Search results for: dynamic vision sensor
4527 Necessary Condition to Utilize Adaptive Control in Wind Turbine Systems to Improve Power System Stability
Authors: Javad Taherahmadi, Mohammad Jafarian, Mohammad Naser Asefi
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The global capacity of wind power has dramatically increased in recent years. Therefore, improving the technology of wind turbines to take different advantages of this enormous potential in the power grid, could be interesting subject for scientists. The doubly-fed induction generator (DFIG) wind turbine is a popular system due to its many advantages such as the improved power quality, high energy efficiency and controllability, etc. With an increase in wind power penetration in the network and with regard to the flexible control of wind turbines, the use of wind turbine systems to improve the dynamic stability of power systems has been of significance importance for researchers. Subsynchronous oscillations are one of the important issues in the stability of power systems. Damping subsynchronous oscillations by using wind turbines has been studied in various research efforts, mainly by adding an auxiliary control loop to the control structure of the wind turbine. In most of the studies, this control loop is composed of linear blocks. In this paper, simple adaptive control is used for this purpose. In order to use an adaptive controller, the convergence of the controller should be verified. Since adaptive control parameters tend to optimum values in order to obtain optimum control performance, using this controller will help the wind turbines to have positive contribution in damping the network subsynchronous oscillations at different wind speeds and system operating points. In this paper, the application of simple adaptive control in DFIG wind turbine systems to improve the dynamic stability of power systems is studied and the essential condition for using this controller is considered. It is also shown that this controller has an insignificant effect on the dynamic stability of the wind turbine, itself.Keywords: almost strictly positive real (ASPR), doubly-fed induction generator (DIFG), simple adaptive control (SAC), subsynchronous oscillations, wind turbine
Procedia PDF Downloads 3774526 Seashore Debris Detection System Using Deep Learning and Histogram of Gradients-Extractor Based Instance Segmentation Model
Authors: Anshika Kankane, Dongshik Kang
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Marine debris has a significant influence on coastal environments, damaging biodiversity, and causing loss and damage to marine and ocean sector. A functional cost-effective and automatic approach has been used to look up at this problem. Computer vision combined with a deep learning-based model is being proposed to identify and categorize marine debris of seven kinds on different beach locations of Japan. This research compares state-of-the-art deep learning models with a suggested model architecture that is utilized as a feature extractor for debris categorization. The model is being proposed to detect seven categories of litter using a manually constructed debris dataset, with the help of Mask R-CNN for instance segmentation and a shape matching network called HOGShape, which can then be cleaned on time by clean-up organizations using warning notifications of the system. The manually constructed dataset for this system is created by annotating the images taken by fixed KaKaXi camera using CVAT annotation tool with seven kinds of category labels. A pre-trained HOG feature extractor on LIBSVM is being used along with multiple templates matching on HOG maps of images and HOG maps of templates to improve the predicted masked images obtained via Mask R-CNN training. This system intends to timely alert the cleanup organizations with the warning notifications using live recorded beach debris data. The suggested network results in the improvement of misclassified debris masks of debris objects with different illuminations, shapes, viewpoints and litter with occlusions which have vague visibility.Keywords: computer vision, debris, deep learning, fixed live camera images, histogram of gradients feature extractor, instance segmentation, manually annotated dataset, multiple template matching
Procedia PDF Downloads 1074525 Effects of Injection Conditions on Flame Structures in Gas-Centered Swirl Coaxial Injector
Authors: Wooseok Song, Sunjung Park, Jongkwon Lee, Jaye Koo
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The objective of this paper is to observe the effects of injection conditions on flame structures in gas-centered swirl coaxial injector. Gaseous oxygen and liquid kerosene were used as propellants. For different injection conditions, two types of injector, which only differ in the diameter of the tangential inlet, were used in this study. In addition, oxidizer injection pressure was varied to control the combustion chamber pressure in different types of injector. In order to analyze the combustion instability intensity, the dynamic pressure was measured in both the combustion chamber and propellants lines. With the increase in differential pressure between the propellant injection pressure and the combustion chamber pressure, the combustion instability intensity increased. In addition, the flame structure was recorded using a high-speed camera to detect CH* chemiluminescence intensity. With the change in the injection conditions in the gas-centered swirl coaxial injector, the flame structure changed.Keywords: liquid rocket engine, flame structure, combustion instability, dynamic pressure
Procedia PDF Downloads 2334524 Rotor Dynamic Analysis for a Shaft Train by Using Finite Element Method
Authors: M. Najafi
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In the present paper, a large turbo-generator shaft train including a heavy-duty gas turbine engine, a coupling, and a generator is established. The method of analysis is based on finite element simplified model for lateral and torsional vibration calculation. The basic elements of rotor are the shafts and the disks which are represented as circular cross section flexible beams and rigid body elements, respectively. For more accurate results, the gyroscopic effect and bearing dynamics coefficients and function of rotation are taken into account, and for the influence of shear effect, rotor has been modeled in the form of Timoshenko beam. Lateral critical speeds, critical speed map, damped mode shapes, Campbell diagram, zones of instability, amplitudes, phase angles response due to synchronous forces of excitation and amplification factor are calculated. Also, in the present paper, the effect of imbalanced rotor and effects of changing in internal force and temperature are studied.Keywords: rotor dynamic analysis, finite element method, shaft train, Campbell diagram
Procedia PDF Downloads 1364523 [Keynote Speech]: Simulation Studies of Pulsed Voltage Effects on Cells
Authors: Jiahui Song
