Search results for: Lattice reduction aided detection
2852 Synthesis of Gold Nanoparticles Stabilized in Na-Montmorillonite for Nitrophenol Reduction
Authors: F. Ammari, M. Chenouf
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Synthesis of gold nanoparticles has attracted much attention since the pioneering discovery of the high catalytic activity of supported gold nanoparticles in the reaction of CO oxidation at low temperature. In this research field, we used Na-montmorillonite for gold nanoparticles stabilization; various gold loading percentage 1, 2 and 5% were used for gold nanoparticles preparation. The gold nanoparticles were obtained using chemical reduction method using NaBH4 as reductant agent. The obtained gold nanoparticles stabilized in Na-montmorillonite were used as catalysts for the reduction of 4- nitrophenol to aminophenol with sodium borohydride at room temperature. The UV-Vis results confirmed directly the gold nanoparticles formation. The XRD and N2 adsorption results showed the formation of gold nanoparticles in the pores of montmorillonite with an average size of 5 nm obtained on samples with 2% gold loading percentage. The gold particles size increased with the increase of gold loading percentage. The reduction reaction of 4- nitrophenol into 4-aminophenol with NaBH4 catalyzed by Au-Namontmorillonite catalyst exhibits remarkably a high activity; the reaction was completed within 9 min for 1%Au-Na-montmorillonite and within 3 min for 2%Au-Na-montmorillonite.Keywords: Chemical reduction, gold, montmorillonite, nanoparticles, 4-nitrophenol.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21172851 Human Fall Detection by FMCW Radar Based on Time-Varying Range-Doppler Features
Authors: Xiang Yu, Chuntao Feng, Lu Yang, Meiyang Song, Wenhao Zhou
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The existing two-dimensional micro-Doppler features extraction ignores the correlation information between the spatial and temporal dimension features. For the range-Doppler map, the time dimension is introduced, and a frequency modulation continuous wave (FMCW) radar human fall detection algorithm based on time-varying range-Doppler features is proposed. Firstly, the range-Doppler sequence maps are generated from the echo signals of the continuous motion of the human body collected by the radar. Then the three-dimensional data cube composed of multiple frames of range-Doppler maps is input into the three-dimensional Convolutional Neural Network (3D CNN). The spatial and temporal features of time-varying range-Doppler are extracted by the convolution layer and pool layer at the same time. Finally, the extracted spatial and temporal features are input into the fully connected layer for classification. The experimental results show that the proposed fall detection algorithm has a detection accuracy of 95.66%.
Keywords: FMCW radar, fall detection, 3D CNN, time-varying range-Doppler features.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5402850 Deep Learning Based, End-to-End Metaphor Detection in Greek with Recurrent and Convolutional Neural Networks
Authors: Konstantinos Perifanos, Eirini Florou, Dionysis Goutsos
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This paper presents and benchmarks a number of end-to-end Deep Learning based models for metaphor detection in Greek. We combine Convolutional Neural Networks and Recurrent Neural Networks with representation learning to bear on the metaphor detection problem for the Greek language. The models presented achieve exceptional accuracy scores, significantly improving the previous state-of-the-art results, which had already achieved accuracy 0.82. Furthermore, no special preprocessing, feature engineering or linguistic knowledge is used in this work. The methods presented achieve accuracy of 0.92 and F-score 0.92 with Convolutional Neural Networks (CNNs) and bidirectional Long Short Term Memory networks (LSTMs). Comparable results of 0.91 accuracy and 0.91 F-score are also achieved with bidirectional Gated Recurrent Units (GRUs) and Convolutional Recurrent Neural Nets (CRNNs). The models are trained and evaluated only on the basis of training tuples, the related sentences and their labels. The outcome is a state-of-the-art collection of metaphor detection models, trained on limited labelled resources, which can be extended to other languages and similar tasks.Keywords: Metaphor detection, deep learning, representation learning, embeddings.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5662849 Virtual Environment Design Guidelines for Elderly People in Early Detection of Dementia
Authors: Syadiah Nor Wan Shamsuddin, Valerie Lesk , Hassan Ugail
