Search results for: high performance concrete
24805 Personalized Learning: An Analysis Using Item Response Theory
Authors: A. Yacob, N. Hj. Ali, M. H. Yusoff, M. Y. MohdSaman, W. M. A. F. W. Hamzah
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Personalized learning becomes increasingly popular which not is restricted by time, place or any other barriers. This study proposes an analysis of Personalized Learning using Item Response Theory which considers course material difficulty and learner ability. The study investigates twenty undergraduate students at TATI University College, who are taking programming subject. By using the IRT, it was found that, finding the most appropriate problem levels to each student include high and low level test items together is not a problem. Thus, the student abilities can be asses more accurately and fairly. Learners who experience more anxiety will affect a heavier cognitive load and receive lower test scores. Instructors are encouraged to provide a supportive learning environment to enhance learning effectiveness because Cognitive Load Theory concerns the limited capacity of the brain to absorb new information.Keywords: assessment, item response theory, cognitive load theory, learning, motivation, performance
Procedia PDF Downloads 31724804 Effects of Inlet Filtration Pressure Loss on Single and Two-Spool Gas Turbine
Authors: Enyia James Diwa, Dodeye Ina Igbong, Archibong Archibong Eso
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Gas turbine operators have been faced with the dramatic financial setback resulting from compressor fouling. In a highly deregulated power industry where there is stiffness in the market competition, has made it imperative to improvise means of reducing maintenance cost in other to yield maximum profit. Compressor fouling results from the deposition of contaminants in the presence of oil and moisture on the compressor blade or annulus surfaces, which leads to a loss in flow capacity and compressor efficiency. These combined effects reduce power output, increase heat rate and cause creep life reduction. This paper also contains a model of two gas turbine engines via Cranfield University software known as TURBOMATCH, which is simulation software for detecting engine fouling rate. The model engines are of different configurations and capacities, and are operating in two different modes of constant output power and turbine inlet temperature for a two and three stage filter system. The idea is to investigate the more economically viable filtration systems by gas turbine users based on performance only. It has been demonstrated in the results that the two spool engine is a little more beneficial compared to the single spool. This is as a result of a higher pressure ratio of the two spools as well as the deceleration of the high-pressure compressor and high-pressure turbine speed in a constant TET. Meanwhile, the inlet filtration system was properly designed and balanced with a well-timed and economical compressor washing regime/scheme to control compressor fouling. The different technologies of inlet air filtration and compressor washing are considered and an attempt at optimization with respect to the cost of a combination of both control measures are made.Keywords: inlet filtration, pressure loss, single spool, two spool
Procedia PDF Downloads 32224803 Analyzing Tensile Strength in Different Composites at High Temperatures: Insights from 761 Tests
Authors: Milad Abolfazli, Milad Bazli
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In this critical review, the topic of how composites maintain their tensile strength when exposed to elevated temperatures will be studied. A comprehensive database of 761 tests have been analyzed and closely examined to study the various factors that affect the strength retention. Conclusions are drawn from the collective research efforts of numerous scholars who have investigated this subject. Through the analysis of these tests, the relationships between the tensile strength retention and various effective factors are investigated. This review is meant to be a practical resource for researchers and engineers. It provides valuable information that can guide the development of composites tailored for high-temperature applications. By offering a deeper understanding of how composites behave in extreme heat, the paper contributes to the advancement of materials science and engineering.Keywords: tesnile tests, high temperatures, FRP composites, mechanical perfomance
Procedia PDF Downloads 7124802 Oriented Strandboard-GEOGYPTM Undelayment, a Novel Composite Flooring System
Authors: B. Noruziaan, A. Shvarzman, R. Leahy
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An innovative flooring underlayment was produced and tested. The composite system is made of common OSB boards and a layer of eco-friendly non-cement gypsum based material (GeoGypTM). It was found that the shear bond between the two materials is sufficient to secure the composite interaction between the two. The very high compressive strength and relatively high tensile strength of the non-cement based component together with its high modulus of elasticity provides enough strength and stiffness for the composite product to cover wider spacing between the joists. The initial findings of this study indicate that with joist spacing as wide as 800 mm, the flooring system provides enough strength without compromising the serviceability requirements of the building codes.Keywords: Composite, floor deck, gypsum based, lumber joist, non-cement, oriented strandboard, shear bond
Procedia PDF Downloads 42024801 Bidirectional Long Short-Term Memory-Based Signal Detection for Orthogonal Frequency Division Multiplexing With All Index Modulation
Authors: Mahmut Yildirim
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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection
Procedia PDF Downloads 7224800 Design Guidelines for URM Infills and Effect of Construction Sequence on Seismic Performance of Code Compliant RC Frame Buildings
Authors: Putul Haldar, Yogendra Singh, D. K. Paul
