Search results for: co-processing of signaling parameters
Commenced in January 2007
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Paper Count: 8920

Search results for: co-processing of signaling parameters

5770 Minimum Data of a Speech Signal as Special Indicators of Identification in Phonoscopy

Authors: Nazaket Gazieva

Abstract:

Voice biometric data associated with physiological, psychological and other factors are widely used in forensic phonoscopy. There are various methods for identifying and verifying a person by voice. This article explores the minimum speech signal data as individual parameters of a speech signal. Monozygotic twins are believed to be genetically identical. Using the minimum data of the speech signal, we came to the conclusion that the voice imprint of monozygotic twins is individual. According to the conclusion of the experiment, we can conclude that the minimum indicators of the speech signal are more stable and reliable for phonoscopic examinations.

Keywords: phonogram, speech signal, temporal characteristics, fundamental frequency, biometric fingerprints

Procedia PDF Downloads 118
5769 Sustainability Assessment Tool for the Selection of Optimal Site Remediation Technologies for Contaminated Gasoline Sites

Authors: Connor Dunlop, Bassim Abbassi, Richard G. Zytner

Abstract:

Life cycle assessment (LCA) is a powerful tool established by the International Organization for Standardization (ISO) that can be used to assess the environmental impacts of a product or process from cradle to grave. Many studies utilize the LCA methodology within the site remediation field to compare various decontamination methods, including bioremediation, soil vapor extraction or excavation, and off-site disposal. However, with the authors' best knowledge, limited information is available in the literature on a sustainability tool that could be used to help with the selection of the optimal remediation technology. This tool, based on the LCA methodology, would consider site conditions like environmental, economic, and social impacts. Accordingly, this project was undertaken to develop a tool to assist with the selection of optimal sustainable technology. Developing a proper tool requires a large amount of data. As such, data was collected from previous LCA studies looking at site remediation technologies. This step identified knowledge gaps or limitations within project data. Next, utilizing the data obtained from the literature review and other organizations, an extensive LCA study is being completed following the ISO 14040 requirements. Initial technologies being compared include bioremediation, excavation with off-site disposal, and a no-remediation option for a generic gasoline-contaminated site. To complete the LCA study, the modelling software SimaPro is being utilized. A sensitivity analysis of the LCA results will also be incorporated to evaluate the impact on the overall results. Finally, the economic and social impacts associated with each option will then be reviewed to understand how they fluctuate at different sites. All the results will then be summarized, and an interactive tool using Excel will be developed to help select the best sustainable site remediation technology. Preliminary LCA results show improved sustainability for the decontamination of a gasoline-contaminated site for each technology compared to the no-remediation option. Sensitivity analyses are now being completed on on-site parameters to determine how the environmental impacts fluctuate at other contaminated gasoline locations as the parameters vary, including soil type and transportation distances. Additionally, the social improvements and overall economic costs associated with each technology are being reviewed. Utilizing these results, the sustainability tool created to assist in the selection of the overall best option will be refined.

Keywords: life cycle assessment, site remediation, sustainability tool, contaminated sites

Procedia PDF Downloads 36
5768 Hybrid Knowledge and Data-Driven Neural Networks for Diffuse Optical Tomography Reconstruction in Medical Imaging

Authors: Paola Causin, Andrea Aspri, Alessandro Benfenati

Abstract:

Diffuse Optical Tomography (DOT) is an emergent medical imaging technique which employs NIR light to estimate the spatial distribution of optical coefficients in biological tissues for diagnostic purposes, in a noninvasive and non-ionizing manner. DOT reconstruction is a severely ill-conditioned problem due to prevalent scattering of light in the tissue. In this contribution, we present our research in adopting hybrid knowledgedriven/data-driven approaches which exploit the existence of well assessed physical models and build upon them neural networks integrating the availability of data. Namely, since in this context regularization procedures are mandatory to obtain a reasonable reconstruction [1], we explore the use of neural networks as tools to include prior information on the solution. 2. Materials and Methods The idea underlying our approach is to leverage neural networks to solve PDE-constrained inverse problems of the form 𝒒 ∗ = 𝒂𝒓𝒈 𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃), (1) where D is a loss function which typically contains a discrepancy measure (or data fidelity) term plus other possible ad-hoc designed terms enforcing specific constraints. In the context of inverse problems like (1), one seeks the optimal set of physical parameters q, given the set of observations y. Moreover, 𝑦̃ is the computable approximation of y, which may be as well obtained from a neural network but also in a classic way via the resolution of a PDE with given input coefficients (forward problem, Fig.1 box ). Due to the severe ill conditioning of the reconstruction problem, we adopt a two-fold approach: i) we restrict the solutions (optical coefficients) to lie in a lower-dimensional subspace generated by auto-decoder type networks. This procedure forms priors of the solution (Fig.1 box ); ii) we use regularization procedures of type 𝒒̂ ∗ = 𝒂𝒓𝒈𝒎𝒊𝒏𝒒 𝐃(𝒚, 𝒚̃)+ 𝑹(𝒒), where 𝑹(𝒒) is a regularization functional depending on regularization parameters which can be fixed a-priori or learned via a neural network in a data-driven modality. To further improve the generalizability of the proposed framework, we also infuse physics knowledge via soft penalty constraints (Fig.1 box ) in the overall optimization procedure (Fig.1 box ). 3. Discussion and Conclusion DOT reconstruction is severely hindered by ill-conditioning. The combined use of data-driven and knowledgedriven elements is beneficial and allows to obtain improved results, especially with a restricted dataset and in presence of variable sources of noise.

