Search results for: graph signal processing

Authors: V. Tabrizi, A. Vali, R. GHasemi, V. Behnamgol

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In this article, a nonlinear model of an under actuated six degrees of freedom (6 DOF) quadrotor UAV is derived on the basis of the Newton-Euler formula. The derivation comprises determining equations of the motion of the quadrotor in three dimensions and approximating the actuation forces through the modeling of aerodynamic coefficients and electric motor dynamics. The robust nonlinear control strategy includes a smooth second order non-singular terminal sliding mode control which is applied to stabilizing this model. The control method is on the basis of super twisting algorithm for removing the chattering and producing smooth control signal. Also, nonsingular terminal sliding mode idea is used for introducing a nonlinear sliding variable that guarantees the finite time convergence in sliding phase. Simulation results show that the proposed algorithm is robust against uncertainty or disturbance and guarantees a fast and precise control signal.

Keywords: quadrotor UAV, nonsingular terminal sliding mode, second order sliding mode t, electronics, control, signal processing

Procedia PDF Downloads 405

Authors: Tomáš Bublík, Miroslav Virius

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This paper presents general results on the Java source code snippet detection problem. We propose the tool which uses graph and sub graph isomorphism detection. A number of solutions for all of these tasks have been proposed in the literature. However, although that all these solutions are really fast, they compare just the constant static trees. Our solution offers to enter an input sample dynamically with the Scripthon language while preserving an acceptable speed. We used several optimizations to achieve very low number of comparisons during the matching algorithm.

Keywords: AST, Java, tree matching, scripthon source code recognition

Procedia PDF Downloads 398

Authors: S. Sadallah

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In this paper, dynamic programming is used to determine the optimal management of financial resources in company. Solution of the problem by consider into simpler substructures is constructed. The optimal management of internal capital of company are simulated. The tools applied in this development are based on graph theory. The software of given problems is built by using greedy algorithm. The obtained model and program maintenance enable us to define the optimal version of management of proper financial flows by using visual diagram on each level of investment.

Keywords: management, software, optimal, greedy algorithm, graph-diagram

Procedia PDF Downloads 258

Authors: Fatima Mokeddem

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The phonocardiogram signal (PCG) is a physiological signal that reflects heart mechanical activity, is a promising tool for curious researchers in this field because it is full of indications and useful information for medical diagnosis. PCG segmentation is a basic step to benefit from this signal. Therefore, this paper presents an algorithm that serves the separation of heart sounds and heart murmurs in case they exist in order to use them in several applications and heart sounds analysis. The separation process presents here is founded on three essential steps filtering, envelope detection, and heart sounds segmentation. The algorithm separates the PCG signal into S1 and S2 and extract cardiac murmurs.

Keywords: phonocardiogram signal, filtering, Envelope, Detection, murmurs, heart sounds

Procedia PDF Downloads 109

Authors: Revoti Prasad Bora, Nikita Katyal, Saurabh Yadav

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Pre-processing plays an important role in various image processing applications. Most of the time due to the similar nature of images, a particular pre-processing or a set of pre-processing steps are sufficient to produce the desired results. However, in the education domain, there is a wide variety of images in various aspects like images with line-based diagrams, chemical formulas, mathematical equations, etc. Hence a single pre-processing or a set of pre-processing steps may not yield good results. Therefore, a Deep Learning based approach for dynamically selecting a relevant pre-processing technique for each image is proposed. The proposed method works as a classifier to detect hidden patterns in the images and predicts the relevant pre-processing technique needed for the image. This approach experimented for an image similarity matching problem but it can be adapted to other use cases too. Experimental results showed significant improvement in average similarity ranking with the proposed method as opposed to static pre-processing techniques.

Keywords: deep-learning, classification, pre-processing, computer vision, image processing, educational data mining

Procedia PDF Downloads 112

Authors: Karunambigai Mevani Govindasamy, Sathishkumar Ayyappan

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In this paper, we formulate the algorithm to find out the dominating function parameters of Intuitionistic Fuzzy Graphs(IFG). The methodology we adopted here is converting any physical problem into an IFG, and that has been transformed into Intuitionistic Fuzzy Matrix. Using Linear Program Solver software (LiPS), we found the defined parameters for the given IFG. We obtained these parameters for a path and cycle IFG. This study can be extended to other varieties of IFG. In particular, we obtain the definition of edge dominating function, minimal edge dominating function, fractional edge domination number (γ_if^') and upper fractional edge domination number (Γ_if^') of an intuitionistic fuzzy graph. Also, we formulated an algorithm which is appropriate to work on LiPS to find fractional edge domination number and upper fractional edge domination number of an IFG.

