Search results for: Deep mixed column
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5291

Search results for: Deep mixed column

4871 Enhancement of Dissolved Oxygen Concentration during the Electrocoagulation Process Using an Innovative Flow Column: Electrocoagulation Reactor

Authors: Khalid S. Hashim, Andy Shaw, Rafid Alkhaddar

Abstract:

Dissolved oxygen (DO) plays a key role in the electrocoagulation process (EC) as it oxidizes the heavy metals, ammonia, and cyanide into other forms that can be removed easily from water. Hence, many of the previous investigations used external aerators to provide the required DO inside EC reactors, especially when the water being treated had a low DO (such as leachate and high organic content waters), or when the DO depleted during the EC treatment. Although the external aeration process effectively enhances the DO concentration, it has a significant impact on energy consumption. Thus, the present project aims to fill a part of this gap in the literature by an innovative use of perforated flow columns in the design of an EC reactor (ECR1). In order to investigate the performance of ECR1, water samples with a controlled DO concentration were pumped at different flow rates (110, 220, and 440 ml/min) to the ECR1 for 10 min. The obtained results demonstrated that the ECR1 increased the DO concentration from 5.0 to 9.54, 10.53, and 11.0 mg/L, which is equivalent to 90.8%, 110.6%, and 120% at flow rates of 110, 220, and 440 mL/min respectively.

Keywords: flow column, electrocoagulation, dissolved oxygen, water treatment

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4870 Numerical Study of Laminar Mixed Convection Heat Transfer of a Nanofluid in a Concentric Annular Tube Using Two-Phase Mixture Model

Authors: Roghayyeh Motallebzadeh, Shahin Hajizadeh, Mohammad Reza Ghasemi

Abstract:

Laminar mixed convection heat transfer of a nanofluid with prescribed constant heat flux on the inner wall of horizontal annular tube has been studied numerically based on two-phase mixture model in different Rayleigh numbers and Azimuth angles. Effects of applying of different volume fractions of Al2O3 nanoparticles in water as a base fluid on hydrodynamic and thermal behaviours of the fluid flow such as axial velocity, secondary flow, temperature, heat transfer coefficient and friction coefficient at the inner and outer wall region, has been investigated. Conservation equations in elliptical form has been utilized and solved in three dimensions for a steady flow. It is observed that, there is a good agreement between results in this work and previously published experimental and numerical works on mixed convection in horizontal annulus. These particles cause to increase convection heat transfer coefficient of the fluid, meanwhile there is no considerable effect on friction coefficient.

Keywords: buoyancy force, laminar mixed convection, mixture model, nano-fluid, two-phase

Procedia PDF Downloads 447
4869 Importance of CT and Timed Barium Esophagogram in the Contemporary Treatment of Patients with Achalasia

Authors: Sanja Jovanovic, Aleksandar Simic, Ognjan Skrobic, Dragan Masulovic, Aleksandra Djuric-Stefanovic

Abstract:

Introduction: Achalasia is an idiopathic primary esophageal motility disorder characterized by esophageal peristalsis and impaired swallow-induced relaxation of the lower esophageal sphincter (LES). It is a rare disease that affects both genders with an incidence of 1/100.000 and a prevalence rate of 10/100,000 per year. Objective: Laparoscopic Heller myotomy (LHM) represents a therapy of choice for patients with achalasia, providing excellent outcomes. The aim of this study was to evaluate the significance of computed tomography (CT) in analyzing achalasia subtypes and timed barium esophagogram (TBE) in evaluation of LHM success, as a part of standardized diagnostic protocol. Method: Fifty-one patients with achalasia, confirmed by manometric studies, in addition to standardized diagnostic methods, underwent CT and TBE. CT was done with multiplanar reconstruction, measuring the wall thickness above the esophago-gastric junction in the axial plane. TBE was performed preoperatively and two days postoperatively swallowing low-density barium sulfate, and plane upright frontal films were performed 1, 2 and 5 minutes after the ingestion. In all patients, LHM was done, and pre and postoperative height and weight of the barium column were compared. Results: According to CT findings we divided patients into 3 subtypes of achalasia according to wall thickness: < 4mm as subtype one, between 4 - 9mm as II, and > 10 mm as subtype 3. Correlation of manometric results, as a reference values, and CT findings indicated CT sensitivity of 90% and specificity of 70 % in establishing subtypes of achalasia. The preoperative values of TBE at 1, 2 and 5 minutes were: median barium column height 17.4 ± 7.4, 15.9 ± 6.2 and 13.9 ± 6.2 cm; median column width 5 ± 1.5, 4.7 ± 1.6 and 4.5 ± 1.8 cm respectively. LHM significantly reduced these values (height 7 ± 4.6, 5.8 ± 4.2, 3.7 ± 3.4 cm; width 2.9 ± 1.3, 2.6 ± 1.3 and 2.4 ± 1.4 cm), indicating the quantitative estimates of emptying as excellent (p value < 0.01). Conclusion: CT has high sensitivity and specificity in evaluation of achalasia subtypes, and can be introduced as an additional method for standardized evaluation of these patients. The quantitative assessment of TBE based on measurements of the barium column is an accurate and beneficial method, which adequately estimates esophageal emptying success of LHM.