Keywords: inverse problem in tomography, deep learning, diffuse optical tomography, regularization

Procedia PDF Downloads 58
5767 Ray Tracing Modified 3D Image Method Simulation of Picocellular Propagation Channel Environment

Authors: Fathi Alwafie

Abstract:

In this paper we present the simulation of the propagation characteristics of the picocellular propagation channel environment. The first aim has been to find a correct description of the environment for received wave. The result of the first investigations is that the environment of the indoor wave significantly changes as we change the electric parameters of material constructions. A modified 3D ray tracing image method tool has been utilized for the coverage prediction. A detailed analysis of the dependence of the indoor wave on the wide-band characteristics of the channel: Root Mean Square (RMS) delay spread characteristics and mean excess delay, is also investigated.

Keywords: propagation, ray tracing, network, mobile computing

Procedia PDF Downloads 382
5766 Turing Pattern in the Oregonator Revisited

Authors: Elragig Aiman, Dreiwi Hanan, Townley Stuart, Elmabrook Idriss

Abstract:

In this paper, we reconsider the analysis of the Oregonator model. We highlight an error in this analysis which leads to an incorrect depiction of the parameter region in which diffusion driven instability is possible. We believe that the cause of the oversight is the complexity of stability analyses based on eigenvalues and the dependence on parameters of matrix minors appearing in stability calculations. We regenerate the parameter space where Turing patterns can be seen, and we use the common Lyapunov function (CLF) approach, which is numerically reliable, to further confirm the dependence of the results on diffusion coefficients intensities.

Keywords: diffusion driven instability, common Lyapunov function (CLF), turing pattern, positive-definite matrix

Procedia PDF Downloads 341
5765 Design of an Electric Arc Furnace for the Production of Metallurgical Grade Silicon

Authors: M. Barbouche, M. Hajji, H. Ezzaouia

Abstract:

This project is a step to manufacture solar grade silicon. It consists in designing an electrical arc furnace in order to produce metallurgical silicon Mg-Si with mutually carbon and high purity of silica. It concerns, first, the development of a functional analysis, a mechanical design and thermodynamic study. Our study covers also, the design of the temperature control system and the design of the electric diagrams. The furnace works correctly. A Labview interface was developed to control all parameters and to supervise the operation of furnace. Characterization tests with X-ray technique and Raman spectroscopy allow us to confirm the metallurgical silicon production.

Keywords: arc furnace, electrical design, silicon manufacturing, regulation, x-ray characterization

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5764 Predicting Aggregation Propensity from Low-Temperature Conformational Fluctuations

Authors: Hamza Javar Magnier, Robin Curtis

Abstract:

There have been rapid advances in the upstream processing of protein therapeutics, which has shifted the bottleneck to downstream purification and formulation. Finding liquid formulations with shelf lives of up to two years is increasingly difficult for some of the newer therapeutics, which have been engineered for activity, but their formulations are often viscous, can phase separate, and have a high propensity for irreversible aggregation1. We explore means to develop improved predictive ability from a better understanding of how protein-protein interactions on formulation conditions (pH, ionic strength, buffer type, presence of excipients) and how these impact upon the initial steps in protein self-association and aggregation. In this work, we study the initial steps in the aggregation pathways using a minimal protein model based on square-well potentials and discontinuous molecular dynamics. The effect of model parameters, including range of interaction, stiffness, chain length, and chain sequence, implies that protein models fold according to various pathways. By reducing the range of interactions, the folding- and collapse- transition come together, and follow a single-step folding pathway from the denatured to the native state2. After parameterizing the model interaction-parameters, we developed an understanding of low-temperature conformational properties and fluctuations, and the correlation to the folding transition of proteins in isolation. The model fluctuations increase with temperature. We observe a low-temperature point, below which large fluctuations are frozen out. This implies that fluctuations at low-temperature can be correlated to the folding transition at the melting temperature. Because proteins “breath” at low temperatures, defining a native-state as a single structure with conserved contacts and a fixed three-dimensional structure is misleading. Rather, we introduce a new definition of a native-state ensemble based on our understanding of the core conservation, which takes into account the native fluctuations at low temperatures. This approach permits the study of a large range of length and time scales needed to link the molecular interactions to the macroscopically observed behaviour. In addition, these models studied are parameterized by fitting to experimentally observed protein-protein interactions characterized in terms of osmotic second virial coefficients.