Keywords: fractional edge domination number, intuitionistic fuzzy cycle, intuitionistic fuzzy graph, intuitionistic fuzzy path

Procedia PDF Downloads 132

Authors: Kim Lytle, Tim Talty, Alan Michaels, Jeff Reed

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Implantable medical devices (IMDs) are medically necessary devices embedded in the human body that monitor chronic disorders or automatically deliver therapies. Most IMDs have wireless capabilities that allow them to share data with an offboard programming device to help medical providers monitor the patient’s health while giving the patient more insight into their condition. However, serious security concerns have arisen as researchers demonstrated these devices could be hacked to obtain sensitive information or harm the patient. Cooperative jamming can be used to prevent privileged information leaks by maintaining an adequate signal-to-noise ratio at the intended receiver while minimizing signal power elsewhere. This paper uses ray tracing to demonstrate how a low number of friendly nodes abiding by Bluetooth Low Energy (BLE) transmission regulations can enhance IMD communication security in an office environment, which in turn may inform how companies and individuals can protect their proprietary and personal information.

Keywords: implantable biomedical devices, communication system security, array signal processing, ray tracing

Procedia PDF Downloads 66

Authors: Jing Qing-feng, Liu Danmei

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Based on the optimum detection, signal projection and Maximum A Posteriori (MAP) rule, Proakis has deduced the theoretical BER equation of Gray coded MPSK signals. Proakis analyzed the BER theoretical equations mainly based on the projection of signals, which is difficult to be understood. This article solve the same problem based on the signal space, which explains the vectors relations among the sending signals, received signals and noises. The more explicit and easy-deduced process is illustrated in this article based on the signal space, which can illustrated the relations among the signals and noises clearly. This kind of deduction has a univocal geometry meaning. It can explain the correlation between the production and calculation of BER in vector level.

Keywords: MPSK, MAP, signal space, BER

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Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

Procedia PDF Downloads 107

Authors: Seyed Ahmad Mojallal

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Let G be a connected threshold graph of order n with m edges and trace T. In this talk we give a lower bound on Laplacian energy in terms of n, m, and T of G. From this we determine the threshold graphs with the first four minimal Laplacian energies. We also list the first 20 minimal Laplacian energies among threshold graphs. Let σ=σ(G) be the number of Laplacian eigenvalues greater than or equal to average degree of graph G. Using this concept, we obtain the threshold graphs with the largest and the second largest Laplacian energies.

Keywords: Laplacian eigenvalues, Laplacian energy, threshold graphs, extremal graphs

Procedia PDF Downloads 356

Authors: Diana Pombo, Maria Loaiza, Mauricio Quijano, Alberto Cadena, Juan Pablo Tello

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In this paper, we present a semi-automatic tool for calculating ejection fraction from an echocardiographic video signal which is derived from a database in DICOM format, of Clinica de la Costa - Barranquilla. Described in this paper are each of the steps and methods used to find the respective calculation that includes acquisition and formation of the test samples, processing and finally the calculation of the parameters to obtain the ejection fraction. Two imaging segmentation methods were compared following a methodological framework that is similar only in the initial stages of processing (process of filtering and image enhancement) and differ in the end when algorithms are implemented (Active Contour and Region Growing Algorithms). The results were compared with the measurements obtained by two different medical specialists in cardiology who calculated the ejection fraction of the study samples using the traditional method, which consists of drawing the region of interest directly from the computer using echocardiography equipment and a simple equation to calculate the desired value. The results showed that if the quality of video samples are good (i.e., after the pre-processing there is evidence of an improvement in the contrast), the values provided by the tool are substantially close to those reported by physicians; also the correlation between physicians does not vary significantly.

Keywords: echocardiography, DICOM, processing, segmentation, EDV, ESV, ejection fraction

Procedia PDF Downloads 399

Authors: Mohmmad A. Obeidat, Amjed Al Fahoum, Ayman M. Mansour

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The recognition of an abnormal activity of the brain functionality is a vital issue. To determine the type of the abnormal activity either a brain image or brain signal are usually considered. Imaging localizes the defect within the brain area and relates this area with somebody functionalities. However, some functions may be disturbed without affecting the brain as in epilepsy. In this case, imaging may not provide the symptoms of the problem. A cheaper yet efficient approach that can be utilized to detect abnormal activity is the measurement and analysis of the electroencephalogram (EEG) signals. The main goal of this work is to come up with a new method to facilitate the classification of the abnormal and disorder activities within the brain directly using EEG signal processing, which makes it possible to be applied in an on-line monitoring system.

