Search results for: rainbow experiments
1671 Mixture of Polymers and Coating Fullerene Soft Nanoparticles
Authors: L. Bouzina, A. Bensafi, M. Duval, C. Mathis, M. Rawiso
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We study the stability and structural properties of mixtures of model nanoparticles and non-adsorbing polymers in the 'protein limit', where the size of polymers exceeds the particle size substantially. We have synthesized in institute (Charles Sadron Strasbourg) model nanoparticles by coating fullerene C60 molecules with low molecular weight polystyrene (PS) chains (6 PS chains with a degree of polymerization close to 25 and 50 are grafted on each fullerene C60 molecule. We will present a Small Angle Neutron scattering (SANS) study of Tetrahydrofuran (THF) solutions involving long polystyrene (PS) chains and fullerene (C60) nanoparticles. Long PS chains and C60 nanoparticles with different arm lengths were synthesized either hydrogenated or deuteriated. They were characterized through Size Exclusion Chromatography (SEC) and Quasielastic Light Scattering (QLS). In this way, the solubility of the C60 nanoparticles in the usual good solvents of PS was controlled. SANS experiments were performed by use of the contrast variation method in order to measure the partial scattering functions related to both components. They allow us to obtain information about the dispersion state of the C60 nanoparticles as well as the average conformation of the long PS chains. Specifically, they show that the addition of long polymer chains leads to the existence of an additional attractive interaction in between soft nanoparticles.Keywords: fulleren nanoparticles, polymer, small angle neutron scattering, solubility
Procedia PDF Downloads 3781670 Optimizing the Elevated Nitritation for Autotrophic/Heterotrophic Denitritation in CSTR by Treating Livestock Wastewater
Authors: Hammad Khan, Wookeun Bae
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The objective of this study was to optimize and control the highly loaded and efficient nitrite production having suitability for autotrophic and heterotrophic denitritation. A lab scale CSTR for partial and full nitritation was operated to treat the livestock manure digester liquor having an ammonium concentration of ~2000 mg-NH4+-N/L and biodegradable contents of ~0.8 g-COD/L. The experiments were performed at 30°C, pH: 8.0 DO: 1.5 mg/L and SRT ranging from 7-20 days. After 125 days operation, >95% nitrite buildup having the ammonium loading rate of ~3.2 kg-NH4+-N/m3-day was seen with almost complete ammonium conversion. On increasing the loading rate further (i.e. from 3.2-6.2 kg-NH4+-N/m3-day), stability of the system remained unaffected. On decreasing the pH from 8 to7.5 and further 7.2, removal rate can be easily controlled as 95%, 75% and even 50%. Results demonstrated that nitritation stability and desired removal rates are controlled by a balance of simultaneous inhibition by FA and FNA, pH affect and DO limitation. These parameters proved to be effective even to produce an appropriate influent for anammox. In addition, a mathematical model, identified through the occurring biological reactions, is proposed to optimize the full and partial nitritation process. The proposed model presents relationship between pH, ammonium and produced nitrite for full and partial nitritation under the varying concentrations of DO, and simultaneous inhibition by FA and FNA.Keywords: stable nitritation, high loading, autrophic denitritation, hetrotrophic denitritation
Procedia PDF Downloads 3291669 Effect of Graphene Oxide Nanoparticles on a Heavy Oilfield: Interfacial Tension, Wettability and Oil Displacement Studies
Authors: Jimena Lizeth Gomez Delgado, Jhon Jairo Rodriguez, Nicolas Santos, Enrique Mejia Ospino
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Nanotechnology has played an important role in the hydrocarbon industry, recently , due to the unique properties of graphene oxide nanoparticles, they have been incorporated in different studies enhanced oil recovery. Nonetheless, very few studies have used graphene oxide nanoparticles in coreflooding experiments. Herein, the use of Graphene oxide (GO) nanoparticle was explored, exploited and evaluated. The performance of Graphene oxide nanoparticles on the interfacial properties in the presence of different electrolyte concentrations representative of field brine and pH conditions was investigated. Moreover, wettability behavior of the nanofluid at the oil/sand interface was studied used contact angle and Amott Harvey evaluation. Experimental result shows that the adsorption of GO on the sandstone surface changes the wettability of the sandstone from being strongly crude oil-wet to intermediate crude oil-wettability. At 900 ppm formation brine with 8 pH solution and 0.09 wt% nanoparticles concentration, Graphene oxide nanofluid exhibited better performance under the different electrolyte concentration studied. Finally, heavy oil displacement test in sandstone cores showed that oil recovery of Graphene oxide nanofluid had 7% incremental oil recovery over conventional waterflooding.Keywords: nanoparticle, graphene oxide, nanotechnology, wettability, enhanced oil recovery, coreflooding
Procedia PDF Downloads 1111668 Selecting Answers for Questions with Multiple Answer Choices in Arabic Question Answering Based on Textual Entailment Recognition
Authors: Anes Enakoa, Yawei Liang