Keywords: protein folding, native-ensemble, conformational fluctuation, aggregation

Procedia PDF Downloads 343
5763 Oviposition Responses of the Malaria Mosquito Anopheles gambiae sensu stricto to Hay Infusion Volatiles in Laboratory Bioassays and Investigation of Volatile Detection Methods

Authors: Lynda K. Eneh, Okal N. Mike, Anna-Karin Borg-Karlson, Ulrike Fillinger, Jenny M. Lindh

Abstract:

The responses of individual gravid Anopheles gambiae sensu stricto (s.s.) to hay infusion volatiles were evaluated under laboratory conditions. Such infusions have long been known to be effective baits for monitoring mosquitoes that vector arboviral and filarial diseases but have previously not been tested for malaria vectors. Hay infusions were prepared by adding sun-dried Bermuda grass to lake water and leaving the mixture in a covered bucket for three days. The proportions of eggs laid by gravid An. gambiae s.s. in diluted (10%) and concentrated infusions ( ≥ 25%) was compared to that laid in lake water in two-choice egg-count bioassays. Furthermore, with the aim to develop a method that can be used to collect volatiles that influence the egg-laying behavior of malaria mosquitoes, different volatile trapping methods were investigated. Two different polymer-traps eluted using two different desorption methods and three parameters were investigated. Porapak®-Q traps and solvent desorption was compared to Tenax®-TA traps and thermal desorption. The parameters investigated were: collection time (1h vs. 20h), addition of salt (0.15 g/ml sodium chloride (NaCl) vs. no NaCl), and stirring the infusion (0 vs. 300 rpm). Sample analysis was with gas chromatography-mass spectrometry (GC-MS). An. gambiae s.s was ten times less likely to lay eggs in concentrated hay infusion than in lake water. The volatiles were best characterized by thermally desorbed Tenax traps, collected for 20 hours from infusion aliquots with sodium chloride added. Ten volatiles identified from headspace and previously indicated as putative oviposition semiochemicals for An. gambiae s.s. or confirmed semiochemicals for other mosquito species were tested in egg-count bioassays. Six of these (3-methylbutanol, phenol, 4-methylphenol, nonanal, indole and 3-methylindole), when added to lake water, were avoided for egg-laying when lake water was offered as the alternative in dual-choice egg count bioassays. These compounds likely contribute to the unfavorable oviposition responses towards hay infusions. This difference in oviposition response of different mosquito species should be considered when designing control measures.

Keywords: Anopheles gambiae, oviposition behaviour, egg-count cage bioassays, hay infusions, volatile detection, semiochemicals

Procedia PDF Downloads 329
5762 Stagnation Point Flow Over a Stretching Cylinder with Variable Thermal Conductivity and Slip Conditions

Authors: M. Y. Malik, Farzana Khan

Abstract:

In this article, we discuss the behavior of viscous fluid near stagnation point over a stretching cylinder with variable thermal conductivity. The effects of slip conditions are also encountered. Thermal conductivity is considered as a linear function of temperature. By using homotopy analysis method and Fehlberg method we compare the graphical results for both momentum and energy equations. The effect of different parameters on velocity and temperature fields are shown graphically.

Keywords: slip conditions, stretching cylinder, heat generation/absorption, stagnation point flow, variable thermal conductivity

Procedia PDF Downloads 400
5761 Effect of Fire on Structural Behavior of Normal and High Strength Concrete Beams

Authors: Alaa I. Arafa, Hemdan O. A. Said. Marwa A. M. Ali

Abstract:

This paper investigates and evaluates experimentally the structural behavior of high strength concrete (HSC) beams under fire and compares it with that of Normal strength concrete (NSC) beams. The main investigated parameters are: concrete compressive strength (300 or 600 kg/cm2); the concrete cover thickness (3 or 5 cm); the degree of temperature (room temperature or 600 oC); the type of cooling (air or water); and the fire exposure time (3 or 5 hours). Test results showed that the concrete compressive strength decreases significantly as the exposure time to fire increases.