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In order to predict or explain a complicated biological process, it is important first to construct mathematical models that can be used to yield analytical solutions. Through numerical simulation, mathematical model results can be used to test scenarios that might not be easily attained in a laboratory experiment, or to predict parameters or phenomena. High-intensity, nanosecond pulse electroporation has been a recent development in bioelectrics. The dynamic pore model can be achieved by including a dynamic aspect and a dependence on the pore population density into pore formation energy equation to analyze and predict such electroporation effects. For greater accuracy, with inclusion of atomistic details, molecular dynamics (MD) simulations were also carried out during this study. Besides inducing pores in cells, external voltages could also be used in principle to modulate action potential generation in nerves. This could have an application in electrically controlled ‘pain management’. Also a simple model-based rate equation treatment of the various cellular bio-chemical processes has been used to predict the pulse number dependent cell survival trends.Keywords: model, high-intensity, nanosecond, bioelectrics
Procedia PDF Downloads 2264522 Development and Metrological Validation of a Control Strategy in Embedded Island Grids Using Battery-Hybrid-Systems
Authors: L. Wilkening, G. Ackermann, T. T. Do
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This article presents an approach for stand-alone and grid-connected mode of a German low-voltage grid with high share of photovoltaic. For this purpose, suitable dynamic system models have been developed. This allows the simulation of dynamic events in very small time ranges and the operation management over longer periods of time. Using these simulations, suitable control parameters could be identified, and their effects on the grid can be analyzed. In order to validate the simulation results, a LV-grid test bench has been implemented at the University of Technology Hamburg. The developed control strategies are to be validated using real inverters, generators and different realistic loads. It is shown that a battery hybrid system installed next to a voltage transformer makes it possible to operate the LV-grid in stand-alone mode without using additional information and communication technology and without intervention in the existing grid units. By simulating critical days of the year, suitable control parameters for stable stand-alone operations are determined and set point specifications for different control strategies are defined.Keywords: battery, e-mobility, photovoltaic, smart grid
Procedia PDF Downloads 1434521 Nonlinear Dynamic Analysis of Base-Isolated Structures Using a Mixed Integration Method: Stability Aspects and Computational Efficiency
Authors: Nicolò Vaiana, Filip C. Filippou, Giorgio Serino
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In order to reduce numerical computations in the nonlinear dynamic analysis of seismically base-isolated structures, a Mixed Explicit-Implicit time integration Method (MEIM) has been proposed. Adopting the explicit conditionally stable central difference method to compute the nonlinear response of the base isolation system, and the implicit unconditionally stable Newmark’s constant average acceleration method to determine the superstructure linear response, the proposed MEIM, which is conditionally stable due to the use of the central difference method, allows to avoid the iterative procedure generally required by conventional monolithic solution approaches within each time step of the analysis. The main aim of this paper is to investigate the stability and computational efficiency of the MEIM when employed to perform the nonlinear time history analysis of base-isolated structures with sliding bearings. Indeed, in this case, the critical time step could become smaller than the one used to define accurately the earthquake excitation due to the very high initial stiffness values of such devices. The numerical results obtained from nonlinear dynamic analyses of a base-isolated structure with a friction pendulum bearing system, performed by using the proposed MEIM, are compared to those obtained adopting a conventional monolithic solution approach, i.e. the implicit unconditionally stable Newmark’s constant acceleration method employed in conjunction with the iterative pseudo-force procedure. According to the numerical results, in the presented numerical application, the MEIM does not have stability problems being the critical time step larger than the ground acceleration one despite of the high initial stiffness of the friction pendulum bearings. In addition, compared to the conventional monolithic solution approach, the proposed algorithm preserves its computational efficiency even when it is adopted to perform the nonlinear dynamic analysis using a smaller time step.Keywords: base isolation, computational efficiency, mixed explicit-implicit method, partitioned solution approach, stability
Procedia PDF Downloads 2784520 The Feasibility of Glycerol Steam Reforming in an Industrial Sized Fixed Bed Reactor Using Computational Fluid Dynamic (CFD) Simulations
Authors: Mahendra Singh, Narasimhareddy Ravuru
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For the past decade, the production of biodiesel has significantly increased along with its by-product, glycerol. Biodiesel-derived glycerol massive entry into the glycerol market has caused its value to plummet. Newer ways to utilize the glycerol by-product must be implemented or the biodiesel industry will face serious economic problems. The biodiesel industry should consider steam reforming glycerol to produce hydrogen gas. Steam reforming is the most efficient way of producing hydrogen and there is a lot of demand for it in the petroleum and chemical industries. This study investigates the feasibility of glycerol steam reforming in an industrial sized fixed bed reactor. In this paper, using computational fluid dynamic (CFD) simulations, the extent of the transport resistances that would occur in an industrial sized reactor can be visualized. An important parameter in reactor design is the size of the catalyst particle. The size of the catalyst cannot be too large where transport resistances are too high, but also not too small where an extraordinary amount of pressure drop occurs. The goal of this paper is to find the best catalyst size under various flow rates that will result in the highest conversion. Computational fluid dynamics simulated the transport resistances and a pseudo-homogenous reactor model was used to evaluate the pressure drop and conversion. CFD simulations showed that glycerol steam reforming has strong internal diffusion resistances resulting in extremely low effectiveness factors. In the pseudo-homogenous reactor model, the highest conversion obtained with a Reynolds number of 100 (29.5 kg/h) was 9.14% using a 1/6 inch catalyst diameter. Due to the low effectiveness factors and high carbon deposition rates, a fluidized bed is recommended as the appropriate reactor to carry out glycerol steam reforming.Keywords: computational fluid dynamic, fixed bed reactor, glycerol, steam reforming, biodiesel
Procedia PDF Downloads 3084519 Monitoring Spatial Distribution of Blue-Green Algae Blooms with Underwater Drones
Authors: R. L. P. De Lima, F. C. B. Boogaard, R. E. De Graaf-Van Dinther