Keywords: EEG, wavelet, epilepsy, detection

Procedia PDF Downloads 493

Authors: Zin Mar Lwin

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Brain Computer Interface (BCI) Systems have developed for people who suffer from severe motor disabilities and challenging to communicate with their environment. BCI allows them for communication by a non-muscular way. For communication between human and computer, BCI uses a type of signal called Electroencephalogram (EEG) signal which is recorded from the human„s brain by means of an electrode. The electroencephalogram (EEG) signal is an important information source for knowing brain processes for the non-invasive BCI. Translating human‟s thought, it needs to classify acquired EEG signal accurately. This paper proposed a typical EEG signal classification system which experiments the Dataset from “Purdue University.” Independent Component Analysis (ICA) method via EEGLab Tools for removing artifacts which are caused by eye blinks. For features extraction, the Time and Frequency features of non-stationary EEG signals are extracted by Matching Pursuit (MP) algorithm. The classification of one of five mental tasks is performed by Multi_Class Support Vector Machine (SVM). For SVMs, the comparisons have been carried out for both 1-against-1 and 1-against-all methods.

Keywords: BCI, EEG, ICA, SVM

Procedia PDF Downloads 245

Authors: Jiwon Lee, Chanho Jung, Si-Hwan Jang, Kyung-Ill Kim, Sanghyun Joo, Wook-Ho Son

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Since the advances in digital imaging technologies have led to development of high quality digital devices, there are a lot of illegal copies of copyrighted video content on the internet. Thus, we propose a high-quality (HQ) video watermarking scheme that can prevent these illegal copies from spreading out. The proposed scheme is applied spatial and temporal gradient methods to improve the fidelity and detection performance. Also, the scheme duplicates the watermark signal temporally to alleviate the signal reduction caused by geometric and signal-processing distortions. Experimental results show that the proposed scheme achieves better performance than previously proposed schemes and it has high fidelity. The proposed scheme can be used in broadcast monitoring or traitor tracking applications which need fast detection process to prevent illegally recorded video content from spreading out.

Keywords: editing prevention technique, gradient method, luminance change, video watermarking

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Authors: Haoshu Li, Shaolong Wan

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The recent focus has been on directional signal amplification of a signal input at one end of a one-dimensional chain and measured at the other end. The amplification rate is given by the end-to-end Green’s functions of the system. In this work, we derive the exact formulas for the end-to-end Green's functions of non-Hermitian single-band systems. While in the bulk region, it is found that the Green's functions are displaced from the prior established integral formula by O(e⁻ᵇᴸ). The results confirm the correspondence between the signal amplification and the non-Hermitian skin effect.

Keywords: non-Hermitian, Green's function, non-Hermitian skin effect, signal amplification

Procedia PDF Downloads 107

Authors: Simeon Mayala, Ida Herdlevær, Jonas Bull Haugsøen, Shamundeeswari Anandan, Sonia Gavasso, Morten Brun

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In this paper, we propose a minimum spanning tree-based method for segmenting brain tumors. The proposed method performs interactive segmentation based on the minimum spanning tree without tuning parameters. The steps involve preprocessing, making a graph, constructing a minimum spanning tree, and a newly implemented way of interactively segmenting the region of interest. In the preprocessing step, a Gaussian filter is applied to 2D images to remove the noise. Then, the pixel neighbor graph is weighted by intensity differences and the corresponding minimum spanning tree is constructed. The image is loaded in an interactive window for segmenting the tumor. The region of interest and the background are selected by clicking to split the minimum spanning tree into two trees. One of these trees represents the region of interest and the other represents the background. Finally, the segmentation given by the two trees is visualized. The proposed method was tested by segmenting two different 2D brain T1-weighted magnetic resonance image data sets. The comparison between our results and the standard gold segmentation confirmed the validity of the minimum spanning tree approach. The proposed method is simple to implement and the results indicate that it is accurate and efficient.

