Search results for: Ring Detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3752

Search results for: Ring Detection

3602 Anthraquinone Labelled DNA for Direct Detection and Discrimination of Closely Related DNA Targets

Authors: Sarah A. Goodchild, Rachel Gao, Philip N. Bartlett

Abstract:

A novel detection approach using immobilized DNA probes labeled with Anthraquinone (AQ) as an electrochemically active reporter moiety has been successfully developed as a new, simple, reliable method for the detection of DNA. This method represents a step forward in DNA detection as it can discriminate between multiple nucleotide polymorphisms within target DNA strands without the need for any additional reagents, reporters or processes such as melting of DNA strands. The detection approach utilizes single-stranded DNA probes immobilized on gold surfaces labeled at the distal terminus with AQ. The effective immobilization has been monitored using techniques such as AC impedance and Raman spectroscopy. Simple voltammetry techniques (Differential Pulse Voltammetry, Cyclic Voltammetry) are then used to monitor the reduction potential of the AQ before and after the addition of complementary strand of target DNA. A reliable relationship between the shift in reduction potential and the number of base pair mismatch has been established and can be used to discriminate between DNA from highly related pathogenic organisms of clinical importance. This indicates that this approach may have great potential to be exploited within biosensor kits for detection and diagnosis of pathogenic organisms in Point of Care devices.

Keywords: Anthraquinone, discrimination, DNA detection, electrochemical biosensor

Procedia PDF Downloads 369
3601 Detection of New Attacks on Ubiquitous Services in Cloud Computing and Countermeasures

Authors: L. Sellami, D. Idoughi, P. F. Tiako

Abstract:

Cloud computing provides infrastructure to the enterprise through the Internet allowing access to cloud services at anytime and anywhere. This pervasive aspect of the services, the distributed nature of data and the wide use of information make cloud computing vulnerable to intrusions that violate the security of the cloud. This requires the use of security mechanisms to detect malicious behavior in network communications and hosts such as intrusion detection systems (IDS). In this article, we focus on the detection of intrusion into the cloud sing IDSs. We base ourselves on client authentication in the computing cloud. This technique allows to detect the abnormal use of ubiquitous service and prevents the intrusion of cloud computing. This is an approach based on client authentication data. Our IDS provides intrusion detection inside and outside cloud computing network. It is a double protection approach: The security user node and the global security cloud computing.

Keywords: cloud computing, intrusion detection system, privacy, trust

Procedia PDF Downloads 282
3600 Detection Characteristics of the Random and Deterministic Signals in Antenna Arrays

Authors: Olesya Bolkhovskaya, Alexey Davydov, Alexander Maltsev

Abstract:

In this paper approach to incoherent signal detection in multi-element antenna array are researched and modeled. Two types of useful signals with unknown wavefront were considered. First one is deterministic (Barker code), the second one is random (Gaussian distribution). The derivation of the sufficient statistics took into account the linearity of the antenna array. The performance characteristics and detecting curves are modeled and compared for different useful signals parameters and for different number of elements of the antenna array. Results of researches in case of some additional conditions can be applied to a digital communications systems.

Keywords: antenna array, detection curves, performance characteristics, quadrature processing, signal detection

Procedia PDF Downloads 364
3599 The Guaranteed Detection of the Seismoacoustic Emission Source in the C-OTDR Systems

Authors: Andrey V. Timofeev

Abstract:

A method is proposed for stable detection of seismoacoustic sources in C-OTDR systems that guarantee given upper bounds for probabilities of type I and type II errors. Properties of the proposed method are rigorously proved. The results of practical applications of the proposed method in a real C-OTDR-system are presented in this.

Keywords: guaranteed detection, C-OTDR systems, change point, interval estimation

Procedia PDF Downloads 228
3598 Real-Time Lane Marking Detection Using Weighted Filter

Authors: Ayhan Kucukmanisa, Orhan Akbulut, Oguzhan Urhan

Abstract:

Nowadays, advanced driver assistance systems (ADAS) have become popular, since they enable safe driving. Lane detection is a vital step for ADAS. The performance of the lane detection process is critical to obtain a high accuracy lane departure warning system (LDWS). Challenging factors such as road cracks, erosion of lane markings, weather conditions might affect the performance of a lane detection system. In this paper, 1-D weighted filter based on row filtering to detect lane marking is proposed. 2-D input image is filtered by 1-D weighted filter considering four-pixel values located symmetrically around the center of candidate pixel. Performance evaluation is carried out by two metrics which are true positive rate (TPR) and false positive rate (FPR). Experimental results demonstrate that the proposed approach provides better lane marking detection accuracy compared to the previous methods while providing real-time processing performance.