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Blue-green algae blooms (cyanobacteria) is currently a relevant ecological problem that is being addressed by most water authorities in the Netherlands. These can affect recreation areas by originating unpleasant smells and toxins that can poison humans and animals (e.g. fish, ducks, dogs). Contamination events usually take place during summer months, and their frequency is increasing with climate change. Traditional monitoring of this bacteria is expensive, labor-intensive and provides only limited (point sampling) information about the spatial distribution of algae concentrations. Recently, a novel handheld sensor allowed water authorities to quicken their algae surveying and alarm systems. This study converted the mentioned algae sensor into a mobile platform, by combining it with an underwater remotely operated vehicle (also equipped with other sensors and cameras). This provides a spatial visualization (mapping) of algae concentrations variations within the area covered with the drone, and also in depth. Measurements took place in different locations in the Netherlands: i) lake with thick silt layers at the bottom, very eutrophic former bottom of the sea and frequent / intense mowing regime; ii) outlet of waste water into large reservoir; iii) urban canal system. Results allowed to identify probable dominant causes of blooms (i), provide recommendations for the placement of an outlet, day-night differences in algae behavior (ii), or the highlight / pinpoint higher algae concentration areas (iii). Although further research is still needed to fully characterize these processes and to optimize the measuring tool (underwater drone developments / improvements), the method here presented can already provide valuable information about algae behavior and spatial / temporal variability and shows potential as an efficient monitoring system.Keywords: blue-green algae, cyanobacteria, underwater drones / ROV / AUV, water quality monitoring
Procedia PDF Downloads 2074518 Magnetic (Ethylene-Octene) Polymer Composites Reinforced With Carbon Black
Authors: Marcin Maslowski, Marian Zaborski
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The aim of the study was to receive magnetorheological elastomer composites (MRE) with the best mechanical characteristics. MRE based on different magnetoactive fillers in ethylene-octene rubber are reported and studied. To improve mechanical properties of polymer mixtures, also carbon black (N550) was added during the composites preparation process. Micro and nan-sized magnetites (Fe3O4), as well as gamma iron oxide (gamma-Fe2O3) and carbonyl iron powder (CIP) are added together with carbon black (N550) were found to be an active fillers systems improving both static and dynamic mechanical properties of elastomers. They also changed magnetic properties of composites. Dynamic-mechanical analysis (DMA) indicates the presence of strongly developed secondary structure in vulcanizates. Reinforcing character of applied different fillers systems results in an increased stress at 100% elongation, tensile strength and cross-linking density of the vulcanizates. Studies investigated by vibration sample magnetometer (VSM) proved that all composites exhibit good magnetic properties.Keywords: carbon black, mechanical properties, magnetorheological composites, magnetic fillers
Procedia PDF Downloads 3404517 Dynamic Log Parsing and Intelligent Anomaly Detection Method Combining Retrieval Augmented Generation and Prompt Engineering
Authors: Liu Linxin
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As system complexity increases, log parsing and anomaly detection become more and more important in ensuring system stability. However, traditional methods often face the problems of insufficient adaptability and decreasing accuracy when dealing with rapidly changing log contents and unknown domains. To this end, this paper proposes an approach LogRAG, which combines RAG (Retrieval Augmented Generation) technology with Prompt Engineering for Large Language Models, applied to log analysis tasks to achieve dynamic parsing of logs and intelligent anomaly detection. By combining real-time information retrieval and prompt optimisation, this study significantly improves the adaptive capability of log analysis and the interpretability of results. Experimental results show that the method performs well on several public datasets, especially in the absence of training data, and significantly outperforms traditional methods. This paper provides a technical path for log parsing and anomaly detection, demonstrating significant theoretical value and application potential.Keywords: log parsing, anomaly detection, retrieval-augmented generation, prompt engineering, LLMs
Procedia PDF Downloads 294516 The Use of Correlation Difference for the Prediction of Leakage in Pipeline Networks
Authors: Mabel Usunobun Olanipekun, Henry Ogbemudia Omoregbee
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Anomalies such as water pipeline and hydraulic or petrochemical pipeline network leakages and bursts have significant implications for economic conditions and the environment. In order to ensure pipeline systems are reliable, they must be efficiently controlled. Wireless Sensor Networks (WSNs) have become a powerful network with critical infrastructure monitoring systems for water, oil and gas pipelines. The loss of water, oil and gas is inevitable and is strongly linked to financial costs and environmental problems, and its avoidance often leads to saving of economic resources. Substantial repair costs and the loss of precious natural resources are part of the financial impact of leaking pipes. Pipeline systems experts have implemented various methodologies in recent decades to identify and locate leakages in water, oil and gas supply networks. These methodologies include, among others, the use of acoustic sensors, measurements, abrupt statistical analysis etc. The issue of leak quantification is to estimate, given some observations about that network, the size and location of one or more leaks in a water pipeline network. In detecting background leakage, however, there is a greater uncertainty in using these methodologies since their output is not so reliable. In this work, we are presenting a scalable concept and simulation where a pressure-driven model (PDM) was used to determine water pipeline leakage in a system network. These pressure data were collected with the use of acoustic sensors located at various node points after a predetermined distance apart. We were able to determine with the use of correlation difference to determine the leakage point locally introduced at a predetermined point between two consecutive nodes, causing a substantial pressure difference between in a pipeline network. After de-noising the signal from the sensors at the nodes, we successfully obtained the exact point where we introduced the local leakage using the correlation difference model we developed.Keywords: leakage detection, acoustic signals, pipeline network, correlation, wireless sensor networks (WSNs)
Procedia PDF Downloads 1094515 Comparison of Meshing Stiffness of Altered Tooth Sum Spur Gear Tooth with Different Pressure Angles
Authors: H. K. Sachidananda, K. Raghunandana, B. Shivamurthy