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Early detection of dementia by testing the spatial memory can be applied using a virtual environment. This paper presents guidelines on how to design a virtual environment specifically for elderly in early detection of dementia. The specific design needs to be considered because the effectiveness of the technology relies on the ability of the end user to use it. The primary goal of these guidelines is to promote accessibility. Based on these guidelines, a virtual simulation was developed and evaluated. The results on usability of acceptance and satisfaction that are tested on young (control group) and elderly participants indicate that these guidelines are reliable and useful for use with elderly people.Keywords: Virtual Environment, spatial memory, design, guidelines
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18632848 Visualization of Code Clone Detection Results and the Implementation with Structured Data
Authors: Kazuaki Maeda
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This paper describes a code clone visualization method, called FC graph, and the implementation issues. Code clone detection tools usually show the results in a textual representation. If the results are large, it makes a problem to software maintainers with understanding them. One of the approaches to overcome the situation is visualization of code clone detection results. A scatter plot is a popular approach to the visualization. However, it represents only one-to-one correspondence and it is difficult to find correspondence of code clones over multiple files. FC graph represents correspondence among files, code clones and packages in Java. All nodes in FC graph are positioned using force-directed graph layout, which is dynami- cally calculated to adjust the distances of nodes until stabilizing them. We applied FC graph to some open source programs and visualized the results. In the author’s experience, FC graph is helpful to grasp correspondence of code clones over multiple files and also code clones with in a file.
Keywords: code clone detection, program comprehension, software maintenance, visualization
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15212847 Structural and Optical Properties ofInxAlyGa1-x-yN Quaternary Alloys
Authors: N. H. Abd Raof, H. Abu Hassan, S.K. Mohd Bakhori, S. S. Ng, Z. Hassan
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Quaternary InxAlyGa1-x-yN semiconductors have attracted much research interest because the use of this quaternary offer the great flexibility in tailoring their band gap profile while maintaining their lattice-matching and structural integrity. The structural and optical properties of InxAlyGa1-x-yN alloys grown by molecular beam epitaxy (MBE) is presented. The structural quality of InxAlyGa1-x-yN layers was characterized using high-resolution X-ray diffraction (HRXRD). The results confirm that the InxAlyGa1-x-yN films had wurtzite structure and without phase separation. As the In composition increases, the Bragg angle of the (0002) InxAlyGa1-x-yN peak gradually decreases, indicating the increase in the lattice constant c of the alloys. FWHM of (0002) InxAlyGa1-x-yN decreases with increasing In composition from 0 to 0.04, that could indicate the decrease of quality of the samples due to point defects leading to non-uniformity of the epilayers. UV-VIS spectroscopy have been used to study the energy band gap of InxAlyGa1-x-yN. As the indium (In) compositions increases, the energy band gap decreases. However, for InxAlyGa1-x-yN with In composition of 0.1, the band gap shows a sudden increase in energy. This is probably due to local alloy compositional fluctuations in the epilayer. The bowing parameter which appears also to be very sensitive on In content is investigated and obtained b = 50.08 for quaternary InxAlyGa1-x-yN alloys. From photoluminescence (PL) measurement, green luminescence (GL) appears at PL spectrum of InxAlyGa1-x-yN, emitted for all x at ~530 nm and it become more pronounced as the In composition (x) increased, which is believed cause by gallium vacancies and related to isolated native defects.Keywords: HRXRD, nitrides, PL, quaternary, UV-VIS.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15802846 The Knapsack Sharing Problem: A Tree Search Exact Algorithm
Authors: Mhand Hifi, Hedi Mhalla
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In this paper, we study the knapsack sharing problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of a tree search for optimally solving the problem. The used method combines two complementary phases: a reduction interval search phase and a branch and bound procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for decomposing the problem into a series of knapsack problems. Second, the tree search procedure is applied in order to attain a set of optimal capacities characterizing the knapsack problems. Finally, the performance of the proposed optimal algorithm is evaluated on a set of instances of the literature and its runtime is compared to the best exact algorithm of the literature.
