Search results for: spontaneous smile detection

Authors: Emine G. Cansu Ergun

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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 159

Authors: Eshta Ranyal, Kamal Jain, Vikrant Ranyal

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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

Procedia PDF Downloads 136

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

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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

Procedia PDF Downloads 403

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

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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

Procedia PDF Downloads 349

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

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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

Procedia PDF Downloads 181

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

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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

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Authors: Majed Sanan, Mohammad Rammal, Wassim Rammal

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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 382

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

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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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Authors: Anton Stadler, Thorsten Ike

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In this paper, we present a video based smoke detection algorithm based on TVL1 optical flow estimation. The main part of the algorithm is an accumulating system for motion angles and upward motion speed of the flow field. We optimized the usage of TVL1 flow estimation for the detection of smoke with very low smoke density. Therefore, we use adapted flow parameters and estimate the flow field on difference images. We show in theory and in evaluation that this improves the performance of smoke detection significantly. We evaluate the smoke algorithm using videos with different smoke densities and different backgrounds. We show that smoke detection is very reliable in varying scenarios. Further we verify that our algorithm is very robust towards crowded scenes disturbance videos.

Keywords: low density, optical flow, upward smoke motion, video based smoke detection

Procedia PDF Downloads 355

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

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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

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

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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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Authors: Jie Yang, Jian-Min Meng

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A GPU-based floating object detection scheme is presented in this paper which is designed for floating mine detection tasks. This system uses contrast and motion information to eliminate as many false positives as possible while avoiding false negatives. The GPU computation platform is deployed to allow detecting objects in real-time. From the experimental results, it is shown that with certain configuration, the GPU-based scheme can speed up the computation up to one thousand times compared to the CPU-based scheme.

Keywords: object detection, GPU, motion estimation, parallel processing

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Authors: Vedant Subhash

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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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Authors: Manuel Alves, Angelica Reis, Armindo Lobo, Valdemar Leiras

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In industry 4.0, it is common to have a lot of sensor data. In this deluge of data, hints of possible problems are difficult to spot. The digital twin concept aims to help answer this problem, but it is mainly used as a monitoring tool to handle the visualisation of data. Failure detection is of paramount importance in any industry, and it consumes a lot of resources. Any improvement in this regard is of tangible value to the organisation. The aim of this paper is to add the ability to forecast test failures, curtailing detection times. To achieve this, several anomaly detection algorithms were compared with a symbolic regression approach. To this end, Isolation Forest, One-Class SVM and an auto-encoder have been explored. For the symbolic regression PySR library was used. The first results show that this approach is valid and can be added to the tools available in this context as a low resource anomaly detection method since, after training, the only requirement is the calculation of a polynomial, a useful feature in the digital twin context.

Keywords: anomaly detection, digital twin, industry 4.0, symbolic regression

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Authors: S. Ghasemi, K. Khorasani

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In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: component, formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault

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Authors: Katarzyna Drela, Miroslaw Wielgos, Mikolaj Wrobel, Barbara Lukomska

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Mesenchymal stem cells (MSCs) have a great potential in regenerative medicine. Since the initial number of isolated MSCs is limited, in vitro propagation is often required to reach sufficient numbers of cells for therapeutic applications. During long-term culture MSCs may undergo genetic or epigenetic alterations that subsequently increase the probability of spontaneous malignant transformation. Thus, factors that influence genomic stability of MSCs following long-term expansions need to be clarified before cultured MSCs are employed for clinical application. The aim of our study was to investigate the potential for spontaneous transformation of human neonatal cord blood (HUCB-MSCs) and adult bone marrow (BM-MSCs) derived MSCs. Materials and Methods: HUCB-MSCs and BM-MSCs were isolated by standard Ficoll gradient centrifugations method. Isolated cells were initially plated in high density 106 cells per cm2. After 48 h medium were changed and non-adherent cells were removed. The malignant transformation of MSCs in vitro was evaluated by morphological changes, proliferation rate, ability to enter cell senescence, the telomerase expression and chromosomal abnormality. Proliferation of MSCs was analyzed with WST-1 reduction method and population doubling time (PDT) was calculated at different culture stages. Then the expression pattern of genes characteristic for mesenchymal or epithelial cells, as well as transcriptions factors were examined by RT-PCR. Concomitantly, immunocytochemical analysis of gene-related proteins was employed. Results: Our studies showed that MSCs from all bone marrow isolations ultimately entered senescence and did not undergo spontaneous malignant transformation. However, HUCB-MSCs from one of the 15 donors displayed an increased proliferation rate, failed to enter senescence, and exhibited an altered cell morphology. In this sample we observed two different cell phenotypes: one mesenchymal-like exhibited spindle shaped morphology and express specific mesenchymal surface markers (CD73, CD90, CD105, CD166) with low proliferation rate, and the second one with round, densely package epithelial-like cells with significantly increased proliferation rate. The PDT of epithelial-like populations was around 1day and 100% of cells were positive for proliferation marker Ki-67. Moreover, HUCB-MSCs showed a positive expression of human telomerase reverse transcriptase (hTERT), cMYC and exhibit increased number of CFU during the long-term culture in vitro. Furthermore, karyotype analysis revealed chromosomal abnormalities including duplications. Conclusions: Our studies demonstrate that HUCB-MSCs are susceptible to spontaneous malignant transformation during long-term culture. Spontaneous malignant transformation process following in vitro culture has enormous effect on the biosafety issues of future cell-based therapies and regenerative medicine regimens.