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The estimation of gear tooth stiffness is important for finding the load distribution between the gear teeth when two consecutive sets of teeth are in contact. Based on dynamic model a C-program has been developed to compute mesh stiffness. By using this program position dependent mesh stiffness of spur gear tooth for various profile shifts have been computed for a fixed center distance and altering tooth-sum gearing (100 by ± 4%). It is found that the C-program using dynamic model is one of the rapid soft computing technique which helps in design of gears. The mesh tooth stiffness along the path of contact is studied for both 20° and 25° pressure angle gears at various profile shifts. Better tooth stiffness is noticed in case of negative alteration tooth-sum gears compared to standard and positive alteration tooth-sum gears. Also, in case of negative alteration tooth-sum gearing better mesh stiffness is noticed in 20° pressure angle when compared to 25°.Keywords: altered tooth-sum gearing, bending fatigue, mesh stiffness, spur gear
Procedia PDF Downloads 3254514 Maintenance Optimization for a Multi-Component System Using Factored Partially Observable Markov Decision Processes
Authors: Ipek Kivanc, Demet Ozgur-Unluakin
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Over the past years, technological innovations and advancements have played an important role in the industrial world. Due to technological improvements, the degree of complexity of the systems has increased. Hence, all systems are getting more uncertain that emerges from increased complexity, resulting in more cost. It is challenging to cope with this situation. So, implementing efficient planning of maintenance activities in such systems are getting more essential. Partially Observable Markov Decision Processes (POMDPs) are powerful tools for stochastic sequential decision problems under uncertainty. Although maintenance optimization in a dynamic environment can be modeled as such a sequential decision problem, POMDPs are not widely used for tackling maintenance problems. However, they can be well-suited frameworks for obtaining optimal maintenance policies. In the classical representation of the POMDP framework, the system is denoted by a single node which has multiple states. The main drawback of this classical approach is that the state space grows exponentially with the number of state variables. On the other side, factored representation of POMDPs enables to simplify the complexity of the states by taking advantage of the factored structure already available in the nature of the problem. The main idea of factored POMDPs is that they can be compactly modeled through dynamic Bayesian networks (DBNs), which are graphical representations for stochastic processes, by exploiting the structure of this representation. This study aims to demonstrate how maintenance planning of dynamic systems can be modeled with factored POMDPs. An empirical maintenance planning problem of a dynamic system consisting of four partially observable components deteriorating in time is designed. To solve the empirical model, we resort to Symbolic Perseus solver which is one of the state-of-the-art factored POMDP solvers enabling approximate solutions. We generate some more predefined policies based on corrective or proactive maintenance strategies. We execute the policies on the empirical problem for many replications and compare their performances under various scenarios. The results show that the computed policies from the POMDP model are superior to the others. Acknowledgment: This work is supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK) under grant no: 117M587.Keywords: factored representation, maintenance, multi-component system, partially observable Markov decision processes
Procedia PDF Downloads 1354513 Enhance Security in XML Databases: XLog File for Severity-Aware Trust-Based Access Control
Authors: A: Asmawi, L. S. Affendey, N. I. Udzir, R. Mahmod
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The topic of enhancing security in XML databases is important as it includes protecting sensitive data and providing a secure environment to users. In order to improve security and provide dynamic access control for XML databases, we presented XLog file to calculate user trust values by recording users’ bad transaction, errors and query severities. Severity-aware trust-based access control for XML databases manages the access policy depending on users' trust values and prevents unauthorized processes, malicious transactions and insider threats. Privileges are automatically modified and adjusted over time depending on user behaviour and query severity. Logging in database is an important process and is used for recovery and security purposes. In this paper, the Xlog file is presented as a dynamic and temporary log file for XML databases to enhance the level of security.Keywords: XML database, trust-based access control, severity-aware, trust values, log file
Procedia PDF Downloads 3004512 Proportionally Damped Finite Element State-Space Model of Composite Laminated Plate with Localized Interface Degeneration
Authors: Shi Qi Koo, Ahmad Beng Hong Kueh
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In the present work, the finite element formulation for the investigation of the effects of a localized interfacial degeneration on the dynamic behavior of the [90˚/0˚] laminated composite plate employing the state-space technique is performed. The stiffness of the laminate is determined by assembling the stiffnesses of sub-elements. This includes an introduction of an interface layer adopting the virtually zero-thickness formulation to model the interfacial degeneration. Also, the kinematically consistent mass matrix and proportional damping have been formulated to complete the free vibration governing expression. To simulate the interfacial degeneration of the laminate, the degenerated areas are defined from the center propagating outwards in a localized manner. It is found that the natural frequency, damped frequency and damping ratio of the plate decreases as the degenerated area of the interface increases. On the contrary, the loss factor increases correspondingly.Keywords: dynamic finite element, localized interface degeneration, proportional damping, state-space modeling
Procedia PDF Downloads 2964511 Naturally Occurring Abietic Acid for Liquid Crystalline Epoxy Curing Agents
Authors: Rasha A.Ibrahim El-Ghazawy, Ashraf M. El-Saeed, Heusin El-Shafey, M. Abdel-Raheim, Maher A. El-Sockary
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Two thermotropic liquid crystalline curing agents based on abietic acid with different mesogens (LCC1 and LCC2) were synthesized for producing thermally stable liquid crystal networks suitable for high performance epoxy coatings. Differential scanning calorimetry (DSC) and polarized optical microscope (POM) was used to identify the liquid crystal phase transformation temperatures and texture, respectively. POM micro graphs for both LCCs revealing cholesteric texture. A multifunctional epoxy resin with two abietic acid moieties was also synthesized. Dynamic mechanical (DMA) and thermogravimetric (TGA) analyses show that the fully bio-based cured epoxies by either LCCs possess high glass transition temperature (Tg), high modulus (G`) and improved thermal stability. The chemical structure of the synthesized LCCs and epoxy resin was investigated through FTIR and 1HNMR spectroscopic techniques.Keywords: abietic acid, dynamic mechanical analysis, epoxy resin, liquid crystal, thermo gravimetric analysis
Procedia PDF Downloads 3634510 Use of Giant Magneto Resistance Sensors to Detect Micron to Submicron Biologic Objects