Keywords: Branch and bound, combinatorial optimization, knap¬sack, knapsack sharing, heuristics, interval reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15652845 Intelligent Agents for Distributed Intrusion Detection System
Authors: M. Benattou, K. Tamine
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This paper presents a distributed intrusion detection system IDS, based on the concept of specialized distributed agents community representing agents with the same purpose for detecting distributed attacks. The semantic of intrusion events occurring in a predetermined network has been defined. The correlation rules referring the process which our proposed IDS combines the captured events that is distributed both spatially and temporally. And then the proposed IDS tries to extract significant and broad patterns for set of well-known attacks. The primary goal of our work is to provide intrusion detection and real-time prevention capability against insider attacks in distributed and fully automated environments.Keywords: Mobile agent, specialized agent, interpreter agent, event rules, correlation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18392844 Ductility, Rμ, and Overstrength Factors for V Braced Reinforced Concrete Buildings
Authors: Birendra Kumar Bohara
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Steel bracings are used to improve the seismic behaviors of the structures. In this study, 8, 12 and 16 story reinforced concrete (RC) buildings with steel bracings are used in three base shear contributions (25%, 50% and 75%) in the columns. With the help of pushover analysis and capacity curves, the overstrength factors, ductility factors and ductility reduction factors are investigated for braced RC buildings. It is observed that when the base shear contribution in the columns increases the ductility reduction factor also increases. The results show that when the time period of the structures increases, the ductility reduction factors of the structures decrease.
Keywords: Steel bracing, overstrength factor, ductility, ductility reduction factors, base shear contributions.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3982843 Detection of Cyberattacks on the Metaverse Based on First-Order Logic
Authors: Sulaiman Al Amro
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There are currently considerable challenges concerning data security and privacy, particularly in relation to modern technologies. This includes the virtual world known as the Metaverse, which consists of a virtual space that integrates various technologies, and therefore susceptible to cyber threats such as malware, phishing, and identity theft. This has led recent studies to propose the development of Metaverse forensic frameworks and the integration of advanced technologies, including machine learning for intrusion detection and security. In this context, the application of first-order logic offers a formal and systematic approach to defining the conditions of cyberattacks, thereby contributing to the development of effective detection mechanisms. In addition, formalizing the rules and patterns of cyber threats has the potential to enhance the overall security posture of the Metaverse and thus the integrity and safety of this virtual environment. The current paper focuses on the primary actions employed by avatars for potential attacks, including Interval Temporal Logic (ITL) and behavior-based detection to detect an avatar’s abnormal activities within the Metaverse. The research established that the proposed framework attained an accuracy of 92.307%, resulting in the experimental results demonstrating the efficacy of ITL, including its superior performance in addressing the threats posed by avatars within the Metaverse domain.