Keywords: brain tumor, brain tumor segmentation, minimum spanning tree, segmentation, image processing

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Authors: Adrienne Kline, Jaydip Desai

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Electroencephalogram (EEG) is a noninvasive technique that registers signals originating from the firing of neurons in the brain. The Emotiv EEG Neuroheadset is a consumer product comprised of 14 EEG channels and was used to record the reactions of the neurons within the brain to two forms of stimuli in 10 participants. These stimuli consisted of auditory and visual formats that provided directions of ‘right’ or ‘left.’ Participants were instructed to raise their right or left arm in accordance with the instruction given. A scenario in OpenViBE was generated to both stimulate the participants while recording their data. In OpenViBE, the Graz Motor BCI Stimulator algorithm was configured to govern the duration and number of visual stimuli. Utilizing EEGLAB under the cross platform MATLAB®, the electrodes most stimulated during the study were defined. Data outputs from EEGLAB were analyzed using IBM SPSS Statistics® Version 20. This aided in determining the electrodes to use in the development of a brain-machine interface (BMI) using real-time EEG signals from the Emotiv EEG Neuroheadset. Signal processing and feature extraction were accomplished via the Simulink® signal processing toolbox. An Arduino™ Duemilanove microcontroller was used to link the Emotiv EEG Neuroheadset and the right and left Mecha TE™ Hands.

Keywords: brain-machine interface, EEGLAB, emotiv EEG neuroheadset, OpenViBE, simulink

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Authors: Heramb Somthankar, Anujoy Chakraborty

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This paper presents a classification study on yield prediction in semiconductor production using machine learning approaches. A complicated semiconductor production process is generally monitored continuously by signals acquired from sensors and measurement sites. A monitoring system contains a variety of signals, all of which contain useful information, irrelevant information, and noise. In the case of each signal being considered a feature, "Feature Selection" is used to find the most relevant signals. The open-source UCI SECOM Dataset provides 1567 such samples, out of which 104 fail in quality assurance. Feature extraction and selection are performed on the dataset, and useful signals were considered for further study. Afterward, common machine learning algorithms were employed to predict whether the signal yields pass or fail. The most relevant algorithm is selected for prediction based on the accuracy and loss of the ML model.

Keywords: deep learning, feature extraction, feature selection, machine learning classification algorithms, semiconductor production monitoring, signal processing, time-series analysis

Procedia PDF Downloads 66

Authors: Qin Long, Li Xiaoge

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The Knowledge Graphs have now become a new form of knowledge representation. However, there is no consensus in regard to a plausible and definition of entities and relationships in the domain-specific knowledge graph. Further, in conjunction with several limitations and deficiencies, various domain-specific entities and relationships recognition approaches are far from perfect. Specifically, named entity recognition in Chinese domain is a critical task for the natural language process applications. However, a bottleneck problem with Chinese named entity recognition in new domains is the lack of annotated data. To address this challenge, a domain distant supervised named entity recognition framework is proposed. The framework is divided into two stages: first, the distant supervised corpus is generated based on the entity linking model of graph attention neural network; secondly, the generated corpus is trained as the input of the distant supervised named entity recognition model to train to obtain named entities. The link model is verified in the ccks2019 entity link corpus, and the F1 value is 2% higher than that of the benchmark method. The re-pre-trained BERT language model is added to the benchmark method, and the results show that it is more suitable for distant supervised named entity recognition tasks. Finally, it is applied in the computer field, and the results show that this framework can obtain domain named entities.

Keywords: distant named entity recognition, entity linking, knowledge graph, graph attention neural network

Procedia PDF Downloads 66

Authors: J. C. Valenzuela-Tripodoro, P. Álvarez-Ruíz, M. A. Mateos-Camacho, M. Cera