Authors: Manon Giraud, Francois-Damien Delapierre, Guenaelle Jasmin-Lebras, Cecile Feraudet-Tarisse, Stephanie Simon, Claude Fermon
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Early diagnosis or detection of harmful substances at low level is a growing field of high interest. The ideal test should be cheap, easy to use, quick, reliable, specific, and with very low detection limit. Combining the high specificity of antibodies-functionalized magnetic beads used to immune-capture biologic objects and the high sensitivity of a GMR-based sensors, it is possible to even detect these biologic objects one by one, such as a cancerous cell, a bacteria or a disease biomarker. The simplicity of the detection process makes its use possible even for untrained staff. Giant Magneto Resistance (GMR) is a recently discovered effect consisting in the electrical resistance modification of some conductive layers when exposed to a magnetic field. This effect allows the detection of very low variations of magnetic field (typically a few tens of nanoTesla). Magnetic nanobeads coated with antibodies targeting the analytes are mixed with a biological sample (blood, saliva) and incubated for 45 min. Then the mixture is injected in a very simple microfluidic chip and circulates above a GMR sensor that detects changes in the surrounding magnetic field. Magnetic particles do not create a field sufficient to be detected. Therefore, only the biological objects surrounded by several antibodies-functionalized magnetic beads (that have been captured by the complementary antigens) are detected when they move above the sensor. Proof of concept has been carried out on NS1 mouse cancerous cells diluted in PBS which have been bonded to magnetic 200nm particles. Signals were detected in cells-containing samples while none were recorded for negative controls. Binary response was hence assessed for this first biological model. The precise quantification of the analytes and its detection in highly diluted solution is the step now in progress.Keywords: early diagnosis, giant magnetoresistance, lab-on-a-chip, submicron particle
Procedia PDF Downloads 2484509 Experimental Options for the Role of Dynamic Torsion in General Relativity
Authors: Ivan Ravlich, Ivan Linscott, Sigrid Close
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The experimental search for spin coupling in General Relativity via torsion has been inconclusive. In this work, further experimental avenues to test dynamic torsion are proposed and evaluated. In the extended theory, by relaxing the torsion free condition on the metric connection, general relativity is reformulated to relate the spin density of particles to a new quantity, the torsion tensor. In torsion theories, the spin tensor and torsion tensor are related in much the same way as the stress-energy tensor is related to the metric connection. Similarly, as the metric is the field associated with the metric connection, fields can be associated with the torsion tensor resulting in a field that is either propagating or static. Experimental searches for static torsion have thus far been inconclusive, and currently, there have been no experimental tests for propagating torsion. Experimental tests of propagating theories of torsion are proposed utilizing various spin densities of matter, such as interfaces in superconducting materials and plasmas. The experimental feasibility and observable bounds are estimated, and the most viable candidates are selected to pursue in detail in a future work.Keywords: general relativity, gravitation, propagating torsion, spin density
Procedia PDF Downloads 2304508 Study of Linear Generator for Vibration Energy Harvesting of Frequency more than 50Hz
Authors: Seong-Jin Cho, Jin Ho Kim
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Energy harvesting is the technology which gathers and converts external energies such as light, vibration and heat which are disposed into reusable electrical energy and uses such electrical energy. The vibration energy harvesting is very interesting technology because it produces very high density of energy and unaffected by the climate. Vibration energy can be harvested by the electrostatic, electromagnetic and piezoelectric systems. The electrostatic system has low energy conversion efficiency, and the piezoelectric system is expensive and needs the frequent maintenance because it is made of piezoelectric ceramic. On the other hand, the electromagnetic system has a long life time and high harvesting efficiency, and it is relatively cheap. The electromagnetic harvesting system includes the linear generator and the rotary-type generator. The rotary-type generators require the additional mechanical conversion device if it uses linear motion of vibration. But, the linear generator uses directly linear motion of vibration without a mechanical conversion device, and it has uncomplicated structure and light weight compared with the rotary-type generator. Therefore, the linear electromagnetic generator can be useful in using vibration energy harvesting. The pole transformer systems need electricity sensor system for sending voltage and power information to administrator. Therefore, the battery is essential, and its regular maintenance of replacement is required. In case of the transformer of high location in mountainous areas, the person can’t easily access it resulting in high maintenance cost. To overcome these problems, we designed and developed the linear electromagnetic generator which can replace battery in electricity sensor system for sending voltage and power information of the pole transformer. And, it uses vibration energy of frequency more than 50 Hz by the pole transformer. In order to analyze the electromagnetic characteristics of small linear electric generator, a commercial electromagnetic finite element analysis program "MAXWELL" was used. Then, through the actual production and experiment of linear generator, we confirmed output power of linear generator.Keywords: energy harvesting, frequency, linear generator, experiment
Procedia PDF Downloads 2604507 Estimates of Freshwater Content from ICESat-2 Derived Dynamic Ocean Topography
Authors: Adan Valdez, Shawn Gallaher, James Morison, Jordan Aragon
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Global climate change has impacted atmospheric temperatures contributing to rising sea levels, decreasing sea ice, and increased freshening of high latitude oceans. This freshening has contributed to increased stratification inhibiting local mixing and nutrient transport and modifying regional circulations in polar oceans. In recent years, the Western Arctic has seen an increase in freshwater volume at an average rate of 397+-116 km3/year. The majority of the freshwater volume resides in the Beaufort Gyre surface lens driven by anticyclonic wind forcing, sea ice melt, and Arctic river runoff. The total climatological freshwater content is typically defined as water fresher than 34.8. The near-isothermal nature of Arctic seawater and non-linearities in the equation of state for near-freezing waters result in a salinity driven pycnocline as opposed to the temperature driven density structure seen in the lower latitudes. In this study, we investigate the relationship between freshwater content and remotely sensed dynamic ocean topography (DOT). In-situ measurements of freshwater content are useful in providing information