Search results for: noise disturbance
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1433

Search results for: noise disturbance

1103 A Nonlocal Means Algorithm for Poisson Denoising Based on Information Geometry

Authors: Dongxu Chen, Yipeng Li

Abstract:

This paper presents an information geometry NonlocalMeans(NLM) algorithm for Poisson denoising. NLM estimates a noise-free pixel as a weighted average of image pixels, where each pixel is weighted according to the similarity between image patches in Euclidean space. In this work, every pixel is a Poisson distribution locally estimated by Maximum Likelihood (ML), all distributions consist of a statistical manifold. A NLM denoising algorithm is conducted on the statistical manifold where Fisher information matrix can be used for computing distribution geodesics referenced as the similarity between patches. This approach was demonstrated to be competitive with related state-of-the-art methods.

Keywords: image denoising, Poisson noise, information geometry, nonlocal-means

Procedia PDF Downloads 270
1102 A SiGe Low Power RF Front-End Receiver for 5.8GHz Wireless Biomedical Application

Authors: Hyunwon Moon

Abstract:

It is necessary to realize new biomedical wireless communication systems which send the signals collected from various bio sensors located at human body in order to monitor our health. Also, it should seamlessly connect to the existing wireless communication systems. A 5.8 GHz ISM band low power RF front-end receiver for a biomedical wireless communication system is implemented using a 0.5 µm SiGe BiCMOS process. To achieve low power RF front-end, the current optimization technique for selecting device size is utilized. The implemented low noise amplifier (LNA) shows a power gain of 9.8 dB, a noise figure (NF) of below 1.75 dB, and an IIP3 of higher than 7.5 dBm while current consumption is only 6 mA at supply voltage of 2.5 V. Also, the performance of a down-conversion mixer is measured as a conversion gain of 11 dB and SSB NF of 10 dB.

Keywords: biomedical, LNA, mixer, receiver, RF front-end, SiGe

Procedia PDF Downloads 303
1101 Steady State Rolling and Dynamic Response of a Tire at Low Frequency

Authors: Md Monir Hossain, Anne Staples, Kuya Takami, Tomonari Furukawa

Abstract:

Tire noise has a significant impact on ride quality and vehicle interior comfort, even at low frequency. Reduction of tire noise is especially important due to strict state and federal environmental regulations. The primary sources of tire noise are the low frequency structure-borne noise and the noise that originates from the release of trapped air between the tire tread and road surface during each revolution of the tire. The frequency response of the tire changes at low and high frequency. At low frequency, the tension and bending moment become dominant, while the internal structure and local deformation become dominant at higher frequencies. Here, we analyze tire response in terms of deformation and rolling velocity at low revolution frequency. An Abaqus FEA finite element model is used to calculate the static and dynamic response of a rolling tire under different rolling conditions. The natural frequencies and mode shapes of a deformed tire are calculated with the FEA package where the subspace-based steady state dynamic analysis calculates dynamic response of tire subjected to harmonic excitation. The analysis was conducted on the dynamic response at the road (contact point of tire and road surface) and side nodes of a static and rolling tire when the tire was excited with 200 N vertical load for a frequency ranging from 20 to 200 Hz. The results show that frequency has little effect on tire deformation up to 80 Hz. But between 80 and 200 Hz, the radial and lateral components of displacement of the road and side nodes exhibited significant oscillation. For the static analysis, the fluctuation was sharp and frequent and decreased with frequency. In contrast, the fluctuation was periodic in nature for the dynamic response of the rolling tire. In addition to the dynamic analysis, a steady state rolling analysis was also performed on the tire traveling at ground velocity with a constant angular motion. The purpose of the computation was to demonstrate the effect of rotating motion on deformation and rolling velocity with respect to a fixed Newtonian reference point. The analysis showed a significant variation in deformation and rolling velocity due to centrifugal and Coriolis acceleration with respect to a fixed Newtonian point on ground.

