Search results for: contrast limited adaptive histogram equalization
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6477

Search results for: contrast limited adaptive histogram equalization

6327 Domain Adaptive Dense Retrieval with Query Generation

Authors: Rui Yin, Haojie Wang, Xun Li

Abstract:

Recently, mainstream dense retrieval methods have obtained state-of-the-art results on some datasets and tasks. However, they require large amounts of training data, which is not available in most domains. The severe performance degradation of dense retrievers on new data domains has limited the use of dense retrieval methods to only a few domains with large training datasets. In this paper, we propose an unsupervised domain-adaptive approach based on query generation. First, a generative model is used to generate relevant queries for each passage in the target corpus, and then, the generated queries are used for mining negative passages. Finally, the query-passage pairs are labeled with a cross-encoder and used to train a domain-adapted dense retriever. We also explore contrastive learning as a method for training domain-adapted dense retrievers and show that it leads to strong performance in various retrieval settings. Experiments show that our approach is more robust than previous methods in target domains that require less unlabeled data.

Keywords: dense retrieval, query generation, contrastive learning, unsupervised training

Procedia PDF Downloads 76
6326 Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

Abstract:

Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

Procedia PDF Downloads 127
6325 Novel Adaptive Radial Basis Function Neural Networks Based Approach for Short-Term Load Forecasting of Jordanian Power Grid

Authors: Eyad Almaita

Abstract:

In this paper, a novel adaptive Radial Basis Function Neural Networks (RBFNN) algorithm is used to forecast the hour by hour electrical load demand in Jordan. A small and effective RBFNN model is used to forecast the hourly total load demand based on a small number of features. These features are; the load in the previous day, the load in the same day in the previous week, the temperature in the same hour, the hour number, the day number, and the day type. The proposed adaptive RBFNN model can enhance the reliability of the conventional RBFNN after embedding the network in the system. This is achieved by introducing an adaptive algorithm that allows the change of the weights of the RBFNN after the training process is completed, which will eliminates the need to retrain the RBFNN model again. The data used in this paper is real data measured by National Electrical Power co. (Jordan). The data for the period Jan./2012-April/2013 is used train the RBFNN models and the data for the period May/2013- Sep. /2013 is used to validate the models effectiveness.

Keywords: load forecasting, adaptive neural network, radial basis function, short-term, electricity consumption

Procedia PDF Downloads 323
6324 An Energy Efficient Spectrum Shaping Scheme for Substrate Integrated Waveguides Based on Spread Reshaping Code

Authors: Yu Zhao, Rainer Gruenheid, Gerhard Bauch

Abstract:

In the microwave and millimeter-wave transmission region, substrate-integrated waveguide (SIW) is a very promising candidate for the development of circuits and components. It facilitates the transmission at the data rates in excess of 200 Gbit/s. An SIW mimics a rectangular waveguide by approximating the closed sidewalls with a via fence. This structure suppresses the low frequency components and makes the channel of the SIW a bandpass or high pass filter. This channel characteristic impedes the conventional baseband transmission using non-return-to-zero (NRZ) pulse shaping scheme. Therefore, mixers are commonly proposed to be used as carrier modulator and demodulator in order to facilitate a passband transmission. However, carrier modulation is not an energy efficient solution, because modulation and demodulation at high frequencies consume a lot of energy. For the first time to our knowledge, this paper proposes a spectrum shaping scheme of low complexity for the channel of SIW, namely spread reshaping code. It aims at matching the spectrum of the transmit signal to the channel frequency response. It facilitates the transmission through the SIW channel while it avoids using carrier modulation. In some cases, it even does not need equalization. Simulations reveal a good performance of this scheme, such that, as a result, eye opening is achieved without any equalization or modulation for the respective transmission channels.