Keywords: Cyberattacks, detection, first-order logic, Metaverse, privacy, security.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 842842 Designing a Framework for Network Security Protection
Authors: Eric P. Jiang
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As the Internet continues to grow at a rapid pace as the primary medium for communications and commerce and as telecommunication networks and systems continue to expand their global reach, digital information has become the most popular and important information resource and our dependence upon the underlying cyber infrastructure has been increasing significantly. Unfortunately, as our dependency has grown, so has the threat to the cyber infrastructure from spammers, attackers and criminal enterprises. In this paper, we propose a new machine learning based network intrusion detection framework for cyber security. The detection process of the framework consists of two stages: model construction and intrusion detection. In the model construction stage, a semi-supervised machine learning algorithm is applied to a collected set of network audit data to generate a profile of normal network behavior and in the intrusion detection stage, input network events are analyzed and compared with the patterns gathered in the profile, and some of them are then flagged as anomalies should these events are sufficiently far from the expected normal behavior. The proposed framework is particularly applicable to the situations where there is only a small amount of labeled network training data available, which is very typical in real world network environments.Keywords: classification, data analysis and mining, network intrusion detection, semi-supervised learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18022841 Fast Object/Face Detection Using Neural Networks and Fast Fourier Transform
Authors: Hazem M. El-Bakry, Qiangfu Zhao
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Recently, fast neural networks for object/face detection were presented in [1-3]. The speed up factor of these networks relies on performing cross correlation in the frequency domain between the input image and the weights of the hidden layer. But, these equations given in [1-3] for conventional and fast neural networks are not valid for many reasons presented here. In this paper, correct equations for cross correlation in the spatial and frequency domains are presented. Furthermore, correct formulas for the number of computation steps required by conventional and fast neural networks given in [1-3] are introduced. A new formula for the speed up ratio is established. Also, corrections for the equations of fast multi scale object/face detection are given. Moreover, commutative cross correlation is achieved. Simulation results show that sub-image detection based on cross correlation in the frequency domain is faster than classical neural networks.Keywords: Conventional Neural Networks, Fast Neural Networks, Cross Correlation in the Frequency Domain.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24952840 Detection of Breast Cancer in the JPEG2000 Domain
Authors: Fayez M. Idris, Nehal I. AlZubaidi
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Breast cancer detection techniques have been reported to aid radiologists in analyzing mammograms. We note that most techniques are performed on uncompressed digital mammograms. Mammogram images are huge in size necessitating the use of compression to reduce storage/transmission requirements. In this paper, we present an algorithm for the detection of microcalcifications in the JPEG2000 domain. The algorithm is based on the statistical properties of the wavelet transform that the JPEG2000 coder employs. Simulation results were carried out at different compression ratios. The sensitivity of this algorithm ranges from 92% with a false positive rate of 4.7 down to 66% with a false positive rate of 2.1 using lossless compression and lossy compression at a compression ratio of 100:1, respectively.Keywords: Breast cancer, JPEG2000, mammography, microcalcifications.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15822839 A Real-time Computer Vision System for VehicleTracking and Collision Detection
Authors: Mustafa Kisa, Fatih Mehmet Botsali
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Recent developments in automotive technology are focused on economy, comfort and safety. Vehicle tracking and collision detection systems are attracting attention of many investigators focused on safety of driving in the field of automotive mechatronics. In this paper, a vision-based vehicle detection system is presented. Developed system is intended to be used in collision detection and driver alert. The system uses RGB images captured by a camera in a car driven in the highway. Images captured by the moving camera are used to detect the moving vehicles in the image. A vehicle ahead of the camera is detected in daylight conditions. The proposed method detects moving vehicles by subtracting successive images. Plate height of the vehicle is determined by using a plate recognition algorithm. Distance of the moving object is calculated by using the plate height. After determination of the distance of the moving vehicle relative speed of the vehicle and Time-to-Collision are calculated by using distances measured in successive images. Results obtained in road tests are discussed in order to validate the use of the proposed method.
Keywords: Image possessing, vehicle tracking, license plate detection, computer vision.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 31062838 Surface Flattening Assisted with 3D Mannequin Based On Minimum Energy
Authors: Shih-Wen Hsiao, Rong-Qi Chen, Chien-Yu Lin
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The topic of surface flattening plays a vital role in the field of computer aided design and manufacture. Surface flattening enables the production of 2D patterns and it can be used in design and manufacturing for developing a 3D surface to a 2D platform, especially in fashion design. This study describes surface flattening based on minimum energy methods according to the property of different fabrics. Firstly, through the geometric feature of a 3D surface, the less transformed area can be flattened on a 2D platform by geodesic. Then, strain energy that has accumulated in mesh can be stably released by an approximate implicit method and revised error function. In some cases, cutting mesh to further release the energy is a common way to fix the situation and enhance the accuracy of the surface flattening, and this makes the obtained 2D pattern naturally generate significant cracks. When this methodology is applied to a 3D mannequin constructed with feature lines, it enhances the level of computer-aided fashion design. Besides, when different fabrics are applied to fashion design, it is necessary to revise the shape of a 2D pattern according to the properties of the fabric. With this model, the outline of 2D patterns can be revised by distributing the strain energy with different results according to different fabric properties. Finally, this research uses some common design cases to illustrate and verify the feasibility of this methodology.