Keywords: natural frequency, rotational motion, steady state rolling, subspace-based steady state dynamic analysis

Procedia PDF Downloads 353
1100 Graph Neural Networks and Rotary Position Embedding for Voice Activity Detection

Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

Procedia PDF Downloads 51
1099 Feasibility of Using Musical Intervention to Promote Growth in Preterm Infants in the Neonatal Intensive Care Unit (NICU)

Authors: Yutong An

Abstract:

Premature babies in the Neonatal Intensive Care Unit (NICU) are usually protected in individual incubators to ensure a constant temperature and humidity. Accompanied by 24-hour monitoring by medical equipment, this provides a considerable degree of protection for the growth of preterm babies. However, preterm babies are still continuously exposed to noise at excessively high decibels (>45dB). Such noise has a highly damaging effect on the growth and development of preterm babies. For example, in the short term, it can lead to sleep deprivation, stress reactions, and difficulty calming emotions, while in the long term, it can trigger endocrine disorders, metabolic disorders, and hearing impairment. Fortunately, musical interventions in the NICU have been shown to provide calmness to newborns. This article integrates existing research on three types of music that are beneficial for preterm infants and their respective advantages and disadvantages. This paper aims to present a possibility, based on existing NICU equipment and experimental data related to musical interventions, to reduce the impact of noise on preterm babies in the NICU through a system design approach that incorporates a personalized adjustable music system in the incubator and an overall music enhancement in the open bay of the NICU.

Keywords: music interventions, neonatal intensive care unit (NICU), premature babies, neonatal nursing

Procedia PDF Downloads 47
1098 Measurement of Acoustic Loss in Nano-Layered Coating Developed for Thermal Noise Reduction

Authors: E. Cesarini, M. Lorenzini, R. Cardarelli, S. Chao, E. Coccia, V. Fafone, Y. Minenkow, I. Nardecchia, I. M. Pinto, A. Rocchi, V. Sequino, C. Taranto

Abstract:

Structural relaxation processes in optical coatings represent a fundamental limit to the sensitivity of gravitational waves detectors, MEMS, optical metrology and entangled state experiments. To face this problem, many research lines are now active, in particular the characterization of new materials and novel solutions to be employed as coatings in future gravitational wave detectors. Nano-layered coating deposition is among the most promising techniques. We report on the measurement of acoustic loss of nm-layered composites (Ti2O/SiO2), performed with the GeNS nodal suspension, compared with sputtered λ/4 thin films nowadays employed.

Keywords: mechanical measurement, nanomaterials, optical coating, thermal noise

Procedia PDF Downloads 411
1097 3D Numerical Studies on Jets Acoustic Characteristics of Chevron Nozzles for Aerospace Applications

Authors: R. Kanmaniraja, R. Freshipali, J. Abdullah, K. Niranjan, K. Balasubramani, V. R. Sanal Kumar

Abstract:

The present environmental issues have made aircraft jet noise reduction a crucial problem in aero-acoustics research. Acoustic studies reveal that addition of chevrons to the nozzle reduces the sound pressure level reasonably with acceptable reduction in performance. In this paper comprehensive numerical studies on acoustic characteristics of different types of chevron nozzles have been carried out with non-reacting flows for the shape optimization of chevrons in supersonic nozzles for aerospace applications. The numerical studies have been carried out using a validated steady 3D density based, k-ε turbulence model. In this paper chevron with sharp edge, flat edge, round edge and U-type edge are selected for the jet acoustic characterization of supersonic nozzles. We observed that compared to the base model a case with round-shaped chevron nozzle could reduce 4.13% acoustic level with 0.6% thrust loss. We concluded that the prudent selection of the chevron shape will enable an appreciable reduction of the aircraft jet noise without compromising its overall performance. It is evident from the present numerical simulations that k-ε model can predict reasonably well the acoustic level of chevron supersonic nozzles for its shape optimization.

Keywords: supersonic nozzle, Chevron, acoustic level, shape optimization of Chevron nozzles, jet noise suppression

Procedia PDF Downloads 496
1096 Harvesting Alternative Energy: Exploring Exergy, Human Power, Animal Body Heat, and Noise as Sustainable Sources

Authors: Fatemeh Yazdandoust, Derrick Mirrindi

Abstract:

The excessive use of non-renewable fossil fuels has led to a pressing energy crisis that demands urgent attention. While renewable sources like solar, wind, and water have gained significant attention as alternatives, we must explore additional avenues. This study takes an interdisciplinary approach, investigating the potential of waste streams from energy production and other untapped natural sources as sustainable energy solutions. Through a review of case studies, this study demonstrates how these alternative sources, including human power, animal body heat, and noise, can seamlessly integrate into architecture and urban planning. This article first discusses passive design strategies integrating alternative energy sources into vernacular architecture. Then, it reviews the waste stream (exergy) and potential energy sources, such as human power, animal body heat, and noise, in contemporary proposals and case studies. It demonstrates how an alternative energy design strategy may easily incorporate these many sources into our architecture and urban planning through passive and active design strategies to increase the energy efficiency of our built environment.