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Question Answering (QA) system is one of the most important and demanding tasks in the field of Natural Language Processing (NLP). In QA systems, the answer generation task generates a list of candidate answers to the user's question, in which only one answer is correct. Answer selection is one of the main components of the QA, which is concerned with selecting the best answer choice from the candidate answers suggested by the system. However, the selection process can be very challenging especially in Arabic due to its particularities. To address this challenge, an approach is proposed to answer questions with multiple answer choices for Arabic QA systems based on Textual Entailment (TE) recognition. The developed approach employs a Support Vector Machine that considers lexical, semantic and syntactic features in order to recognize the entailment between the generated hypotheses (H) and the text (T). A set of experiments has been conducted for performance evaluation and the overall performance of the proposed method reached an accuracy of 67.5% with C@1 score of 80.46%. The obtained results are promising and demonstrate that the proposed method is effective for TE recognition task.Keywords: information retrieval, machine learning, natural language processing, question answering, textual entailment
Procedia PDF Downloads 1461667 Seed Germination, Seedling Emergence and Response to Herbicides of Papaver Species (Papaver rhoeas and P. dubium)
Authors: Faezeh Zaefarian1, Sajedeh Golmohammadzadeh, Mohammad Rezvani
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Weed management decisions for weed species can be derived from knowledge of seed germination biology. Experiments were conducted in laboratory and greenhouse to determine the effects of light, temperature, salt and water stress, seed burial depth on seed germination and seedling emergence of Papaver rhoeas and P.dubium and to assay the response of these species to commonly available POST herbicides. Germination of the Papaver seeds was influenced by the tested temperatures (day/night temperatures of 20 and 25 °C) and light. The concentrations of sodium chloride, ranging from 0 to 80 mM, influence germination of seeds. The osmotic potential required for 50% inhibition of maximum germination of P. rhoeas was -0.27 MPa and for P. dubium species was 0.25 MPa. Seedling emergence was greatest for the seeds placed at 1 cm and emergence declined with increased burial depth in the soil. No seedlings emerged from a burial depth of 6 cm. The herbicide 2,4-D at 400 g ai ha-1 provided excellent control of both species when applied at the four-leaf and six-leaf stages. However, at the six-leaf stage, percent control was reduced. The information gained from this study could contribute to developing components of integrated weed management strategies for Papaver species.Keywords: germination, papaver species, planting depth, POST herbicides
Procedia PDF Downloads 2471666 The Communication Library DIALOG for iFDAQ of the COMPASS Experiment
Authors: Y. Bai, M. Bodlak, V. Frolov, S. Huber, V. Jary, I. Konorov, D. Levit, J. Novy, D. Steffen, O. Subrt, M. Virius
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Modern experiments in high energy physics impose great demands on the reliability, the efficiency, and the data rate of Data Acquisition Systems (DAQ). This contribution focuses on the development and deployment of the new communication library DIALOG for the intelligent, FPGA-based Data Acquisition System (iFDAQ) of the COMPASS experiment at CERN. The iFDAQ utilizing a hardware event builder is designed to be able to readout data at the maximum rate of the experiment. The DIALOG library is a communication system both for distributed and mixed environments, it provides a network transparent inter-process communication layer. Using the high-performance and modern C++ framework Qt and its Qt Network API, the DIALOG library presents an alternative to the previously used DIM library. The DIALOG library was fully incorporated to all processes in the iFDAQ during the run 2016. From the software point of view, it might be considered as a significant improvement of iFDAQ in comparison with the previous run. To extend the possibilities of debugging, the online monitoring of communication among processes via DIALOG GUI is a desirable feature. In the paper, we present the DIALOG library from several insights and discuss it in a detailed way. Moreover, the efficiency measurement and comparison with the DIM library with respect to the iFDAQ requirements is provided.Keywords: data acquisition system, DIALOG library, DIM library, FPGA, Qt framework, TCP/IP
Procedia PDF Downloads 3201665 Understanding Nanocarrier Efficacy in Drug Delivery Systems Using Molecular Dynamics
Authors: Maedeh Rahimnejad, Bahman Vahidi, Bahman Ebrahimi Hoseinzadeh, Fatemeh Yazdian, Puria Motamed Fath, Roghieh Jamjah
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Introduction: The intensive labor and high cost of developing new vehicles for controlled drug delivery highlights the need for a change in their discovery process. Computational models can be used to accelerate experimental steps and control the high cost of experiments. Methods: In this work, to better understand the interaction of anti-cancer drug and the nanocarrier with the cell membrane, we have done molecular dynamics simulation using NAMD. We have chosen paclitaxel for the drug molecule and dipalmitoylphosphatidylcholine (DPPC) as a natural phospholipid nanocarrier. Results: Next, center of mass (COM) between molecules and the van der Waals interaction energy close to the cell membrane has been analyzed. Furthermore, the simulation results of the paclitaxel interaction with the cell membrane and the interaction of DPPC as a nanocarrier loaded by the drug with the cell membrane have been compared. Discussion: Analysis by molecular dynamics (MD) showed that not only the energy between the nanocarrier and the cell membrane is low, but also the center of mass amount decreases in the nanocarrier and the cell membrane system during the interaction; therefore they show significantly better interaction in comparison to the individual drug with the cell membrane.Keywords: anti-cancer drug, center of mass, interaction energy, molecular dynamics simulation, nanocarrier