Keywords: bandpass channel, eye-opening, switching frequency, substrate-integrated waveguide, spectrum shaping scheme, spread reshaping code

Procedia PDF Downloads 140
6323 Implementation of Model Reference Adaptive Control in Tuning of Controller Gains for Following-Vehicle System with Fixed Time Headway

Authors: Fatemeh Behbahani, Rubiyah Yusof

Abstract:

To avoid collision between following vehicles and vehicles in front, it is vital to keep appropriate, safe spacing between both vehicles over all speeds. Therefore, the following vehicle needs to have exact information regarding the speed and spacing between vehicles. This project is conducted to simulate the tuning of controller gain for a vehicle-following system through the selected control strategy, spacing control policy and fixed-time headway policy. In addition, the paper simulates and designs an adaptive gain controller for a road-vehicle-following system which uses information on the spacing, velocity and also acceleration of a preceding vehicle in the proposed one-vehicle look-ahead strategy. The mathematical model is implemented using Kirchhoff and Newton’s Laws, and stability simulated. The trial-error method was used to obtain a suitable value of controller gain. However, the adaptive-based controller system was able to optimize the gain value automatically. Model Reference Adaptive Control (MRAC) is designed and utilized and based on firstly the Gradient and secondly the Lyapunov approach. The Lyapunov approach considers stability. The Gradient approach was found to improve the best value of gain in the controller system with fixed-time headway.

Keywords: one-vehicle look-ahead, model reference adaptive, stability, tuning gain controller, MRAC

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6322 UML Model for Double-Loop Control Self-Adaptive Braking System

Authors: Heung Sun Yoon, Jong Tae Kim

Abstract:

In this paper, we present an activity diagram model for double-loop control self-adaptive braking system. Since activity diagram helps to improve visibility of self-adaption, we can easily find where improvement is needed on double-loop control. Double-loop control is adopted since the design conditions and actual conditions can be different. The system is reconfigured in runtime by using double-loop control. We simulated to verify and validate our model by using MATLAB. We compared single-loop control model with double-loop control model. Simulation results show that double-loop control provides more consistent brake power control than single-loop control.

Keywords: activity diagram, automotive, braking system, double-loop, self-adaptive, UML, vehicle

Procedia PDF Downloads 394
6321 A Comprehensive Review of Adaptive Building Energy Management Systems Based on Users’ Feedback

Authors: P. Nafisi Poor, P. Javid

Abstract:

Over the past few years, the idea of adaptive buildings and specifically, adaptive building energy management systems (ABEMS) has become popular. Well-performed management in terms of energy is to create a balance between energy consumption and user comfort; therefore, in new energy management models, efficient energy consumption is not the sole factor and the user's comfortability is also considered in the calculations. One of the main ways of measuring this factor is by analyzing user feedback on the conditions to understand whether they are satisfied with conditions or not. This paper provides a comprehensive review of recent approaches towards energy management systems based on users' feedbacks and subsequently performs a comparison between them premised upon their efficiency and accuracy to understand which approaches were more accurate and which ones resulted in a more efficient way of minimizing energy consumption while maintaining users' comfortability. It was concluded that the highest accuracy rate among the presented works was 95% accuracy in determining satisfaction and up to 51.08% energy savings can be achieved without disturbing user’s comfort. Considering the growing interest in designing and developing adaptive buildings, these studies can support diverse inquiries about this subject and can be used as a resource to support studies and researches towards efficient energy consumption while maintaining the comfortability of users.

Keywords: adaptive buildings, energy efficiency, intelligent buildings, user comfortability

Procedia PDF Downloads 118
6320 Object Detection in Digital Images under Non-Standardized Conditions Using Illumination and Shadow Filtering

Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

Abstract:

In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

Procedia PDF Downloads 198
6319 Hypersensitivity Reactions Following Intravenous Administration of Contrast Medium

Authors: Joanna Cydejko, Paulina Mika

Abstract:

Hypersensitivity reactions are side effects of medications that resemble an allergic reaction. Anaphylaxis is a generalized, severe allergic reaction of the body caused by exposure to a specific agent at a dose tolerated by a healthy body. The most common causes of anaphylaxis are food (about 70%), Hymenoptera venoms (22%), and medications (7%), despite detailed diagnostics in 1% of people, the cause of the anaphylactic reaction was not indicated. Contrast media are anaphylactic agents of unknown mechanism. Hypersensitivity reactions can occur with both immunological and non-immunological mechanisms. Symptoms of anaphylaxis occur within a few seconds to several minutes after exposure to the allergen. Contrast agents are chemical compounds that make it possible to visualize or improve the visibility of anatomical structures. In the diagnosis of computed tomography, the preparations currently used are derivatives of the triiodide benzene ring. Pharmacokinetic and pharmacodynamic properties, i.e., their osmolality, viscosity, low chemotoxicity and high hydrophilicity, have an impact on better tolerance of the substance by the patient's body. In MRI diagnostics, macrocyclic gadolinium contrast agents are administered during examinations. The aim of this study is to present the results of the number and severity of anaphylactic reactions that occurred in patients in all age groups undergoing diagnostic imaging with intravenous administration of contrast agents. In non-ionic iodine CT and in macrocyclic gadolinium MRI. A retrospective assessment of the number of adverse reactions after contrast administration was carried out on the basis of data from the Department of Radiology of the University Clinical Center in Gdańsk, and it was assessed whether their different physicochemical properties had an impact on the incidence of acute complications. Adverse reactions are divided according to the severity of the patient's condition and the diagnostic method used in a given patient. Complications following the administration of a contrast medium in the form of acute anaphylaxis accounted for less than 0.5% of all diagnostic procedures performed with the use of a contrast agent. In the analysis period from January to December 2022, 34,053 CT scans and 15,279 MRI examinations with the use of contrast medium were performed. The total number of acute complications was 21, of which 17 were complications of iodine-based contrast agents and 5 of gadolinium preparations. The introduction of state-of-the-art contrast formulations was an important step toward improving the safety and tolerability of contrast agents used in imaging. Currently, contrast agents administered to patients are considered to be one of the best-tolerated preparations used in medicine. However, like any drug, they can be responsible for the occurrence of adverse reactions resulting from their toxic effects. The increase in the number of imaging tests performed with the use of contrast agents has a direct impact on the number of adverse events associated with their administration. However, despite the low risk of anaphylaxis, this risk should not be marginalized. The growing threat associated with the mass performance of radiological procedures with the use of contrast agents forces the knowledge of the rules of conduct in the event of symptoms of hypersensitivity to these preparations.

Keywords: anaphylactic, contrast medium, diagnostic, medical imagine

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6318 Evolved Bat Algorithm Based Adaptive Fuzzy Sliding Mode Control with LMI Criterion

Authors: P.-W. Tsai, C.-Y. Chen, C.-W. Chen

Abstract:

In this paper, the stability analysis of a GA-Based adaptive fuzzy sliding model controller for a nonlinear system is discussed. First, a nonlinear plant is well-approximated and described with a reference model and a fuzzy model, both involving FLC rules. Then, FLC rules and the consequent parameter are decided on via an Evolved Bat Algorithm (EBA). After this, we guarantee a new tracking performance inequality for the control system. The tracking problem is characterized to solve an eigenvalue problem (EVP). Next, an adaptive fuzzy sliding model controller (AFSMC) is proposed to stabilize the system so as to achieve good control performance. Lyapunov’s direct method can be used to ensure the stability of the nonlinear system. It is shown that the stability analysis can reduce nonlinear systems into a linear matrix inequality (LMI) problem. Finally, a numerical simulation is provided to demonstrate the control methodology.

Keywords: adaptive fuzzy sliding mode control, Lyapunov direct method, swarm intelligence, evolved bat algorithm

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6317 Enhancing the Bionic Eye: A Real-time Image Optimization Framework to Encode Color and Spatial Information Into Retinal Prostheses

Authors: William Huang

Abstract:

Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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6316 An Adaptive Distributed Incremental Association Rule Mining System

Authors: Adewale O. Ogunde, Olusegun Folorunso, Adesina S. Sodiya

Abstract:

Most existing Distributed Association Rule Mining (DARM) systems are still facing several challenges. One of such challenges that have not received the attention of many researchers is the inability of existing systems to adapt to constantly changing databases and mining environments. In this work, an Adaptive Incremental Mining Algorithm (AIMA) is therefore proposed to address these problems. AIMA employed multiple mobile agents for the entire mining process. AIMA was designed to adapt to changes in the distributed databases by mining only the incremental database updates and using this to update the existing rules in order to improve the overall response time of the DARM system. In AIMA, global association rules were integrated incrementally from one data site to another through Results Integration Coordinating Agents. The mining agents in AIMA were made adaptive by defining mining goals with reasoning and behavioral capabilities and protocols that enabled them to either maintain or change their goals. AIMA employed Java Agent Development Environment Extension for designing the internal agents’ architecture. Results from experiments conducted on real datasets showed that the adaptive system, AIMA performed better than the non-adaptive systems with lower communication costs and higher task completion rates.