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In 2004, it was introduced the concept of Roman domination in graphs. This concept was initially inspired and related to the defensive strategy of the Roman Empire. An undefended place is a city so that no legions are established on it, whereas a strong place is a city in which two legions are deployed. This situation may be modeled by labeling the vertices of a finite simple graph with labels {0, 1, 2}, satisfying the condition that any 0-vertex must be adjacent to, at least, a 2-vertex. Roman domination in graphs is a variant of classic domination. Clearly, the main aim is to obtain such labeling of the vertices of the graph with minimum cost, that is to say, having minimum weight (sum of all vertex labels). Formally, a function f: V (G) → {0, 1, 2} is a Roman dominating function (RDF) in the graph G = (V, E) if f(u) = 0 implies that f(v) = 2 for, at least, a vertex v which is adjacent to u. The weight of an RDF is the positive integer w(f)= ∑_(v∈V)▒〖f(v)〗. The Roman domination number, γ_R (G), is the minimum weight among all the Roman dominating functions? Obviously, the set of vertices with a positive label under an RDF f is a dominating set in the graph, and hence γ(G)≤γ_R (G). In this work, we start the study of a generalization of RDF in which we consider that any undefended place should be defended from a sudden attack by, at least, k legions. These legions can be deployed in the city or in any of its neighbours. A function f: V → {0, 1, . . . , k + 1} such that f(N[u]) ≥ k + |AN(u)| for all vertex u with f(u) < k, where AN(u) represents the set of active neighbours (i.e., with a positive label) of vertex u, is called a [k]-multiple Roman dominating functions and it is denoted by [k]-MRDF. The minimum weight of a [k]-MRDF in the graph G is the [k]-multiple Roman domination number ([k]-MRDN) of G, denoted by γ_[kR] (G). First, we prove that the [k]-multiple Roman domination decision problem is NP-complete even when restricted to bipartite and chordal graphs. A problem that had been resolved for other variants and wanted to be generalized. We know the difficulty of calculating the exact value of the [k]-MRD number, even for families of particular graphs. Here, we present several upper and lower bounds for the [k]-MRD number that permits us to estimate it with as much precision as possible. Finally, some graphs with the exact value of this parameter are characterized.

Keywords: multiple roman domination function, decision problem np-complete, bounds, exact values

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Authors: Zerihun Ketema Tadesse, Dabbu Suman Reddy

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Brain-Computer Interfaces (BCIs) give the possibility for disabled people to communicate and control devices. This work aims at developing steady-state visual evoked potential (SSVEP)-based BCI for patients with limb disabilities. In hospitals, devices like nurse emergency call devices, lights, and TV sets are what patients use most frequently, but these devices are operated manually or using the remote control. Thus, disabled patients are not able to operate these devices by themselves. Hence, SSVEP-based BCI system that can allow disabled patients to control nurse calling device and other devices is proposed in this work. Portable LED visual stimulator that flickers at specific frequencies of 7Hz, 8Hz, 9Hz and 10Hz were developed as part of this project. Disabled patients can stare at specific flickering LED of visual stimulator and Emotiv EPOC used to acquire EEG signal in a non-invasive way. The acquired EEG signal can be processed to generate various control signals depending upon the amplitude and duration of signal components. MATLAB software is used for signal processing and analysis and also for command generation. Arduino is used as a hardware interface device to receive and transmit command signals to the experimental setup. Therefore, this study is focused on the design and development of Steady-state visually evoked potential (SSVEP)-based BCI for limb disabled patients, which helps them to operate and control devices in the hospital room/wards.

Keywords: SSVEP-BCI, Limb Disabled Patients, LED Visual Stimulator, EEG signal, control devices, hospital room/wards

Procedia PDF Downloads 194

Authors: Scott N. Gerard, Aliza Heching, Susann M. Keohane, Samuel S. Adams

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The world-wide population of people over 60 years of age is growing rapidly. The explosion is placing increasingly onerous demands on individual families, multiple industries and entire countries. Current, human-intensive approaches to eldercare are not sustainable, but IoT and AI technologies can help. The Knowledge Reactor (KR) is a contextual, data fusion engine built to address this and other similar problems. It fuses and centralizes IoT and System of Record/Engagement data into a reactive knowledge graph. Cognitive applications and services are constructed with its multiagent architecture. The KR can scale-up and scaledown, because it exploits container-based, horizontally scalable services for graph store (JanusGraph) and pub-sub (Kafka) technologies. While the KR can be applied to many domains that require IoT and AI technologies, this paper describes how the KR specifically supports the challenging domain of cognitive eldercare. Rule- and machine learning-based analytics infer activities of daily living from IoT sensor readings. KR scalability, adaptability, flexibility and usability are demonstrated.

