Search results for: motion detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4543

Search results for: motion detection

4423 The Effect of Scapular Stabilization Exercises on Chronic Neck Pain

Authors: Amany Mohamed, Alaa Balbaa, Magdoline Mishel

Abstract:

Background: Pain in the neck or scapular region is one of the most frequent symptoms in cervical radiculopathy, which is commonly caused by degenerative process in the spine. Purpose: To determine the effect of scapular stabilization exercises in the treatment of chronic neck pain regarding pain and disability and limitation in the range of motion. Patients and Methods: Thirty male and female patients with chronic neck pain were involved. Aged between 30-50 years old. They were randomly assigned into two groups. In group (A), patients received physical therapy program in the form of infrared, transcutaneous electrical nerve stimulation (TENS), Stretching and cervical stabilization exercises. In group (B), patients received scapular stabilization exercises in addition to the same physical therapy program. Treatment was given 3 times a week for 4 weeks. Range of motion of the cervical spine, range of motion of the scapula, neck pain and disability were assessed before and after treatment. Results: There was significant improvement in both groups (A and B) in cervical range of motion, pain and disability. Group (B) showed more significant improvement than group (A) in cervical range of motion and pain and disability. There was no significant improvement in both groups in scapular range of motion. Conclusion: Scapular stabilization exercises should be used as an integral part in the rehabilitation program

Keywords: Neck pain, neck stabilization exercise, scapular stabilization exercise, chronic neck pain

Procedia PDF Downloads 268
4422 Advanced Mouse Cursor Control and Speech Recognition Module

Authors: Prasad Kalagura, B. Veeresh kumar

Abstract:

We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

Procedia PDF Downloads 549
4421 Covariance of the Queue Process Fed by Isonormal Gaussian Input Process

Authors: Samaneh Rahimirshnani, Hossein Jafari

Abstract:

In this paper, we consider fluid queueing processes fed by an isonormal Gaussian process. We study the correlation structure of the queueing process and the rate of convergence of the running supremum in the queueing process. The Malliavin calculus techniques are applied to obtain relations that show the workload process inherits the dependence properties of the input process. As examples, we consider two isonormal Gaussian processes, the sub-fractional Brownian motion (SFBM) and the fractional Brownian motion (FBM). For these examples, we obtain upper bounds for the covariance function of the queueing process and its rate of convergence to zero. We also discover that the rate of convergence of the queueing process is related to the structure of the covariance function of the input process.

Keywords: queue length process, Malliavin calculus, covariance function, fractional Brownian motion, sub-fractional Brownian motion

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4420 Use of Hierarchical Temporal Memory Algorithm in Heart Attack Detection

Authors: Tesnim Charrad, Kaouther Nouira, Ahmed Ferchichi

Abstract:

In order to reduce the number of deaths due to heart problems, we propose the use of Hierarchical Temporal Memory Algorithm (HTM) which is a real time anomaly detection algorithm. HTM is a cortical learning algorithm based on neocortex used for anomaly detection. In other words, it is based on a conceptual theory of how the human brain can work. It is powerful in predicting unusual patterns, anomaly detection and classification. In this paper, HTM have been implemented and tested on ECG datasets in order to detect cardiac anomalies. Experiments showed good performance in terms of specificity, sensitivity and execution time.

Keywords: cardiac anomalies, ECG, HTM, real time anomaly detection

Procedia PDF Downloads 188
4419 A Novel Combustion Engine, Design and Modeling

Authors: M. A. Effati, M. R. Hojjati, M. Razmdideh

Abstract:

Nowadays, engine developments have focused on internal combustion engine design call for increased engine power, reduced engine size and improved fuel economy, simultaneously. In this paper, a novel design for combustion engine is proposed. Two combustion chambers were designed in two sides of cylinder. Piston was designed in a way that two sides of piston would transfer heat energy due to combustion to linear motion. This motion would convert to rotary motion through the designed mechanism connected to connecting rod. Connecting rod operation was analyzed to evaluate applied stress in 3000, 4500 and 6000 rpm. Boundary conditions including generated pressure in each side of cylinder in these 3 situations was calculated.