Keywords: alternative energy sources, energy exchange, human and animal power, potential energy sources, waste stream

Procedia PDF Downloads 36
1095 Performance Evaluation of Wideband Code Division Multiplication Network

Authors: Osama Abdallah Mohammed Enan, Amin Babiker A/Nabi Mustafa

Abstract:

The aim of this study is to evaluate and analyze different parameters of WCDMA (wideband code division multiplication). Moreover, this study also incorporates brief yet throughout analysis of WCDMA’s components as well as its internal architecture. This study also examines different power controls. These power controls may include open loop power control, closed or inner group loop power control and outer loop power control. Different handover techniques or methods of WCDMA are also illustrated in this study. These handovers may include hard handover, inter system handover and soft and softer handover. Different duplexing techniques are also described in the paper. This study has also presented an idea about different parameters of WCDMA that leads the system towards QoS issues. This may help the operator in designing and developing adequate network configuration. In addition to this, the study has also investigated various parameters including Bit Energy per Noise Spectral Density (Eb/No), Noise rise, and Bit Error Rate (BER). After simulating these parameters, using MATLAB environment, it was investigated that, for a given Eb/No value the system capacity increase by increasing the reuse factor. Besides that, it was also analyzed that, noise rise is decreasing for lower data rates and for lower interference levels. Finally, it was examined that, BER increase by using one type of modulation technique than using other type of modulation technique.

Keywords: duplexing, handover, loop power control, WCDMA

Procedia PDF Downloads 199
1094 Long-Term Structural Behavior of Resilient Materials for Reduction of Floor Impact Sound

Authors: Jung-Yoon Lee, Jongmun Kim, Hyo-Jun Chang, Jung-Min Kim

Abstract:

People’s tendency towards living in apartment houses is increasing in a densely populated country. However, some residents living in apartment houses are bothered by noise coming from the houses above. In order to reduce noise pollution, the communities are increasingly imposing a bylaw, including the limitation of floor impact sound, minimum thickness of floors, and floor soundproofing solutions. This research effort focused on the specific long-time deflection of resilient materials in the floor sound insulation systems of apartment houses. The experimental program consisted of testing nine floor sound insulation specimens subjected to sustained load for 45 days. Two main parameters were considered in the experimental investigation: three types of resilient materials and magnitudes of loads. The test results indicated that the structural behavior of the floor sound insulation systems under long-time load was quite different from that the systems under short-time load. The loading period increased the deflection of floor sound insulation systems and the increasing rate of the long-time deflection of the systems with ethylene vinyl acetate was smaller than that of the systems with low density ethylene polystyrene.

Keywords: resilient materials, floor sound insulation systems, long-time deflection, sustained load, noise pollution

Procedia PDF Downloads 255
1093 A Nonlinear Stochastic Differential Equation Model for Financial Bubbles and Crashes with Finite-Time Singularities

Authors: Haowen Xi

Abstract:

We propose and solve exactly a class of non-linear generalization of the Black-Scholes process of stochastic differential equations describing price bubble and crashes dynamics. As a result of nonlinear positive feedback, the faster-than-exponential price positive growth (bubble forming) and negative price growth (crash forming) are found to be the power-law finite-time singularity in which bubbles and crashes price formation ending at finite critical time tc. While most literature on the market bubble and crash process focuses on the nonlinear positive feedback mechanism aspect, very few studies concern the noise level on the same process. The present work adds to the market bubble and crashes literature by studying the external sources noise influence on the critical time tc of the bubble forming and crashes forming. Two main results will be discussed: (1) the analytical expression of expected value of the critical time is found and unexpected critical slowing down due to the coupling external noise is predicted; (2) numerical simulations of the nonlinear stochastic equation is presented, and the probability distribution of Prob(tc) is found to be the inverse gamma function.