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Un-Reinforced Masonry (URM) infilled RC framed buildings are the most common construction practice for modern multi-storey buildings in India like many other parts of the world. Although the behavior and failure pattern of the global structure changes significantly due to infill-frame interaction, the general design practice is to treat them as non-structural elements and their stiffness, strength and interaction with frame is often ignored, as it is difficult to simulate. Indian Standard, like many other major national codes, does not provide any explicit guideline for modeling of infills. This paper takes a stock of controlling design provisions in some of the major national seismic design codes (BIS 2002; CEN 2004; NZS-4230 2004; ASCE-41 2007) to ensure the desired seismic performance of infilled frame. Most of the national codes on seismic design of buildings still lack in adequate guidelines on modeling and design of URM infilled frames results in variable assumption in analysis and design. This paper, using nonlinear pushover analysis, also presents the effect of one of such assumptions of conventional ‘simultaneous’ analysis procedure of infilled frame on the seismic performance of URM infilled RC frame buildings.Keywords: URM infills, RC frame, seismic design codes, construction sequence of infilled frame
Procedia PDF Downloads 38924799 Exploring the Impact of Input Sequence Lengths on Long Short-Term Memory-Based Streamflow Prediction in Flashy Catchments
Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz
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Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.Keywords: LSTMs, streamflow, hyperparameters, hydrology
Procedia PDF Downloads 7024798 Cost-Effective Materials for Hydrocarbons Recovery from Produced Water
Authors: Fahd I. Alghunaimi, Hind S. Dossary, Norah W. Aljuryyed, Tawfik A. Saleh
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Produced water (PW) is one of the largest by-volume waste streams and one of the most challenging effluents in the oil and gas industry. This is due to the variation of contaminants that make up PW. Severalmaterialshavebeen developed, studied, and implemented to remove hydrocarbonsfrom PW. Adsorption is one of the most effective ways ofremoving oil fromPW. In this work, three new and cost-effective hydrophobic adsorbentmaterials based on 9-octadecenoic acid grafted graphene (POG) were synthesized for oil/water separation. Graphene derived from graphite was modified with 9-octadecenoic acid to yield 9-octadecenoic acid grafted graphene (OG). The newsynthesized materials which called POG25, POG50, and POG75 were characterized by using N₂-physisorption (BET) and Fourier transform infrared (FTIR). The BET surface area of POG75 was the highest with 288 m²/g, whereas POG50 was 225 m²/g and POG25 was lowest 79 m²/g. These three materials were also evaluated for their oil-water separation efficiency using a model mixture, whichdemonstrated that POG-75 has the highest oil removal efficiency and the faster rate of the adsorption (Figure-1). POG75 was regenerated, and its performance was verified again with a little reduced adsorption rate compared to the fresh material. The mixtures that used in the performance test were prepared by mixing nonpolar organic liquids such as heptane, dodecane, or hexadecane into the colored water. In general, the new materials showed fast uptake of the certain quantity of the oildue to the high hydrophobicity nature of the materials, which repel water as confirmed by the contact angle of approximately 150˚. Besides that, novel superhydrophobic material was also synthesized by introducing hydrophobic branches of laurate on the surface of the stainless steel mesh (SSM). This novel mesh could help to hold the novel adsorbent materials in a column to remove oil from PW. Both BOG-75 and the novel mesh have the potential to remove oil contaminants from produced water, which will help to provide an opportunity to recover useful components, in addition, to reduce the environmental impact and reuse produced water in several applications such as fracturing.Keywords: graphite to graphene, oleophilic, produced water, separation
Procedia PDF Downloads 12224797 Anomaly Detection Based on System Log Data
Authors: M. Kamel, A. Hoayek, M. Batton-Hubert
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With the increase of network virtualization and the disparity of vendors, the continuous monitoring and detection of anomalies cannot rely on static rules. An advanced analytical methodology is needed to discriminate between ordinary events and unusual anomalies. In this paper, we focus on log data (textual data), which is a crucial source of information for network performance. Then, we introduce an algorithm used as a pipeline to help with the pretreatment of such data, group it into patterns, and dynamically label each pattern as an anomaly or not. Such tools will provide users and experts with continuous real-time logs monitoring capability to detect anomalies and failures in the underlying system that can affect performance. An application of real-world data illustrates the algorithm.Keywords: logs, anomaly detection, ML, scoring, NLP
Procedia PDF Downloads 9424796 Copper Oxide Doped Carbon Catalyst for Anodic Half-Cell of Vanadium Redox Flow Battery
Authors: Irshad U. Khan, Tanmay Paul, Murali Mohan Seepana
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This paper presents a study on synthesizing and characterizing a Copper oxide doped Carbon (CuO-C) electrocatalyst for the negative half-cell reactions of Vanadium Redox Flow Battery (VRFB). The CuO was synthesized using a microreactor. The electrocatalyst was characterized using X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Field Emission Scanning Electron Microscopy (SEM). The electrochemical performance was assessed by linear sweep voltammetry (LSV). The findings suggest that the synthesized CuO exhibited favorable crystallinity, morphology, and surface area, which reflects improved cell performance.Keywords: ECSA, electrocatalyst, energy storage, Tafel
Procedia PDF Downloads 9124795 A Voice Signal Encryption Scheme Based on Chaotic Theory
Authors: Hailang Yang