Keywords: achalasia, computed tomography, esophagography, myotomy

Procedia PDF Downloads 199
4868 Analysis and Prediction of Netflix Viewing History Using Netflixlatte as an Enriched Real Data Pool

Authors: Amir Mabhout, Toktam Ghafarian, Amirhossein Farzin, Zahra Makki, Sajjad Alizadeh, Amirhossein Ghavi

Abstract:

The high number of Netflix subscribers makes it attractive for data scientists to extract valuable knowledge from the viewers' behavioural analyses. This paper presents a set of statistical insights into viewers' viewing history. After that, a deep learning model is used to predict the future watching behaviour of the users based on previous watching history within the Netflixlatte data pool. Netflixlatte in an aggregated and anonymized data pool of 320 Netflix viewers with a length 250 000 data points recorded between 2008-2022. We observe insightful correlations between the distribution of viewing time and the COVID-19 pandemic outbreak. The presented deep learning model predicts future movie and TV series viewing habits with an average loss of 0.175.

Keywords: data analysis, deep learning, LSTM neural network, netflix

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4867 Failure Criterion for Mixed Mode Fracture of Cracked Wood Specimens

Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

Abstract:

Investigation of fracture of wood components can prevent from catastrophic failures. Created fracture process zone (FPZ) in crack tip vicinity has important effect on failure of cracked composite materials. In this paper, a failure criterion for fracture investigation of cracked wood specimens under mixed mode I/II loading is presented. This criterion is based on maximum strain energy release rate and material nonlinearity in the vicinity of crack tip due to presence of microcracks. Verification of results with available experimental data proves the coincidence of the proposed criterion with the nature of fracture of wood. To simplify the estimation of nonlinear properties of FPZ, a damage factor is also introduced for engineering and application purposes.

Keywords: fracture criterion, mixed mode loading, damage zone, micro cracks

Procedia PDF Downloads 273
4866 Application of Deep Eutectic Solvent in the Extraction of Ferulic Acid from Palm Pressed Fibre

Authors: Ng Mei Han, Nu'man Abdul Hadi

Abstract:

Extraction of ferulic acid from palm pressed fiber using deep eutectic solvent (DES) of choline chloride-acetic acid (ChCl-AA) and choline chloride-citric acid (ChCl-CA) are reported. Influence of water content in DES on the extraction efficiency was investigated. ChCl-AA and ChCl-CA experienced a drop in viscosity from 9.678 to 1.429 and 22.658 ± 1.655 mm2/s, respectively as the water content in the DES increased from 0 to 50 wt% which contributed to higher extraction efficiency for the ferulic acid. Between 41,155 ± 940 mg/kg ferulic acid was obtained after 6 h reflux when ChCl-AA with 30 wt% water was used for the extraction compared to 30,940 ± 621 mg/kg when neat ChCl-AA was used. Although viscosity of the DES could be improved with the addition of water, there is a threshold where the DES could tolerate the presence of water without changing its solvent behavior. The optimum condition for extraction of ferulic acid from palm pressed fiber was heating for 6 h with DES containing 30 wt% water.

Keywords: deep eutectic solvent, extraction, ferulic acid, palm fibre

Procedia PDF Downloads 58
4865 Deep Routing Strategy: Deep Learning based Intelligent Routing in Software Defined Internet of Things.

Authors: Zabeehullah, Fahim Arif, Yawar Abbas

Abstract:

Software Defined Network (SDN) is a next genera-tion networking model which simplifies the traditional network complexities and improve the utilization of constrained resources. Currently, most of the SDN based Internet of Things(IoT) environments use traditional network routing strategies which work on the basis of max or min metric value. However, IoT network heterogeneity, dynamic traffic flow and complexity demands intelligent and self-adaptive routing algorithms because traditional routing algorithms lack the self-adaptions, intelligence and efficient utilization of resources. To some extent, SDN, due its flexibility, and centralized control has managed the IoT complexity and heterogeneity but still Software Defined IoT (SDIoT) lacks intelligence. To address this challenge, we proposed a model called Deep Routing Strategy (DRS) which uses Deep Learning algorithm to perform routing in SDIoT intelligently and efficiently. Our model uses real-time traffic for training and learning. Results demonstrate that proposed model has achieved high accuracy and low packet loss rate during path selection. Proposed model has also outperformed benchmark routing algorithm (OSPF). Moreover, proposed model provided encouraging results during high dynamic traffic flow.