Keywords: combustion engine, design, finite element method, modeling

Procedia PDF Downloads 476
4418 Design of a New Architecture of IDS Called BiIDS (IDS Based on Two Principles of Detection)

Authors: Yousef Farhaoui

Abstract:

An IDS is a tool which is used to improve the level of security.In this paper we present different architectures of IDS. We will also discuss measures that define the effectiveness of IDS and the very recent works of standardization and homogenization of IDS. At the end, we propose a new model of IDS called BiIDS (IDS Based on the two principles of detection).

Keywords: intrusion detection, architectures, characteristic, tools, security

Procedia PDF Downloads 434
4417 Proposed Anticipating Learning Classifier System for Cloud Intrusion Detection (ALCS-CID)

Authors: Wafa' Slaibi Alsharafat

Abstract:

Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

Procedia PDF Downloads 446
4416 Object Tracking in Motion Blurred Images with Adaptive Mean Shift and Wavelet Feature

Authors: Iman Iraei, Mina Sharifi

Abstract:

A method for object tracking in motion blurred images is proposed in this article. This paper shows that object tracking could be improved with this approach. We use mean shift algorithm to track different objects as a main tracker. But, the problem is that mean shift could not track the selected object accurately in blurred scenes. So, for better tracking result, and increasing the accuracy of tracking, wavelet transform is used. We use a feature named as blur extent, which could help us to get better results in tracking. For calculating of this feature, we should use Harr wavelet. We can look at this matter from two different angles which lead to determine whether an image is blurred or not and to what extent an image is blur. In fact, this feature left an impact on the covariance matrix of mean shift algorithm and cause to better performance of tracking. This method has been concentrated mostly on motion blur parameter. transform. The results reveal the ability of our method in order to reach more accurately tracking.

Keywords: mean shift, object tracking, blur extent, wavelet transform, motion blur

Procedia PDF Downloads 182
4415 Crater Detection Using PCA from Captured CMOS Camera Data

Authors: Tatsuya Takino, Izuru Nomura, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of detecting the craters from the image of the lunar surface. This proposal assumes that it is applied to SLIM (Smart Lander for Investigating Moon) working group aiming at the pinpoint landing on the lunar surface and investigating scientific research. It is difficult to equip and use high-performance computers for the small space probe. So, it is necessary to use a small computer with an exclusive hardware such as FPGA. We have studied the crater detection using principal component analysis (PCA), In this paper, We implement detection algorithm into the FPGA, and the detection is performed on the data that was captured from the CMOS camera.

Keywords: crater detection, PCA, FPGA, image processing

Procedia PDF Downloads 516
4414 On-Road Text Detection Platform for Driver Assistance Systems

Authors: Guezouli Larbi, Belkacem Soundes

Abstract:

The automation of the text detection process can help the human in his driving task. Its application can be very useful to help drivers to have more information about their environment by facilitating the reading of road signs such as directional signs, events, stores, etc. In this paper, a system consisting of two stages has been proposed. In the first one, we used pseudo-Zernike moments to pinpoint areas of the image that may contain text. The architecture of this part is based on three main steps, region of interest (ROI) detection, text localization, and non-text region filtering. Then, in the second step, we present a convolutional neural network architecture (On-Road Text Detection Network - ORTDN) which is considered a classification phase. The results show that the proposed framework achieved ≈ 35 fps and an mAP of ≈ 90%, thus a low computational time with competitive accuracy.

Keywords: text detection, CNN, PZM, deep learning

Procedia PDF Downloads 56
4413 Are There Any Positive Effects of Motivational Interviewing on Motion Sickness?