Keywords: lane marking filter, lane detection, ADAS, LDWS

Procedia PDF Downloads 164
3597 Numerical Investigation of Fluid Flow, Characteristics of Thermal Performance and Enhancement of Heat Transfer of Corrugated Pipes with Various Geometrical Configurations

Authors: Ahmed Ramadhan Al-Obaidi, Jassim Alhamid

Abstract:

In this investigation, the flow pattern, characteristics of thermal-hydraulic, and improvement of heat transfer performance are evaluated using a numerical technique in three dimensions corrugated pipe heat exchanger. The modification was made under different corrugated pipe geometrical parameters, including corrugated ring angle (CRA), distance between corrugated ring (DBCR), and corrugated diameter (CD), the range of Re number from 2000 to 12000. The numerical results are validated with available experimental data. The numerical outcomes reveal that there is an important change in flow field behaviour and a significant increase in friction factor and improvement in heat transfer performance owing to the use of the corrugated shape in the heat exchanger pipe as compared to the conventional smooth pipe. Using corrugated pipe with different configurations makes the flow more turbulence, flow separation, boundary layer distribution, flow mixing, and that leads to augmenting the performance of heat transfer. Moreover, the value of pressure drop, and the Nusselt number increases as the corrugated pipe geometrical parameters increase. Furthermore, the corrugation configuration shapes have an important influence on the thermal evaluation performance factor, and the maximum value was more than 1.3. Numerical simulation can be performed to predict the various geometrical configurations effects on fluid flow, thermal performance, and heat transfer enhancement.

Keywords: corrugated ring angle, corrugated diameter, Nusselt number, heat transfer

Procedia PDF Downloads 113
3596 Cells Detection and Recognition in Bone Marrow Examination with Deep Learning Method

Authors: Shiyin He, Zheng Huang

Abstract:

In this paper, deep learning methods are applied in bio-medical field to detect and count different types of cells in an automatic way instead of manual work in medical practice, specifically in bone marrow examination. The process is mainly composed of two steps, detection and recognition. Mask-Region-Convolutional Neural Networks (Mask-RCNN) was used for detection and image segmentation to extract cells and then Convolutional Neural Networks (CNN), as well as Deep Residual Network (ResNet) was used to classify. Result of cell detection network shows high efficiency to meet application requirements. For the cell recognition network, two networks are compared and the final system is fully applicable.

Keywords: cell detection, cell recognition, deep learning, Mask-RCNN, ResNet

Procedia PDF Downloads 156
3595 CdS Quantum Dots as Fluorescent Probes for Detection of Naphthalene

Authors: Zhengyu Yan, Yan Yu, Jianqiu Chen

Abstract:

A novel sensing system has been designed for naphthalene detection based on the quenched fluorescence signal of CdS quantum dots. The fluorescence intensity of the system reduced significantly after adding CdS quantum dots to the water pollution model because of the fluorescent static quenching f mechanism. Herein, we have demonstrated the facile methodology can offer a convenient and low analysis cost with the recovery rate as 97.43%-103.2%, which has potential application prospect.

Keywords: CdS quantum dots, modification, detection, naphthalene

Procedia PDF Downloads 463
3594 Burnout Recognition for Call Center Agents by Using Skin Color Detection with Hand Poses

Authors: El Sayed A. Sharara, A. Tsuji, K. Terada

Abstract:

Call centers have been expanding and they have influence on activation in various markets increasingly. A call center’s work is known as one of the most demanding and stressful jobs. In this paper, we propose the fatigue detection system in order to detect burnout of call center agents in the case of a neck pain and upper back pain. Our proposed system is based on the computer vision technique combined skin color detection with the Viola-Jones object detector. To recognize the gesture of hand poses caused by stress sign, the YCbCr color space is used to detect the skin color region including face and hand poses around the area related to neck ache and upper back pain. A cascade of clarifiers by Viola-Jones is used for face recognition to extract from the skin color region. The detection of hand poses is given by the evaluation of neck pain and upper back pain by using skin color detection and face recognition method. The system performance is evaluated using two groups of dataset created in the laboratory to simulate call center environment. Our call center agent burnout detection system has been implemented by using a web camera and has been processed by MATLAB. From the experimental results, our system achieved 96.3% for upper back pain detection and 94.2% for neck pain detection.