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To ensure the confidentiality and integrity of speech signals in communication transmission, this paper proposes a voice signal encryption scheme based on chaotic theory. Firstly, the scheme utilizes chaotic mapping to generate a key stream and then employs the key stream to perform bitwise exclusive OR (XOR) operations for encrypting the speech signal. Additionally, the scheme utilizes a chaotic hash function to generate a Message Authentication Code (MAC), which is appended to the encrypted data to verify the integrity of the data. Subsequently, we analyze the security performance and encryption efficiency of the scheme, comparing and optimizing it against existing solutions. Finally, experimental results demonstrate that the proposed scheme can resist common attacks, achieving high-quality encryption and speed.Keywords: chaotic theory, XOR encryption, chaotic hash function, Message Authentication Code (MAC)
Procedia PDF Downloads 5124794 Transition 1970 Volkswagen Beetle from Internal Combustion Engine Vehicle to Electric Vehicle, Modeling and Simulation
Authors: Jamil Khalil Izraqi
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This paper investigates the transition of a 1970 Volkswagen Beetle from an internal combustion engine (ICE) to an EV using Matlab/Simulink modeling and simulation. The performance of the EV drivetrain system was simulated under various operating conditions, including standard and custom driving cycles in Turkey and Jordan (Amman), respectively. The results of this paper indicate that the transition is viable and that modeling and simulation can help in understanding the performance and efficiency of the electric drivetrain system, including battery pack, power electronics, and brushless direct current (BLDC) Motor.Keywords: BLDC, buck-boost, inverter, SOC, drive-cycle
Procedia PDF Downloads 10124793 Consumption of Animal and Vegetable Protein on Muscle Power in Road Cyclists from 18 to 20 Years in Bogota, Colombia
Authors: Oscar Rubiano, Oscar Ortiz, Natalia Morales, Lida Alfonso, Johana Alvarado, Adriana Gutierrez, Daniel Botero
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Athletes who usually use protein supplements, are those who practice strength and power sports, whose goal is to achieve a large muscle mass. However, it has also been explored in sports or endurance activities such as cycling, and where despite requiring high power, prominent muscle development can impede good competitive performance due to the determinant of body mass for good performance of the athlete body. This research shows, the effect with protein supplements establishes a protein - muscle mass ratio, although in a lesser proportion the relationship between protein types and muscle power. Thus, we intend to explore as a first approximation, the behavior of muscle power in lower limbs after the intake of two protein supplements from different sources. The aim of the study was to describe the behavior of muscle power in lower limbs after the consumption of animal protein (AP) and vegetable protein (VP) in four route cyclists from 18 to 20 years of the Bogota cycling league. The methodological design of this study is quantitative, with a non-probabilistic sampling, based on a pre-experimental model. The jumping power was evaluated before and after the intervention by means of the squat jump test (SJ), Counter movement jump (CMJ) and Abalacov (AB). Cyclists consumed a drink with whey protein and a soy isolate after training four times a week for three months. The amount of protein in each cyclist, was calculated according to body weight (0.5 g / kg of muscle mass). The results show that subjects who consumed PV improved muscle strength and landing strength. In contrast, the power and landing force decreased for subjects who consumed PA. For the group that consumed PV, the increase was positive at 164.26 watts, 135.70 watts and 33.96 watts for the AB, SJ and CMJ jumps respectively. While for PA, the differences of the medians were negative at -32.29 watts, -82.79 watts and -143.86 watts for the AB, SJ and CMJ jumps respectively. The differences of the medians in the AB jump were positive for both the PV (121.61 Newton) and PA (454.34 Newton) cases, however, the difference was greater for PA. For the SJ jump, the difference for the PA cases was 371.52 Newton, while for the PV cases the difference was negative -448.56 Newton, so the difference was greater in the SJ jump for PA. In jump CMJ, the differences of the medians were negative for the cases of PA and PV, being -7.05 for PA and - 958.2 for PV. So the difference was greater for PA. The conclusion of this study shows that serum protein supplementation showed no improvement in muscle power in the lower limbs of the cyclists studied, which could suggest that whey protein does not have a beneficial effect on performance in terms of power, either, showed an impact on body composition. In contrast, supplementation with soy isolate showed positive effects on muscle power, body.Keywords: animal protein (AP), muscle power, supplements, vegetable protein (VP)
Procedia PDF Downloads 17724792 A Conceptual Framework of the Individual and Organizational Antecedents to Knowledge Sharing
Authors: Muhammad Abdul Basit Memon
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The importance of organizational knowledge sharing and knowledge management has been documented in numerous research studies in available literature, since knowledge sharing has been recognized as a founding pillar for superior organizational performance and a source of gaining competitive advantage. Built on this, most of the successful organizations perceive knowledge management and knowledge sharing as a concern of high strategic importance and spend huge amounts on the effective management and sharing of organizational knowledge. However, despite some very serious endeavors, many firms fail to capitalize on the benefits of knowledge sharing because of being unaware of the individual characteristics, interpersonal, organizational and contextual factors that influence knowledge sharing; simply the antecedent to knowledge sharing. The extant literature on antecedents to knowledge sharing, offers a range of antecedents mentioned in a number of research articles and research studies. Some of the previous studies about antecedents to knowledge sharing, studied antecedents to knowledge sharing regarding inter-organizational knowledge transfer; others focused on inter and intra organizational knowledge sharing and still others investigated organizational factors. Some