Keywords: mesenchymal stem cells, spontaneous, transformation, long-term culture

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Authors: Raffaele A. Calogero

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RNAseq represents an attractive methodology for the detection of functional genomic variants. RNAseq results obtained from polyA+ RNA selection protocol (POLYA) and from exonic regions capturing protocol (ACCESS) indicate that ACCESS detects 10% more coding SNV/INDELs with respect to POLYA. ACCESS requires less reads for coding SNV detection with respect to POLYA. However, if the analysis aims at identifying SNV/INDELs also in the 5’ and 3’ UTRs, POLYA is definitively the preferred method. No particular advantage comes from ACCESS or POLYA in the detection of fusion transcripts.

Keywords: fusion transcripts, INDEL, RNA-seq, WES, SNV

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Authors: M. Y. Kang, Euntaek Yoon, H. D. Choi

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To calculate the full energy (FE) absorption peak efficiency for arbitrary volume sample, we developed and verified the EXVol (Efficiency calculator for EXtended Voluminous source) code which is based on effective solid angle method. EXVol is possible to describe the source area as a non-uniform three-dimensional (x, y, z) source. And decompose and set it into several sets of volume units. Users can equally divide (x, y, z) coordinate system to calculate the detection efficiency at a specific position of a cylindrical volume source. By determining the detection efficiency for differential volume units, the total radiative absolute distribution and the correction factor of the detection efficiency can be obtained from the nondestructive measurement of the source. In order to check the performance of the EXVol code, Si ingot of 20 cm in diameter and 50 cm in height were used as a source. The detector was moved at the collimation geometry to calculate the detection efficiency at a specific position and compared with the experimental values. In this study, the performance of the EXVol code was extended to obtain the detection efficiency distribution at a specific position in a large volume source.

Keywords: attenuation, EXVol, detection efficiency, volume source

Procedia PDF Downloads 185

Authors: Mohd Zamri Osman, Mohd Aizaini Maarof, Mohd Foad Rohani

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Human skin detection recognized as the primary step in most of the applications such as face detection, illicit image filtering, hand recognition and video surveillance. The performance of any skin detection applications greatly relies on the two components: feature extraction and classification method. Skin color is the most vital information used for skin detection purpose. However, color feature alone sometimes could not handle images with having same color distribution with skin color. A color feature of pixel-based does not eliminate the skin-like color due to the intensity of skin and skin-like color fall under the same distribution. Hence, the statistical color analysis will be exploited such mean and standard deviation as an additional feature to increase the reliability of skin detector. In this paper, we studied the effectiveness of statistical color feature for human skin detection. Furthermore, the paper analyzed the integrated color and texture using eight classifiers with three color spaces of RGB, YCbCr, and HSV. The experimental results show that the integrating statistical feature using Random Forest classifier achieved a significant performance with an F1-score 0.969.

Keywords: color space, neural network, random forest, skin detection, statistical feature

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Authors: Yang Zhou, Kangfeng Zheng, Wei Ni, Ren Ping Liu

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Software-defined networking (SDN) provides a solution for scalable network framework with decoupled control and data plane. However, this architecture also induces a particular distributed denial-of-service (DDoS) attack that can affect or even overwhelm the SDN network. DDoS attack detection problem has to date been mostly researched as entropy comparison problem. However, this problem lacks the utilization of SDN, and the results are not accurate. In this paper, we propose a DDoS attack detection method, which interprets DDoS detection as a signature matching problem and is formulated as Earth Mover’s Distance (EMD) model. Considering the feasibility and accuracy, we further propose to define the cost function of EMD to be a generalized Kullback-Leibler divergence. Simulation results show that our proposed method can detect DDoS attacks by comparing EMD values with the ones computed in the case without attacks. Moreover, our method can significantly increase the true positive rate of detection.