Keywords: call center agents, fatigue, skin color detection, face recognition

Procedia PDF Downloads 261
3593 Voltage Controlled Ring Oscillator for RF Applications in 0.18 µm CMOS Technology

Authors: Mohammad Arif Sobhan Bhuiyan, Zainal Abidin Nordin, Mamun Bin Ibne Reaz

Abstract:

A compact and power efficient high performance Voltage Controlled Oscillator (VCO) is a must in analog and digital circuits especially in the communication system, but the best trade-off among the performance parameters is a challenge for researchers. In this paper, a design of a compact 3-stage differential voltage controlled ring oscillator (VCRO) with low phase noise, low power and higher tuning bandwidth is proposed in 0.18 µm CMOS technology. The VCRO is designed with symmetric load and positive feedback techniques to achieve higher gain and minimum delay. The proposed VCRO can operate at tuning range of 3.9-5.0 GHz at 1.6 V supply voltage. The circuit consumes only 1.0757 mW of power and produces -129 dbc/Hz. The total active area of the proposed VCRO is only 11.74 x 37.73 µm2. Such a VCO can be the best choice for compact and low-power RF applications.

Keywords: CMOS, VCO, VCRO, oscillator

Procedia PDF Downloads 442
3592 In situ Ortho-Quinone Methide Reactions for Construction of Flavonoids with Fused Ring Systems

Authors: Vidia A. Nuraini, Eugene M. H. Yee, Mohan Bhadbhade, David StC. Black, Naresh Kumar

Abstract:

Flavonoids are naturally occurring compounds that have been shown to exhibit a wide range of biological properties including anticancer and anti-inflammatory activities. However, flavonoids suffer from low bioavailability, which limits their overall utility for therapeutic applications. One of the methods to overcome this limitation is through structural modification of natural flavonoids. In this study, flavanone, isoflavanone, and isoflavene, were structurally modified through the introduction of additional fused-ring systems via ortho-quinone methide intermediates (o-QMs). These intermediates can readily undergo a [4+2] cycloaddition through an inverse-electron-demand Diels–Alder reaction with electron-rich dienophiles. A regioselective Mannich reaction using bis-(N,N-dimethylamino)methane was employed to generate the o-QM precursors of flavanone, isoflavanone, and isoflavene. The o-QM intermediates were subsequently generated in situ through thermal elimination of the dimethylamine functionality and reacted with a variety of dienophiles to produce novel flavonoids with fused-ring systems. A total of 21 novel flavonoid analogs were successfully synthesized. The X-ray crystal structure of cycloaddition adducts, particularly those derived from 3,4-dihydro-2H-pyran and p-methoxystyrene revealed a special case of enantiomeric disorder, where two enantiomers in equal amounts superpose with one another, with the exception for atoms that have opposite configuration. The anticancer properties of fused-ring systems derived from isoflavene were evaluated against the neuroblastoma SKN-BE(2)C, the triple negative breast cancer MDA-MB-231, and the glioblastoma U87 cancer cell lines. One of these cycloaddition adducts had displayed improved anti-proliferative activity against MDA-MB-231 and U87 cancer cell lines as compared to the parent compound. Further anticancer and anti-inflammatory activities of the flavanone and isoflavanone analogs are currently being investigated.

Keywords: Diels-Alder reaction, flavonoids, Mannich reaction, ortho-quinone methide.