on the freshening rate of the Beaufort Gyre; however, their collection is costly and time consuming. NASA’s Advanced Topographic Laser Altimeter System (ATLAS) derived dynamic ocean topography (DOT), and Air Expendable CTD (AXCTD) derived Freshwater Content are used to develop a linear regression model. In-situ data for the regression model is collected across the 150° West meridian, which typically defines the centerline of the Beaufort Gyre. Two freshwater content models are determined by integrating the freshwater volume between the surface and an isopycnal corresponding to reference salinities of 28.7 and 34.8. These salinities correspond to those of the winter pycnocline and total climatological freshwater content, respectively. Using each model, we determine the strength of the linear relationship between freshwater content and satellite derived DOT. The result of this modeling study could provide a future predictive capability of freshwater volume changes in the Beaufort-Chukchi Sea using non in-situ methods. Successful employment of the ICESat-2’s DOT approximation of freshwater content could potentially reduce reliance on field deployment platforms to characterize physical ocean properties.Keywords: ICESat-2, dynamic ocean topography, freshwater content, beaufort gyre
Procedia PDF Downloads 874506 GIS Data Governance: GIS Data Submission Process for Build-in Project, Replacement Project at Oman electricity Transmission Company
Authors: Rahma Saleh Hussein Al Balushi
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Oman Electricity Transmission Company's (OETC) vision is to be a renowned world-class transmission grid by 2025, and one of the indications of achieving the vision is obtaining Asset Management ISO55001 certification, which required setting out a documented Standard Operating Procedures (SOP). Hence, documented SOP for the Geographical information system data process has been established. Also, to effectively manage and improve OETC power transmission, asset data and information need to be governed as such by Asset Information & GIS department. This paper will describe in detail the current GIS data submission process and the journey for developing it. The methodology used to develop the process is based on three main pillars, which are system and end-user requirements, Risk evaluation, data availability, and accuracy. The output of this paper shows the dramatic change in the used process, which results subsequently in more efficient, accurate, and updated data. Furthermore, due to this process, GIS has been and is ready to be integrated with other systems as well as the source of data for all OETC users. Some decisions related to issuing No objection certificates (NOC) for excavation permits and scheduling asset maintenance plans in Computerized Maintenance Management System (CMMS) have been made consequently upon GIS data availability. On the Other hand, defining agreed and documented procedures for data collection, data systems update, data release/reporting and data alterations has also contributed to reducing the missing attributes and enhance data quality index of GIS transmission data. A considerable difference in Geodatabase (GDB) completeness percentage was observed between the years 2017 and year 2022. Overall, concluding that by governance, asset information & GIS department can control the GIS data process; collect, properly record, and manage asset data and information within the OETC network. This control extends to other applications and systems integrated with/related to GIS systems.Keywords: asset management ISO55001, standard procedures process, governance, CMMS
Procedia PDF Downloads 1254505 Defense Mechanism Maturity and the Severity of Mood Disorder Symptoms
Authors: Maja Pandža, Sanjin Lovrić, Iva Čolak, Josipa Mandarić, Miro Klarić
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This study explores the role of symptoms related to mood disorders salience on different types of defense mechanisms (mature, neurotic, immature) predominance. Total of 177 both clinical and non-clinical participants in Mostar, Bosnia & Herzegovina, completed a battery of questionnaires associated with defense mechanisms and self-reported depression and anxiety symptoms. The sample was additionally divided into four groups, given the level of symptoms experienced: 1. minimal, 2. mild, 3. moderate, 4. severe depression/anxiety. Participants with minimal anxiety and depression symptoms use mature defense mechanisms more often than other three groups. Immature mechanisms are most commonly used by the group with severe depression/anxiety levels in comparison with other groups. These differences are discussed on the dynamic level of analysis to have a better understanding of the relationship between defense mechanisms' maturity and degree of mood disorders' symptom severity. Also, results given could serve as an implication for the psychotherapeutic treatment plans.Keywords: anxiety/depression symptoms, clinical/non-clinical sample, defense mechanism maturity, dynamic approach
Procedia PDF Downloads 4574504 Fault Diagnosis of Nonlinear Systems Using Dynamic Neural Networks
Authors: E. Sobhani-Tehrani, K. Khorasani, N. Meskin
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This paper presents a novel integrated hybrid approach for fault diagnosis (FD) of nonlinear systems. Unlike most FD techniques, the proposed solution simultaneously accomplishes fault detection, isolation, and identification (FDII) within a unified diagnostic module. At the core of this solution is a bank of adaptive neural parameter estimators (NPE) associated with a set of single-parameter fault models. The NPEs continuously estimate unknown fault parameters (FP) that are indicators of faults in the system. Two NPE structures including series-parallel and parallel are developed with their exclusive set of desirable attributes. The parallel scheme is extremely robust to measurement noise and possesses a simpler, yet more solid, fault isolation logic. On the contrary, the series-parallel scheme displays short FD delays and is robust to closed-loop system transients due to changes in control commands. Finally, a fault tolerant observer (FTO) is designed to extend the capability of the NPEs to systems with partial-state measurement.Keywords: hybrid fault diagnosis, dynamic neural networks, nonlinear systems, fault tolerant observer
Procedia PDF Downloads 4014503 Remote Radiation Mapping Based on UAV Formation
Authors: Martin Arguelles Perez, Woosoon Yim, Alexander Barzilov