Keywords: experimental, fire, high strength concrete beams, monotonic loading

Procedia PDF Downloads 375
5760 Performance Comparison of Prim’s and Ant Colony Optimization Algorithm to Select Shortest Path in Case of Link Failure

Authors: Rimmy Yadav, Avtar Singh

Abstract:

—Ant Colony Optimization (ACO) is a promising modern approach to the unused combinatorial optimization. Here ACO is applied to finding the shortest during communication link failure. In this paper, the performances of the prim’s and ACO algorithm are made. By comparing the time complexity and program execution time as set of parameters, we demonstrate the pleasant performance of ACO in finding excellent solution to finding shortest path during communication link failure.

Keywords: ant colony optimization, link failure, prim’s algorithm, shortest path

Procedia PDF Downloads 378
5759 Effect on Haemolymph Cellular Parameters of Periplaneta Americana Following Challenge with Agrobacterium Tumefaciens: A Possible Microbial Control Agent

Authors: Fouzia Qamar, Shahida Hasnain

Abstract:

The present study is primarily concerned with the alteration in haemocyte profile of adult male Periplaneta americana with emphasis on the effect of bacterial inoculations on the haemogram i.e., total haemocyte count (THC) and differential haemocyte count (DHC) of different haemocyte types of the target insect. Haemolymph cellular profile showed considerable alterations under the effect of nine strains of Agrobacterium tumefaciens after 8, 16 and 24 hrs of treatment thereby signifying the potential role of Agrobacterium tumefaciens as a possible biocontrol agent against the house hold pests.

Keywords: Agrobacterium tumefaciens, Periplaneta americana, Haemolymph, cellular parametes

Procedia PDF Downloads 364
5758 Emulation Model in Architectural Education

Authors: Ö. Şenyiğit, A. Çolak

Abstract:

It is of great importance for an architectural student to know the parameters through which he/she can conduct his/her design and makes his/her design effective in architectural education. Therefore; an empirical application study was carried out through the designing activity using the emulation model to support the design and design approaches of architectural students. During the investigation period, studies were done on the basic design elements and principles of the fall semester, and the emulation model, one of the designing methods that constitute the subject of the study, was fictionalized as three phased “recognition-interpretation-application”. As a result of the study, it was observed that when students were given a key method during the design process, their awareness increased and their aspects improved as well.

Keywords: basic design, design education, design methods, emulation

Procedia PDF Downloads 212
5757 A Comparison for Some Elastic and Mechanical Properties of Neptunium Dioxide

Authors: E. Güler, M. Güler

Abstract:

We report some elastic quantities of cubic fluorite type plutonium dioxide (PuO2) with a recent EAM type interatomic potential through geometry optimization calculations. Typical cubic elastic constants, bulk modulus, shear modulus, young modulus and other related elastic quantities were calculated during present research. After present calculations, we have compared our results with the existing theoretical data of literature. Our results are consistent with previous theoretical findings of the considered parameters of PuO2.

Keywords: PuO2, elastic properties, bulk modulus, mechanical properties

Procedia PDF Downloads 288
5756 Shelf Life and Overall Quality of Pretreated and Modified Atmosphere Packaged ‘Ready-To-Eat’ Pomegranate arils cv. Bhagwa Stored at 1⁰C

Authors: Sangram Dhumal, Anil Karale

Abstract:

The effect of different pretreatments and modified atmosphere packaging on the quality of minimally processed pomegranate arils of Bhagwa cultivar was evaluated during storage at 1⁰C for 16 days. Hand extracted pomegranate arils were pretreated with different antioxidants and surfactants viz., 100ppm sodium hypochlorite plus 0.5 percent ascorbic acid plus 0.5 percent citric acid, 10 and 20 percent honey solution, 0.1 percent nanosilver stipulated food grade hydrogen peroxide alone and in combination with 10 percent honey solution and control. The disinfected, rinsed and air-dried pomegranate arils were packed in polypropylene punnets (135g each) with different modified atmospheres and stored up to 16 days at 1⁰C. Changes in colour, pH, total soluble solids, sugars, anthocyanins, phenols, acidity, antioxidant activity, microbial and yeast and mold count over initial values were recorded in all the treatments under study but highest on those without antioxidant and surfactant treatments. Pretreated arils stored at 1⁰C recorded decrease in L*, b* value, pH, levels of non-reducing and total sugars, polyphenols, antioxidant activity and acceptability of arils and increase in total soluble solids, a* value, anthocyanins and microbial count. Increase in anthocyanin content was observed in modified atmosphere packaged pretreated arils stored at 1⁰C. Modified atmosphere packaging with 100 percent nitrogen recorded minimum changes in physicochemical and sensorial parameters with minimum microbial growth. Untreated arils in perforated punnets and with air (control) gave shelf life up to 6 days only. The pretreatment of arils with 10 percent honey plus 0.1 percent nanosilver stipulated food grade hydrogen peroxide and packaging in 100 percent nitrogen recorded minimum changes in physicochemical parameters. The treatment also restricted microbial growth and maintained colour, anthocyanin pigmentation, antioxidant activity and overall fresh like quality of arils. The same dipping treatment along with modified atmosphere packaging extended the shelf life of fresh ready to eat arils up to 14 to 16 days with enhanced acceptability when stored at 1⁰C.