Procedia PDF Downloads 221
3591 A Green Approach towards the Production of CaCO₃ Scaffolds for Bone Tissue Engineering

Authors: Sudhir Kumar Sharma, Abiy D. Woldetsadik, Mazin Magzoub, Ramesh Jagannathan

Abstract:

It is well known that bioactive ceramics exhibit specific biological affinities, especially in the area of tissue re-generation. In this context, we report the development of an eminently scalable, novel, supercritical CO₂ based process for the fabrication of hierarchically porous 'soft' CaCO₃ scaffolds. Porosity at the macro, micro, and nanoscales was obtained through process optimization of the so-called 'coffee-ring effect'. Exposure of these CaCO₃ scaffolds to monocytic THP-1 cells yielded negligible levels of tumor necrosis factor-alpha (TNF-α) thereby confirming the lack of immunogenicity of the scaffolds. ECM protein treatment of the scaffolds showed enhanced adsorption comparable to standard control such as glass. In vitro studies using osteoblast precursor cell line, MC3T3, also demonstrated the cytocompatibility of hierarchical porous CaCO₃ scaffolds.

Keywords: supercritical CO2, CaCO3 scaffolds, coffee-ring effect, ECM proteins

Procedia PDF Downloads 267
3590 Pyrazolylpyrazolines: Design, Synthesis and Biological Evaluation as Dual Acting Antimalarial-Antileishmanial Agents

Authors: Adnan Bekhit, Eskedar Lodebo, Ariaya Hymete, Hanan Ragab, Alaa El-Din Bekhit

Abstract:

Malaria and leishmaniasis have emerged as serious universal health problems throughout history of mankind. According to the WHO 2008 malarial report, half of the world population is at risk of malarial infection with an estimate of 1 million deaths occurring annually mainly in the African region. Furthermore, 12-15 million people are infected with Leishmaniasis worldwide. Despite the continuous introduction of a large number of agents for the treatment of malaria, there is still unmet medical needs due to the emergence of resistance. Resistance has occurred for almost all therapeutic agents approved for the treatment of malaria. Accordingly, it was the aim of this work to design and synthesis a group of antimalarial-antileshmanial agents that would show inhibitory activity against chloroquine-resistant strain of Plasmodium falciparum. The synthesized compounds were designed to contain a pyrazolylpyrazoline moiety having an aromatic group (p-tolyl or p-chlorophenyl) at N1-position of one pyrazoline ring due to the reports of promising activities of such compounds. A formyl or acyl substituent was introduced at the N1-position of the other pyrazoline ring, to investigate the effect of bulkiness of acyl substituents at this position. The synthesized compounds were evaluated for their in-vivo antimalarial activity against Plasmodium berghei infected mice at dose levels of 20 and 30 mg/Kg. the two most active compounds were evaluated for their antimalarial activity against chloroquin-resistant strain (RKL9) of Plasmodium falciparum. In addition, the synthesized compounds were tested for their in-vitro antileshmanial activity against Leishmania aethiopica promastigotes and amastigotes. For both antimalarial and antileishmanial activities, compounds having an N1-p-tolyl group at the first pyrazoline ring did not require bulkiness at the second pyrazoline ring nitrogen where the compound bearing an acetyl group proved to be the most active of the whole series. On the other hand, bulkiness at the N1-position of the second pyazoline ring was necessary in case of compounds carrying the p-chlorophenyl group, where the two derivatives having an N1-butanoyl and an N1-benzoyl moieties at the second pyrazoline showed the best activity. Furthermore, the toxicity of the active compounds were tested and were proved to be non-toxic at 125, 250 and 500 mg/Kg. In addition, docking of the most active compound (having a p-tolyl group at the first pyrazoline-N and an acetyl moiety on the other pyrazoline-N) was performed against dihydrofolate reductase enzyme.