Keywords: ambient sensing, AI, artificial intelligence, eldercare, IoT, internet of things, knowledge graph

Procedia PDF Downloads 145

Authors: Yan Li

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Purpose: There is a lack of suitable recommendation systems to assist engineering teaching. The existing traditional engineering pedagogies lack learning interests for postgraduate students. The knowledge graph-based recommender system aims to enhance postgraduate students’ programming skills, with a focus on programming courses. Design/methodology/approach: The case study will be used as a major research method, and the two case studies will be taken in both two teaching styles of the universities (Zhejiang University and the University of Nottingham Ningbo China), followed by the interviews. Quantitative and qualitative research methods will be combined in this study. Research limitations/implications: The case studies were only focused on two teaching styles universities, which is not comprehensive enough. The subject was limited to postgraduate students. Originality/value: The study collected and analyzed the data from two teaching styles of universities’ perspectives. It explored the challenges of Engineering education and tried to seek potential enhancement.

Keywords: knowledge graph and recommender system, engineering pedagogy, programming skills, postgraduate students

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Authors: M. Yousefi, N. Nasirzadeh

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In this paper, behavior of an oscillator under injection of another signal has been investigated. Also, variation of output signal amplitude versus injected signal phase variation, the effect of varying the amplitude of injected signal and quality factor of the oscillator has been investigated. The results show that the locking time depends on phase and the best locking time happens at 180-degrees phase. Also, the effect of injected lock has been discussed. Simulations show that the locking time decreases with signal injection to bulk. Locking time has been investigated versus various phase differences. The effect of phase and amplitude changes on locking time of a typical LC oscillator in 180 nm technology has been investigated.

Keywords: analysis, oscillator, injection-lock oscillator, phase modulation

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Authors: Khanh D.Do, Loi V.Nguyen, Thanh N.Nguyen, Thang M.Nguyen, Vu T.Tran

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Along with the development of Secondary surveillance radar (SSR) in air traffic surveillance systems, the Multipath phenomena has always been a noticeable problem. This following article discusses the geometrical aspect and power aspect of the Multipath interference caused by reflection in SSR and proposes a method to deal with these unwanted multipath targets (ghosts) by false-target position predicting and adaptive target suppressing. A field-experiment example is mentioned at the end of the article to demonstrate the efficiency of this measure.

Keywords: multipath, secondary surveillance radar, digital signal processing, reflection

Procedia PDF Downloads 115

Authors: Olomon Wu, Hung Lu, Nick Wilkins, Daniel Kerr, Zekeriya Aliyazicioglu, H. K. Hwang

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Multiple Input Multiple Output (MIMO) radar has received increasing attention in recent years. MIMO radar has many advantages over conventional phased array radar such as target detection, resolution enhancement, and interference suppression. In this paper, the results are presented from a simulation study of MIMO Uniformly-Spaced Linear Array (ULA) antennas. The performance is investigated under varied parameters, including varied array size, Pseudo Random (PN) sequence length, number of snapshots, and Signal to Noise Ratio (SNR). The results of MIMO are compared to a traditional array antenna.

Keywords: MIMO radar, phased array antenna, target detection, radar signal processing

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Authors: Hossam M. Moftah, Aboul Ella Hassanien

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In the recent years the importance of automatic traffic control has increased due to the traffic jams problem especially in big cities for signal control and efficient traffic management. Traffic counting as a kind of traffic control is important to know the road traffic density in real time. This paper presents a fast and robust traffic counting system using different image processing techniques. The proposed system is composed of the following four fundamental building phases: image acquisition, pre-processing, object detection, and finally counting the connected objects. The object detection phase is comprised of the following five steps: subtracting the background, converting the image to binary, closing gaps and connecting nearby blobs, image smoothing to remove noises and very small objects, and detecting the connected objects. Experimental results show the great success of the proposed approach.

Keywords: traffic counting, traffic management, image processing, object detection, computer vision

Procedia PDF Downloads 267

Authors: Hend Alrasheed

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Due to their different properties that have led to avoid several limitations of classic client/server systems, there has been a great interest in the development and the improvement of different peer to peer systems. Understanding the properties of complex peer to peer networks is essential for their future improvements. It was shown that the performances of peer to peer protocols are directly related to their underlying topologies. Therefore, multiple efforts have analyzed the topologies of different peer to peer systems. This study presents an overview of major findings of close experimental analyses to different topologies of three unstructured peer to peer systems: BitTorrent, Gnutella, and FreeNet.

Keywords: peer to peer networks, network topology, graph diameter, clustering coefficient, small-world property, random graph, degree distribution

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Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

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In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

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Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca de Marchi

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This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes available a larger monitored area. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary chars the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: data compression, ultrasonic communication, guided waves, FEM analysis

Procedia PDF Downloads 97