Procedia PDF Downloads 3011664 mKDNAD: A Network Flow Anomaly Detection Method Based On Multi-teacher Knowledge Distillation
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Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning
Procedia PDF Downloads 1261663 The Effect of Micro-Arc Oxidation Coated Piston Crown on Engine Characteristics in a Spark Ignited Engine
Authors: A.Velavan, C. G. Saravanan, M. Vikneswaran, E. James Gunasekaran
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In present investigation, experiments were carried out to compare the effect of the ceramic coated piston crown and uncoated piston on combustion, performance and emission characteristics of a port injected Spark Ignited engine. The piston crown was coated with aluminium alloy in the form ceramic oxide layer of thickness 500 µm using micro-arc oxidation technique. This ceramic coating will act as a thermal barrier which reduces in-cylinder heat rejection and increases the durability of the piston by withstanding high temperature and pressure produced during combustion. Flame visualization inside the combustion chamber was carried out using AVL Visioscope combustion analyzer to predict the type of combustion occurs at different load condition. Based on the experimental results, it was found that the coated piston shows an improved thermal efficiency when compared to uncoated piston. This is because more heat presents in the combustion chamber which helps efficient combustion of the fuel. The CO and HC emissions were found to be reduced due to better combustion of the fuel whereas NOx emission was increased due to increase in combustion temperature for ceramic coated piston.Keywords: coated piston, micro-arc oxidation, thermal barrier, thermal efficiency, visioscope
Procedia PDF Downloads 1501662 Imp_hist-Si: Improved Hybrid Image Segmentation Technique for Satellite Imagery to Decrease the Segmentation Error Rate
Authors: Neetu Manocha
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Image segmentation is a technique where a picture is parted into distinct parts having similar features which have a place with similar items. Various segmentation strategies have been proposed as of late by prominent analysts. But, after ultimate thorough research, the novelists have analyzed that generally, the old methods do not decrease the segmentation error rate. Then author finds the technique HIST-SI to decrease the segmentation error rates. In this technique, cluster-based and threshold-based segmentation techniques are merged together. After then, to improve the result of HIST-SI, the authors added the method of filtering and linking in this technique named Imp_HIST-SI to decrease the segmentation error rates. The goal of this research is to find a new technique to decrease the segmentation error rates and produce much better results than the HIST-SI technique. For testing the proposed technique, a dataset of Bhuvan – a National Geoportal developed and hosted by ISRO (Indian Space Research Organisation) is used. Experiments are conducted using Scikit-image & OpenCV tools of Python, and performance is evaluated and compared over various existing image segmentation techniques for several matrices, i.e., Mean Square Error (MSE) and Peak Signal Noise Ratio (PSNR).Keywords: satellite image, image segmentation, edge detection, error rate, MSE, PSNR, HIST-SI, linking, filtering, imp_HIST-SI
Procedia PDF Downloads 1421661 A Slip Transmission through Alpha/Beta Boundaries in a Titanium Alloy (Ti-6Al-4V)
Authors: Rayan B. M. Ameen, Ian P. Jones, Yu Lung Chiu
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Single alpha-beta colony micro-pillars have been manufactured from a polycrystalline commercial Ti-6Al-4V sample using Focused Ion Beam (FIB). Each pillar contained two alpha lamellae separated by a thin fillet of beta phase. A nano-indenter was then used to conduct uniaxial micro-compression tests on Ti alloy single crystals, using a diamond flat tip as a compression platen. By controlling the crystal orientation along the micro-pillar using Electron back scattering diffraction (EBSD) different slip systems have been selectively activated. The advantage of the micro-compression method over conventional mechanical testing techniques is the ability to localize a single crystal volume which is characterizable after deformation. By matching the stress-strain relations resulting from micro-compression experiments to TEM (Transmission Electron Microscopy) studies of slip transmission mechanisms through the α-β interfaces, some proper constitutive material parameters such as the role of these interfaces in determining yield, strain-hardening behaviour, initial dislocation density and the critical resolved shear stress are suggested.Keywords: α/β-Ti alloy, focused ion beam, micro-mechanical test, nano-indentation, transmission electron diffraction, plastic flow
Procedia PDF Downloads 3871660 Storage Study of Bael (Aegle marmelos Correa.) Fruit and Pulp of Cv. Pant Sujata
Authors: B. R. Jana, Madhumita Singh