Keywords: pyrazoline derivatives, in-vivo antimalarial activity, docking, dihydrofolate reductase

Procedia PDF Downloads 308
3589 Comprehensive Review of Adversarial Machine Learning in PDF Malware

Authors: Preston Nabors, Nasseh Tabrizi

Abstract:

Portable Document Format (PDF) files have gained significant popularity for sharing and distributing documents due to their universal compatibility. However, the widespread use of PDF files has made them attractive targets for cybercriminals, who exploit vulnerabilities to deliver malware and compromise the security of end-user systems. This paper reviews notable contributions in PDF malware detection, including static, dynamic, signature-based, and hybrid analysis. It presents a comprehensive examination of PDF malware detection techniques, focusing on the emerging threat of adversarial sampling and the need for robust defense mechanisms. The paper highlights the vulnerability of machine learning classifiers to evasion attacks. It explores adversarial sampling techniques in PDF malware detection to produce mimicry and reverse mimicry evasion attacks, which aim to bypass detection systems. Improvements for future research are identified, including accessible methods, applying adversarial sampling techniques to malicious payloads, evaluating other models, evaluating the importance of features to malware, implementing adversarial defense techniques, and conducting comprehensive examination across various scenarios. By addressing these opportunities, researchers can enhance PDF malware detection and develop more resilient defense mechanisms against adversarial attacks.

Keywords: adversarial attacks, adversarial defense, adversarial machine learning, intrusion detection, PDF malware, malware detection, malware detection evasion

Procedia PDF Downloads 14
3588 Thermal Performance of Radial Heat Sinks for LED Applications

Authors: Jongchul Park, Chan Byon

Abstract:

In this study, the thermal performance of radial heat sinks for LED applications is investigated numerically and experimentally. The effect of geometrical parameters such as inner radius, fin height, fin length, and fin spacing, as well as the Elenbaas number, is considered. In addition, the effects of augmentation of concentric ring, perforation, and duct are extensively explored in order to enhance the thermal performance of conventional radial heat sink. The results indicate that the Elenbaas number and the fin radius have a significant effect on the thermal performance of the heat sink. The concentric ring affects the performance much, but the degree of affection is highly dependent on the orientation. The perforation always brings about higher thermal performance. The duct can effectively prevent the bypass of the natural convection flow, which in turn reduces the thermal resistance of the radial heat sink significantly.

Keywords: heat transfer, radial heat sink, LED, Elenbaas

Procedia PDF Downloads 382
3587 SPR Immunosensor for the Detection of Staphylococcus aureus

Authors: Muhammad Ali Syed, Arshad Saleem Bhatti, Chen-zhong Li, Habib Ali Bokhari

Abstract:

Surface plasmon resonance (SPR) biosensors have emerged as a promising technique for bioanalysis as well as microbial detection and identification. Real time, sensitive, cost effective, and label free detection of biomolecules from complex samples is required for early and accurate diagnosis of infectious diseases. Like many other types of optical techniques, SPR biosensors may also be successfully utilized for microbial detection for accurate, point of care, and rapid results. In the present study, we have utilized a commercially available automated SPR biosensor of BI company to study the microbial detection form water samples spiked with different concentration of Staphylococcus aureus bacterial cells. The gold thin film sensor surface was functionalized to react with proteins such as protein G, which was used for directed immobilization of monoclonal antibodies against Staphylococcus aureus. The results of our work reveal that this immunosensor can be used to detect very small number of bacterial cells with higher sensitivity and specificity. In our case 10^3 cells/ml of water have been successfully detected. Therefore, it may be concluded that this technique has a strong potential to be used in microbial detection and identification.

Keywords: surface plasmon resonance (SPR), Staphylococcus aureus, biosensors, microbial detection

Procedia PDF Downloads 444
3586 Detection of Parkinsonian Freezing of Gait

Authors: Sang-Hoon Park, Yeji Ho, Gwang-Moon Eom

Abstract:

Fast and accurate detection of Freezing of Gait (FOG) is desirable for appropriate application of cueing which has been shown to ameliorate FOG. Utilization of frequency spectrum of leg acceleration to derive the freeze index requires much calculation and it would lead to delayed cueing. We hypothesized that FOG can be reasonably detected from the time domain amplitude of foot acceleration. A time instant was recognized as FOG if the mean amplitude of the acceleration in the time window surrounding the time instant was in the specific FOG range. Parameters required in the FOG detection was optimized by simulated annealing. The suggested time domain methods showed performances comparable to those of frequency domain methods.