Keywords: adaptivity, data mining, distributed association rule mining, incremental mining, mobile agents

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6315 Allopurinol Prophylactic Therapy in the Prevention of Contrast Induced Nephropathy in High Risk Patients Undergoing Coronary Angiography: A Prospective Randomized Controlled Trial

Authors: Seyed Fakhreddin Hejazi, Leili Iranirad, Mohammad Sadeghi, Mohsen Talebizadeh

Abstract:

Background: Contrast-induced nephropathy (CIN) remains to be a potentially serious complication of radiographic procedures. We performed this clinical trial to assess the preventive effect of allopurinol against CIN in high-risk patients undergoing coronary angiography. Methods: In this prospective randomized controlled trial, 140 patients with at least two risk factors for CIN undergoing coronary angiography were randomly assigned to either the allopurinol group or the control group. Patients in the allopurinol group received 300 mg allopurinol 24 hours before a procedure and intravenous hydration for 12 hours before and after coronary angiography, whereas patients in the control group received intravenous hydration. Serum creatinine (SCr), blood urea nitrogen (BUN) and uric acid were measured before contrast exposure and at 48 hours. CIN was defined as an increase of 25% in serum creatinine (SCr) or >0.5 mg/dl 48 hours after contrast administration. Results: CIN occurred in 11 out of 70 (7.9%) patients in the control group and in 8 out of 70 (5.7%) patients in the allopurinol group. There was no significant difference in the incidence of CIN between the two groups at 48 hours after administering the radiocontrast agent (p = 0.459). However, there were significant differences between the two groups in SCr, BUN, uric acid, and eGFR 48 hours after radiocontrast administration (p < 0.05). Conclusion: Our findings revealed that allopurinol had no substantial efficacy over hydration protocol in high-risk patients for the development of CIN.

Keywords: contrast-induced nephropathy, allopurinol, coronary angiography, contrast agent

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6314 Study of Contrast Induced Nephropathy in Patients Undergoing Cardiac Catheterization: Upper Egypt Experience

Authors: Ali Kassem, Sharf Eldeen-Shazly, Alshemaa Lotfy

Abstract:

Introduction: Contrast-induced nephropathy (CIN) has been the third leading cause of hospital-acquired renal failure. Patients with cardiac diseases are particularly at risk especially with repeated injections of contrast media. CIN is generally defined as an increase in serum creatinine concentration of > 0.5 mg/dL or 25% above baseline within 48 hours after contrast administration. Aim of work: To examine the frequency of CIN for patients undergoing cardiac catheterization at Sohag University Hospital (Upper Egypt) and to identify possible risk factors for CIN in these patients. Material and methods: The study included 104 patients with mean age 56.11 ±10.03, 64(61.5%) are males while 40(38.5%) are females. 44(42.3%) patients are diabetics, 43(41%) patients are hypertensive, 6(5.7%) patients have congestive heart failure, 69(66.3%) patients on statins, 74 (71.2 %) are on ACEIs or ARBs, 19(15.4%) are on metformin, 6 (5.8%) are on NSAIDs, 30(28.8%) are on diuretics. RESULTS: Patients were classified at the end of the study into two groups: Group A: Included 91 patients who did not develop CIN. Group B: Included 13 patients who developed CIN, of which serum creatinine raised > 0.5mg/dl in 6 patients and raised > 25% from the baseline after the procedure in 13 patients. The overall incidence of CIN was 12.5%. CIN increased with older age. There was an increase in the incidence of CIN in diabetic versus non-diabetic patients (20.5% and 6.7%) respectively. (p< 0.03). There was a highly significant increase in the incidence of CIN in patients with CHF versus those without CHF (100% and 71%) respectively, (P<0001). Patients on diuretics showed a significant increase in the incidence of CIN representing 61.5% of all patients who developed CIN. Conclusion: Older patients, diabetic patients, patients with CHF and patients on diuretics have higher risk of developing CIN during coronary catheterization and should receive reno-protective measures before contrast exposure.

