3, pT4) relying only on primary tumor sizes. Summarizing: a) CoM-III describes correctly primary tumor and secondary distant metastases growth of IA, IIA, IIB, IIIB (T1-4N1-3M0) stages in patients with lymph nodes metastases (N1-3); b) facilitates the understanding of the appearance period and inception of secondary distant metastases.

Keywords: breast cancer, exponential growth model, mathematical model, primary tumor, secondary metastases, survival

Procedia PDF Downloads 302