Keywords: freezing of gait, detection, Parkinson's disease, time-domain method

Procedia PDF Downloads 415
3585 Multi-Spectral Deep Learning Models for Forest Fire Detection

Authors: Smitha Haridasan, Zelalem Demissie, Atri Dutta, Ajita Rattani

Abstract:

Aided by the wind, all it takes is one ember and a few minutes to create a wildfire. Wildfires are growing in frequency and size due to climate change. Wildfires and its consequences are one of the major environmental concerns. Every year, millions of hectares of forests are destroyed over the world, causing mass destruction and human casualties. Thus early detection of wildfire becomes a critical component to mitigate this threat. Many computer vision-based techniques have been proposed for the early detection of forest fire using video surveillance. Several computer vision-based methods have been proposed to predict and detect forest fires at various spectrums, namely, RGB, HSV, and YCbCr. The aim of this paper is to propose a multi-spectral deep learning model that combines information from different spectrums at intermediate layers for accurate fire detection. A heterogeneous dataset assembled from publicly available datasets is used for model training and evaluation in this study. The experimental results show that multi-spectral deep learning models could obtain an improvement of about 4.68 % over those based on a single spectrum for fire detection.

Keywords: deep learning, forest fire detection, multi-spectral learning, natural hazard detection

Procedia PDF Downloads 203
3584 Leukocyte Detection Using Image Stitching and Color Overlapping Windows

Authors: Lina, Arlends Chris, Bagus Mulyawan, Agus B. Dharmawan

Abstract:

Blood cell analysis plays a significant role in the diagnosis of human health. As an alternative to the traditional technique conducted by laboratory technicians, this paper presents an automatic white blood cell (leukocyte) detection system using Image Stitching and Color Overlapping Windows. The advantage of this method is to present a detection technique of white blood cells that are robust to imperfect shapes of blood cells with various image qualities. The input for this application is images from a microscope-slide translation video. The preprocessing stage is performed by stitching the input images. First, the overlapping parts of the images are determined, then stitching and blending processes of two input images are performed. Next, the Color Overlapping Windows is performed for white blood cell detection which consists of color filtering, window candidate checking, window marking, finds window overlaps, and window cropping processes. Experimental results show that this method could achieve an average of 82.12% detection accuracy of the leukocyte images.

Keywords: color overlapping windows, image stitching, leukocyte detection, white blood cell detection

Procedia PDF Downloads 274
3583 Design, Synthesis and Anti-Inflammatory Activity of Some Coumarin and Flavone Derivatives Containing 1,4 Dioxane Ring System

Authors: Asif Husain, Shah Alam Khan

Abstract:

Coumarins and flavones are oxygen containing heterocyclic compounds which are present in various biologically active compounds. Both the heterocyclic rings are associated with diverse biological actions, therefore considered as an important scaffold for the design of molecules of pharmaceutical interest. Aim: To synthesize and evaluate the in vivo anti-inflammatory activity of few coumrain and flavone derivatives containing 1,4 dioxane ring system. Materials and methods: Coumarin derivatives (3a-d) were synthesized by reacting 7,8 dihydroxy coumarin (2a) and its 4-methyl derivative (2b) with epichlorohydrin/ethylene dibromide. The flavone derivatives (10a-d) were prepared by using quercetin and 3,4 dihydroxy flavones. Compounds of both the series were also evaluated for their anti-inflammatory, analgesic activity and ulcerogenicity in animal models by reported methods. Results and Discussion: The structures of all newly synthesized compounds were confirmed with the help of IR, 1H NMR, 13C NMR and Mass spectral studies. Elemental analyses data for each element analyzed (C, H, N) was found to be within acceptable range of ±0.4 %. Flavone derivatives, but in particular quercetin containing 1,4 dioxane ring system (10d) showed better anti-inflammatory and analgesic activity along with reduced gastrointestinal toxicity as compared to other synthesized compounds. The results of anti-inflammatory and analgesic activities of both the series are comparable with the positive control, diclofenac. Conclusion: Compound 10d, a quercetin derivative, emerged as a lead molecule which exhibited potent anti-inflammatory and analgesic activity with significant reduced gastric toxicity.