of the organizational antecedents to KS can relate to the characteristics and underlying aspects of knowledge being shared e.g., specificity and complexity of the underlying knowledge to be transferred; others relate to specific organizational characteristics e.g., age and size of the organization, decentralization and absorptive capacity of the firm and still others relate to the social relations and networks of organizations such as social ties, trusting relationships, and value systems. In the same way some researchers have highlighted on only one aspect like organizational commitment, transformational leadership, knowledge-centred culture, learning and performance orientation and social network-based relationships in the organizations. A bulk of the existing research articles on antecedents to knowledge sharing has mainly discussed organizational or environmental factors affecting knowledge sharing. However, the focus, later on, shifted towards the analysis of individuals or personal determinants as antecedents for the individual’s engagement in knowledge sharing activities, like personality traits, attitude and self efficacy etc. For example, employees’ goal orientations (i.e. learning orientation or performance orientation is an important individual antecedent of knowledge sharing behaviour. While being consistent with the existing literature therefore, the antecedents to knowledge sharing can be classified as being individual and organizational. This paper is an endeavor to discuss a conceptual framework of the individual and organizational antecedents to knowledge sharing in the light of the available literature and empirical evidence. This model not only can help in getting familiarity and comprehension on the subject matter by presenting a holistic view of the antecedents to knowledge sharing as discussed in the literature, but can also help the business managers and especially human resource managers to find insights about the salient features of organizational knowledge sharing. Moreover, this paper can help provide a ground for research students and academicians to conduct both qualitative as well and quantitative research and design an instrument for conducting survey on the topic of individual and organizational antecedents to knowledge sharing.Keywords: antecedents to knowledge sharing, knowledge management, individual and organizational, organizational knowledge sharing
Procedia PDF Downloads 32424791 The Influence of Carbamazepine on the Activity of CYP3A4 in Patients with Alcoholism
Authors: Mikhail S. Zastrozhin, Valery V. Smirnov, Dmitry A. Sychev, Ludmila M. Savchenko, Evgeny A. Bryun, Mark O. Nechaev
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Cytochrome P-450 isoenzyme 3A4 takes part in the biotransformation of medical drugs. The activity of CYP isoenzymes depends on genetic (polymorphisms of genes which encoded it) and phenotypic factors (a kind of food, a concomitant drug therapy). The aim of the study was to evaluate a carbamazepine effect on the CYP3A4 activity in patients with alcohol addiction. The study included 25 men with alcohol dependence, who received haloperidol during the exacerbation of the addiction. CYP3A4 activity was assessed by urinary 6-beta-hydroxycortisol/cortisol ratios measured by high performance liquid chromatography with mass spectrometry. The study modeled a graph and an equation of the logarithmic regression, that reflects the dependence of CYP3A4 activity on a dose of carbamazepine: y = 5,5 * 9,1 * 10-5 * x2. The study statistically significant demonstrates the effect of carbamazepine on CYP2D6 isozyme activity in patients with alcohol addiction.Keywords: CYP3A4, biotransformation, carbamazepine, alcohol abuse
Procedia PDF Downloads 27924790 Behaviour of Reinforced Concrete Infilled Frames under Seismic Loads
Authors: W. Badla
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A significant portion of the buildings constructed in Algeria is structural frames with infill panels which are usually considered as non structural components and are neglected in the analysis. However, these masonry panels tend to influence the structural response. Thus, these structures can be regarded as seismic risk buildings, although in the Algerian seismic code there is little guidance on the seismic evaluation of infilled frame buildings. In this study, three RC frames with 2, 4, and 8 story and subjected to three recorded Algerian accelerograms are studied. The diagonal strut approach is adopted for modeling the infill panels and a fiber model is used to model RC members. This paper reports on the seismic evaluation of RC frames with brick infill panels. The results obtained show that the masonry panels enhance the load lateral capacity of the buildings and the infill panel configuration influences the response of the structures.Keywords: seismic design, RC frames, infill panels, non linear dynamic analysis
Procedia PDF Downloads 54624789 Predicting Radioactive Waste Glass Viscosity, Density and Dissolution with Machine Learning
Authors: Joseph Lillington, Tom Gout, Mike Harrison, Ian Farnan
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The vitrification of high-level nuclear waste within borosilicate glass and its incorporation within a multi-barrier repository deep underground is widely accepted as the preferred disposal method. However, for this to happen, any safety case will require validation that the initially localized radionuclides will not be considerably released into the near/far-field. Therefore, accurate mechanistic models are necessary to predict glass dissolution, and these should be robust to a variety of incorporated waste species and leaching test conditions, particularly given substantial variations across international waste-streams. Here, machine learning is used to predict glass material properties (viscosity, density) and glass leaching model parameters from large-scale industrial data. A variety of different machine learning algorithms have been compared to assess performance. Density was predicted solely from composition, whereas viscosity additionally considered temperature. To predict suitable glass leaching model parameters, a large simulated dataset was created by coupling MATLAB and the chemical reactive-transport code HYTEC, considering the state-of-the-art GRAAL model (glass reactivity in allowance of the alteration layer). The trained models were then subsequently applied to the large-scale industrial, experimental data to identify potentially appropriate model parameters. Results indicate that ensemble methods can accurately predict viscosity as a function of temperature and composition across all three industrial datasets. Glass density prediction shows reliable learning performance with predictions primarily being within the experimental uncertainty of the test data. Furthermore, machine learning can predict glass dissolution model parameters behavior, demonstrating potential value in GRAAL model development and in assessing suitable model parameters for large-scale industrial glass dissolution data.Keywords: machine learning, predictive modelling, pattern recognition, radioactive waste glass