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Storage study of bael fruit and pulp were conducted at ICAR-RCER, Research Centre Ranchi to find out suitable storage life to extent the availability of the fruit and produce the value added product in form of fruit. The cultivar under storage is Pant Sujata. CFB box packing resulted in minimum 21 % PLW during 2010-11 during its 28-35 days storage under ambient temperature. CFB box and Gunny bag retains maximum total sugar (17.3-17.4 °B) after 28 days storage. Bael pulp of cultivar Pant Sujata can be stored up to 2 months at 4 °C with good quality condition. Treatments were highly significant in the characters such as T.S.S., acidity, reducing sugar and total sugar. Storage conditions and treatments interaction were insignificant in all characters except acidity. The maximum T.S.S. of 21.87 °B has been found in sample treated with 800 ppm benzoic acid when kept for two months at 4 °C temperature. This treatment also resulted in retaining the maximum reducing sugar (8.09 %) and total sugar content (9.52 %) at same storage condition than other treatments. From the present experiments, it is concluded that CFB box packing and pulp storage with 800 ppm benzoic acid at 4 °C are important to extent the availability of bael for two months.Keywords: bael, storage, fruits, pulp, benzoic acid
Procedia PDF Downloads 2481659 A Survey and Theory of the Effects of Various Hamlet Videos on Viewers’ Brains
Authors: Mark Pizzato
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How do ideas, images, and emotions in stage-plays and videos affect us? Do they evoke a greater awareness (or cognitive reappraisal of emotions) through possible shifts between left-cortical, right-cortical, and subcortical networks? To address these questions, this presentation summarizes the research of various neuroscientists, especially Bernard Baars and others involved in Global Workspace Theory, Matthew Lieberman in social neuroscience, Iain McGilchrist on left and right cortical functions, and Jaak Panksepp on the subcortical circuits of primal emotions. Through such research, this presentation offers an ‘inner theatre’ model of the brain, regarding major hubs of neural networks and our animal ancestry. It also considers recent experiments, by Mario Beauregard, on the cognitive reappraisal of sad, erotic, and aversive film clips. Finally, it applies the inner-theatre model and related research to survey results of theatre students who read and then watched the ‘To be or not to be’ speech in 8 different video versions (from stage and screen productions) of William Shakespeare’s Hamlet. Findings show that students become aware of left-cortical, right-cortical, and subcortical brain functions—and shifts between them—through staging and movie-making choices in each of the different videos.Keywords: cognitive reappraisal, Hamlet, neuroscience, Shakespeare, theatre
Procedia PDF Downloads 3181658 Random Subspace Neural Classifier for Meteor Recognition in the Night Sky
Authors: Carlos Vera, Tetyana Baydyk, Ernst Kussul, Graciela Velasco, Miguel Aparicio
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This article describes the Random Subspace Neural Classifier (RSC) for the recognition of meteors in the night sky. We used images of meteors entering the atmosphere at night between 8:00 p.m.-5: 00 a.m. The objective of this project is to classify meteor and star images (with stars as the image background). The monitoring of the sky and the classification of meteors are made for future applications by scientists. The image database was collected from different websites. We worked with RGB-type images with dimensions of 220x220 pixels stored in the BitMap Protocol (BMP) format. Subsequent window scanning and processing were carried out for each image. The scan window where the characteristics were extracted had the size of 20x20 pixels with a scanning step size of 10 pixels. Brightness, contrast and contour orientation histograms were used as inputs for the RSC. The RSC worked with two classes and classified into: 1) with meteors and 2) without meteors. Different tests were carried out by varying the number of training cycles and the number of images for training and recognition. The percentage error for the neural classifier was calculated. The results show a good RSC classifier response with 89% correct recognition. The results of these experiments are presented and discussed.Keywords: contour orientation histogram, meteors, night sky, RSC neural classifier, stars
Procedia PDF Downloads 1421657 Multi-Modal Feature Fusion Network for Speaker Recognition Task
Authors: Xiang Shijie, Zhou Dong, Tian Dan
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Speaker recognition is a crucial task in the field of speech processing, aimed at identifying individuals based on their vocal characteristics. However, existing speaker recognition methods face numerous challenges. Traditional methods primarily rely on audio signals, which often suffer from limitations in noisy environments, variations in speaking style, and insufficient sample sizes. Additionally, relying solely on audio features can sometimes fail to capture the unique identity of the speaker comprehensively, impacting recognition accuracy. To address these issues, we propose a multi-modal network architecture that simultaneously processes both audio and text signals. By gradually integrating audio and text features, we leverage the strengths of both modalities to enhance the robustness and accuracy of speaker recognition. Our experiments demonstrate significant improvements with this multi-modal approach, particularly in complex environments, where recognition performance has been notably enhanced. Our research not only highlights the limitations of current speaker recognition methods but also showcases the effectiveness of multi-modal fusion techniques in overcoming these limitations, providing valuable insights for future research.Keywords: feature fusion, memory network, multimodal input, speaker recognition
Procedia PDF Downloads 401656 Electrochemical Treatment and Chemical Analyses of Tannery Wastewater Using Sacrificial Aluminum Electrode, Ethiopia
Authors: Dessie Tibebe, Muluken Asmare, Marye Mulugeta, Yezbie Kassa, Zerubabel Moges, Dereje Yenealem, Tarekegn Fentie, Agmas Amare