Keywords: SDN, IoT, DL, ML, DRS

Procedia PDF Downloads 87
4864 Experimental Model of the Behaviour of Bolted Angles Connections with Stiffeners

Authors: Abdulkadir Cuneyt Aydin, Mahyar Maali, Mahmut Kılıç, Merve Sağıroğlu

Abstract:

The moment-rotation curves of semi-rigid connections are the visual expressions of the actual behaviour discovered in beam-to-column connections experiments. This research was to determine the behaviour of the connection using full-scale experiments under statically loaded. The stiffeners which are typically attached to beams web or flanges to control local buckling and to increase shear capacity in a beam web are almost always used in modern designs. They must also provide sufficient moment of inertia to control out of plane deformations. This study was undertaken to analyse the influence of stiffeners in the angles and beams on the behaviour of the beam-to-column joints. In addition, the aim was to provide necessary data to improve the Eurocode 3. The main parameters observed are the evolution of the resistance, the stiffness, the rotation capacity, the ductility of a joint and the Energy Dissipation. Experimental tests show that the plastic flexural resistance and the energy dissipation increased when thickness of stiffener beam, thickness of stiffener angles were increased in the test specimens. And also, while stiffness of joints, the bending moment capacity and the maximum bending moment increased with the increasing thickness of stiffener beam, these values decreased with the increasing thickness of stiffener angles. So, it is observed that the beam stiffener of angles are important in improving resistance moment of beam-to-column semi-rigid joints.

Keywords: bolted angles connection, semi-rigid joints, ductility of a joint, angles and beams stiffeners

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4863 Safe Disposal of Pyrite Rich Waste Rock Using Alkali Phosphate Treatment

Authors: Jae Gon Kim, Yongchan Cho, Jungwha Lee

Abstract:

Acid rock drainage (ARD) is generated by the oxidation of pyrite (FeS₂) contained in the excavated rocks upon its exposure to atmosphere and is an environmental concern at construction site due to its high acidity and high concentration of toxic elements. We developed the safe disposal method with the reduction of ARD generation by an alkali phosphate treatment. A pyrite rich andesite was collected from a railway construction site. The collected rock sample was crushed to be less than 3/8 inches in diameter using a jaw crusher. The crushed rock was filled in an acryl tube with 20 cm in diameter and 40 cm in height. Two treatments for the ARD reduction were conducted with duplicates: 1) the addition of 10mM KH₂PO₄_3% NaHCO₃ and 2) the addition of 10mM KH₂PO₄_3% NaHCO₃ and ordinary portland cement (OPC) on the top of the column. After the treatments, 500 ml of distilled water added to each column for every week for 3 weeks and then the column was flushed with 1,500 ml of distilled water in the 4th week. The pH, electrical conductivity (EC), concentrations of anions and cations of the leachates were monitored for 10 months. The pH of the leachates from the untreated column showed 2.1-3.7, but the leachates from the columns treated with the alkali phosphate solution with or without the OPC addition showed pH 6.7–8.9. The leachates from the treated columns had much lower concentrations of SO₄²⁻ and toxic elements such as Al, Mn, Fe and heavy metals than those from the untreated columns. However, the leachates from the treated columns had a higher As concentration than those from the untreated columns. There was no significant difference in chemical property between the leachates from the treated columns with and without the OPC addition. The chemistry of leachates indicates that the alkali phosphate treatment decreased the oxidation of sulfide and neutralized the acidic pore water. No significant effect of the OPC addition on the leachate chemistry has shown during 10-month experiment. However, we expect a positive effect of the OPC addition on the reduction of ARD generation in terms of long period. According to the results of this experiment, the alkali phosphate treatment of sulfide rich rock can be a promising technology for the safe disposal method with the ARD reduction.

Keywords: acid rock drainage, alkali phosphate treatment, pyrite rich rock, safe disposal

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4862 The Evaluation of Fuel Desulfurization Performance of Choline-Chloride Based Deep Eutectic Solvents with Addition of Graphene Oxide as Catalyst

Authors: Chiau Yuan Lim, Hayyiratul Fatimah Mohd Zaid, Fai Kait Chong

Abstract:

Deep Eutectic Solvent (DES) is used in various applications due to its simplicity in synthesis procedure, biodegradable, inexpensive and easily available chemical ingredients. Graphene Oxide is a popular catalyst that being used in various processes due to its stacking carbon sheets in layer which theoretically rapid up the catalytic processes. In this study, choline chloride based DESs were synthesized and ChCl-PEG(1:4) was found to be the most effective DES in performing desulfurization, which it is able to remove up to 47.4% of the sulfur content in the model oil in just 10 minutes, and up to 95% of sulfur content after repeat the process for six times. ChCl-PEG(1:4) able to perform up to 32.7% desulfurization on real diesel after 6 multiple stages. Thus, future research works should focus on removing the impurities on real diesel before utilising DESs in petroleum field.