Authors: Unal Demirtas, Mehmet Ergin Dipcin, Mehmet Cetin

Abstract:

Background: Applied to student candidates prior to entering the air force academy, under the name of Cadet selection flights and executed as 7-8 sorties under the surveillance of flight instructors, this training is mainly towards appraising students’ characteristics of flying ability. All pilot cadets are gone through physical examination before cadet selection flight in a military hospital. Some cadets may show motion sickness symptoms during this flights. The most common symptoms: Nausea, vomiting, vertigo, headache, anxiety, paresthaesia, asthenia, muscle contraction and excitement. These cadets are examined by flight surgeon, after this flight surgeon and psychologist have an motivational interviewing with these cadets. Method: In this study, we have applied a survey that we question the severity of the symptom to the candidates that have motion sickness after the first sortie. We have questioned the candidate who had a motivational interviewing by the psychologist after the treatment of the flight surgeon that whether the candidate relived the complaints that he has at the previous sortie after the second sortie and whether there is decrease or increase in the severity of the complaints compared to the previous flight. Findings: 15 candidates have applied for the flight surgeon with at least one of the motion sickness symptoms. 11 of the 15 candidates showing motion sickness symptoms after the first flight expressed that their complaints are decreased after the motivational interviewing and 4 of the candidates stated that there are no changes in their complaints. The frequently expressed complaints are nausea, vertigo, headache, exhaustion and vomiting respectively. 7 out of 15 candidates expressed that they have same kind of complains in bus, ship etc. Conclusion: It is observed in our study that only conducting motivational interviewing with the candidates without any organic disorders without giving any drugs has a positive effect on the candidates in terms of motion sickness.

Keywords: aeromedicine, candidate, motion sickness, motivational interviewing, pilot

Procedia PDF Downloads 446
4412 A Paper Based Sensor for Mercury Ion Detection

Authors: Emine G. Cansu Ergun

Abstract:

Conjugated system based sensors for selective detection of metal ions have been taking attention during last two decades. Fluorescent sensors are the promising candidates for ion detection due to their high selectivity towards metal ions, and rapid response times. Detection of mercury in an environmenet is important since mercury is a toxic element for human. Beyond the maximum allowable limit, mercury may cause serious problems in human health by spreading into the atmosphere, water and the food chain. In this study, a quinoxaline and 3,4-ethylenedioxy thiophene based donor-acceptor-donor type conjugated molecule used as a fluorescent sensor for detecting the mercury ion in aqueous medium. Among other various cations, existence of mercury resulted in a full quenching of the fluorescence signal. Then, a paper based sensor is constructed and used for mercury detection. As a result it is concluded that the offering sensor is a good candidate for selective mercury detection in aqueous media both in solution and paper based forms.

Keywords: Conjugated molecules , fluorescence quenching, metal ion detection , sensors

Procedia PDF Downloads 129
4411 Automated Pothole Detection Using Convolution Neural Networks and 3D Reconstruction Using Stereovision

Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

Abstract:

Potholes are a severe threat to road safety and a major contributing factor towards road distress. In the Indian context, they are a major road hazard. Timely detection of potholes and subsequent repair can prevent the roads from deteriorating. To facilitate the roadway authorities in the timely detection and repair of potholes, we propose a pothole detection methodology using convolutional neural networks. The YOLOv3 model is used as it is fast and accurate in comparison to other state-of-the-art models. You only look once v3 (YOLOv3) is a state-of-the-art, real-time object detection system that features multi-scale detection. A mean average precision(mAP) of 73% was obtained on a training dataset of 200 images. The dataset was then increased to 500 images, resulting in an increase in mAP. We further calculated the depth of the potholes using stereoscopic vision by reconstruction of 3D potholes. This enables calculating pothole volume, its extent, which can then be used to evaluate the pothole severity as low, moderate, high.