Keywords: DDoS detection, EMD, relative entropy, SDN

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Authors: Emhimed Saffor

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In this paper, the problem of edge detection in digital images is considered. Three methods of edge detection based on mathematical morphology algorithm were applied on two sets (Brain and Chest) CT images. 3x3 filter for first method, 5x5 filter for second method and 7x7 filter for third method under MATLAB programming environment. The results of the above-mentioned methods are subjectively evaluated. The results show these methods are more efficient and satiable for medical images, and they can be used for different other applications.

Keywords: CT images, Matlab, medical images, edge detection

Procedia PDF Downloads 337

Authors: Victoria Siriaki Jorry, I. S. Mbalawata, Hayong Shin

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The main objective in a change detection problem is to develop algorithms for efficient detection of gradual and/or abrupt changes in the parameter distribution of a process or time series data. In this paper, we present a modified cumulative (MCUSUM) algorithm to detect the start and end of a time-varying linear drift in mean value of a time series data based on likelihood ratio test procedure. The design, implementation and performance of the proposed algorithm for a linear drift detection is evaluated and compared to the existing CUSUM algorithm using different performance measures. An approach to accurately approximate the threshold of the MCUSUM is also provided. Performance of the MCUSUM for gradual change-point detection is compared to that of standard cumulative sum (CUSUM) control chart designed for abrupt shift detection using Monte Carlo Simulations. In terms of the expected time for detection, the MCUSUM procedure is found to have a better performance than a standard CUSUM chart for detection of the gradual change in mean. The algorithm is then applied and tested to a randomly generated time series data with a gradual linear trend in mean to demonstrate its usefulness.

Keywords: average run length, CUSUM control chart, gradual change detection, likelihood ratio test

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Authors: Sarita Puri, Tapan K. Chaudhuri

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Chaperonin GroEL is a tetradecameric Escherichia coli protein having identical subunits of 57 kDa. The elucidation of thermodynamic parameters related to stability for the native GroEL is not feasible as it undergoes irreversible unfolding because of its large size (800kDa) and multimeric nature. Nevertheless, it is important to determine the thermodynamic stability parameters for the highly stable GroEL protein as it helps in folding and holding of many substrate proteins during many cellular stresses. Properly folded monomers work as building-block for the formation of native tetradecameric GroEL. Spontaneous refolding behavior of monomeric GroEL makes it suitable for protein-denaturant interactions and thermodynamic stability based studies. The urea mediated unfolding is a three state process which means there is the formation of one intermediate state along with native and unfolded states. The heat mediated denaturation is a two-state process. The unfolding process is reversible as observed by the spontaneous refolding of denatured protein in both urea and head mediated refolding processes. Analysis of folding/unfolding data provides a measure of various thermodynamic stability parameters for the monomeric GroEL. The proposed mechanism of unfolding of monomeric GroEL is a three state process which involves formation of one stable intermediate having folded apical domain and unfolded equatorial, intermediate domains. Research in progress is to demonstrate the importance of specific residues in stability and oligomerization of GroEL protein. Several mutant versions of GroEL are under investigation to resolve the above mentioned issue.

Keywords: equilibrium unfolding, monomeric GroEl, spontaneous refolding, thermodynamic stability

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Authors: Kaveh Shahi, Helmi Z. M. Shafri, Ebrahim Taherzadeh

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In remote sensing, shadow causes problems in many applications such as change detection and classification. It is caused by objects which are elevated, thus can directly affect the accuracy of information. For these reasons, it is very important to detect shadows particularly in urban high spatial resolution imagery which created a significant problem. This paper focuses on automatic shadow detection based on a new spectral index for multispectral imagery known as Shadow Detection Index (SDI). The new spectral index was tested on different areas of World-View 2 images and the results demonstrated that the new spectral index has a massive potential to extract shadows effectively and automatically.

Keywords: spectral index, shadow detection, remote sensing images, World-View 2

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Authors: Nam-Uk Kim, Sung-Hwan Kim, Tai-Myoung Chung

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Typical security management systems are not suitable for detecting APT attack, because they cannot draw the big picture from trivial events of security solutions. Although SIEM solutions have security analysis engine for that, their security analysis mechanisms need to be verified in academic field. Although this paper proposes merely an architectural model for APT detection, we will keep studying on correlation analysis mechanism in the future.