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High-fidelity radiation monitoring is an essential component in the enhancement of the situational awareness capabilities of the Department of Energy’s Office of Environmental Management (DOE-EM) personnel. In this paper, multiple units of unmanned aerial vehicles (UAVs) each equipped with a cadmium zinc telluride (CZT) gamma-ray sensor are used for radiation source localization, which can provide vital real-time data for the EM tasks. To achieve this goal, a fully autonomous system of multicopter-based UAV swarm in 3D tetrahedron formation is used for surveying the area of interest and performing radiation source localization. The CZT sensor used in this study is suitable for small-size multicopter UAVs due to its small size and ease of interfacing with the UAV’s onboard electronics for high-resolution gamma spectroscopy enabling the characterization of radiation hazards. The multicopter platform with a fully autonomous flight feature is suitable for low-altitude applications such as radiation contamination sites. The conventional approach uses a single UAV mapping in a predefined waypoint path to predict the relative location and strength of the source, which can be time-consuming for radiation localization tasks. The proposed UAV swarm-based approach can significantly improve its ability to search for and track radiation sources. In this paper, two approaches are developed using (a) 2D planar circular (3 UAVs) and (b) 3D tetrahedron formation (4 UAVs). In both approaches, accurate estimation of the gradient vector is crucial for heading angle calculation. Each UAV carries the CZT sensor; the real-time radiation data are used for the calculation of a bulk heading vector for the swarm to achieve a UAV swarm’s source-seeking behavior. Also, a spinning formation is studied for both cases to improve gradient estimation near a radiation source. In the 3D tetrahedron formation, a UAV located closest to the source is designated as a lead unit to maintain the tetrahedron formation in space. Such a formation demonstrated a collective and coordinated movement for estimating a gradient vector for the radiation source and determining an optimal heading direction of the swarm. The proposed radiation localization technique is studied by computer simulation and validated experimentally in the indoor flight testbed using gamma sources. The technology presented in this paper provides the capability to readily add/replace radiation sensors to the UAV platforms in the field conditions enabling extensive condition measurement and greatly improving situational awareness and event management. Furthermore, the proposed radiation localization approach allows long-term measurements to be efficiently performed at wide areas of interest to prevent disasters and reduce dose risks to people and infrastructure.Keywords: radiation, unmanned aerial system(UAV), source localization, UAV swarm, tetrahedron formation
Procedia PDF Downloads 994502 Dynamic Degradation Mechanism of SiC VDMOS under Proton Irradiation
Authors: Junhong Feng, Wenyu Lu, Xinhong Cheng, Li Zheng, Yuehui Yu
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The effects of proton irradiation on the properties of gate oxide were evaluated by monitoring the static parameters (such as threshold voltage and on-resistance) and dynamic parameters (Miller plateau time) of 1700V SiC VDMOS before and after proton irradiation. The incident proton energy was 3MeV, and the doses were 5 × 10¹² P / cm², 1 × 10¹³ P / cm², respectively. The results show that the threshold voltage of MOS exhibits negative drift under proton irradiation, and the near-interface traps in the gate oxide layer are occupied by holes generated by the ionization effect of irradiation, thus forming more positive charges. The basis for selecting TMiller is that the change time of Vgs is the time when Vds just shows an upward trend until it rises to a stable value. The degradation of the turn-off time of the Miller platform verifies that the capacitance Cgd becomes larger, reflecting that the gate oxide layer is introduced into the trap by the displacement effect caused by proton irradiation, and the interface state deteriorates. As a more sensitive area in the irradiation process, the gate oxide layer will be optimized for its parameters (such as thickness, type, etc.) in subsequent studies.Keywords: SiC VDMOS, proton radiation, Miller time, gate oxide
Procedia PDF Downloads 914501 A Microsurgery-Specific End-Effector Equipped with a Bipolar Surgical Tool and Haptic Feedback
Authors: Hamidreza Hoshyarmanesh, Sanju Lama, Garnette R. Sutherland
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In tele-operative robotic surgery, an ideal haptic device should be equipped with an intuitive and smooth end-effector to cover the surgeon’s hand/wrist degrees of freedom (DOF) and translate the hand joint motions to the end-effector of the remote manipulator with low effort and high level of comfort. This research introduces the design and development of a microsurgery-specific end-effector, a gimbal mechanism possessing 4 passive and 1 active DOFs, equipped with a bipolar forceps and haptic feedback. The robust gimbal structure is comprised of three light-weight links/joint, pitch, yaw, and roll, each consisting of low-friction support and a 2-channel accurate optical position sensor. The third link, which provides the tool roll, was specifically designed to grip the tool prongs and accommodate a low mass geared actuator together with a miniaturized capstan-rope mechanism. The actuator is able to generate delicate torques, using a threaded cylindrical capstan, to emulate the sense of pinch/coagulation during conventional microsurgery. While the tool left prong is fixed to the rolling link, the right prong bears a miniaturized drum sector with a large diameter to expand the force scale and resolution. The drum transmits the actuator output torque to the right prong and generates haptic force feedback at the tool level. The tool is also equipped with a hall-effect sensor and magnet bar installed vis-à-vis on the inner side of the two prongs to measure the tooltip distance and provide an analogue signal to the control system. We believe that such a haptic end-effector could significantly increase the accuracy of telerobotic surgery and help avoid high forces that are known to cause bleeding/injury.Keywords: end-effector, force generation, haptic interface, robotic surgery, surgical tool, tele-operation
Procedia PDF Downloads 1184500 Dynamic-cognition of Strategic Mineral Commodities; An Empirical Assessment
Authors: Carlos Tapia Cortez, Serkan Saydam, Jeff Coulton, Claude Sammut
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Strategic mineral commodities (SMC) both energetic and metals have long been fundamental for human beings. There is a strong and long-run relation between the mineral resources industry and society's evolution, with the provision of primary raw materials, becoming one of the most significant drivers of economic growth. Due to mineral resources’ relevance for the entire economy and society, an understanding of the SMC market behaviour to simulate price fluctuations has become crucial for governments and firms. For any human activity, SMC price fluctuations are affected by economic, geopolitical, environmental, technological and psychological issues, where cognition has a major role. Cognition is defined as the capacity to store information in memory, processing and decision making for problem-solving or human adaptation. Thus, it has a significant role in those systems that exhibit dynamic equilibrium through time, such as economic growth. Cognition allows not only understanding past behaviours and trends in SCM markets but also supports future expectations of demand/supply levels and prices, although speculations are unavoidable. Technological developments may also be defined as a cognitive system. Since the Industrial Revolution, technological developments have had a significant influence on SMC production costs and prices, likewise allowing co-integration between commodities and market locations. It suggests a close relation between structural breaks, technology and prices