Keywords: CNN, pothole detection, pothole severity, YOLO, stereovision

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4410 Study of Effects of 3D Semi-Spheriacl Basin-Shape-Ratio on the Frequency Content and Spectral Amplitudes of the Basin-Generated Surface Waves

Authors: Kamal, J. P. Narayan

Abstract:

In the present wok the effects of basin-shape-ratio on the frequency content and spectral amplitudes of the basin-generated surface waves and the associated spatial variation of ground motion amplification and differential ground motion in a 3D semi-spherical basin has been studied. A recently developed 3D fourth-order spatial accurate time-domain finite-difference (FD) algorithm based on the parsimonious staggered-grid approximation of the 3D viscoelastic wave equations was used to estimate seismic responses. The simulated results demonstrated the increase of both the frequency content and the spectral amplitudes of the basin-generated surface waves and the duration of ground motion in the basin with the increase of shape-ratio of semi-spherical basin. An increase of the average spectral amplification (ASA), differential ground motion (DGM) and the average aggravation factor (AAF) towards the centre of the semi-spherical basin was obtained.

Keywords: 3D viscoelastic simulation, basin-generated surface waves, basin-shape-ratio effects, average spectral amplification, aggravation factors and differential ground motion

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4409 Cross Site Scripting (XSS) Attack and Automatic Detection Technology Research

Authors: Tao Feng, Wei-Wei Zhang, Chang-Ming Ding

Abstract:

Cross-site scripting (XSS) is one of the most popular WEB Attacking methods at present, and also one of the most risky web attacks. Because of the population of JavaScript, the scene of the cross site scripting attack is also gradually expanded. However, since the web application developers tend to only focus on functional testing and lack the awareness of the XSS, which has made the on-line web projects exist many XSS vulnerabilities. In this paper, different various techniques of XSS attack are analyzed, and a method automatically to detect it is proposed. It is easy to check the results of vulnerability detection when running it as a plug-in.

Keywords: XSS, no target attack platform, automatic detection,XSS detection

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4408 Incorporating Multiple Supervised Learning Algorithms for Effective Intrusion Detection

Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

Abstract:

As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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4407 Highly Accurate Target Motion Compensation Using Entropy Function Minimization

Authors: Amin Aghatabar Roodbary, Mohammad Hassan Bastani

Abstract:

One of the defects of stepped frequency radar systems is their sensitivity to target motion. In such systems, target motion causes range cell shift, false peaks, Signal to Noise Ratio (SNR) reduction and range profile spreading because of power spectrum interference of each range cell in adjacent range cells which induces distortion in High Resolution Range Profile (HRRP) and disrupt target recognition process. Thus Target Motion Parameters (TMPs) effects compensation should be employed. In this paper, such a method for estimating TMPs (velocity and acceleration) and consequently eliminating or suppressing the unwanted effects on HRRP based on entropy minimization has been proposed. This method is carried out in two major steps: in the first step, a discrete search method has been utilized over the whole acceleration-velocity lattice network, in a specific interval seeking to find a less-accurate minimum point of the entropy function. Then in the second step, a 1-D search over velocity is done in locus of the minimum for several constant acceleration lines, in order to enhance the accuracy of the minimum point found in the first step. The provided simulation results demonstrate the effectiveness of the proposed method.

Keywords: automatic target recognition (ATR), high resolution range profile (HRRP), motion compensation, stepped frequency waveform technique (SFW), target motion parameters (TMPs)

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4406 Music Note Detection and Dictionary Generation from Music Sheet Using Image Processing Techniques

Authors: Muhammad Ammar, Talha Ali, Abdul Basit, Bakhtawar Rajput, Zobia Sohail

Abstract:

Music note detection is an area of study for the past few years and has its own influence in music file generation from sheet music. We proposed a method to detect music notes on sheet music using basic thresholding and blob detection. Subsequently, we created a notes dictionary using a semi-supervised learning approach. After notes detection, for each test image, the new symbols are added to the dictionary. This makes the notes detection semi-automatic. The experiments are done on images from a dataset and also on the captured images. The developed approach showed almost 100% accuracy on the dataset images, whereas varying results have been seen on captured images.