Keywords: bubble, crash, finite-time-singular, numerical simulation, price dynamics, stochastic differential equations

Procedia PDF Downloads 115
1092 Study on Acoustic Source Detection Performance Improvement of Microphone Array Installed on Drones Using Blind Source Separation

Authors: Youngsun Moon, Yeong-Ju Go, Jong-Soo Choi

Abstract:

Most drones that currently have surveillance/reconnaissance missions are basically equipped with optical equipment, but we also need to use a microphone array to estimate the location of the acoustic source. This can provide additional information in the absence of optical equipment. The purpose of this study is to estimate Direction of Arrival (DOA) based on Time Difference of Arrival (TDOA) estimation of the acoustic source in the drone. The problem is that it is impossible to measure the clear target acoustic source because of the drone noise. To overcome this problem is to separate the drone noise and the target acoustic source using Blind Source Separation(BSS) based on Independent Component Analysis(ICA). ICA can be performed assuming that the drone noise and target acoustic source are independent and each signal has non-gaussianity. For maximized non-gaussianity each signal, we use Negentropy and Kurtosis based on probability theory. As a result, we can improve TDOA estimation and DOA estimation of the target source in the noisy environment. We simulated the performance of the DOA algorithm applying BSS algorithm, and demonstrated the simulation through experiment at the anechoic wind tunnel.

Keywords: aeroacoustics, acoustic source detection, time difference of arrival, direction of arrival, blind source separation, independent component analysis, drone

Procedia PDF Downloads 147
1091 A Study of Chaos Control Schemes for Plankton-Fish Dynamics

Authors: Rajinder Pal Kaur, Amit Sharma, Anuj Kumar Sharma, Govind Prasad Sahu

Abstract:

The existence of chaos in the marine ecosystems may cause planktonic blooms, disease outbreaks, extinction of some plankton species, or some complex dynamics in oceans, which can adversely affect the sustainable marine ecosystem. The control of the chaotic plankton-fish dynamics is one of the main motives of marine ecologists. In this paper, we have studied the impact of phytoplankton refuge, zooplankton refuge, and fear effect on the chaotic plankton-fish dynamics incorporating phytoplankton, zooplankton, and fish biomass. The fear of fish predation transfers the unpredictable(chaotic) behavior of the plankton system to a stable orbit. The defense mechanism developed by prey species due to fear of the predator population can also terminate chaos from the given dynamics. Moreover, the impact of external disturbances like seasonality, noise, periodic fluctuations, and time delay on the given chaotic plankton system has also been discussed. We have applied feedback mechanisms to control the complexity of the system through the parameter noise. The non-feedback schemes are implemented to observe the role of seasonal force, periodic fluctuations, and time delay in suppressing the given chaotic system. Analytical results are substantiated by numerical simulation.

Keywords: plankton, chaos, noise, seasonality, fluctuations, fear effect, prey refuge

Procedia PDF Downloads 67
1090 Identification of Wiener Model Using Iterative Schemes

Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

Procedia PDF Downloads 379
1089 The Prevalence of Symptoms of Common Mental Disorders Among Professional Golfers

Authors: Georgia Hopley, Andrew Murray, Alan Macpherson

Abstract:

Objectives: This study aims to (i) assess the prevalence of symptoms of mental health disorders among a cohort of professional golfers, (ii) compare prevalence values with data from the general population and other elite athlete cohorts, and (iii) assess how players cope with mental health problems and players’ opinions on the mental health support services available to them. Methods: Players competing on the 2020 Challenge Tour (n=261) were sent a questionnaire that assessed symptoms of depression, distress, anxiety, sleep disturbance, and obsessive-compulsive disorder. Questions were also included to assess coping behaviors and opinions on current support measures. Results: The two-week symptom prevalence was 10.3% for depression, 51.7% for distress, 8.6% for anxiety, 10.3% for sleep disturbance, 13.8% for obsessive thoughts, and 27.6% for compulsive behavior. The prevalence of symptoms is comparable with other elite athlete cohorts, and symptoms of anxiety and distress were reported more frequently than in the general population. 67% of players who had experienced a mental health issue did not seek professional help at the time, and 61% of players did not think sufficient support was available to them. Conclusion: Mental health problems are prevalent among elite golfers; however, this study demonstrates that the majority of players do not seek help from professionally accredited practitioners. Following the discussion of this study, the European Tour Group now provides a 24/7 mental health crisis hotline for players and has educated staff members on how to identify players with mental health issues and signpost them to the appropriate support.