Keywords: cardiac diseases, contrast-induced nephropathy, coronary catheterization, CIN

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6313 Adaptive Cooperative Scheme Considering the User Location

Authors: Bit-Na Kwon, Hyun-Jee Yang, Dong-Hyun Ha, Hyoung-Kyu Song

Abstract:

In this paper, an adaptive cooperative scheme in the cell edge is proposed. The proposed scheme considers the location of a user and applies the suitable cooperative scheme. In cellular systems, the performance of communication is degraded if the user is located in the cell edge. In conventional scheme, two base stations are used in order to obtain diversity gain. However, the performance of communication is not sufficiently improved since the distance between each base station and a user is still distant. Therefore, we propose a scheme that the relays are used and the cooperative scheme is adaptively applied according to the user location. Through simulation results, it is confirmed that the proposed scheme has better performance than the conventional scheme.

Keywords: adaptive transmission, cooperative communication, diversity gain, OFDM

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6312 Design of Reconfigurable Fixed-Point LMS Adaptive FIR Filter

Authors: S. Padmapriya, V. Lakshmi Prabha

Abstract:

In this paper, an efficient reconfigurable fixed-point Least Mean Square Adaptive FIR filter is proposed. The proposed architecture has two methods of operation: one is area efficient design and the other is optimized power. Pipelining of the adder blocks and partial product generator are used to achieve low area and reversible logic is used to obtain low power design. Depending upon the input samples and filter coefficients, one of the techniques is chosen. Least-Mean-Square adaptation is performed to update the weights. The architecture is coded using Verilog and synthesized in cadence encounter 0.18μm technology. The synthesized results show that the area reduction ratio of the proposed when compared with conventional technique is about 1.2%.

Keywords: adaptive filter, carry select adder, least mean square algorithm, reversible logic

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6311 Theoretical Approach and Proof of Concept Implementation of Adaptive Partition Scheduling Module for Linux

Authors: Desislav Andreev, Veselin Stanev

Abstract:

Linux operating system continues to gain popularity with every passed year. This is due to its open-source license and a great number of distributions, covering users’ needs. At first glance it seems that Linux can be integrated in every type of systems – it is already present in personal computers, smartphones and even in some embedded systems like Raspberry Pi. However, Linux still does not meet the performance and security requirements to run effectively on a real-time system. Real-time systems are very time-restricted – their processes have to execute and finish at strict time intervals. The Completely Fair Scheduler present in Linux does not have such scheduling capabilities and it is not able to ensure that critical-time processes will execute on time. One of the ways to solve this problem is implementing an Adaptive Partition Scheduler solution similar to that present in QNX Neutrino operating system. This type of scheduling divides the CPU in multiple adaptive partitions where each partition holds a percentage of CPU usage called budget, which allows optimal usage of the CPU resources and also provides protection against cyber attacks such as Denial of Service. This approach will also benefit systems, where functional safety is highly demanded, such as the instrumental clusters in the Automotive industry. The purpose of this paper is to present a concept of Adaptive Partition Scheduler designed for Linux-based operating systems.

Keywords: adaptive partitions, Linux kernel modules, real-time systems, scheduling

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6310 Self-Tuning Dead-Beat PD Controller for Pitch Angle Control of a Bench-Top Helicopter

Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

Abstract:

This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

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6309 Adaptive Control of Magnetorheological Damper Using Duffing-Like Model

Authors: Hung-Jiun Chi, Cheng-En Tsai, Jia-Ying Tu

Abstract:

Semi-active control of Magnetorheological (MR) dampers for vibration reduction of structural systems has received considerable attention in civil and earthquake engineering, because the effective stiffness and damping properties of MR fluid can change in a very short time in reaction to external loading, requiring only a low level of power. However, the inherent nonlinear dynamics of hysteresis raise challenges in the modeling and control processes. In order to control the MR damper, an innovative Duffing-like equation is proposed to approximate the hysteresis dynamics in a deterministic and systematic manner than previously has been possible. Then, the model-reference adaptive control technique based on the Duffing-like model and the Lyapunov method is discussed. Parameter identification work with experimental data is presented to show the effectiveness of the Duffing-like model. In addition, simulation results show that the resulting adaptive gains enable the MR damper force to track the desired response of the reference model satisfactorily, verifying the effectiveness of the proposed modeling and control techniques.