Procedia PDF Downloads 11624788 Predicting and Optimizing the Mechanical Behavior of a Flax Reinforced Composite
Authors: Georgios Koronis, Arlindo Silva
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This study seeks to understand the mechanical behavior of a natural fiber reinforced composite (epoxy/flax) in more depth, utilizing both experimental and numerical methods. It is attempted to identify relationships between the design parameters and the product performance, understand the effect of noise factors and reduce process variations. Optimization of the mechanical performance of manufactured goods has recently been implemented by numerous studies for green composites. However, these studies are limited and have explored in principal mass production processes. It is expected here to discover knowledge about composite’s manufacturing that can be used to design artifacts that are of low batch and tailored to niche markets. The goal is to reach greater consistency in the performance and further understand which factors play significant roles in obtaining the best mechanical performance. A prediction of response function (in various operating conditions) of the process is modeled by the DoE. Normally, a full factorial designed experiment is required and consists of all possible combinations of levels for all factors. An analytical assessment is possible though with just a fraction of the full factorial experiment. The outline of the research approach will comprise of evaluating the influence that these variables have and how they affect the composite mechanical behavior. The coupons will be fabricated by the vacuum infusion process defined by three process parameters: flow rate, injection point position and fiber treatment. Each process parameter is studied at 2-levels along with their interactions. Moreover, the tensile and flexural properties will be obtained through mechanical testing to discover the key process parameters. In this setting, an experimental phase will be followed in which a number of fabricated coupons will be tested to allow for a validation of the design of the experiment’s setup. Finally, the results are validated by performing the optimum set of in a final set of experiments as indicated by the DoE. It is expected that after a good agreement between the predicted and the verification experimental values, the optimal processing parameter of the biocomposite lamina will be effectively determined.Keywords: design of experiments, flax fabrics, mechanical performance, natural fiber reinforced composites
Procedia PDF Downloads 20424787 The Use of Additives to Prevent Fouling in Polyethylene and Polypropylene Gas and Slurry Phase Processes
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All polyethylene processes are highly exothermic, and the safe removal of the heat of reaction is a fundamental issue in the process design. In slurry and gas processes, the velocity of the polymer particles in the reactor and external coolers can be very high, and under certain conditions, this can lead to static charging of these particles. Such static charged polymer particles may start building up on the reactor wall, limiting heat transfer, and ultimately leading to severe reactor fouling and forced reactor shut down. Statsafe™ is an FDA approved anti-fouling additive currently used around the world for polyolefin production as an anti-fouling additive. The unique polymer chemistry aids static discharge, which prevents the build-up of charged polyolefin particles, which could lead to fouling. Statsafe™ is being used and trailed in gas, slurry, and a combination of these technologies around the world. We will share data to demonstrate how the use of Statsafe™ allows more stable operation at higher solids level by eliminating static, which would otherwise prevent closer packing of particles in the hydrocarbon slurry. Because static charge generation depends also on the concentration of polymer particles in the slurry, the maximum slurry concentration can be higher when using Statsafe™, leading to higher production rates. The elimination of fouling also leads to less downtime. Special focus will be made on the impact anti-static additives have on catalyst performance within the polymerization process and how this has been measured. Lab-scale studies have investigated the effect on the activity of Ziegler Natta catalysts when anti-static additives are used at various concentrations in gas and slurry, polyethylene and polypropylene processes. An in-depth gas phase study investigated the effect of additives on the final polyethylene properties such as particle size, morphology, fines, bulk density, melt flow index, gradient density, and melting point.Keywords: anti-static additives, catalyst performance, FDA approved anti-fouling additive, polymerisation
Procedia PDF Downloads 20424786 Real-time Rate and Rhythms Feedback Control System in Patients with Atrial Fibrillation
Authors: Mohammad A. Obeidat, Ayman M. Mansour
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Capturing the dynamic behavior of the heart to improve control performance, enhance robustness, and support diagnosis is very important in establishing real time models for the heart. Control Techniques and strategies have been utilized to improve system costs, reliability, and estimation accuracy for different types of systems such as biomedical, industrial, and other systems that required tuning input/output relation and/or monitoring. Simulations are performed to illustrate potential applications of the technology. In this research, a new control technology scheme is used to enhance the performance of the Af system and meet the design specifications.Keywords: atrial fibrillation, dynamic behavior, closed loop, signal, filter