Keywords: music note, sheet music, optical music recognition, blob detection, thresholding, dictionary generation

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4405 Efficient Iterative V-BLAST Detection Technique in Wireless Communication System

Authors: Hwan-Jun Choi, Sung-Bok Choi, Hyoung-Kyu Song

Abstract:

Recently, among the MIMO-OFDM detection techniques, a lot of papers suggested V-BLAST scheme which can achieve high data rate. Therefore, the signal detection of MIMOOFDM system is important issue. In this paper, efficient iterative VBLAST detection technique is proposed in wireless communication system. The proposed scheme adjusts the number of candidate symbol and iterative scheme based on channel state. According to the simulation result, the proposed scheme has better BER performance than conventional schemes and similar BER performance of the QRD-M with iterative scheme. Moreover complexity of proposed scheme has 50.6 % less than complexity of QRD-M detection with iterative scheme. Therefore the proposed detection scheme can be efficiently used in wireless communication.

Keywords: MIMO-OFDM, V-BLAST, QR-decomposition, QRDM, DFE, iterative scheme, channel condition

Procedia PDF Downloads 502
4404 Combination between Intrusion Systems and Honeypots

Authors: Majed Sanan, Mohammad Rammal, Wassim Rammal

Abstract:

Today, security is a major concern. Intrusion Detection, Prevention Systems and Honeypot can be used to moderate attacks. Many researchers have proposed to use many IDSs ((Intrusion Detection System) time to time. Some of these IDS’s combine their features of two or more IDSs which are called Hybrid Intrusion Detection Systems. Most of the researchers combine the features of Signature based detection methodology and Anomaly based detection methodology. For a signature based IDS, if an attacker attacks slowly and in organized way, the attack may go undetected through the IDS, as signatures include factors based on duration of the events but the actions of attacker do not match. Sometimes, for an unknown attack there is no signature updated or an attacker attack in the mean time when the database is updating. Thus, signature-based IDS fail to detect unknown attacks. Anomaly based IDS suffer from many false-positive readings. So there is a need to hybridize those IDS which can overcome the shortcomings of each other. In this paper we propose a new approach to IDS (Intrusion Detection System) which is more efficient than the traditional IDS (Intrusion Detection System). The IDS is based on Honeypot Technology and Anomaly based Detection Methodology. We have designed Architecture for the IDS in a packet tracer and then implemented it in real time. We have discussed experimental results performed: both the Honeypot and Anomaly based IDS have some shortcomings but if we hybridized these two technologies, the newly proposed Hybrid Intrusion Detection System (HIDS) is capable enough to overcome these shortcomings with much enhanced performance. In this paper, we present a modified Hybrid Intrusion Detection System (HIDS) that combines the positive features of two different detection methodologies - Honeypot methodology and anomaly based intrusion detection methodology. In the experiment, we ran both the Intrusion Detection System individually first and then together and recorded the data from time to time. From the data we can conclude that the resulting IDS are much better in detecting intrusions from the existing IDSs.

Keywords: security, intrusion detection, intrusion prevention, honeypot, anomaly-based detection, signature-based detection, cloud computing, kfsensor

Procedia PDF Downloads 343
4403 Mosaic Augmentation: Insights and Limitations

Authors: Olivia A. Kjorlien, Maryam Asghari, Farshid Alizadeh-Shabdiz

Abstract:

The goal of this paper is to investigate the impact of mosaic augmentation on the performance of object detection solutions. To carry out the study, YOLOv4 and YOLOv4-Tiny models have been selected, which are popular, advanced object detection models. These models are also representatives of two classes of complex and simple models. The study also has been carried out on two categories of objects, simple and complex. For this study, YOLOv4 and YOLOv4 Tiny are trained with and without mosaic augmentation for two sets of objects. While mosaic augmentation improves the performance of simple object detection, it deteriorates the performance of complex object detection, specifically having the largest negative impact on the false positive rate in a complex object detection case.