Keywords: magnetorheological damper, duffing equation, model-reference adaptive control, Lyapunov function, hysteresis

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6308 Cessna Citation X Performances Improvement by an Adaptive Winglet during the Cruise Flight

Authors: Marine Segui, Simon Bezin, Ruxandra Mihaela Botez

Abstract:

As part of a ‘Morphing-Wing’ idea, this study consists of measuring how a winglet, which is able to change its shape during the flight, is efficient. Conventionally, winglets are fixed-vertical platforms at the wingtips, optimized for a cruise condition that the airplane should use most of the time. However, during a cruise, an airplane flies through a lot of cruise conditions corresponding to altitudes variations from 30,000 to 45,000 ft. The fixed winglets are not optimized for these variations, and consequently, they are supposed to generate some drag, and thus to deteriorate aircraft fuel consumption. This research assumes that it exists a winglet position that reduces the fuel consumption for each cruise condition. In this way, the methodology aims to find these optimal winglet positions, and to further simulate, and thus estimate the fuel consumption of an aircraft wearing this type of adaptive winglet during several cruise conditions. The adaptive winglet is assumed to have degrees of freedom given by the various changes of following surfaces: the tip chord, the sweep and the dihedral angles. Finally, results obtained during cruise simulations are presented in this paper. These results show that an adaptive winglet can reduce, thus improve up to 2.12% the fuel consumption of an aircraft during a cruise.

Keywords: aerodynamic, Cessna, Citation X, optimization, winglet

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6307 Image Encryption Using Eureqa to Generate an Automated Mathematical Key

Authors: Halima Adel Halim Shnishah, David Mulvaney

Abstract:

Applying traditional symmetric cryptography algorithms while computing encryption and decryption provides immunity to secret keys against different attacks. One of the popular techniques generating automated secret keys is evolutionary computing by using Eureqa API tool, which got attention in 2013. In this paper, we are generating automated secret keys for image encryption and decryption using Eureqa API (tool which is used in evolutionary computing technique). Eureqa API models pseudo-random input data obtained from a suitable source to generate secret keys. The validation of generated secret keys is investigated by performing various statistical tests (histogram, chi-square, correlation of two adjacent pixels, correlation between original and encrypted images, entropy and key sensitivity). Experimental results obtained from methods including histogram analysis, correlation coefficient, entropy and key sensitivity, show that the proposed image encryption algorithms are secure and reliable, with the potential to be adapted for secure image communication applications.

Keywords: image encryption algorithms, Eureqa, statistical measurements, automated key generation

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6306 Particle Swarm Optimization Based Vibration Suppression of a Piezoelectric Actuator Using Adaptive Fuzzy Sliding Mode Controller

Authors: Jin-Siang Shaw, Patricia Moya Caceres, Sheng-Xiang Xu

Abstract:

This paper aims to integrate the particle swarm optimization (PSO) method with the adaptive fuzzy sliding mode controller (AFSMC) to achieve vibration attenuation in a piezoelectric actuator subject to base excitation. The piezoelectric actuator is a complicated system made of ferroelectric materials and its performance can be affected by nonlinear hysteresis loop and unknown system parameters and external disturbances. In this study, an adaptive fuzzy sliding mode controller is proposed for the vibration control of the system, because the fuzzy sliding mode controller is designed to tackle the unknown parameters and external disturbance of the system, and the adaptive algorithm is aimed for fine-tuning this controller for error converging purpose. Particle swarm optimization method is used in order to find the optimal controller parameters for the piezoelectric actuator. PSO starts with a population of random possible solutions, called particles. The particles move through the search space with dynamically adjusted speed and direction that change according to their historical behavior, allowing the values of the particles to quickly converge towards the best solutions for the proposed problem. In this paper, an initial set of controller parameters is applied to the piezoelectric actuator which is subject to resonant base excitation with large amplitude vibration. The resulting vibration suppression is about 50%. Then PSO is applied to search for an optimal controller in the neighborhood of this initial controller. The performance of the optimal fuzzy sliding mode controller found by PSO indeed improves up to 97.8% vibration attenuation. Finally, adaptive version of fuzzy sliding mode controller is adopted for further improving vibration suppression. Simulation result verifies the performance of the adaptive controller with 99.98% vibration reduction. Namely the vibration of the piezoelectric actuator subject to resonant base excitation can be completely annihilated using this PSO based adaptive fuzzy sliding mode controller.