Keywords: elite athletes, golf, mental health, sport science, sport psychiatry

Procedia PDF Downloads 41
1088 Gas Sensor Based On a One-Dimensional Nano-Grating Au/ Co/ Au/ TiO2 Magneto-Plasmonic Structure

Authors: S. M. Hamidi, M. Afsharnia

Abstract:

Gas sensors based on magneto-plasmonic (MP) structures have attracted much attention due to the high signal to noise ratio in these type of sensors. In these sensors, both the plasmonic and the MO properties of the resulting MP structure become interrelated because the surface Plasmon resonance (SPR) of the metallic medium. This interconnection can be modified the sensor responses and enhanced the signal to noise ratio. So far the sensor features of multilayered structures made of noble and ferromagnetic metals as Au/Co/Au MP multilayer with TiO2 sensor layer have been extensively studied, but their SPR assisted sensor response need to the krestchmann configuration. Here, we present a systematic study on the new MP structure based on one-dimensional nano-grating Au/ Co/ Au/ TiO2 multilayer to utilize as an inexpensive and easy to use gas sensor.

Keywords: Magneto-plasmonic structures, Gas sensor, nano-garting

Procedia PDF Downloads 433
1087 Simulations of a Jet Impinging on a Flat Plate

Authors: Reda Mankbadi

Abstract:

In this paper we explore the use of a second-order unstructured-grid, finite-volume code for direct noise prediction. We consider a Mach 1.5 jet impinging on a perpendicular flat plate. Hybrid LES-RANS simulations are used to calculate directly both the flow field and the radiated sound. The ANSYS Fluent commercial code is utilized for the calculations. The acoustic field is obtained directly from the simulations and is compared with the integral approach of Ffowcs Williams-Hawkings (FWH). Results indicate the existence of a preferred radiation angle. The spectrum obtained is in good agreement with observations. This points out to the possibility of handling the effects of complicated geometries on noise radiation by using unstructured second-orders codes.

Keywords: CFD, Ffowcs Williams-Hawkings (FWH), imping jet, ANSYS fluent commercial code, hybrid LES-RANS simulations

Procedia PDF Downloads 433
1086 Path-Tracking Controller for Tracked Mobile Robot on Rough Terrain

Authors: Toshifumi Hiramatsu, Satoshi Morita, Manuel Pencelli, Marta Niccolini, Matteo Ragaglia, Alfredo Argiolas

Abstract:

Automation technologies for agriculture field are needed to promote labor-saving. One of the most relevant problems in automated agriculture is represented by controlling the robot along a predetermined path in presence of rough terrain or incline ground. Unfortunately, disturbances originating from interaction with the ground, such as slipping, make it quite difficult to achieve the required accuracy. In general, it is required to move within 5-10 cm accuracy with respect to the predetermined path. Moreover, lateral velocity caused by gravity on the incline field also affects slipping. In this paper, a path-tracking controller for tracked mobile robots moving on rough terrains of incline field such as vineyard is presented. The controller is composed of a disturbance observer and an adaptive controller based on the kinematic model of the robot. The disturbance observer measures the difference between the measured and the reference yaw rate and linear velocity in order to estimate slip. Then, the adaptive controller adapts “virtual” parameter of the kinematics model: Instantaneous Centers of Rotation (ICRs). Finally, target angular velocity reference is computed according to the adapted parameter. This solution allows estimating the effects of slip without making the model too complex. Finally, the effectiveness of the proposed solution is tested in a simulation environment.

Keywords: the agricultural robot, autonomous control, path-tracking control, tracked mobile robot

Procedia PDF Downloads 160
1085 Complete Ensemble Empirical Mode Decomposition with Adaptive Noise Temporal Convolutional Network for Remaining Useful Life Prediction of Lithium Ion Batteries

Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

Abstract:

Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

Procedia PDF Downloads 127
1084 Integrating System-Level Infrastructure Resilience and Sustainability Based on Fractal: Perspectives and Review

Authors: Qiyao Han, Xianhai Meng

Abstract:

Urban infrastructures refer to the fundamental facilities and systems that serve cities. Due to the global climate change and human activities in recent years, many urban areas around the world are facing enormous challenges from natural and man-made disasters, like flood, earthquake and terrorist attack. For this reason, urban resilience to disasters has attracted increasing attention from researchers and practitioners. Given the complexity of infrastructure systems and the uncertainty of disasters, this paper suggests that studies of resilience could focus on urban functional sustainability (in social, economic and environmental dimensions) supported by infrastructure systems under disturbance. It is supposed that urban infrastructure systems with high resilience should be able to reconfigure themselves without significant declines in critical functions (services), such as primary productivity, hydrological cycles, social relations and economic prosperity. Despite that some methods have been developed to integrate the resilience and sustainability of individual infrastructure components, more work is needed to enable system-level integration. This research presents a conceptual analysis framework for integrating resilience and sustainability based on fractal theory. It is believed that the ability of an ecological system to maintain structure and function in face of disturbance and to reorganize following disturbance-driven change is largely dependent on its self-similar and hierarchical fractal structure, in which cross-scale resilience is produced by the replication of ecosystem processes dominating at different levels. Urban infrastructure systems are analogous to ecological systems because they are interconnected, complex and adaptive, are comprised of interconnected components, and exhibit characteristic scaling properties. Therefore, analyzing resilience of ecological system provides a better understanding about the dynamics and interactions of infrastructure systems. This paper discusses fractal characteristics of ecosystem resilience, reviews literature related to system-level infrastructure resilience, identifies resilience criteria associated with sustainability dimensions, and develops a conceptual analysis framework. Exploration of the relevance of identified criteria to fractal characteristics reveals that there is a great potential to analyze infrastructure systems based on fractal. In the conceptual analysis framework, it is proposed that in order to be resilient, urban infrastructure system needs to be capable of “maintaining” and “reorganizing” multi-scale critical functions under disasters. Finally, the paper identifies areas where further research efforts are needed.

Keywords: fractal, urban infrastructure, sustainability, system-level resilience

Procedia PDF Downloads 257
1083 Ureteral Stents with Extraction Strings: Patient-Reported Outcomes

Authors: Rammah Abdlbagi, Similoluwa Biyi, Aakash Pai

Abstract:

Introduction: Short-term ureteric stents are commonly placed after ureteroscopy procedures. The removal usually entails having a flexible cystoscopy, which entails a further invasive procedure. There are often delays in removing the stent as departments have limited cystoscopy availability. However, if stents with extraction strings are used, the patient or a clinician can remove them. The aim of the study is to assess the safety and effectiveness of the use of a stent with a string. Method: A retrospective, single-institution study was conducted over a three-month period. Twenty consecutive patients had ureteric stents with string insertion. Ten of the patients had a stent removal procedure previously with flexible cystoscopy. A validated questionnaire was used to assess outcomes. Primary outcomes included: dysuria, hematuria, urinary frequency, and disturbance of the patient’s daily activities. Secondary outcomes included pain experience during the stent removal. Result: Fifteen patients (75%) experienced hematuria and frequency. Two patients experienced pain and discomfort during the stent removal (10%). Two patients had experienced a disturbance in their daily activity (10%). All patients who had stent removal before using flexible cystoscopy preferred the removal of the stent using a string. None of the patients had stent displacement. The median stent dwell time was five days. Conclusion: Patient reported outcomes measures for the indwelling period of a stent with extraction string are equivalent to the published data on stents. Extraction strings mean that the stent dwell time can be reduced. The removal of the stent on extraction strings is more tolerable than the conventional stent.

Keywords: ureteric stent, string flexible cystoscopy, stent symptoms, validated questionnaire

Procedia PDF Downloads 78
1082 Multi-Objective Optimal Design of a Cascade Control System for a Class of Underactuated Mechanical Systems

Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

Abstract:

This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: cascade control, multi-Loop control systems, multiobjective optimization, optimal control

Procedia PDF Downloads 138
1081 Comprehensive Analysis of Power Allocation Algorithms for OFDM Based Communication Systems

Authors: Rakesh Dubey, Vaishali Bahl, Dalveer Kaur

Abstract:

The spiralling urge for high rate data transmission over wireless mediums needs intelligent use of electromagnetic resources considering restrictions like power ingestion, spectrum competence, robustness against multipath propagation and implementation intricacy. Orthogonal frequency division multiplexing (OFDM) is a capable technique for next generation wireless communication systems. For such high rate data transfers there is requirement of proper allocation of resources like power and capacity amongst the sub channels. This paper illustrates various available methods of allocating power and the capacity requirement with the constraint of Shannon limit.