Procedia PDF Downloads 42124785 An intelligent Troubleshooting System and Performance Evaluator for Computer Network
Authors: Iliya Musa Adamu
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This paper seeks to develop an expert system that would troubleshoot computer network and evaluate the network system performance so as to reduce the workload on technicians and increase the efficiency and effectiveness of solutions proffered to computer network problems. The platform of the system was developed using ASP.NET, whereas the codes are implemented in Visual Basic and integrated with SQL Server 2005. The knowledge base was represented using production rule, whereas the searching method that was used in developing the network troubleshooting expert system is the forward-chaining-rule-based-system. This software tool offers the advantage of providing an immediate solution to most computer network problems encountered by computer users.Keywords: expert system, forward chaining rule based system, network, troubleshooting
Procedia PDF Downloads 64724784 Online Prediction of Nonlinear Signal Processing Problems Based Kernel Adaptive Filtering
Authors: Hamza Nejib, Okba Taouali
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This paper presents two of the most knowing kernel adaptive filtering (KAF) approaches, the kernel least mean squares and the kernel recursive least squares, in order to predict a new output of nonlinear signal processing. Both of these methods implement a nonlinear transfer function using kernel methods in a particular space named reproducing kernel Hilbert space (RKHS) where the model is a linear combination of kernel functions applied to transform the observed data from the input space to a high dimensional feature space of vectors, this idea known as the kernel trick. Then KAF is the developing filters in RKHS. We use two nonlinear signal processing problems, Mackey Glass chaotic time series prediction and nonlinear channel equalization to figure the performance of the approaches presented and finally to result which of them is the adapted one.Keywords: online prediction, KAF, signal processing, RKHS, Kernel methods, KRLS, KLMS
Procedia PDF Downloads 39924783 Implant Operation Guiding Device for Dental Surgeons
Authors: Daniel Hyun
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Dental implants are one of the top 3 reasons to sue a dentist for malpractice. It involves dental implant complications, usually because of the angle of the implant from the surgery. At present, surgeons usually use a 3D-printed navigator that is customized for the patient’s teeth. However, those can’t be reused for other patients as they require time. Therefore, I made a guiding device to assist the surgeon in implant operations. The surgeon can input the objective of the operation, and the device constantly checks if the surgery is heading towards the objective within the set range, telling the surgeon by manipulating the LED. We tested the prototypes’ consistency and accuracy by checking the graph, average standard deviation, and the average change of the calculated angles. The accuracy of performance was also acquired by running the device and checking the outputs. My first prototype used accelerometer and gyroscope sensors from the Arduino MPU6050 sensor, getting a changeable graph, achieving 0.0295 of standard deviations, 0.25 of average change, and 66.6% accuracy of performance. The second prototype used only the gyroscope, and it got a constant graph, achieved 0.0062 of standard deviation, 0.075 of average change, and 100% accuracy of performance, indicating that the accelerometer sensor aggravated the functionality of the device. Using the gyroscope sensor allowed it to measure the orientations of separate axes without affecting each other and also increased the stability and accuracy of the measurements.Keywords: implant, guide, accelerometer, gyroscope, handpiece
Procedia PDF Downloads 4324782 The Impact of Teaching Critical Reading Strategies on Students' Performance in English and Communication Skills in College of Education, Azare, Bauchi State Nigeria
Authors: Musa Galadima Toro
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The study focused on the impact of teaching critical reading strategies on students’ performance in English and communication skills at the college of education Azare Bauchi state, Nigeria. It adopted a pre-test, post-test experimental group design. A sample of two hundred and forty (240) students was randomly selected from four departments within the school. The students were randomized into two groups: experimental and control groups. The experimental group was taught critical reading strategies as a form of treatment, while the control group involved in normal reading comprehension exercises. The findings of the study showed a significant difference in the performance of students who were taught critical reading strategies at the post- test level. Recommendations based on the findings of the study were proffered such as placing more emphasis on teaching critical reading strategies in order to improve students’ creative thinking skills and also encouraging students to read articles in science and humanities to improve their reading skills among others.Keywords: English, communication skill, critical reading, strategies
Procedia PDF Downloads 27224781 Characterization of Sintered Fe-Cr-Mn Powder Mixtures Containing Intermetallics
Authors: A. Yonetken, A. Erol, M. Cakmakkaya
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Intermetallic materials are among advanced technology materials that have outstanding mechanical and physical properties for high temperature applications. Especially creep resistance, low density and high hardness properties stand out in such intermetallics. The microstructure, mechanical properties of %88Ni-%10Cr and %2Mn powders were investigated using specimens produced by tube furnace sintering at 900-1300°C temperature. A composite consisting of ternary additions, a metallic phase, Fe ,Cr and Mn have been prepared under Ar shroud and then tube furnace sintered. XRD, SEM (Scanning Electron Microscope), were investigated to characterize the properties of the specimens. Experimental results carried out for composition %88Ni-%10Cr and %2Mn at 1300°C suggest that the best properties as 138,80HV and 6,269/cm3 density were obtained at 1300°C.Keywords: composite, high temperature, intermetallic, sintering