Keywords: adaptive fuzzy sliding mode controller, particle swarm optimization, piezoelectric actuator, vibration suppression

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6305 Weighted Rank Regression with Adaptive Penalty Function

Authors: Kang-Mo Jung

Abstract:

The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

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6304 Enhancement of Underwater Haze Image with Edge Reveal Using Pixel Normalization

Authors: M. Dhana Lakshmi, S. Sakthivel Murugan

Abstract:

As light passes from source to observer in the water medium, it is scattered by the suspended particulate matter. This scattering effect will plague the captured images with non-uniform illumination, blurring details, halo artefacts, weak edges, etc. To overcome this, pixel normalization with an Amended Unsharp Mask (AUM) filter is proposed to enhance the degraded image. To validate the robustness of the proposed technique irrespective of atmospheric light, the considered datasets are collected on dual locations. For those images, the maxima and minima pixel intensity value is computed and normalized; then the AUM filter is applied to strengthen the blurred edges. Finally, the enhanced image is obtained with good illumination and contrast. Thus, the proposed technique removes the effect of scattering called de-hazing and restores the perceptual information with enhanced edge detail. Both qualitative and quantitative analyses are done on considering the standard non-reference metric called underwater image sharpness measure (UISM), and underwater image quality measure (UIQM) is used to measure color, sharpness, and contrast for both of the location images. It is observed that the proposed technique has shown overwhelming performance compared to other deep-based enhancement networks and traditional techniques in an adaptive manner.

Keywords: underwater drone imagery, pixel normalization, thresholding, masking, unsharp mask filter

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6303 Image Denoising Using Spatial Adaptive Mask Filter for Medical Images

Authors: R. Sumalatha, M. V. Subramanyam

Abstract:

In medical image processing the quality of the image is degraded in the presence of noise. Especially in ultra sound imaging and Magnetic resonance imaging the data was corrupted by signal dependent noise known as salt and pepper noise. Removal of noise from the medical images is a critical issue for researchers. In this paper, a new type of technique Adaptive Spatial Mask Filter (ASMF) has been proposed. The proposed filter is used to increase the quality of MRI and ultra sound images. Experimental results show that the proposed filter outperforms the implementation of mean, median, adaptive median filters in terms of MSE and PSNR.

Keywords: salt and pepper noise, ASMF, PSNR, MSE

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6302 Research on Robot Adaptive Polishing Control Technology

Authors: Yi Ming Zhang, Zhan Xi Wang, Hang Chen, Gang Wang

Abstract:

Manual polishing has problems such as high labor intensity, low production efficiency and difficulty in guaranteeing the consistency of polishing quality. It is more and more necessary to replace manual polishing with robot polishing. Polishing force directly affects the quality of polishing, so accurate tracking and control of polishing force is one of the most important conditions for improving the accuracy of robot polishing. The traditional force control strategy is difficult to adapt to the strong coupling of force control and position control during the robot polishing process. Therefore, based on the analysis of force-based impedance control and position-based impedance control, this paper proposed a new type of adaptive controller. Based on force feedback control of active compliance control, the controller can adaptively estimate the stiffness and position of the external environment and eliminate the steady-state force error produced by traditional impedance control. The simulation results of the model shows that the adaptive controller has good adaptability to changing environmental positions and environmental stiffness, and can accurately track and control polishing force.