Keywords: choline chloride, deep eutectic solvent, fuel desulfurization, graphene oxide

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4861 Influence of MgO Physically Mixed with Tungsten Oxide Supported Silica Catalyst on Coke Formation

Authors: Thidaya Thitiapichart

Abstract:

The effect of additional magnesium oxide (MgO) was investigated by using the tungsten oxide supported on silica catalyst (WOx/SiO2) physically mixed with MgO in a weight ratio 1:1. The both fresh and spent catalysts were characterized by FT-Raman spectrometer, UV-Vis spectrometer, X-Ray diffraction (XRD), and temperature programmed oxidation (TPO). The results indicated that the additional MgO could enhance the conversion of trans-2-butene due to isomerization reaction. However, adding MgO would increase the amount of coke deposit on the WOx/SiO2 catalyst. The TPO profile presents two peaks when the WOx/SiO2 catalyst was physically mixed with MgO. The further peak was suggested to be coming from the coke precursor that could be produced by isomerization reaction of the undesired product. Then, the occurred coke precursor could deposit and form coke on the acid catalyst.

Keywords: coke formation, metathesis, magnesium oxide, physically mix

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4860 Hydrogeological Study of Shallow and Deep Aquifers in Balaju-Boratar Area, Kathmandu, Central Nepal

Authors: Hitendra Raj Joshi, Bipin Lamichhane

Abstract:

Groundwater is the main source of water for the industries of Balaju Industrial District (BID) and the denizens of Balaju-Boratar area. The quantity of groundwater is in a fatal condition in the area than earlier days. Water levels in shallow wells have highly lowered and deep wells are not providing an adequate amount of water as before because of higher extraction rate than the recharge rate. The main recharge zone of the shallow aquifer lies at the foot of Nagarjuna mountain, where recent colluvial debris are accumulated. Urbanization in the area is the main reason for decreasing water table. Recharge source for the deep aquifer in the region is aquiclude leakage. Sand layer above the Kalimati clay is the shallow aquifer zone, which is limited only in Balaju and eastern part of the Boratar, while the layer below the Kalimati clay spreading around Gongabu, Machhapohari, and Balaju area is considered as a potential area of deep aquifer. Over extraction of groundwater without considering water balance in the aquifers may dry out the source and can initiate the land subsidence problem. Hence, all the responsible of the industries in BID area and the denizens of Balaju-Boratar area should be encouraged to practice artificial groundwater recharge.

Keywords: aquiclude leakage, Kalimati clay, groundwater recharge

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4859 Study of Syntactic Errors for Deep Parsing at Machine Translation

Authors: Yukiko Sasaki Alam, Shahid Alam

Abstract:

Syntactic parsing is vital for semantic treatment by many applications related to natural language processing (NLP), because form and content coincide in many cases. However, it has not yet reached the levels of reliable performance. By manually examining and analyzing individual machine translation output errors that involve syntax as well as semantics, this study attempts to discover what is required for improving syntactic and semantic parsing.

Keywords: syntactic parsing, error analysis, machine translation, deep parsing

Procedia PDF Downloads 526
4858 Modelling of Moisture Loss and Oil Uptake during Deep-Fat Frying of Plantain

Authors: James A. Adeyanju, John O. Olajide, Akinbode A. Adedeji

Abstract:

A predictive mathematical model based on the fundamental principles of mass transfer was developed to simulate the moisture content and oil content during Deep-Fat Frying (DFF) process of dodo. The resulting governing equation, that is, partial differential equation that describes rate of moisture loss and oil uptake was solved numerically using explicit Finite Difference Technique (FDT). Computer codes were written in MATLAB environment for the implementation of FDT at different frying conditions and moisture loss as well as oil uptake simulation during DFF of dodo. Plantain samples were sliced into 5 mm thickness and fried at different frying oil temperatures (150, 160 and 170 ⁰C) for periods varying from 2 to 4 min. The comparison between the predicted results and experimental data for the validation of the model showed reasonable agreement. The correlation coefficients between the predicted and experimental values of moisture and oil transfer models ranging from 0.912 to 0.947 and 0.895 to 0.957, respectively. The predicted results could be further used for the design, control and optimization of deep-fat frying process.

Keywords: frying, moisture loss, modelling, oil uptake

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4857 Prussian Blue/Chitosan Mixed-Matrix Membranes with Improved Separation Performance of Ethanol/Water Mixtures

Authors: Ting-YuLiu, Yi-Feng Lin

Abstract:

Porous Prussian Blue (PB) nanoparticles were successfully incorporated into chitosan (CS) membranes to form PB/CS mixed-matrix membranes (MMMs) and the as-prepared PB/CS MMMs were used to dehydration of ethanol at 25 oC in the pervaporation process. The effect of PB loading in CS matrix on pervaporation performance was investigated. The FESEM, EDS, FTIR and XRD measurements were also used for the characterization of the PB/CS MMMs. The PB/CS membranes with 30 wt% PB loading show the best performance with the permeate flux of 614 g/m2h and the separation factor of 1472. The pervaporation using the PB/CS membranes exhibits outstanding performance as compared with the previously reported CS based membranes and MMMs. The present work demonstrates good pervaporation performance of the PB/CS MMMs for the separation of 90wt% ethanol aqueous solution, moreover, it has an opportunity for dehydration of bioethanol in this system of pervaporation.