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The performance of electrocoagulation (EC) using Aluminium electrodes for the treatment of effluent-containing chromium metal using a fixed bed electrochemical batch reactor was studied. In the present work, the efficiency evaluation of EC in removing physicochemical and heavy metals from real industrial tannery wastewater in the Amhara region, collected from Bahirdar, Debre Brihan, and Haik, was investigated. The treated and untreated samples were determined by AAS and ICP OES spectrophotometers. The results indicated that selected heavy metals were removed in all experiments with high removal percentages. The optimal results were obtained regarding both cost and electrocoagulation efficiency with initial pH = 3, initial concentration = 40 mg/L, electrolysis time = 30 min, current density = 40 mA/cm2, and temperature = 25oC favored metal removal. The maximum removal percentages of selected metals obtained were 84.42% for Haik, 92.64% for Bahir Dar and 94.90% for Debre Brihan. The sacrificial electrode and sludge were characterized by FT-IR, SEM and XRD. After treatment, some metals like chromium will be used again as a tanning agent in leather processing to promote a circular economy.Keywords: electrochemical, treatment, aluminum, tannery effluent
Procedia PDF Downloads 1161655 Computational Experiment on Evolution of E-Business Service Ecosystem
Authors: Xue Xiao, Sun Hao, Liu Donghua
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E-commerce is experiencing rapid development and evolution, but traditional research methods are difficult to fully demonstrate the relationship between micro factors and macro evolution in the development process of e-commerce, which cannot provide accurate assessment for the existing strategies and predict the future evolution trends. To solve these problems, this paper presents the concept of e-commerce service ecosystem based on the characteristics of e-commerce and business ecosystem theory, describes e-commerce environment as a complex adaptive system from the perspective of ecology, constructs a e-commerce service ecosystem model by using Agent-based modeling method and Java language in RePast simulation platform and conduct experiment through the way of computational experiment, attempt to provide a suitable and effective researching method for the research on e-commerce evolution. By two experiments, it can be found that system model built in this paper is able to show the evolution process of e-commerce service ecosystem and the relationship between micro factors and macro emergence. Therefore, the system model constructed by Agent-based method and computational experiment provides proper means to study the evolution of e-commerce ecosystem.Keywords: e-commerce service ecosystem, complex system, agent-based modeling, computational experiment
Procedia PDF Downloads 3611654 A Hybrid Feature Selection Algorithm with Neural Network for Software Fault Prediction
Authors: Khalaf Khatatneh, Nabeel Al-Milli, Amjad Hudaib, Monther Ali Tarawneh
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Software fault prediction identify potential faults in software modules during the development process. In this paper, we present a novel approach for software fault prediction by combining a feedforward neural network with particle swarm optimization (PSO). The PSO algorithm is employed as a feature selection technique to identify the most relevant metrics as inputs to the neural network. Which enhances the quality of feature selection and subsequently improves the performance of the neural network model. Through comprehensive experiments on software fault prediction datasets, the proposed hybrid approach achieves better results, outperforming traditional classification methods. The integration of PSO-based feature selection with the neural network enables the identification of critical metrics that provide more accurate fault prediction. Results shows the effectiveness of the proposed approach and its potential for reducing development costs and effort by detecting faults early in the software development lifecycle. Further research and validation on diverse datasets will help solidify the practical applicability of the new approach in real-world software engineering scenarios.Keywords: feature selection, neural network, particle swarm optimization, software fault prediction
Procedia PDF Downloads 991653 Development of Fuzzy Logic Control Ontology for E-Learning
Authors: Muhammad Sollehhuddin A. Jalil, Mohd Ibrahim Shapiai, Rubiyah Yusof
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Nowadays, ontology is common in many areas like artificial intelligence, bioinformatics, e-commerce, education and many more. Ontology is one of the focus areas in the field of Information Retrieval. The purpose of an ontology is to describe a conceptual representation of concepts and their relationships within a particular domain. In other words, ontology provides a common vocabulary for anyone who needs to share information in the domain. There are several ontology domains in various fields including engineering and non-engineering knowledge. However, there are only a few available ontology for engineering knowledge. Fuzzy logic as engineering knowledge is still not available as ontology domain. In general, fuzzy logic requires step-by-step guidelines and instructions of lab experiments. In this study, we presented domain ontology for Fuzzy Logic Control (FLC) knowledge. We give Table of Content (ToC) with middle strategy based on the Uschold and King method to develop FLC ontology. The proposed framework is developed using Protégé as the ontology tool. The Protégé’s ontology reasoner, known as the Pellet reasoner is then used to validate the presented framework. The presented framework offers better performance based on consistency and classification parameter index. In general, this ontology can provide a platform to anyone who needs to understand FLC knowledge.Keywords: engineering knowledge, fuzzy logic control ontology, ontology development, table of content