Keywords: robot polishing, force feedback, impedance control, adaptive control

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6301 Gray Level Image Encryption

Authors: Roza Afarin, Saeed Mozaffari

Abstract:

The aim of this paper is image encryption using Genetic Algorithm (GA). The proposed encryption method consists of two phases. In modification phase, pixels locations are altered to reduce correlation among adjacent pixels. Then, pixels values are changed in the diffusion phase to encrypt the input image. Both phases are performed by GA with binary chromosomes. For modification phase, these binary patterns are generated by Local Binary Pattern (LBP) operator while for diffusion phase binary chromosomes are obtained by Bit Plane Slicing (BPS). Initial population in GA includes rows and columns of the input image. Instead of subjective selection of parents from this initial population, a random generator with predefined key is utilized. It is necessary to decrypt the coded image and reconstruct the initial input image. Fitness function is defined as average of transition from 0 to 1 in LBP image and histogram uniformity in modification and diffusion phases, respectively. Randomness of the encrypted image is measured by entropy, correlation coefficients and histogram analysis. Experimental results show that the proposed method is fast enough and can be used effectively for image encryption.

Keywords: correlation coefficients, genetic algorithm, image encryption, image entropy

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6300 Contrast Enhanced Magnetic Resonance Angiography in Rats with Gadobenate Dimeglumine at 3T

Authors: Jao Jo-Chi, Chen Yen-Ku, Jaw Twei-Shiun, Chen Po-Chou

Abstract:

This study aimed to investigate the magnetic resonance (MR) signal enhancement ratio (ER) of contrast-enhanced MR angiography (CE-MRA) in normal rats with gadobenate dimeglumine (Gd-BOPTA) using a clinical 3T scanner and an extremity coil. The relaxivities of Gd-BOPTA with saline only and with 4.5 % human serum albumin (HSA) were also measured. Compared with Gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA), Gd-BOPTA had higher relaxivities. The maximum ER of Aorta (ERa), kidney, liver and muscle with Gd-BOPTA were higher than those with Gd-DTPA. The maximum ERa appeared at 1.2 min and decayed to half at 10 min after Gd-BOPTA injection. This information is helpful for the design of CE-MRA study of rats.

Keywords: contrast-enhanced magnetic resonance angiography, Gd-BOPTA, Gd-DTPA, rat

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6299 Reduction of Impulsive Noise in OFDM System using Adaptive Algorithm

Authors: Alina Mirza, Sumrin M. Kabir, Shahzad A. Sheikh

Abstract:

The Orthogonal Frequency Division Multiplexing (OFDM) with high data rate, high spectral efficiency and its ability to mitigate the effects of multipath makes them most suitable in wireless application. Impulsive noise distorts the OFDM transmission and therefore methods must be investigated to suppress this noise. In this paper, a State Space Recursive Least Square (SSRLS) algorithm based adaptive impulsive noise suppressor for OFDM communication system is proposed. And a comparison with another adaptive algorithm is conducted. The state space model-dependent recursive parameters of proposed scheme enables to achieve steady state mean squared error (MSE), low bit error rate (BER), and faster convergence than that of some of existing algorithm.

Keywords: OFDM, impulsive noise, SSRLS, BER

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6298 Application of Adaptive Architecture in Building Technologies: A Case Study of Neuhoff Site in Nashville, Tennessee

Authors: Shohreh Moshiri, Hossein Alimohammadi

Abstract:

Building construction has a great impact on climate change. Adaptive design strategies were developed to provide new life and purpose to old buildings and create new environments with economic benefits to meet resident needs. The role of smart material systems is undeniable in providing adaptivity of the architectural environments and their effects on creating better adaptive building environments. In this research, a case study named Neuhoff site located near Cumberland River in the Germantown neighborhood in the city of Nashville, Tennessee, was considered. This building in the early 1920s was constructed as a meat-packing facility and then served as a mixed-use space; however, New City has partnered with world-class architects to reinvent this site to be changed to mixed-use waterfront development. The future office space will be designed with LEED certification as a goal. Environmentally friendly sensitive materials and designs will offer for all adaptive reuse of the building. The smart materials and their applications, especially in the field of building technology and architecture, were emphasized in providing a renovation plan for the site. The advantages and qualities of smart material systems were targeted to explore in this research on the field of architecture. Also, this research helps to understand better the effects of smart material systems on the construction and design processes, exploration of the way to make architecture with better adaptive characteristics, plus provide optimal environmental situations for the users, which reflect on the climatic, structural, and architectural performances.

Keywords: adaptive architecture, building technology, case study, smart material systems

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