Keywords: Surface flattening, Strain energy, Minimum energy, approximate implicit method, Fashion design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26102837 Methane versus Carbon Dioxide: Mitigation Prospects
Authors: Alexander J. Severinsky, Allen L. Sessoms
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Atmospheric carbon dioxide (CO2) has dominated the discussion around the causes of climate change. This is a reflection of a 100-year time horizon for all greenhouse gases that became a norm. The 100-year time horizon is much too long – and yet, almost all mitigation efforts, including those set in the near-term frame of within 30 years, are still geared toward it. In this paper, we show that for a 30-year time horizon, methane (CH4) is the greenhouse gas whose radiative forcing exceeds that of CO2. In our analysis, we use the radiative forcing of greenhouse gases in the atmosphere, because they directly affect the rise in temperature on Earth. We found that in 2019, the radiative forcing (RF) of methane was ~2.5 W/m2 and that of carbon dioxide was ~2.1 W/m2. Under a business-as-usual (BAU) scenario until 2050, such forcing would be ~2.8 W/m2 and ~3.1 W/m2 respectively. There is a substantial spread in the data for anthropogenic and natural methane (CH4) emissions, along with natural gas, (which is primarily CH4), leakages from industrial production to consumption. For this reason, we estimate the minimum and maximum effects of a reduction of these leakages, and assume an effective immediate reduction by 80%. Such action may serve to reduce the annual radiative forcing of all CH4 emissions by ~15% to ~30%. This translates into a reduction of RF by 2050 from ~2.8 W/m2 to ~2.5 W/m2 in the case of the minimum effect that can be expected, and to ~2.15 W/m2 in the case of the maximum effort to reduce methane leakages. Under the BAU, we find that the RF of CO2 will increase from ~2.1 W/m2 now to ~3.1 W/m2 by 2050. We assume a linear reduction of 50% in anthropogenic emission over the course of the next 30 years, which would reduce the radiative forcing of CO2 from ~3.1 W/m2 to ~2.9 W/m2. In the case of "net zero," the other 50% of only anthropogenic CO2 emissions reduction would be limited to being either from sources of emissions or directly from the atmosphere. In this instance, the total reduction would be from ~3.1 W/m2 to ~2.7 W/m2, or ~0.4 W/m2. To achieve the same radiative forcing as in the scenario of maximum reduction of methane leakages of ~2.15 W/m2, an additional reduction of radiative forcing of CO2 would be approximately 2.7 -2.15 = 0.55 W/m2. In total, one would need to remove ~660 GT of CO2 from the atmosphere in order to match the maximum reduction of current methane leakages, and ~270 GT of CO2 from emitting sources, to reach "negative emissions". This amounts to over 900 GT of CO2.
Keywords: Methane Leakages, Methane Radiative Forcing, Methane Mitigation, Methane Net Zero.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6562836 Efficiency of Different GLR Test-statistics for Spatial Signal Detection
Authors: Olesya Bolkhovskaya, Alexander Maltsev
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In this work the characteristics of spatial signal detec¬tion from an antenna array in various sample cases are investigated. Cases for a various number of available prior information about the received signal and the background noise are considered. The spatial difference between a signal and noise is only used. The performance characteristics and detecting curves are presented. All test-statistics are obtained on the basis of the generalized likelihood ratio (GLR). The received results are correct for a short and long sample.