Procedia PDF Downloads 40724780 The Cooperation among Insulin, Cortisol and Thyroid Hormones in Morbid Obese Children and Metabolic Syndrome
Authors: Orkide Donma, Mustafa M. Donma
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Obesity, a disease associated with a low-grade inflammation, is a risk factor for the development of metabolic syndrome (MetS). So far, MetS risk factors such as parameters related to glucose and lipid metabolisms as well as blood pressure were considered for the evaluation of this disease. There are still some ambiguities related to the characteristic features of MetS observed particularly in pediatric population. Hormonal imbalance is also important, and quite a lot information exists about the behaviour of some hormones in adults. However, the hormonal profiles in pediatric metabolism have not been cleared yet. The aim of this study is to investigate the profiles of cortisol, insulin, and thyroid hormones in children with MetS. The study population was composed of morbid obese (MO) children without (Group 1) and with (Group 2) MetS components. WHO BMI-for age and sex percentiles were used for the classification of obesity. The values above 99 percentile were defined as morbid obesity. Components of MetS (central obesity, glucose intolerance, high blood pressure, high triacylglycerol levels, low levels of high density lipoprotein cholesterol) were determined. Anthropometric measurements were performed. Ratios as well as obesity indices were calculated. Insulin, cortisol, thyroid stimulating hormone (TSH), free T3 and free T4 analyses were performed by electrochemiluminescence immunoassay. Data were evaluated by statistical package for social sciences program. p<0.05 was accepted as the degree for statistical significance. The mean ages±SD values of Group 1 and Group 2 were 9.9±3.1 years and 10.8±3.2 years, respectively. Body mass index (BMI) values were calculated as 27.4±5.9 kg/m2 and 30.6±8.1 kg/m2, successively. There were no statistically significant differences between the ages and BMI values of the groups. Insulin levels were statistically significantly increased in MetS in comparison with the levels measured in MO children. There was not any difference between MO children and those with MetS in terms of cortisol, T3, T4 and TSH. However, T4 levels were positively correlated with cortisol and negatively correlated with insulin. None of these correlations were observed in MO children. Cortisol levels in both MO as well as MetS group were significantly correlated. Cortisol, insulin, and thyroid hormones are essential for life. Cortisol, called the control system for hormones, orchestrates the performance of other key hormones. It seems to establish a connection between hormone imbalance and inflammation. During an inflammatory state, more cortisol is produced to fight inflammation. High cortisol levels prevent the conversion of the inactive form of the thyroid hormone T4 into active form T3. Insulin is reduced due to low thyroid hormone. T3, which is essential for blood sugar control- requires cortisol levels within the normal range. Positive association of T4 with cortisol and negative association of it with insulin are the indicators of such a delicate balance among these hormones also in children with MetS.Keywords: children, cortisol, insulin, metabolic syndrome, thyroid hormones
Procedia PDF Downloads 14824779 An Efficient Approach for Speed up Non-Negative Matrix Factorization for High Dimensional Data
Authors: Bharat Singh Om Prakash Vyas
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Now a day’s applications deal with High Dimensional Data have tremendously used in the popular areas. To tackle with such kind of data various approached has been developed by researchers in the last few decades. To tackle with such kind of data various approached has been developed by researchers in the last few decades. One of the problems with the NMF approaches, its randomized valued could not provide absolute optimization in limited iteration, but having local optimization. Due to this, we have proposed a new approach that considers the initial values of the decomposition to tackle the issues of computationally expensive. We have devised an algorithm for initializing the values of the decomposed matrix based on the PSO (Particle Swarm Optimization). Through the experimental result, we will show the proposed method converse very fast in comparison to other row rank approximation like simple NMF multiplicative, and ACLS techniques.Keywords: ALS, NMF, high dimensional data, RMSE
Procedia PDF Downloads 34224778 Comparison of Non-destructive Devices to Quantify the Moisture Content of Bio-Based Insulation Materials on Construction Sites
Authors: Léa Caban, Lucile Soudani, Julien Berger, Armelle Nouviaire, Emilio Bastidas-Arteaga
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Improvement of the thermal performance of buildings is a high concern for the construction industry. With the increase in environmental issues, new types of construction materials are being developed. These include bio-based insulation materials. They capture carbon dioxide, can be produced locally, and have good thermal performance. However, their behavior with respect to moisture transfer is still facing some issues. With a high porosity, the mass transfer is more important in those materials than in mineral insulation ones. Therefore, they can be more sensitive to moisture disorders such as mold growth, condensation risks or decrease of the wall energy efficiency. For this reason, the initial moisture content on the construction site is a piece of crucial knowledge. Measuring moisture content in a laboratory is a mastered task. Diverse methods exist but the easiest and the reference one is gravimetric. A material is weighed dry and wet, and its moisture content is mathematically deduced. Non-destructive methods (NDT) are promising tools to determine in an easy