Keywords: pervaporation, chitosan, Prussian blue, mixed-matrix membrane

Procedia PDF Downloads 391
4856 Trading off Accuracy for Speed in Powerdrill

Authors: Filip Buruiana, Alexander Hall, Reimar Hofmann, Thomas Hofmann, Silviu Ganceanu, Alexandru Tudorica

Abstract:

In-memory column-stores make interactive analysis feasible for many big data scenarios. PowerDrill is a system used internally at Google for exploration in logs data. Even though it is a highly parallelized column-store and uses in memory caching, interactive response times cannot be achieved for all datasets (note that it is common to analyze data with 50 billion records in PowerDrill). In this paper, we investigate two orthogonal approaches to optimize performance at the expense of an acceptable loss of accuracy. Both approaches can be implemented as outer wrappers around existing database engines and so they should be easily applicable to other systems. For the first optimization we show that memory is the limiting factor in executing queries at speed and therefore explore possibilities to improve memory efficiency. We adapt some of the theory behind data sketches to reduce the size of particularly expensive fields in our largest tables by a factor of 4.5 when compared to a standard compression algorithm. This saves 37% of the overall memory in PowerDrill and introduces a 0.4% relative error in the 90th percentile for results of queries with the expensive fields. We additionally evaluate the effects of using sampling on accuracy and propose a simple heuristic for annotating individual result-values as accurate (or not). Based on measurements of user behavior in our real production system, we show that these estimates are essential for interpreting intermediate results before final results are available. For a large set of queries this effectively brings down the 95th latency percentile from 30 to 4 seconds.

Keywords: big data, in-memory column-store, high-performance SQL queries, approximate SQL queries

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4855 Investigation of Turbulent Flow in a Bubble Column Photobioreactor and Consequent Effects on Microalgae Cultivation Using Computational Fluid Dynamic Simulation

Authors: Geetanjali Yadav, Arpit Mishra, Parthsarathi Ghosh, Ramkrishna Sen

Abstract:

The world is facing problems of increasing global CO2 emissions, climate change and fuel crisis. Therefore, several renewable and sustainable energy alternatives should be investigated to replace non-renewable fuels in future. Algae presents itself a versatile feedstock for the production of variety of fuels (biodiesel, bioethanol, bio-hydrogen etc.) and high value compounds for food, fodder, cosmetics and pharmaceuticals. Microalgae are simple microorganisms that require water, light, CO2 and nutrients for growth by the process of photosynthesis and can grow in extreme environments, utilize waste gas (flue gas) and waste waters. Mixing, however, is a crucial parameter within the culture system for the uniform distribution of light, nutrients and gaseous exchange in addition to preventing settling/sedimentation, creation of dark zones etc. The overarching goal of the present study is to improve photobioreactor (PBR) design for enhancing dissolution of CO2 from ambient air (0.039%, v/v), pure CO2 and coal-fired flue gas (10 ± 2%) into microalgal PBRs. Computational fluid dynamics (CFD), a state-of-the-art technique has been used to solve partial differential equations with turbulence closure which represents the dynamics of fluid in a photobioreactor. In this paper, the hydrodynamic performance of the PBR has been characterized and compared with that of the conventional bubble column PBR using CFD. Parameters such as flow rate (Q), mean velocity (u), mean turbulent kinetic energy (TKE) were characterized for each experiment that was tested across different aeration schemes. The results showed that the modified PBR design had superior liquid circulation properties and gas-liquid transfer that resulted in creation of uniform environment inside PBR as compared to conventional bubble column PBR. The CFD technique has shown to be promising to successfully design and paves path for a future research in order to develop PBRs which can be commercially available for scale-up microalgal production.

Keywords: computational fluid dynamics, microalgae, bubble column photbioreactor, flue gas, simulation

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4854 Artificial Neural Network Based Approach for Estimation of Individual Vehicle Speed under Mixed Traffic Condition

Authors: Subhadip Biswas, Shivendra Maurya, Satish Chandra, Indrajit Ghosh

Abstract:

Developing speed model is a challenging task particularly under mixed traffic condition where the traffic composition plays a significant role in determining vehicular speed. The present research has been conducted to model individual vehicular speed in the context of mixed traffic on an urban arterial. Traffic speed and volume data have been collected from three midblock arterial road sections in New Delhi. Using the field data, a volume based speed prediction model has been developed adopting the methodology of Artificial Neural Network (ANN). The model developed in this work is capable of estimating speed for individual vehicle category. Validation results show a great deal of agreement between the observed speeds and the predicted values by the model developed. Also, it has been observed that the ANN based model performs better compared to other existing models in terms of accuracy. Finally, the sensitivity analysis has been performed utilizing the model in order to examine the effects of traffic volume and its composition on individual speeds.