Keywords: advanced persistent threat, anomaly detection, data mining

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Authors: Yeongyu Choi, Ju H. Park, Ho-Youl Jung

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In this paper, we propose labeling based RANSAC algorithm for lane detection. Advanced driver assistance systems (ADAS) have been widely researched to avoid unexpected accidents. Lane detection is a necessary system to assist keeping lane and lane departure prevention. The proposed vision based lane detection method applies Canny edge detection, inverse perspective mapping (IPM), K-means algorithm, mathematical morphology operations and 8 connected-component labeling. Next, random samples are selected from each labeling region for RANSAC. The sampling method selects the points of lane with a high probability. Finally, lane parameters of straight line or curve equations are estimated. Through the simulations tested on video recorded at daytime and nighttime, we show that the proposed method has better performance than the existing RANSAC algorithm in various environments.

Keywords: Canny edge detection, k-means algorithm, RANSAC, inverse perspective mapping

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Authors: Charalambous-Darden Nefi, Antoniou Phivi

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This study presents drawing as an alternative tool for facilitating interaction and communication among the members of a class (teachers and students) in an inclusive school setting. It applies elements of the Collaborative Drawing Method (CDM), an interactive method of drawing where two individuals draw together on the same surface. For the past ten years, the facilitators of this study have been researching the effects of spontaneous and non-spontaneous drawing upon elementary school students with Autism Spectrum Conditions (ASC). This research eventually led them to the application of elements of the CDM. The method was applied to both adults and children and children with one another. The astonishing outcomes of these applications indicate that collaborative drawing, with its inclusive nature, has the potential to help individuals develop interaction and communication among themselves, making it suitable for everyone. This workshop aims to allow the participants to become familiar with the CDM by applying it during the workshop, with the ultimate goal of enhancing their educational approaches by adding the CDM to their teaching methods.

Keywords: autism, collaborative drawing, autism spectrum condition, ASC

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Authors: Alison Ryan, Himani Chhabra, Mohammed Dungarwalla, Judith Jones

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Background: Impacted and ectopic teeth present in 1-2% of orthodontic patients and often require joint surgical and orthodontic management. The authors present two patients undergoing orthodontic treatment, where the impacted teeth, in a hopeless position, spontaneously erupted during the period of cessation of general anaesthetic lists during the COVID-19 pandemic. Patient information: A healthy 11-year-old boy was referred to the Department of Oral and Maxillofacial Surgery for the management of a mesioangular impacted LR7. The patient was seen by the joint oral surgery/orthodontic team, who planned for the removal of the LR7 under general anaesthetic. A healthy 13-year-old boy was referred to the same Department and team for surgical extraction of unerupted and buccally impacted UL3 and UR3 under general anaesthetic. Management and outcome: The majority of elective dental-alveolar work ceased as a result of the global pandemic. On resumption of activity, the first patient was reviewed in July 2021. The LR7 had spontaneously erupted in a favourable position, and following MDT review, a decision was made to forgo any further surgical intervention. The second patient was reviewed in July 2021. The UL3 had clinically erupted, and there was radiographic evidence of favourable movement of UR3. Due to the nature of the patient’s malocclusion, the decision was made to proceed with the extractions as previously planned. Key Learning Points: Severely impacted teeth do have a prospect of spontaneous eruption or alignment without clinical intervention, and current literature states the initial location, axial inclination, degree of root formation, and relation of the impacted tooth to adjacent teeth roots may influence spontaneous eruption. There is potential to introduce a period of observation to account for this possibility in the developing dentition, with the aim of reducing the unnecessary need for surgical intervention. This could help prevent episodes of general anaesthetic and allocate theatre space more appropriately.

Keywords: spontaneous eruption, impaction, observation, hopeless position, surgical, orthodontic, change in treatment plan

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Authors: Gherbi Nabil

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Detection of ground targets in SAR radar images is an important area for radar information processing. In the literature, various algorithms have been discussed in this context. However, most of them are of low robustness and accuracy. To this end, we discuss target detection in SAR images based on compressive sensing. Firstly, traditional SAR image target detection algorithms are discussed, and their limitations are highlighted. Secondly, a compressive sensing method is proposed based on the sparsity of SAR images. Next, the detection problem is solved using Multiple Measurements Vector configuration. Furthermore, a robust Alternating Direction Method of Multipliers (ADMM) is developed to solve the optimization problem. Finally, the detection results obtained using raw complex data are presented. Experimental results on real SAR images have verified the effectiveness of the proposed algorithm.

Keywords: compressive sensing, raw complex data, synthetic aperture radar, ADMM

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Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

Procedia PDF Downloads 510