Keywords: anthocyanin content, pomegranate, MAP, minimally processed, microbial quality, Bhagwa, shelf-life, overall quality

Procedia PDF Downloads 161
5755 The Role of Speed Reduction Model in Urban Highways Tunnels Accidents

Authors: Khashayar Kazemzadeh, Mohammad Hanif Dasoomi

Abstract:

According to the increasing travel demand in cities, bridges and tunnels are viewed as one of the fundamental components of cities transportation systems. Normally, due to geometric constraints forms in the tunnels, the considered speed in the tunnels is lower than the speed in connected highways. Therefore, drivers tend to reduce the speed near the entrance of the tunnels. In this paper, the effect of speed reduction on accident happened in the entrance of the tunnels has been discussed. The relation between accidents frequency and the parameters of speed, traffic volume and time of the accident in the mentioned tunnel has been analyzed and the mathematical model has been proposed.

Keywords: urban highway, accident, tunnel, mathematical model

Procedia PDF Downloads 452
5754 Bifurcation and Chaos of the Memristor Circuit

Authors: Wang Zhulin, Min Fuhong, Peng Guangya, Wang Yaoda, Cao Yi

Abstract:

In this paper, a magnetron memristor model based on hyperbolic sine function is presented and the correctness proved by studying the trajectory of its voltage and current phase, and then a memristor chaotic system with the memristor model is presented. The phase trajectories and the bifurcation diagrams and Lyapunov exponent spectrum of the magnetron memristor system are plotted by numerical simulation, and the chaotic evolution with changing the parameters of the system is also given. The paper includes numerical simulations and mathematical model, which confirming that the system, has a wealth of dynamic behavior.

Keywords: memristor, chaotic circuit, dynamical behavior, chaotic system

Procedia PDF Downloads 481
5753 Advancing Microstructure Evolution in Tungsten Through Rolling in Laser Powder Bed Fusion

Authors: Narges Shayesteh Moghaddam

Abstract:

Tungsten (W), a refractory metal known for its remarkably high melting temperature, offers tremendous potential for use in challenging environments prevalent in sectors such as space exploration, defense, and nuclear industries. Additive manufacturing, especially the Laser Powder-Bed Fusion (LPBF) technique, emerges as a beneficial method for fabricating tungsten parts. This technique enables the production of intricate components while simultaneously reducing production lead times and associated costs. However, the inherent brittleness of tungsten and its tendency to crack under high-temperature conditions pose significant challenges to the manufacturing process. Our research primarily focuses on the process of rolling tungsten parts in a layer-by-layer manner in LPBF and the subsequent changes in microstructure. Our objective is not only to identify the alterations in the microstructure but also to assess their implications on the physical properties and performance of the fabricated tungsten parts. To examine these aspects, we conducted an extensive series of experiments that included the fabrication of tungsten samples through LPBF and subsequent characterization using advanced materials analysis techniques. These investigations allowed us to scrutinize shifts in various microstructural features, including, but not limited to, grain size and grain boundaries occurring during the rolling process. The results of our study provide crucial insights into how specific factors, such as plastic deformation occurring during the rolling process, influence the microstructural characteristics of the fabricated parts. This information is vital as it provides a foundation for understanding how the parameters of the layer-by-layer rolling process affect the final tungsten parts. Our research significantly broadens the current understanding of microstructural evolution in tungsten parts produced via the layer-by-layer rolling process in LPBF. The insights obtained will play a pivotal role in refining and optimizing manufacturing parameters, thus improving the mechanical properties of tungsten parts and, therefore, enhancing their performance. Furthermore, these findings will contribute to the advancement of manufacturing techniques, facilitating the wider application of tungsten parts in various high-demand sectors. Through these advancements, this research represents a significant step towards harnessing the full potential of tungsten in high-temperature and high-stress applications.

Keywords: additive manufacturing, rolling, tungsten, refractory materials

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5752 Reaction Kinetics of Biodiesel Production from Refined Cottonseed Oil Using Calcium Oxide

Authors: Ude N. Callistus, Amulu F. Ndidi, Onukwuli D. Okechukwu, Amulu E. Patrick

Abstract:

Power law approximation was used in this study to evaluate the reaction orders of calcium oxide, CaO catalyzed transesterification of refined cottonseed oil and methanol. The kinetics study was carried out at temperatures of 45, 55 and 65 oC. The kinetic parameters such as reaction order 2.02 and rate constant 2.8 hr-1g-1cat, obtained at the temperature of 65 oC best fitted the kinetic model. The activation energy, Ea obtained was 127.744 KJ/mol. The results indicate that the transesterification reaction of the refined cottonseed oil using calcium oxide catalyst is approximately second order reaction.