Keywords: speed model, artificial neural network, arterial, mixed traffic

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4853 Native Point Defects in ZnO

Authors: A. M. Gsiea, J. P. Goss, P. R. Briddon, Ramadan. M. Al-habashi, K. M. Etmimi, Khaled. A. S. Marghani

Abstract:

Using first-principles methods based on density functional theory and pseudopotentials, we have performed a details study of native defects in ZnO. Native point defects are unlikely to be cause of the unintentional n-type conductivity. Oxygen vacancies, which considered most often been invoked as shallow donors, have high formation energies in n-type ZnO, in edition are a deep donors. Zinc interstitials are shallow donors, with high formation energies in n-type ZnO, and thus unlikely to be responsible on their own for unintentional n-type conductivity under equilibrium conditions, as well as Zn antisites which have higher formation energies than zinc interstitials. Zinc vacancies are deep acceptors with low formation energies for n-type and in which case they will not play role in p-type coductivity of ZnO. Oxygen interstitials are stable in the form of electrically inactive split interstitials as well as deep acceptors at the octahedral interstitial site under n-type conditions. Our results may provide a guide to experimental studies of point defects in ZnO.

Keywords: DFT, native, n-type, ZnO

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4852 Transport of Analytes under Mixed Electroosmotic and Pressure Driven Flow of Power Law Fluid

Authors: Naren Bag, S. Bhattacharyya, Partha P. Gopmandal

Abstract:

In this study, we have analyzed the transport of analytes under a two dimensional steady incompressible flow of power-law fluids through rectangular nanochannel. A mathematical model based on the Cauchy momentum-Nernst-Planck-Poisson equations is considered to study the combined effect of mixed electroosmotic (EO) and pressure driven (PD) flow. The coupled governing equations are solved numerically by finite volume method. We have studied extensively the effect of key parameters, e.g., flow behavior index, concentration of the electrolyte, surface potential, imposed pressure gradient and imposed electric field strength on the net average flow across the channel. In addition to study the effect of mixed EOF and PD on the analyte distribution across the channel, we consider a nonlinear model based on general convective-diffusion-electromigration equation. We have also presented the retention factor for various values of electrolyte concentration and flow behavior index.

Keywords: electric double layer, finite volume method, flow behavior index, mixed electroosmotic/pressure driven flow, non-Newtonian power-law fluids, numerical simulation

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4851 Applications of AI, Machine Learning, and Deep Learning in Cyber Security

Authors: Hailyie Tekleselase

Abstract:

Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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4850 Anti-Phosphorylcholine T Cell Dependent Antibody

Authors: M. M. Rahman, A. Liu, A. Frostegard, J. Frostegard

Abstract:

The human immune system plays an essential role in cardiovascular disease (CVD) and atherosclerosis. Our earlier studies showed that major immunocompetent cells including T cells are activated by phosphorylcholine epitope. Further, we have determined for the first time in a clinical cohort that antibodies against phosphorylcholine (anti-PC) are negatively and independently associated with the development of atherosclerosis and thus a low risk of cardiovascular diseases. It is still unknown whether activated T cells play a role in anti-PC production. Here we aim to clarify the role of T cells in anti-PC production. B cell alone, or with CD3 T, CD4 T or with CD8 T cells were cultured in polystyrene plates to examine anti-PC IgM production. In addition to mixed B cell with CD3 T cell culture, B cells with CD3 T cells were also cultured in transwell co-culture plates. Further, B cells alone and mixed B cell with CD3 T cell cultures with or without anti-HLA 2 antibody were cultured for 6 days. Anti-PC IgM was detected by ELISA in independent experiments. More than 8 fold higher levels of anti-PC IgM were detected by ELISA in mixed B cell with CD3 T cell cultures in comparison to B cells alone. After the co-culture of B and CD3 T cells in transwell plates, there were no increased antibody levels indicating that B and T cells need to interact to augment anti-PC IgM production. Furthermore, anti-PC IgM was abolished by anti-HLA 2 blocking antibody in mixed B and CD3 T cells culture. In addition, the lack of increased anti-PC IgM in mixed B with CD8 T cells culture and the increased levels of anti-PC in mixed B with CD4 T cells culture support the role of helper T cell for the anti-PC IgM production. Atherosclerosis is a major cause of cardiovascular diseases, but anti-PC IgM is a protection marker for atherosclerosis development. Understanding the mechanism involved in the anti-PC IgM regulation could play an important role in strategies to raise anti-PC IgM. Studies suggest that anti-PC is T-cell independent antibody, but our study shows the major role of T cell in anti-PC IgM production. Activation of helper T cells by immunization could be a possible mechanism for raising anti-PC levels.