Procedia PDF Downloads 3011652 Achieving the Elevated Nitritation for Autotrophic/Heterotrophic Denitritation in CSTR by Treating Livestock Wastewater
Authors: Hammad Khan, Wookeun Bae
Abstract:
The objective of this study was to achieve, optimize and control the highly loaded and efficient nitrite production having suitability for autotrophic and heterotrophic denitritation. A lab scale CSTR for partial and full nitritation was operated to treat the livestock manure digester liquor having an ammonium concentration of ~2000 mg-NH4+-N/L and biodegradable contents of ~0.8 g-COD/L. The experiments were performed at 30°C, pH: 8.0, DO: 1.5 mg/L and SRT ranging from 7-20 days. After 125 days operation, >95% nitrite buildup having the ammonium loading rate of ~3.2 kg-NH4+-N/m3-day was seen with almost complete ammonium conversion. On increasing the loading rate further (i-e, from 3.2-6.2 kg-NH4+-N/m3-day), stability of the system remained unaffected. On decreasing the pH from 8 to 7.5 and further 7.2, removal rate can be easily controlled as 95%, 75% and even 50%. Results demonstrated that nitritation stability and desired removal rates are controlled by a balance of simultaneous inhibition by FA & FNA, pH affect and DO limitation. These parameters proved to be effective even to produce an appropriate influent for anammox. In addition, a mathematical model, identified through the occurring biological reactions, is proposed to optimize the full and partial nitritation process. The proposed model present relationship between pH, ammonium and produced nitrite for full and partial nitritation under the varying concentrations of DO, and simultaneous inhibition by FA and FNA.Keywords: stable nitritation, high loading, autrophic denitritation, hetrotrophic denitritation
Procedia PDF Downloads 2761651 Experimental Investigation on the Mechanical Behaviour of Three-Leaf Masonry Walls under In-Plane Loading
Authors: Osama Amer, Yaser Abdel-Aty, Mohamed Abd El Hady
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The present paper illustrates an experimental approach to provide understanding of the mechanical behavior and failure mechanisms of different typologies of unreinforced three-leaf masonry walls of historical Islamic architectural heritage in Egypt. The main objective of this study is to investigate the propagation of possible cracking, ultimate load, deformations and failure mechanisms. Experimental data on interface-shear and compression tests on large scale three-leaf masonry wallets are provided. The wallets were built basically of Egyptian limestone and modified lime mortar. External wallets were built of stone blocks while the inner leaf was built of rubble limestone. Different loading conditions and dimensions of core layer for two types of collar joints (with and without shear keys) are considered in the tests. Mechanical properties of the constituent materials of masonry were tested and a database of characteristic properties was created. The results of the experiments will highlight the properties, force-displacement curves, stress distribution of multiple-leaf masonry walls contributing to the derivation of rational design rules and validation of numerical models.Keywords: masonry, three-leaf walls, mechanical behavior, testing, architectural heritage
Procedia PDF Downloads 2941650 The Dynamic Metadata Schema in Neutron and Photon Communities: A Case Study of X-Ray Photon Correlation Spectroscopy
Authors: Amir Tosson, Mohammad Reza, Christian Gutt
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Metadata stands at the forefront of advancing data management practices within research communities, with particular significance in the realms of neutron and photon scattering. This paper introduces a groundbreaking approach—dynamic metadata schema—within the context of X-ray Photon Correlation Spectroscopy (XPCS). XPCS, a potent technique unravelling nanoscale dynamic processes, serves as an illustrative use case to demonstrate how dynamic metadata can revolutionize data acquisition, sharing, and analysis workflows. This paper explores the challenges encountered by the neutron and photon communities in navigating intricate data landscapes and highlights the prowess of dynamic metadata in addressing these hurdles. Our proposed approach empowers researchers to tailor metadata definitions to the evolving demands of experiments, thereby facilitating streamlined data integration, traceability, and collaborative exploration. Through tangible examples from the XPCS domain, we showcase how embracing dynamic metadata standards bestows advantages, enhancing data reproducibility, interoperability, and the diffusion of knowledge. Ultimately, this paper underscores the transformative potential of dynamic metadata, heralding a paradigm shift in data management within the neutron and photon research communities.Keywords: metadata, FAIR, data analysis, XPCS, IoT
Procedia PDF Downloads 651649 Pricing European Options under Jump Diffusion Models with Fast L-stable Padé Scheme
Authors: Salah Alrabeei, Mohammad Yousuf
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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.Keywords: Integral differential equations, , L-stable methods, pricing European options, Jump–diffusion model
Procedia PDF Downloads 1541648 An Immune-Inspired Web Defense Architecture
Authors: Islam Khalil, Amr El-Kadi