Keywords: refined cottonseed oil, transesterification, CaO, heterogeneous catalysts, kinetic model

Procedia PDF Downloads 518
5751 A Deep Learning Approach for Optimum Shape Design

Authors: Cahit Perkgöz

Abstract:

Artificial intelligence has brought new approaches to solving problems in almost every research field in recent years. One of these topics is shape design and optimization, which has the possibility of applications in many fields, such as nanotechnology and electronics. A properly constructed cost function can eliminate the need for labeled data required in deep learning and create desired shapes. In this work, the network parameters are optimized differentially, which differs from traditional approaches. The methods are tested for physics-related structures and successful results are obtained. This work is supported by Eskişehir Technical University scientific research project (Project No: 20ADP090)

Keywords: deep learning, shape design, optimization, artificial intelligence

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5750 An Overview of Thermal Storage Techniques for Solar Thermal Applications

Authors: Talha Shafiq

Abstract:

The traditional electricity operation in solar thermal plants is designed to operate on a single path initiating at power plant and executes at the consumer. Due to lack of energy storage facilities during this operation, a decrease in the efficiency is often observed with the power plant performance. This paper reviews the significance of energy storage in supply design and elaborates various methods that can be adopted in this regard which are equally cost effective and environmental friendly. Moreover, various parameters in thermal storage technique are also critically analyzed to clarify the pros and cons in this facility. Discussing the different thermal storage system, their technical and economical evaluation has also been reviewed.

Keywords: thermal energy storage, sensible heat storage, latent heat storage, thermochemical heat storage

Procedia PDF Downloads 539
5749 The Use of Venous Glucose, Serum Lactate and Base Deficit as Biochemical Predictors of Mortality in Polytraumatized Patients: Acomparative with Trauma and Injury Severity Score and Acute Physiology and Chronic Health Evalution IV

Authors: Osama Moustafa Zayed

Abstract:

Aim of the work: To evaluate the effectiveness of venous glucose, levels of serum lactate and base deficit in polytraumatized patients as simple parameters to predict the mortality in these patients. Compared to the predictive value of Trauma and injury severity (TRISS) and Acute Physiology And Chronic Health Evaluation IV (APACHE IV). Introduction: Trauma is a serious global health problem, accounting for approximately one in 10 deaths worldwide. Trauma accounts for 5 million deaths per year. Prediction of mortality in trauma patients is an important part of trauma care. Several trauma scores have been devised to predict injury severity and risk of mortality. The trauma and injury severity score (TRISS) was most common used. Regardless of the accuracy of trauma scores, is based on an anatomical description of every injury and cannot be assigned to the patients until a full diagnostic procedure has been performed. So we hypothesized that alterations in admission glucose, lactate levels and base deficit would be an early and easy rapid predictor of mortality. Patient and Method: a comparative cross-sectional study. 282 Polytraumatized patients attended to the Emergency Department(ED) of the Suez Canal university Hospital constituted. The period from 1/1/2012 to 1/4/2013 was included. Results: We found that the best cut off value of TRISS probability of survival score for prediction of mortality among poly-traumatized patients is = 90, with 77% sensitivity and 89% specificity using area under the ROC curve (0.89) at (95%CI). APACHE IV demonstrated 67% sensitivity and 95% specificity at 95% CI at cut off point 99. The best cutoff value of Random Blood Sugar (RBS) for prediction of mortality was>140 mg/dl, with 89%, sensitivity, 49% specificity. The best cut off value of base deficit for prediction of mortality was less than -5.6 with 64% sensitivity, 93% specificity. The best cutoff point of lactate for prediction of mortality was > 2.6 mmol/L with 92%, sensitivity, 42% specificity. Conclusion: According to our results from all evaluated predictors of mortality (laboratory and scores) and mortality based on the estimated cutoff values using ROC curves analysis, the highest risk of mortality was found using a cutoff value of 90 in TRISS score while with laboratory parameters the highest risk of mortality was with serum lactate > 2.6 . Although that all of the three parameter are accurate in predicting mortality in poly-traumatized patients and near with each other, as in serum lactate the area under the curve 0.82, in BD 0.79 and 0.77 in RBS.