Keywords: anti-PC, atherosclerosis, aardiovascular diseases, phosphorylcholine

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4849 The Detection of Implanted Radioactive Seeds on Ultrasound Images Using Convolution Neural Networks

Authors: Edward Holupka, John Rossman, Tye Morancy, Joseph Aronovitz, Irving Kaplan

Abstract:

A common modality for the treatment of early stage prostate cancer is the implantation of radioactive seeds directly into the prostate. The radioactive seeds are positioned inside the prostate to achieve optimal radiation dose coverage to the prostate. These radioactive seeds are positioned inside the prostate using Transrectal ultrasound imaging. Once all of the planned seeds have been implanted, two dimensional transaxial transrectal ultrasound images separated by 2 mm are obtained through out the prostate, beginning at the base of the prostate up to and including the apex. A common deep neural network, called DetectNet was trained to automatically determine the position of the implanted radioactive seeds within the prostate under ultrasound imaging. The results of the training using 950 training ultrasound images and 90 validation ultrasound images. The commonly used metrics for successful training were used to evaluate the efficacy and accuracy of the trained deep neural network and resulted in an loss_bbox (train) = 0.00, loss_coverage (train) = 1.89e-8, loss_bbox (validation) = 11.84, loss_coverage (validation) = 9.70, mAP (validation) = 66.87%, precision (validation) = 81.07%, and a recall (validation) = 82.29%, where train and validation refers to the training image set and validation refers to the validation training set. On the hardware platform used, the training expended 12.8 seconds per epoch. The network was trained for over 10,000 epochs. In addition, the seed locations as determined by the Deep Neural Network were compared to the seed locations as determined by a commercial software based on a one to three months after implant CT. The Deep Learning approach was within \strikeout off\uuline off\uwave off2.29\uuline default\uwave default mm of the seed locations determined by the commercial software. The Deep Learning approach to the determination of radioactive seed locations is robust, accurate, and fast and well within spatial agreement with the gold standard of CT determined seed coordinates.

Keywords: prostate, deep neural network, seed implant, ultrasound

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4848 MIOM: A Mixed-Initiative Operational Model for Robots in Urban Search and Rescue

Authors: Mario Gianni, Federico Nardi, Federico Ferri, Filippo Cantucci, Manuel A. Ruiz Garcia, Karthik Pushparaj, Fiora Pirri

Abstract:

In this paper, we describe a Mixed-Initiative Operational Model (MIOM) which directly intervenes on the state of the functionalities embedded into a robot for Urban Search&Rescue (USAR) domain applications. MIOM extends the reasoning capabilities of the vehicle, i.e. mapping, path planning, visual perception and trajectory tracking, with operator knowledge. Especially in USAR scenarios, this coupled initiative has the main advantage of enhancing the overall performance of a rescue mission. In-field experiments with rescue responders have been carried out to evaluate the effectiveness of this operational model.

Keywords: mixed-initiative planning and control, operator control interfaces for rescue robotics, situation awareness, urban search, rescue robotics

Procedia PDF Downloads 337
4847 An Intelligent Baby Care System Based on IoT and Deep Learning Techniques

Authors: Chinlun Lai, Lunjyh Jiang

Abstract:

Due to the heavy burden and pressure of caring for infants, an integrated automatic baby watching system based on IoT smart sensing and deep learning machine vision techniques is proposed in this paper. By monitoring infant body conditions such as heartbeat, breathing, body temperature, sleeping posture, as well as the surrounding conditions such as dangerous/sharp objects, light, noise, humidity and temperature, the proposed system can analyze and predict the obvious/potential dangerous conditions according to observed data and then adopt suitable actions in real time to protect the infant from harm. Thus, reducing the burden of the caregiver and improving safety efficiency of the caring work. The experimental results show that the proposed system works successfully for the infant care work and thus can be implemented in various life fields practically.

Keywords: baby care system, Internet of Things, deep learning, machine vision

Procedia PDF Downloads 207
4846 Numerical Investigation of Mixed Convection for Rarefied Gases in Square Enclosures

Authors: Wael Al-Kouz

Abstract:

Numerical simulations to study heat transfer and flow characteristics of mixed convection for rarefied gas in a square enclosure are utilized. Effect of the geometry in terms of the location of the inlet and exit openings are investigated. Moreover, effect of Knudsen number on the flow and heat transfer characteristics is illustrated and discussed. Results of the simulations show that there is a configuration that yields better heat transfer. This configuration is found to be the geometry in which the inlet opening is in the top left corner and the exit opening is at the bottom right corner. In addition, it is found that by increasing Knudsen number, Nusselt number will decrease.