Keywords: GLR test-statistic, detection task, generalized likelihood ratio, antenna array, detection curves, performance characteristics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15222835 The Effects of Different Level Cluster Tip Reduction and Foliar Boric Acid Applications on Yield and Yield Components of Italia Grape Cultivar
Authors: A. Akin
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This study was carried out on Italia grape variety (Vitis vinifera L.) in Konya province, Turkey in 2016. The cultivar is five years old and grown on 1103 Paulsen rootstock. It was determined the effects of applications of the Control (C), 1/3 Cluster Tip Reduction (1/3 CTR), 1/6 Cluster Tip Reduction (1/6 CTR), 1/9 Cluster Tip Reduction (1/9 CTR), 1/3 CTR+Boric Acid (BA), 1/6 CTR+BA, 1/9 CTR+BA, on yield and yield components of the Italia grape variety. The results were obtained as the highest fresh grape yield (4.74 g) with 1/9 CTR+BA application; the highest cluster weight (220.08 g) with 1/3 CTR application; the highest 100 berry weight (565.85 g) with 1/9 CTR+BA application; as the highest maturity index (49.28) with 1/9 CTR+BA application; as the highest must yield (685.33 ml/kg) with 1/3 CTR+BA and (685.33 ml/kg) with 1/9 CTR+BA applications. To increase the fresh grape yield, 100 berry weight and maturity index in the Italia grape variety, the 1/9 CTR+BA application can be recommended.Keywords: Italia grape variety, boric acid, cluster tip reduction, yield, yield components.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10032834 Stereoselective Reduction of Amino Ketone with Sodium Borohydride in the Presence of Metal Chloride. A Simple Pathway to S-Propranolol
Authors: R. Inkum, A. Teerawutgulrag, P. Puangsombat, N. Rakariyatham
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Propranolol is worldwide hypertension drug that is active in S-isomer. Patients must use this drug throughout their lives, and this action employsa significant level of expenditure. A simpler synthesis and lower cost can reduce the price for the patient. A sis pathway of S-propranolol starting from protection of (R,S)-propranolol with di-t-butyldicarbonate and then the product is oxidized with pyridiniumchlorochromate. The selective reduction of ketone occurrs with sodiumborohydride in the presence of metal chloride provided S-propranolol.
Keywords: S-propranolol, selective reduction, sodium borohydride, metal chloride
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21662833 Modern Spectrum Sensing Techniques for Cognitive Radio Networks: Practical Implementation and Performance Evaluation
Authors: Antoni Ivanov, Nikolay Dandanov, Nicole Christoff, Vladimir Poulkov
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Spectrum underutilization has made cognitive radio a promising technology both for current and future telecommunications. This is due to the ability to exploit the unused spectrum in the bands dedicated to other wireless communication systems, and thus, increase their occupancy. The essential function, which allows the cognitive radio device to perceive the occupancy of the spectrum, is spectrum sensing. In this paper, the performance of modern adaptations of the four most widely used spectrum sensing techniques namely, energy detection (ED), cyclostationary feature detection (CSFD), matched filter (MF) and eigenvalues-based detection (EBD) is compared. The implementation has been accomplished through the PlutoSDR hardware platform and the GNU Radio software package in very low Signal-to-Noise Ratio (SNR) conditions. The optimal detection performance of the examined methods in a realistic implementation-oriented model is found for the common relevant parameters (number of observed samples, sensing time and required probability of false alarm).Keywords: Cognitive radio, dynamic spectrum access, GNU Radio, spectrum sensing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11842832 3D Human Reconstruction over Cloud Based Image Data via AI and Machine Learning
Authors: Kaushik Sathupadi, Sandesh Achar
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Human action recognition (HAR) modeling is a critical task in machine learning. These systems require better techniques for recognizing body parts and selecting optimal features based on vision sensors to identify complex action patterns efficiently. Still, there is a considerable gap and challenges between images and videos, such as brightness, motion variation, and random clutters. This paper proposes a robust approach for classifying human actions over cloud-based image data. First, we apply pre-processing and detection, human and outer shape detection techniques. Next, we extract valuable information in terms of cues. We extract two distinct features: fuzzy local binary patterns and sequence representation. Then, we applied a greedy, randomized adaptive search procedure for data optimization and dimension reduction, and for classification, we used a random forest. We tested our model on two benchmark datasets, AAMAZ and the KTH Multi-view Football datasets. Our HAR framework significantly outperforms the other state-of-the-art approaches and achieves a better recognition rate of 91% and 89.6% over the AAMAZ and KTH Multi-view Football datasets, respectively.