Keywords: APACHE IV, emergency department, polytraumatized patients, serum lactate

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5748 E-Bike FE Model Analysis: Connection Stiffness of Elements with Different DOFs

Authors: Lele Zhang, Hui Leng Choo, Alexander Konyukhov, Shuguang Li

Abstract:

Finite Element (FE) model of simplified e-bike structure was generated by main frame with two tiers, which consisted of pipe, mass, beam, and shell elements (pipe 289, beam188, shell 181, shell 281, combin14, link11, mass21). These elements would be introduced and demonstrated using mathematical formulas. Based on coupling theory, constrain equations was proposed. Exporting all the parameters obtained from theory part, the connection stiffness matrix of the whole e-bike structure between each of these elements was detected.

Keywords: coupling theory, stiffness matrix, e-bike, finite element model

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5747 Artificial Neural Networks Application on Nusselt Number and Pressure Drop Prediction in Triangular Corrugated Plate Heat Exchanger

Authors: Hany Elsaid Fawaz Abdallah

Abstract:

This study presents a new artificial neural network(ANN) model to predict the Nusselt Number and pressure drop for the turbulent flow in a triangular corrugated plate heat exchanger for forced air and turbulent water flow. An experimental investigation was performed to create a new dataset for the Nusselt Number and pressure drop values in the following range of dimensionless parameters: The plate corrugation angles (from 0° to 60°), the Reynolds number (from 10000 to 40000), pitch to height ratio (from 1 to 4), and Prandtl number (from 0.7 to 200). Based on the ANN performance graph, the three-layer structure with {12-8-6} hidden neurons has been chosen. The training procedure includes back-propagation with the biases and weight adjustment, the evaluation of the loss function for the training and validation dataset and feed-forward propagation of the input parameters. The linear function was used at the output layer as the activation function, while for the hidden layers, the rectified linear unit activation function was utilized. In order to accelerate the ANN training, the loss function minimization may be achieved by the adaptive moment estimation algorithm (ADAM). The ‘‘MinMax’’ normalization approach was utilized to avoid the increase in the training time due to drastic differences in the loss function gradients with respect to the values of weights. Since the test dataset is not being used for the ANN training, a cross-validation technique is applied to the ANN network using the new data. Such procedure was repeated until loss function convergence was achieved or for 4000 epochs with a batch size of 200 points. The program code was written in Python 3.0 using open-source ANN libraries such as Scikit learn, TensorFlow and Keras libraries. The mean average percent error values of 9.4% for the Nusselt number and 8.2% for pressure drop for the ANN model have been achieved. Therefore, higher accuracy compared to the generalized correlations was achieved. The performance validation of the obtained model was based on a comparison of predicted data with the experimental results yielding excellent accuracy.

Keywords: artificial neural networks, corrugated channel, heat transfer enhancement, Nusselt number, pressure drop, generalized correlations

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5746 Salicornia bigelovii, a Promising Halophyte for Biosaline Agriculture: Lessons Learned from a 4-Year Field Study in United Arab Emirates

Authors: Dionyssia Lyra, Shoaib Ismail

Abstract:

Salinization of natural resources constitutes a significant component of the degradation force that leads to depletion of productive lands and fresh water reserves. The global extent of salt-affected soils is approximately 7% of the earth’s land surface and is expanding. The problems of excessive salt accumulation are most widespread in coastal, arid and semi-arid regions, where agricultural production is substantially hindered. The use of crops that can withstand high saline conditions is extremely interesting in such a context. Salt-loving plants or else ‘halophytes’ thrive when grown in hostile saline conditions, where traditional crops cannot survive. Salicornia bigelovii, a halophytic crop with multiple uses (vegetable, forage, biofuel), has demonstrated remarkable adaptability to harsh climatic conditions prevailing in dry areas with great potential for its expansion. Since 2011, the International Center for Biosaline Agriculture (ICBA) with Masdar Institute (MI) and King Abdul Aziz University of Science & Technology (KAUST) to look into the potential for growing S. bigelovii under hot and dry conditions. Through the projects undertaken, 50 different S. bigelovii genotypes were assessed under high saline conditions. The overall goal was to select the best performing S. bigelovii populations in terms of seed and biomass production for future breeding. Specific objectives included: 1) evaluation of selected S. bigelovii genotypes for various agronomic and growth parameters under field conditions, 2) seed multiplication of S. bigelovii using saline groundwater and 3) acquisition of inbred lines for further breeding. Field trials were conducted for four consecutive years at ICBA headquarters. During the first year, one Salicornia population was evaluated for seed and biomass production at different salinity levels, fertilizer treatments and planting methods. All growth parameters and biomass productivity for the salicornia population showed better performance with optimal biomass production in terms of both salinity level and fertilizer application. During the second year, 46 Salicornia populations (obtained from KAUST and Masdar Institute) were evaluated for 24 growth parameters and treated with groundwater through drip irrigation. The plant material originated from wild collections. Six populations were also assessed for their growth performance under full-strength seawater. Salicornia populations were highly variable for all characteristics under study for both irrigation treatments, indicating that there is a large pool of genetic information available for breeding. Irrigation with the highest level of salinity had a negative impact on the agronomic performance. The maximum seed yield obtained was 2 t/ha at 20 dS/m (groundwater treatment) at 25 cm x 25 cm planting distance. The best performing Salicornia populations for fresh biomass and seed yield were selected for the following season. After continuous selection, the best performing salicornia will be adopted for scaling-up options. Taking into account the results of the production field trials, salicornia expansion will be targeted in coastal areas of the Arabian Peninsula. As a crop with high biofuel and forage potential, its cultivation can improve the livelihood of local farmers.