Keywords: analgesic, anti-inflammatory, 1, 4 dioxane, coumarin, flavone

Procedia PDF Downloads 294
3582 Electrical Dault Detection of Photovoltaic System: A Short-Circuit Fault Case

Authors: Moustapha H. Ibrahim, Dahir Abdourahman

Abstract:

This document presents a short-circuit fault detection process in a photovoltaic (PV) system. The proposed method is developed in MATLAB/Simulink. It determines whatever the size of the installation number of the short circuit module. The proposed algorithm indicates the presence or absence of an abnormality on the power of the PV system through measures of hourly global irradiation, power output, and ambient temperature. In case a fault is detected, it displays the number of modules in a short circuit. This fault detection method has been successfully tested on two different PV installations.

Keywords: PV system, short-circuit, fault detection, modelling, MATLAB-Simulink

Procedia PDF Downloads 202
3581 Ship Detection Requirements Analysis for Different Sea States: Validation on Real SAR Data

Authors: Jaime Martín-de-Nicolás, David Mata-Moya, Nerea del-Rey-Maestre, Pedro Gómez-del-Hoyo, María-Pilar Jarabo-Amores

Abstract:

Ship detection is nowadays quite an important issue in tasks related to sea traffic control, fishery management and ship search and rescue. Although it has traditionally been carried out by patrol ships or aircrafts, coverage and weather conditions and sea state can become a problem. Synthetic aperture radars can surpass these coverage limitations and work under any climatological condition. A fast CFAR ship detector based on a robust statistical modeling of sea clutter with respect to sea states in SAR images is used. In this paper, the minimum SNR required to obtain a given detection probability with a given false alarm rate for any sea state is determined. A Gaussian target model using real SAR data is considered. Results show that SNR does not depend heavily on the class considered. Provided there is some variation in the backscattering of targets in SAR imagery, the detection probability is limited and a post-processing stage based on morphology would be suitable.

Keywords: SAR, generalized gamma distribution, detection curves, radar detection

Procedia PDF Downloads 429
3580 Neural Network in Fixed Time for Collision Detection between Two Convex Polyhedra

Authors: M. Khouil, N. Saber, M. Mestari

Abstract:

In this paper, a different architecture of a collision detection neural network (DCNN) is developed. This network, which has been particularly reviewed, has enabled us to solve with a new approach the problem of collision detection between two convex polyhedra in a fixed time (O (1) time). We used two types of neurons, linear and threshold logic, which simplified the actual implementation of all the networks proposed. The study of the collision detection is divided into two sections, the collision between a point and a polyhedron and then the collision between two convex polyhedra. The aim of this research is to determine through the AMAXNET network a mini maximum point in a fixed time, which allows us to detect the presence of a potential collision.

Keywords: collision identification, fixed time, convex polyhedra, neural network, AMAXNET

Procedia PDF Downloads 389
3579 Hull Detection from Handwritten Digit Image

Authors: Sriraman Kothuri, Komal Teja Mattupalli

Abstract:

In this paper we proposed a novel algorithm for recognizing hulls in a hand written digits. This is an extension to the work on “Digit Recognition Using Freeman Chain code”. In order to find out the hulls in a user given digit it is necessary to follow three steps. Those are pre-processing, Boundary Extraction and at last apply the Hull Detection system in a way to attain the better results. The detection of Hull Regions is mainly intended to increase the machine learning capability in detection of characters or digits. This can also extend this in order to get the hull regions and their intensities in Black Holes in Space Exploration.

Keywords: chain code, machine learning, hull regions, hull recognition system, SASK algorithm

Procedia PDF Downloads 378
3578 A Study of Adaptive Fault Detection Method for GNSS Applications

Authors: Je Young Lee, Hee Sung Kim, Kwang Ho Choi, Joonhoo Lim, Sebum Chun, Hyung Keun Lee

Abstract:

A purpose of this study is to develop efficient detection method for Global Navigation Satellite Systems (GNSS) applications based on adaptive estimation. Due to dependence of radio frequency signals, GNSS measurements are dominated by systematic errors in receiver’s operating environment. Thus, to utilize GNSS for aerospace or ground vehicles requiring high level of safety, unhealthy measurements should be considered seriously. For the reason, this paper proposes adaptive fault detection method to deal with unhealthy measurements in various harsh environments. By the proposed method, the test statistics for fault detection is generated by estimated measurement noise. Pseudorange and carrier-phase measurement noise are obtained at time propagations and measurement updates in process of Carrier-Smoothed Code (CSC) filtering, respectively. Performance of the proposed method was evaluated by field-collected GNSS measurements. To evaluate the fault detection capability, intentional faults were added to measurements. The experimental result shows that the proposed detection method is efficient in detecting unhealthy measurements and improves the accuracy of GNSS positioning under fault occurrence.