and fast way the moisture content in a laboratory or on construction sites. However, the quality and reliability of the measures are influenced by several factors. Classical NDT portable devices usable on-site measure the capacity or the resistivity of materials. Water’s electrical properties are very different from those of construction materials, which is why the water content can be deduced from these measurements. However, most moisture meters are made to measure wooden materials, and some of them can be adapted for construction materials with calibration curves. Anyway, these devices are almost never calibrated for insulation materials. The main objective of this study is to determine the reliability of moisture meters in the measurement of biobased insulation materials. The determination of which one of the capacitive or resistive methods is the most accurate and which device gives the best result is made. Several biobased insulation materials are tested. Recycled cotton, two types of wood fibers of different densities (53 and 158 kg/m3) and a mix of linen, cotton, and hemp. It seems important to assess the behavior of a mineral material, so glass wool is also measured. An experimental campaign is performed in a laboratory. A gravimetric measurement of the materials is carried out for every level of moisture content. These levels are set using a climatic chamber and by setting the relative humidity level for a constant temperature. The mass-based moisture contents measured are considered as references values, and the results given by moisture meters are compared to them. A complete analysis of the uncertainty measurement is also done. These results are used to analyze the reliability of moisture meters depending on the materials and their water content. This makes it possible to determine whether the moisture meters are reliable, and which one is the most accurate. It will then be used for future measurements on construction sites to assess the initial hygrothermal state of insulation materials, on both new-build and renovation projects.Keywords: capacitance method, electrical resistance method, insulation materials, moisture transfer, non-destructive testing
Procedia PDF Downloads 12524777 Effects of Copper Oxide Nanoparticles on the Growth Performance, Antioxidant Enzymes Activity and Gut Morphology of Broiler Chickens
Authors: Mohammad Nassiri, Farhad Ahmadi
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This research was carried out to investigate the effects of copper oxide nanoparticles (nano-CuO) on performance and gut morphology of broiler chickens. A total of 240 one-day-old male chickens (Ross-308) were randomly divided in a completely randomized design, the inclusion of 4 groups of 60 birds with 4 replicates and 15 birds in each. Experimental diets were as follow: T1 control (basal diets, without nano-CuO but contain 9.1 mg Cu/kg from CuO), T2, T3, and T4 basal diet supplementation with 30, 60, and 90 mg nano-CuO/kg, respectively. Feed intake (FI) and gain weight as weekly recorded and on d 21 feed conversion ratio (FCR) were calculated. Furthermore, at the end of the trial (21 d), four birds per treatment (one bird/replicate) randomly selected and after removed blood samples, they slaughtered and then to the analysis of gut morphological. A segment (10 cm) from the middle part of duodenum and jejunum was removed and put in the formalin 10% (pH = 7). The results revealed that nano-CuO had significantly increased body weight (P = 0.029, but feed intake (P = 0.017), and feed conversion ratio (P = 0.031) decreased in the birds that fed 90 mg nano-CuO when compared to control and the other groups. Total antioxidant capacity (P = 0.041), superoxide dismutase (P = 0.036), and glutathione peroxidase (P = 0.048) were more in the birds fed diet inclusion of 60 and 90 mg nano-CuO (T4) than other treatments. The lowest malonaldehyde (MDA) level was observed in T3 (P = 0.23) and T4 (P = 0.028) decreased (P = 0.17). The villi height and villi height to crypt depth (VH/CD ratio) numerically increased (P = 0.09) in the bird fed 90 mg nano-CuO in comparison with other treatments. According to present results, it could be concluded that dietary nano-CuO improved performance parameters and antioxidant status of broiler chickens during starter period. As well, the optimum improvement observed in the birds fed diet inclusion of 90 mg nano-CuO/kg.Keywords: antioxidant, broilers, copper, performance, nanoparticles
Procedia PDF Downloads 57224776 Investigation on the Capacitive Deionization of Functionalized Carbon Nanotubes (F-CNTs) and Silver-Decorated F-CNTs for Water Softening
Authors: Khrizelle Angelique Sablan, Rizalinda De Leon, Jaeyoung Lee, Joey Ocon
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The impending water shortage drives us to find alternative sources of water. One of the possible solutions is desalination of seawater. There are numerous processes by which it can be done and one if which is capacitive deionization. Capacitive deionization is a relatively new technique for water desalination. It utilizes the electric double layer for ion adsorption. Carbon-based materials are commonly used as electrodes for capacitive deionization. In this study, carbon nanotubes (CNTs) were treated in a mixture of nitric and sulfuric acid. The silver addition was also facilitated to incorporate antimicrobial action. The acid-treated carbon nanotubes (f-CNTs) and silver-decorated f-CNTs (Ag@f-CNTs) were used as electrode materials for seawater deionization and compared with CNT and acid-treated CNT. The synthesized materials were characterized using TEM, EDS, XRD, XPS and BET. The electrochemical performance was evaluated using cyclic voltammetry, and the deionization performance was tested on a single cell with water containing 64mg/L NaCl. The results showed that the synthesized Ag@f-CNT-10 H could have better performance than CNT and a-CNT with a maximum ion removal efficiency of 50.22% and a corresponding adsorption capacity of 3.21 mg/g. It also showed antimicrobial activity against E. coli. However, the said material lacks stability as the efficiency decreases with repeated usage of the electrode.Keywords: capacitive deionization, carbon nanotubes, desalination, acid functionalization, silver
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