Keywords: Additive White Gaussian Noise, Multi-Carrier Modulation, Orthogonal Frequency Division Multiplexing (OFDM), Signal to Noise Ratio (SNR), Water Filling

Procedia PDF Downloads 536
1080 Application of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Multipoint Optimal Minimum Entropy Deconvolution in Railway Bearings Fault Diagnosis

Authors: Yao Cheng, Weihua Zhang

Abstract:

Although the measured vibration signal contains rich information on machine health conditions, the white noise interferences and the discrete harmonic coming from blade, shaft and mash make the fault diagnosis of rolling element bearings difficult. In order to overcome the interferences of useless signals, a new fault diagnosis method combining Complete Ensemble Empirical Mode Decomposition with adaptive noise (CEEMDAN) and Multipoint Optimal Minimum Entropy Deconvolution (MOMED) is proposed for the fault diagnosis of high-speed train bearings. Firstly, the CEEMDAN technique is applied to adaptively decompose the raw vibration signal into a series of finite intrinsic mode functions (IMFs) and a residue. Compared with Ensemble Empirical Mode Decomposition (EEMD), the CEEMDAN can provide an exact reconstruction of the original signal and a better spectral separation of the modes, which improves the accuracy of fault diagnosis. An effective sensitivity index based on the Pearson's correlation coefficients between IMFs and raw signal is adopted to select sensitive IMFs that contain bearing fault information. The composite signal of the sensitive IMFs is applied to further analysis of fault identification. Next, for propose of identifying the fault information precisely, the MOMED is utilized to enhance the periodic impulses in composite signal. As a non-iterative method, the MOMED has better deconvolution performance than the classical deconvolution methods such Minimum Entropy Deconvolution (MED) and Maximum Correlated Kurtosis Deconvolution (MCKD). Third, the envelope spectrum analysis is applied to detect the existence of bearing fault. The simulated bearing fault signals with white noise and discrete harmonic interferences are used to validate the effectiveness of the proposed method. Finally, the superiorities of the proposed method are further demonstrated by high-speed train bearing fault datasets measured from test rig. The analysis results indicate that the proposed method has strong practicability.

Keywords: bearing, complete ensemble empirical mode decomposition with adaptive noise, fault diagnosis, multipoint optimal minimum entropy deconvolution

Procedia PDF Downloads 355
1079 Regularization of Gene Regulatory Networks Perturbed by White Noise

Authors: Ramazan I. Kadiev, Arcady Ponosov

Abstract:

Mathematical models of gene regulatory networks can in many cases be described by ordinary differential equations with switching nonlinearities, where the initial value problem is ill-posed. Several regularization methods are known in the case of deterministic networks, but the presence of stochastic noise leads to several technical difficulties. In the presentation, it is proposed to apply the methods of the stochastic singular perturbation theory going back to Yu. Kabanov and Yu. Pergamentshchikov. This approach is used to regularize the above ill-posed problem, which, e.g., makes it possible to design stable numerical schemes. Several examples are provided in the presentation, which support the efficiency of the suggested analysis. The method can also be of interest in other fields of biomathematics, where differential equations contain switchings, e.g., in neural field models.

Keywords: ill-posed problems, singular perturbation analysis, stochastic differential equations, switching nonlinearities

Procedia PDF Downloads 180
1078 Assessment of an ICA-Based Method for Detecting the Effect of Attention in the Auditory Late Response

Authors: Siavash Mirahmadizoghi, Steven Bell, David Simpson

Abstract:

In this work a new independent component analysis (ICA) based method for noise reduction in evoked potentials is evaluated on for auditory late responses (ALR) captured with a 63-channel electroencephalogram (EEG) from 10 normal-hearing subjects. The performance of the new method is compared with a single channel alternative in terms of signal to noise ratio (SNR), the number of channels with an SNR above an empirically derived statistical critical value and an estimate of the effect of attention on the major components in the ALR waveform. The results show that the multichannel signal processing method can significantly enhance the quality of the ALR signal and also detect the effect of the attention on the ALR better than the single channel alternative.

Keywords: auditory late response (ALR), attention, EEG, independent component analysis (ICA), multichannel signal processing

Procedia PDF Downloads 492
1077 Virtual Dimension Analysis of Hyperspectral Imaging to Characterize a Mining Sample

Authors: L. Chevez, A. Apaza, J. Rodriguez, R. Puga, H. Loro, Juan Z. Davalos

Abstract:

Virtual Dimension (VD) procedure is used to analyze Hyperspectral Image (HIS) treatment-data in order to estimate the abundance of mineral components of a mining sample. Hyperspectral images coming from reflectance spectra (NIR region) are pre-treated using Standard Normal Variance (SNV) and Minimum Noise Fraction (MNF) methodologies. The endmember components are identified by the Simplex Growing Algorithm (SVG) and after adjusted to the reflectance spectra of reference-databases using Simulated Annealing (SA) methodology. The obtained abundance of minerals of the sample studied is very near to the ones obtained using XRD with a total relative error of 2%.