Keywords: adaptive estimation, fault detection, GNSS, residual

Procedia PDF Downloads 544
3577 Optical Flow Direction Determination for Railway Crossing Occupancy Monitoring

Authors: Zdenek Silar, Martin Dobrovolny

Abstract:

This article deals with the obstacle detection on a railway crossing (clearance detection). Detection is based on the optical flow estimation and classification of the flow vectors by K-means clustering algorithm. For classification of passing vehicles is used optical flow direction determination. The optical flow estimation is based on a modified Lucas-Kanade method.

Keywords: background estimation, direction of optical flow, K-means clustering, objects detection, railway crossing monitoring, velocity vectors

Procedia PDF Downloads 485
3576 Algorithm Research on Traffic Sign Detection Based on Improved EfficientDet

Authors: Ma Lei-Lei, Zhou You

Abstract:

Aiming at the problems of low detection accuracy of deep learning algorithm in traffic sign detection, this paper proposes improved EfficientDet based traffic sign detection algorithm. Multi-head self-attention is introduced in the minimum resolution layer of the backbone of EfficientDet to achieve effective aggregation of local and global depth information, and this study proposes an improved feature fusion pyramid with increased vertical cross-layer connections, which improves the performance of the model while introducing a small amount of complexity, the Balanced L1 Loss is introduced to replace the original regression loss function Smooth L1 Loss, which solves the problem of balance in the loss function. Experimental results show, the algorithm proposed in this study is suitable for the task of traffic sign detection. Compared with other models, the improved EfficientDet has the best detection accuracy. Although the test speed is not completely dominant, it still meets the real-time requirement.

Keywords: convolutional neural network, transformer, feature pyramid networks, loss function

Procedia PDF Downloads 73
3575 Prevention of Road Accidents by Computerized Drowsiness Detection System

Authors: Ujjal Chattaraj, P. C. Dasbebartta, S. Bhuyan

Abstract:

This paper aims to propose a method to detect the action of the driver’s eyes, using the concept of face detection. There are three major key contributing methods which can rapidly process the framework of the facial image and hence produce results which further can program the reactions of the vehicles as pre-programmed for the traffic safety. This paper compares and analyses the methods on the basis of their reaction time and their ability to deal with fluctuating images of the driver. The program used in this study is simple and efficient, built using the AdaBoost learning algorithm. Through this program, the system would be able to discard background regions and focus on the face-like regions. The results are analyzed on a common computer which makes it feasible for the end users. The application domain of this experiment is quite wide, such as detection of drowsiness or influence of alcohols in drivers or detection for the case of identification.

Keywords: AdaBoost learning algorithm, face detection, framework, traffic safety

Procedia PDF Downloads 131
3574 Intelligent Driver Safety System Using Fatigue Detection

Authors: Samra Naz, Aneeqa Ahmed, Qurat-ul-ain Mubarak, Irum Nausheen

Abstract:

Driver safety systems protect driver from accidents by sensing signs of drowsiness. The paper proposes a technique which can detect the signs of drowsiness and make corresponding decisions to make the driver alert. This paper presents a technique in which the driver will be continuously monitored by a camera and his eyes, head and mouth movements will be observed. If the drowsiness signs are detected on the basis of these three movements under the predefined criteria, driver will be declared as sleepy and he will get alert with the help of alarms. Three robust techniques of drowsiness detection are combined together to make a robust system that can prevent form accident.

Keywords: drowsiness, eye closure, fatigue detection, yawn detection

Procedia PDF Downloads 268
3573 Enhancement of Primary User Detection in Cognitive Radio by Scattering Transform

Authors: A. Moawad, K. C. Yao, A. Mansour, R. Gautier

Abstract:

The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the missed-detection probability is evaluated, and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings, and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved at the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysis- based energy detection.

Keywords: channel estimation, cognitive radio, scattering transform, spectrum sensing

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