Keywords: accuracy, false positives, mosaic augmentation, object detection, YOLOV4, YOLOV4-Tiny

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4402 Contributions at the Define of the Vortex Plane Cyclic Motion

Authors: Petre Stan, Marinica Stan

Abstract:

In this paper, a new way to define the vortex plane cyclic motion is exposed, starting from the physical cause of reacting the vortex. The Navier-Stokes equations are used in cylindrical coordinates for viscous fluids in laminar motion, and are integrated in case of a infinite long revolving cylinder which rotates around a pintle in a viscous fluid that occupies the entire space up to infinite. In this way, a revolving field of velocities in fluid is obtained, having the shape of a vortex in which the intensity is obtained objectively, being given by the physical phenomenon that generates this vortex.

Keywords: cylindrical coordinates, Navier-Stokes equations, viscous fluid, vortex plane

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4401 Motion Capture Based Wizard of Oz Technique for Humanoid Robot

Authors: Rafal Stegierski, Krzysztof Dmitruk

Abstract:

The paper focuses on robotic tele-presence system build around humanoid robot operated with controller-less Wizard of Oz technique. Proposed solution gives possibility to quick start acting as a operator with short, if any, initial training.

Keywords: robotics, motion capture, Wizard of Oz, humanoid robots, human robot interaction

Procedia PDF Downloads 447
4400 Active Islanding Detection Method Using Intelligent Controller

Authors: Kuang-Hsiung Tan, Chih-Chan Hu, Chien-Wu Lan, Shih-Sung Lin, Te-Jen Chang

Abstract:

An active islanding detection method using disturbance signal injection with intelligent controller is proposed in this study. First, a DC\AC power inverter is emulated in the distributed generator (DG) system to implement the tracking control of active power, reactive power outputs and the islanding detection. The proposed active islanding detection method is based on injecting a disturbance signal into the power inverter system through the d-axis current which leads to a frequency deviation at the terminal of the RLC load when the utility power is disconnected. Moreover, in order to improve the transient and steady-state responses of the active power and reactive power outputs of the power inverter, and to further improve the performance of the islanding detection method, two probabilistic fuzzy neural networks (PFNN) are adopted to replace the traditional proportional-integral (PI) controllers for the tracking control and the islanding detection. Furthermore, the network structure and the online learning algorithm of the PFNN are introduced in detail. Finally, the feasibility and effectiveness of the tracking control and the proposed active islanding detection method are verified with experimental results.

Keywords: distributed generators, probabilistic fuzzy neural network, islanding detection, non-detection zone

Procedia PDF Downloads 360
4399 Structural Damage Detection Using Sensors Optimally Located

Authors: Carlos Alberto Riveros, Edwin Fabián García, Javier Enrique Rivero

Abstract:

The measured data obtained from sensors in continuous monitoring of civil structures are mainly used for modal identification and damage detection. Therefore when modal identification analysis is carried out the quality in the identification of the modes will highly influence the damage detection results. It is also widely recognized that the usefulness of the measured data used for modal identification and damage detection is significantly influenced by the number and locations of sensors. The objective of this study is the numerical implementation of two widely known optimum sensor placement methods in beam-like structures

Keywords: optimum sensor placement, structural damage detection, modal identification, beam-like structures.

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4398 Boundary Motion by Curvature: Accessible Modeling of Oil Spill Evaporation/Dissipation

Authors: Gary Miller, Andriy Didenko, David Allison

Abstract:

The boundary of a region in the plane shrinks according to its curvature. A simple algorithm based upon this motion by curvature performed by a spreadsheet simulates the evaporation/dissipation behavior of oil spill boundaries.