Keywords: hyperspectral imaging, minimum noise fraction, MNF, simplex growing algorithm, SGA, standard normal variance, SNV, virtual dimension, XRD

Procedia PDF Downloads 142
1076 Stochastic Response of an Airfoil and Its Effects on Limit Cycle Oscillations’ Behavior under Stall Flutter Regime

Authors: Ketseas Dimitris

Abstract:

In this work, we investigate the effect of noise on a classical two-degree-of-freedom pitch-plunge aeroelastic system. The inlet velocity of the flow is modelled as a stochastically varying parameter by the Ornstein-Uhlenbeck (OU) stochastic process. The system is a 2D airfoil, and the elastic problem is simulated using linear springs. We study the manifestation of Limit Cycle Oscillations (LCO) that correspond to the varying fluid velocity under the dynamic stall regime. We aim to delve into the unexplored facets of the classical pitch-plunge aeroelastic system, seeking a comprehensive understanding of how parametric noise influences the occurrence of LCO and expands the boundaries of its known behavior.

Keywords: aerodynamics, aeroelasticity, computational fluid mechanics, stall flutter, stochastical processes, limit cycle oscillation

Procedia PDF Downloads 43
1075 Resilience-Vulnerability Interaction in the Context of Disasters and Complexity: Study Case in the Coastal Plain of Gulf of Mexico

Authors: Cesar Vazquez-Gonzalez, Sophie Avila-Foucat, Leonardo Ortiz-Lozano, Patricia Moreno-Casasola, Alejandro Granados-Barba

Abstract:

In the last twenty years, academic and scientific literature has been focused on understanding the processes and factors of coastal social-ecological systems vulnerability and resilience. Some scholars argue that resilience and vulnerability are isolated concepts due to their epistemological origin, while others note the existence of a strong resilience-vulnerability relationship. Here we present an ordinal logistic regression model based on the analytical framework about dynamic resilience-vulnerability interaction along adaptive cycle of complex systems and disasters process phases (during, recovery and learning). In this way, we demonstrate that 1) during the disturbance, absorptive capacity (resilience as a core of attributes) and external response capacity explain the probability of households capitals to diminish the damage, and exposure sets the thresholds about the amount of disturbance that households can absorb, 2) at recovery, absorptive capacity and external response capacity explain the probability of households capitals to recovery faster (resilience as an outcome) from damage, and 3) at learning, adaptive capacity (resilience as a core of attributes) explains the probability of households adaptation measures based on the enhancement of physical capital. As a result, during the disturbance phase, exposure has the greatest weight in the probability of capital’s damage, and households with absorptive and external response capacity elements absorbed the impact of floods in comparison with households without these elements. At the recovery phase, households with absorptive and external response capacity showed a faster recovery on their capital; however, the damage sets the thresholds of recovery time. More importantly, diversity in financial capital increases the probability of recovering other capital, but it becomes a liability so that the probability of recovering the household finances in a longer time increases. At learning-reorganizing phase, adaptation (modifications to the house) increases the probability of having less damage on physical capital; however, it is not very relevant. As conclusion, resilience is an outcome but also core of attributes that interacts with vulnerability along the adaptive cycle and disaster process phases. Absorptive capacity can diminish the damage experienced by floods; however, when exposure overcomes thresholds, both absorptive and external response capacity are not enough. In the same way, absorptive and external response capacity diminish the recovery time of capital, but the damage sets the thresholds in where households are not capable of recovering their capital.

Keywords: absorptive capacity, adaptive capacity, capital, floods, recovery-learning, social-ecological systems

Procedia PDF Downloads 119
1074 Identity Verification Using k-NN Classifiers and Autistic Genetic Data

Authors: Fuad M. Alkoot

Abstract:

DNA data have been used in forensics for decades. However, current research looks at using the DNA as a biometric identity verification modality. The goal is to improve the speed of identification. We aim at using gene data that was initially used for autism detection to find if and how accurate is this data for identification applications. Mainly our goal is to find if our data preprocessing technique yields data useful as a biometric identification tool. We experiment with using the nearest neighbor classifier to identify subjects. Results show that optimal classification rate is achieved when the test set is corrupted by normally distributed noise with zero mean and standard deviation of 1. The classification rate is close to optimal at higher noise standard deviation reaching 3. This shows that the data can be used for identity verification with high accuracy using a simple classifier such as the k-nearest neighbor (k-NN). 

Keywords: biometrics, genetic data, identity verification, k nearest neighbor

Procedia PDF Downloads 235