evolution. SCM prices forecasting have been commonly addressed by econometrics and Gaussian-probabilistic models. Econometrics models may incorporate the relationship between variables; however, they are statics that leads to an incomplete approach of prices evolution through time. Gaussian-probabilistic models may evolve through time; however, price fluctuations are addressed by the assumption of random behaviour and normal distribution which seems to be far from the real behaviour of both market and prices. Random fluctuation ignores the evolution of market events and the technical and temporal relation between variables, giving the illusion of controlled future events. Normal distribution underestimates price fluctuations by using restricted ranges, curtailing decisions making into a pre-established space. A proper understanding of SMC's price dynamics taking into account the historical-cognitive relation between economic, technological and psychological factors over time is fundamental in attempting to simulate prices. The aim of this paper is to discuss the SMC market cognition hypothesis and empirically demonstrate its dynamic-cognitive capacity. Three of the largest and traded SMC's: oil, copper and gold, will be assessed to examine the economic, technological and psychological cognition respectively.Keywords: commodity price simulation, commodity price uncertainties, dynamic-cognition, dynamic systems
Procedia PDF Downloads 4634499 The Saudi Arabia 2030 Strategy: Translation Reception and Translator Readiness
Authors: Budur Alsulami
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One of the aims of the recently implemented Saudi Arabia Vision 2030 strategy is focused on strengthening education, entertainment, and tourism to attract international visitors to the country. To promote and increase the tourism sector, tourism translation can serve the tourism industry by translating various materials that promote the country’s tourism such as brochures, catalogues, and websites. In order to achieve the goal of enhancing tourism in Saudi Arabia, promotional texts related to tourism and Saudi culture will need to be translated into English and addressed to non-Arabic-speaking potential tourists. This research aims to measure student readiness to be professional translators who can introduce and promote Saudi Arabia to non-Arabic-speaking tourists. The study will also evaluate students' abilities to promote and convey Saudi culture to non-Arabic tourists by translating tourism texts. Translating tourism materials demands considerable effort and specific translation skills to capture tourists' interest and encourage visits. Numerous scholars have explored challenges in translating tourism promotional materials, focusing on translation methods, cultural issues, course design, and necessary knowledge for tourism translation. Based on these insights, experts recommend that translators prioritize audience expectations, cultural appropriateness, and linguistic conventions while revising course syllabi to include practical skills. This research aims to assess students' readiness to become professional translators aligned with Vision 2030 tourism goals. To accomplish this, in the first stage of the project, twenty students from two Saudi Arabian Universities who have completed at least two years of Translation Studies were invited to translate two tourism texts of 300 words each. These tourism texts contain information about famous tourist sights and traditional food in Saudi Arabia and contained cultural terms and heritage information. The students then completed a questionnaire about the challenges of the text and the process of their translation, and then participated in a semi-structured interview. In the second stage of the project, the students’ translations will be evaluated by a qualified National Accreditation Authority of Translators and Interpreters (NAATI) examiner applying the NAATI rubrics. Finally, these translations will be read and assessed by fifteen to twenty native and near-native readers of English, who will evaluate the quality of the translations based on their understanding and perception of these texts. Results analysed to date suggest that a number of student translators faced challenges such as choosing a suitable translation method, omitting some key terms or words during the translation process, and managing their time, all of which may indicate a lack of practice in translating texts of this nature and lack of awareness regarding translation strategies most suitable for the genre.Keywords: Saudi Arabia Vision 2030, translation, tourism, reader reception, culture, heritage, translator training/competencies
Procedia PDF Downloads 94498 Pattern of Anisometropia, Management and Outcome of Anisometropic Amblyopia
Authors: Husain Rajib, T. H. Sheikh, D. G. Jewel
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Background: Amblyopia is a frequent cause of monocular blindness in children. It can be unilateral or bilateral reduction of best corrected visual acuity associated with decrement in visual processing, accomodation, motility, spatial perception or spatial projection. Anisometropia is an important risk factor for amblyopia that develops when unequal refractive error causes the image to be blurred in the critical developmental period and central inhibition of the visual signal originating from the affected eye associated with significant visual problems including anisokonia, strabismus, and reduced stereopsis. Methods: It is a prospective hospital based study of newly diagnosed of amblyopia seen at the pediatric clinic of Chittagong Eye Infirmary & Training Complex. There were 50 anisometropic amblyopia subjects were examined & questionnaire was piloted. Included were all patients diagnosed with refractive amblyopia between 3 to 13 years, without previous amblyopia treatment, and whose parents were interested to participate in the study. Patients diagnosed with strabismic amblyopia were excluded. Patients were first corrected with the best correction for a month. When the VA in the amblyopic eye did not improve over month, then occlusion treatment was started. Occlusion was done daily for 6-8 hours (full time) together with vision therapy. The occlusion was carried out for 3 months. Results: In this study about 8% subjects had anisometropia from myopia, 18% from hyperopia, 74% from astigmatism. The initial mean visual acuity was 0.74 ± 0.39 Log MAR and after intervention of amblyopia therapy with active vision therapy mean visual acuity was 0.34 ± 0.26 Log MAR. About 94% of subjects were improving at least two lines. The depth of amblyopia associated with type of anisometropic refractive error and magnitude of Anisometropia (p<0.005). By doing this study 10% mild amblyopia, 64% moderate and 26% severe amblyopia were found. Binocular function also decreases with magnitude of Anisometropia. Conclusion: Anisometropic amblyopia is a most important factor in pediatric age group because it can lead to visual impairment. Occlusion therapy with at least one instructed hour of active visual activity practiced out of school hours was effective in anisometropic amblyopes who were diagnosed at the age of 8 years and older, and the patients complied well with the treatment.Keywords: refractive error, anisometropia, amblyopia, strabismic amblyopia
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