Keywords: mathematical modeling, oil, evaporation, dissipation, boundary

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4397 Motion Planning and Posture Control of the General 3-Trailer System

Authors: K. Raghuwaiya, B. Sharma, J. Vanualailai

Abstract:

This paper presents a set of artificial potential field functions that improves upon; in general, the motion planning and posture control, with theoretically guaranteed point and posture stabilities, convergence and collision avoidance properties of the general 3-trailer system in a priori known environment. We basically design and inject two new concepts; ghost walls and the distance optimization technique (DOT) to strengthen point and posture stabilities, in the sense of Lyapunov, of our dynamical model. This new combination of techniques emerges as a convenient mechanism for obtaining feasible orientations at the target positions with an overall reduction in the complexity of the navigation laws. Simulations are provided to demonstrate the effectiveness of the controls laws.

Keywords: artificial potential fields, 3-trailer systems, motion planning, posture

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4396 An Agent-Based Modeling and Simulation of Human Muscle

Authors: Sina Saadati, Mohammadreza Razzazi

Abstract:

In this article, we have tried to present an agent-based model of human muscle. A suitable model of muscle is necessary for the analysis of mankind's movements. It can be used by clinical researchers who study the influence of motion sicknesses, like Parkinson's disease. It is also useful in the development of a prosthesis that receives the electromyography signals and generates force as a reaction. Since we have focused on computational efficiency in this research, the model can compute the calculations very fast. As far as it concerns prostheses, the model can be known as a charge-efficient method. In this paper, we are about to illustrate an agent-based model. Then, we will use it to simulate the human gait cycle. This method can also be done reversely in the analysis of gait in motion sicknesses.

Keywords: agent-based modeling and simulation, human muscle, gait cycle, motion sickness

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4395 Thermal Neutron Detection Efficiency as a Function of Film Thickness for Front and Back Irradiation Detector Devices Coated with ¹⁰B, ⁶LiF, and Pure Li Thin Films

Authors: Vedant Subhash

Abstract:

This paper discusses the physics of the detection of thermal neutrons using thin-film coated semiconductor detectors. The thermal neutron detection efficiency as a function of film thickness is calculated for the front and back irradiation detector devices coated with ¹⁰B, ⁶LiF, and pure Li thin films. The detection efficiency for back irradiation devices is 4.15% that is slightly higher than that for front irradiation detectors, 4.0% for ¹⁰B films of thickness 2.4μm. The theoretically calculated thermal neutron detection efficiency using ¹⁰B film thickness of 1.1 μm for the back irradiation device is 3.0367%, which has an offset of 0.0367% from the experimental value of 3.0%. The detection efficiency values are compared and proved consistent with the given calculations.

Keywords: detection efficiency, neutron detection, semiconductor detectors, thermal neutrons

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4394 Effect of Scarp Topography on Seismic Ground Motion

Authors: Haiping Ding, Rongchu Zhu, Zhenxia Song

Abstract:

Local irregular topography has a great impact on earthquake ground motion. For scarp topography, using numerical simulation method, the influence extent and scope of the scarp terrain on scarp's upside and downside ground motion are discussed in case of different vertical incident SV waves. The results show that: (1) The amplification factor of scarp's upside region is greater than that of the free surface, while the amplification factor of scarp's downside part is less than that of the free surface; (2) When the slope angle increases, for x component, amplification factors of the scarp upside also increase, while the downside part decrease with it. For z component, both of the upside and downside amplification factors will increase; (3) When the slope angle changes, the influence scope of scarp's downside part is almost unchanged, but for the upside part, it slightly becomes greater with the increase of slope angle; (4) Due to the existence of the scarp, the z component ground motion appears at the surface. Its amplification factor increases for larger slope angle, and the peaks of the surface responses are related with incident waves. However, the input wave has little effects on the x component amplification factors.

Keywords: scarp topography, ground motion, amplification factor, vertical incident wave

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