Keywords: biosaline agriculture, genotypes selection, halophytes, Salicornia bigelovii

Procedia PDF Downloads 389
5745 Parasitic Capacitance Modeling in Pulse Transformer Using FEA

Authors: D. Habibinia, M. R. Feyzi

Abstract:

Nowadays, specialized software is vastly used to verify the performance of an electric machine prototype by evaluating a model of the system. These models mainly consist of electrical parameters such as inductances and resistances. However, when the operating frequency of the device is above one kHz, the effect of parasitic capacitances grows significantly. In this paper, a software-based procedure is introduced to model these capacitances within the electromagnetic simulation of the device. The case study is a high-frequency high-voltage pulse transformer. The Finite Element Analysis (FEA) software with coupled field analysis is used in this method.

Keywords: finite element analysis, parasitic capacitance, pulse transformer, high frequency

Procedia PDF Downloads 504
5744 Detection Characteristics of the Random and Deterministic Signals in Antenna Arrays

Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

Abstract:

In this paper approach to incoherent signal detection in multi-element antenna array are researched and modeled. Two types of useful signals with unknown wavefront were considered. First one is deterministic (Barker code), the second one is random (Gaussian distribution). The derivation of the sufficient statistics took into account the linearity of the antenna array. The performance characteristics and detecting curves are modeled and compared for different useful signals parameters and for different number of elements of the antenna array. Results of researches in case of some additional conditions can be applied to a digital communications systems.

Keywords: antenna array, detection curves, performance characteristics, quadrature processing, signal detection

Procedia PDF Downloads 392
5743 A Hybrid Genetic Algorithm for Assembly Line Balancing In Automotive Sector

Authors: Qazi Salman Khalid, Muhammad Khalid, Shahid Maqsood

Abstract:

This paper presents a solution for optimizing the cycle time in an assembly line with human-robot collaboration and diverse operators. A genetic algorithm with tailored parameters is used to address the assembly line balancing problem in the automobile sector. A mathematical model is developed, depicting the problem. Currently, the firm runs on the largest candidate rule; however, it causes a lag in orders, which ultimately gets penalized. The results of the study show that the proposed GA is effective in providing efficient solutions and that the cycle time has significantly impacted productivity.

Keywords: line balancing, cycle time, genetic algorithm, productivity

Procedia PDF Downloads 117
5742 3D Biomechanics Analysis of Tennis Elbow Factors & Injury Prevention Using Computer Vision and AI

Authors: Aaron Yan

Abstract:

Tennis elbow has been a leading injury and problem among amateur and even professional players. Many factors contribute to tennis elbow. In this research, we apply state of the art sensor-less computer vision and AI technology to study the biomechanics of a player’s tennis movements during training and competition as they relate to the causes of tennis elbow. We provide a framework for the analysis of key biomechanical parameters and their correlations with specific tennis stroke and movements that can lead to tennis elbow or elbow injury. We also devise a method for using AI to automatically detect player’s forms that can lead to tennis elbow development for on-court injury prevention.

Keywords: Tennis Elbow, Computer Vision, AI, 3DAT

Procedia PDF Downloads 19
5741 Optimization of Gold Mining Parameters by Cyanidation

Authors: Della Saddam Housseyn

Abstract:

Gold, the quintessential noble metal, is one of the most popular metals today, given its ever-increasing cost in the international market. The Amesmessa gold deposit is one of the gold-producing deposits. The first step in our job is to analyze the ore (considered rich ore). Mineralogical and chemical analysis has shown that the general constitution of the ore is quartz in addition to other phases such as Al2O3, Fe2O3, CaO, dolomite. The second step consists of all the leaching tests carried out in rolling bottles. These tests were carried out on 14 samples to determine the maximum recovery rate and the optimum consumption of reagent (NaCN and CaO). Tests carried out on a pulp density at 50% solid, 500 ppm cyanide concentration and particle size less than 0.6 mm at alkaline pH gave a recovery rate of 94.37%.

Keywords: cyanide, DRX, FX, gold, leaching, rate of recovery, SAA

Procedia PDF Downloads 162