Keywords: Knudsen number, mixed convection, rarefied gas, square enclosure

Procedia PDF Downloads 329
4845 Reliability of Slender Reinforced Concrete Columns: Part 1

Authors: Metwally Abdel Aziz Ahmed, Ahmed Shaban Abdel Hay Gabr, Inas Mohamed Saleh

Abstract:

The main objective of structural design is to ensure safety and functional performance requirements of a structural system for its target reliability levels. In this study, the reliability index for the reinforcement concrete slender columns with rectangular cross section is studied. The variable parameters studied include the loads, the concrete compressive strength, the steel yield strength, the dimensions of concrete cross-section, the reinforcement ratio, and the location of steel placement. Risk analysis program was used to perform the analytical study. The effect of load eccentricity on the reliability index of reinforced concrete slender column was studied and presented. The results of this study indicate that the good quality control improve the performance of slender reinforced columns through increasing the reliability index β.

Keywords: reliability, reinforced concrete, safety, slender column

Procedia PDF Downloads 424
4844 Bioassay Guided Isolation of Antimicrobial and Cytotoxic Components from Ethyl Acetate Extracts of Cassia Sieberiana D.C. (Fabaceae)

Authors: Abubakar Sani

Abstract:

The leaves extracts of Cassia sieberiana D.C. were screened for cytotoxicity using Brine Shrimp Test (BST) and antimicrobial bioassay against Staphylococcus aureus, Salmonella typhi and Escherichia coli using crude ethanol extract, Chloroform soluble fraction, aqueous soluble fraction, ethyl acetate soluble fraction, methanol soluble fraction and n-hexane soluble fraction. The Ethyl acetate fraction obtained proved to be most active in inducing complete lethality at minimum doses in BST and also active on Salmonella typhi. The Bioactivity result was used to guide the column chromatography which led to the isolation of pure compound CSB-8 which was found active in the BST with LC₅₀ value of 34(722-182)µg/ml and showed remarkable activity on Salmonella typhi (zone of inhibition 25mm) at 10,000µg/ml. The ¹H-NMR, ¹³C NMR, FTIR and GC-MS spectra of compound suggested the proposed structure to be 2-pentadecanone.

Keywords: brine shrimp, Cassia sieberiana D. C, Column chromatography, antimicrobial bioassay

Procedia PDF Downloads 118
4843 Biochar - A Multi-Beneficial and Cost-Effective Amendment to Clay Soil for Stormwater Runoff Treatment

Authors: Mohammad Khalid, Mariya Munir, Jacelyn Rice Boyaue

Abstract:

Highways are considered a major source of pollution to storm-water, and its runoff can introduce various contaminants, including nutrients, Indicator bacteria, heavy metals, chloride, and phosphorus compounds, which can have negative impacts on receiving waters. This study assessed the ability of biochar for contaminants removal and to improve the water holding capacity of soil biochar mixture. For this, ten commercially available biochar has been strategically selected. Lab scale batch testing was done at 3% and 6% by the weight of the soil to find the preliminary estimate of contaminants removal along with hydraulic conductivity and water retention capacity. Furthermore, from the above-conducted studies, six best performing candidate and an application rate of 6% has been selected for the column studies. Soil biochar mixture was filled in 7.62 cm assembled columns up to a fixed height of 76.2 cm based on hydraulic conductivity. A total of eight column experiments have been conducted for nutrient, heavy metal, and indicator bacteria analysis over a period of one year, which includes a drying as well as a deicing period. The saturated hydraulic conductivity was greatly improved, which is attributed to the high porosity of the biochar soil mixture. Initial data from the column testing shows that biochar may have the ability to significantly remove nutrients, indicator bacteria, and heavy metals. The overall study demonstrates that biochar could be efficiently applied with clay soil to improve the soil's hydraulic characteristics as well as remove the pollutants from the stormwater runoff.

Keywords: biochar, nutrients, indicator bacteria, storm-water treatment, sustainability

Procedia PDF Downloads 95
4842 Settlement Performance of Soft Clay Reinforced with Granular Columns

Authors: Muneerah Jeludin, V. Sivakumar

Abstract:

Numerous laboratory-based research studies on the behavior of ground improved with granular columns with respect to bearing capacity have been well-documented. However, information on its settlement performance is still scarce. Laboratory model study on the settlement behavior of soft clay reinforced with granular columns was conducted and results are presented. The investigation uses a soft kaolin clay sample of 300 mm in diameter and 400 mm in length. The clay samples were reinforced with single and multiple granular columns of various lengths using the displacement and replacement installation method. The results indicated that that no settlement reduction was achieved for a short single floating column. The settlement reduction factors reported for L/d ratios of 5.0, 7.5 and 10.0 are in the range of 1 to 2. The findings obtained in this research showed that the reduction factors are considerably less and that load-sharing mechanism between columns and surrounding clay is complex, particularly for column groups and is affected by other factors such as negative skin friction.

Keywords: ground improvement, model test, reinforced soil, settlement

Procedia PDF Downloads 442