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With the increased use of web technologies, microservices, and Application Programming Interface (API) for integration between systems, and with the development of containerization of services on the operating system level as a method of isolating system execution and for easing the deployment and scaling of systems, there is a growing need as well as opportunities for providing platforms that improve the security of such services. In our work, we propose an architecture for a containerization platform that utilizes various concepts derived from the human immune system. The goal of the proposed containerization platform is to introduce the concept of slowing down or throttling suspected malicious digital pathogens (intrusions) to reduce their damage footprint while providing more opportunities for forensic inspection of suspected pathogens in addition to the ability to snapshot, rollback, and recover from possible damage. The proposed platform also leverages existing intrusion detection algorithms by integrating and orchestrating their cooperative operation for more effective intrusion detection. We show how this model reduces the damage footprint of intrusions and gives a greater time window for forensic investigation. Moreover, during our experiments, our proposed platform was able to uncover unintentional system design flaws that resulted in internal DDoS-like attacks by submodules of the system itself rather than external intrusions.Keywords: containers, human immunity, intrusion detection, security, web services
Procedia PDF Downloads 991647 Sepiolite as a Processing Aid in Fibre Reinforced Cement Produced in Hatschek Machine
Authors: R. Pérez Castells, J. M. Carbajo
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Sepiolite is used as a processing aid in the manufacture of fibre cement from the start of the replacement of asbestos in the 80s. Sepiolite increases the inter-laminar bond between cement layers and improves homogeneity of the slurries. A new type of sepiolite processed product, Wollatrop TF/C, has been checked as a retention agent for fine particles in the production of fibre cement in a Hatschek machine. The effect of Wollatrop T/FC on filtering and fine particle losses was studied as well as the interaction with anionic polyacrylamide and microsilica. The design of the experiments were factorial and the VDT equipment used for measuring retention and drainage was modified Rapid Köethen laboratory sheet former. Wollatrop TF/C increased the fine particle retention improving the economy of the process and reducing the accumulation of solids in recycled process water. At the same time, drainage time increased sharply at high concentration, however drainage time can be improved by adjusting APAM concentration. Wollatrop TF/C and microsilica are having very small interactions among them. Microsilica does not control fine particle losses while Wollatrop TF/C does efficiently. Further research on APAM type (molecular weight and anionic character) is advisable to improve drainage.Keywords: drainage, fibre-reinforced cement, fine particle losses, flocculation, microsilica, sepiolite
Procedia PDF Downloads 3291646 The Photocatalytic Approach for the Conversion of Polluted Seawater CO₂ into Renewable Source of Energy
Authors: Yasar N. Kavil, Yasser A. Shaban, Radwan K. Al Farawati, Mohamed I. Orif, Shahed U. M. Khanc
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Photocatalytic way of reduction of CO₂ in polluted seawater into chemical fuel, methanol, was successfully gained over Cu/C-co-doped TiO₂ nanoparticles under UV and natural sunlight. A homemade stirred batch annular reactor was used to carry out the photocatalytic reduction experiments. Photocatalysts with various Cu loadings (0, 0.5, 1, 3, 5 and 7 wt.%) were synthesized by the sol-gel procedure and were characterized by XRD, SEM, UV–Vis, FTIR, and XPS. The photocatalytic production of methanol was promoted by the co-doping with C and Cu into TiO₂. This improvement was attributed to the modification of bandgap energy and the hindrance of the charges recombination. The polluted seawater showing the yield depended on its background hydrographic parameters. We assessed two types of polluted seawater system, the observed yield was 2910 and 990 µmol g⁻¹ after 5 h of illumination under UV and natural sunlight respectively in system 1 and the corresponding yield in system 2 was 2250 and 910 µmol g⁻¹ after 5 h of illumination. The production of methanol in the case of oxygen-depleted water was low, this is mainly attributed to the competition of methanogenic bacteria over methanol production. The results indicated that the methanol yield produced by Cu-C/TiO₂ was much higher than those of carbon-modified titanium oxide (C/TiO₂) and Degussa (P25-TiO₂). Under the current experimental condition, the optimum loading was achieved by the doping of 3 wt % of Cu. The highest methanol yield was obtained over 1 g L-1 of 3wt% Cu/C-TiO₂.Keywords: CO₂ photoreduction, copper, Cu/C-co-doped TiO₂, methanol, seawater
Procedia PDF Downloads 2801645 Si3N4-SiC Composites Produced by Using C Black and Sic Powder
Authors: Nilgun Kuskonmaz, Zeynep Taslıcukur Ozturk, Cem Sahin
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In this study, Si3N4-SiC composites were synthesized by using different raw materials. In the first method, Si3N4 and C black powder mixtures were used to fabricate Si3N4-SiC composites by in-situ carbothermal reduction process. The percentage of C black was only changed. The effects of carbon black percentage in the mixtures were analysed by characterization of SiC particles which were obtained in the Si3N4 matrix. In the second method, SiC particles were added to the matrix in different weight ratios. The composites were pressed by cold isostatic method under 150 MPa pressure and pressureless sintered at 1700-1850 °C during 1 hour in the argon atmosphere. AlN and Y2O3 were used as sintering additives. Sintering temperature, time and all the effects on in-situ reaction were studied. The densification and microstructure properties of the produced ceramics were analysed. Density was one of the main subjects in these reactions. It is very important during porous SiC sintering. Green density and relative density were measured higher for CIP samples. Samples which were added carbon black were more porous than SiC added samples. The increase in the carbon black, makes increase in porosity. The outcome of the experiments was SiC powders which were obtained at the grain boundries of β-Si3N4 particles.Keywords: silicon nitride, silicon carbide, carbon black, cold isostatic press, sintering
Procedia PDF Downloads 3111644 A Hybrid Algorithm for Collaborative Transportation Planning among Carriers
Authors: Elham Jelodari Mamaghani, Christian Prins, Haoxun Chen
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In this paper, there is concentration on collaborative transportation planning (CTP) among multiple carriers with pickup and delivery requests and time windows. This problem is a vehicle routing problem with constraints from standard vehicle routing problems and new constraints from a real-world application. In the problem, each carrier has a finite number of vehicles, and each request is a pickup and delivery request with time window. Moreover, each carrier has reserved requests, which must be served by itself, whereas its exchangeable requests can be outsourced to and served by other carriers. This collaboration among carriers can help them to reduce total transportation costs. A mixed integer programming model is proposed to the problem. To solve the model, a hybrid algorithm that combines Genetic Algorithm and Simulated Annealing (GASA) is proposed. This algorithm takes advantages of GASA at the same time. After tuning the parameters of the algorithm with the Taguchi method, the experiments are conducted and experimental results are provided for the hybrid algorithm. The results are compared with those obtained by a commercial solver. The comparison indicates that the GASA significantly outperforms the commercial solver.Keywords: centralized collaborative transportation, collaborative transportation with pickup and delivery, collaborative transportation with time windows, hybrid algorithm of GA and SA
Procedia PDF Downloads 3941643 Grains of Winter Wheat Spelt (Triticum spelta L.) for Save Food Production
Authors: D. Jablonskytė-Raščė, A. Mankevičienė, S. Supronienė, I. Kerienė, S. Maikštėnienė, S. Bliznikas, R. Česnulevičienė
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Organic farming does not allow the use of conventional mineral fertilizers and crop protection products. As a result, in our experiments we chose to grow different species of cereals and to see how cereal species affects mycotoxin accumulation. From the phytopathological and entomological viewpoint, the glumes of spelt grain perform a positive role since they protect grain from the infection of pathogenic microorganisms. On the background of the above-mentioned infection, there were more Fusarium–affected grains of spelt than of common wheat. It can be assumed that spelt is more susceptible to the Fusarium fungi infection than common wheat. This study describes the occurrence of DON, ZEA and T2/HT2 toxin in a survey of spelt and common wheat and their bran as well as flour. The analysis was conducted using the enzyme-linked immunosorbent assay (ELISA) method. The concentrations of DON, ZEA, and T2/HT2 in Triticum spelta and Triticum aestivum are influenced by species, cereal type and year interaction. The highest concentration of mycotoxin was found in spelt grain with glumes. The obtained results indicate the significantly higher concentrations of Fusarium toxins in glumes than in dehulled grain which implicate the possible protective effect of spelt wheat glumes. The lowest DON, ZEA, and T2/HT2 concentration was determined in spelt grain without glumes.Keywords: Fusarium mycotoxins, organic farming, spelt
Procedia PDF Downloads 3161642 Determining Fire Resistance of Wooden Construction Elements through Experimental Studies and Artificial Neural Network
Authors: Sakir Tasdemir, Mustafa Altin, Gamze Fahriye Pehlivan, Sadiye Didem Boztepe Erkis, Ismail Saritas, Selma Tasdemir
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Artificial intelligence applications are commonly used in industry in many fields in parallel with the developments in the computer technology. In this study, a fire room was prepared for the resistance of wooden construction elements and with the mechanism here, the experiments of polished materials were carried out. By utilizing from the experimental data, an artificial neural network (ANN) was modeled in order to evaluate the final cross sections of the wooden samples remaining from the fire. In modelling, experimental data obtained from the fire room were used. In the system developed, the first weight of samples (ws-gr), preliminary cross-section (pcs-mm2), fire time (ft-minute), fire temperature (t-oC) as input parameters and final cross-section (fcs-mm2) as output parameter were taken. When the results obtained from ANN and experimental data are compared after making statistical analyses, the data of two groups are determined to be coherent and seen to have no meaning difference between them. As a result, it is seen that ANN can be safely used in determining cross sections of wooden materials after fire and it prevents many disadvantages.Keywords: artificial neural network, final cross-section, fire retardant polishes, fire safety, wood resistance.
Procedia PDF Downloads 387