Keywords: Computer vision, human motion analysis, random forest, machine learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 682831 Modified Hankel Matrix Approach for Model Order Reduction in Time Domain
Authors: C. B. Vishwakarma
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The author presented a method for model order reduction of large-scale time-invariant systems in time domain. In this approach, two modified Hankel matrices are suggested for getting reduced order models. The proposed method is simple, efficient and retains stability feature of the original high order system. The viability of the method is illustrated through the examples taken from literature.
Keywords: Model Order Reduction, Stability, Hankel Matrix, Time-Domain, Integral Square Error.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20872830 Resilient Machine Learning in the Nuclear Industry: Crack Detection as a Case Study
Authors: Anita Khadka, Gregory Epiphaniou, Carsten Maple
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There is a dramatic surge in the adoption of Machine Learning (ML) techniques in many areas, including the nuclear industry (such as fault diagnosis and fuel management in nuclear power plants), autonomous systems (including self-driving vehicles), space systems (space debris recovery, for example), medical surgery, network intrusion detection, malware detection, to name a few. Artificial Intelligence (AI) has become a part of everyday modern human life. To date, the predominant focus has been developing underpinning ML algorithms that can improve accuracy, while factors such as resiliency and robustness of algorithms have been largely overlooked. If an adversarial attack is able to compromise the learning method or data, the consequences can be fatal, especially but not exclusively in safety-critical applications. In this paper, we present an in-depth analysis of five adversarial attacks and two defence methods on a crack detection ML model. Our analysis shows that it can be dangerous to adopt ML techniques without rigorous testing, since they may be vulnerable to adversarial attacks, especially in security-critical areas such as the nuclear industry. We observed that while the adopted defence methods can effectively defend against different attacks, none of them could protect against all five adversarial attacks entirely.
Keywords: Resilient Machine Learning, attacks, defences, nuclear industry, crack detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5202829 Numerical Study of Base Drag Reduction Using Locked Vortex Flow Management Technique for Lower Subsonic Regime
Authors: Kailas S. Jagtap, Karthik Sundarraj, Nirmal Kumar, S. Rajnarasimha, Prakash S. Kulkarni
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The issue of turbulence base streams and the drag related to it have been of important attention for rockets, missiles, and aircraft. Different techniques are used for base drag reduction. This paper presents the numerical study of numerous drag reduction technique. The base drag or afterbody drag of bluff bodies can be reduced easily using locked vortex drag reduction technique. For bluff bodies having a cylindrical shape, the base drag is much larger compared to streamlined bodies. For such bodies using splitter plates, the vortex can be trapped between the base and the plate, which results in smooth flow. Splitter plate with round and curved corner shapes has influence in drag reduction. In this paper, the comparison is done between single splitter plate as different positions and with the bluff body. Base drag for the speed of 30m/s can be reduced about 20% to 30% by using single splitter plate as compared to the bluff body.
Keywords: Base drag, bluff body, splitter plate, vortex flow, ANSYS, Fluent.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9342828 Characteristics of Wall Thickness Increase in Pipe Reduction Process using Planetary Rolls
Authors: Yuji Kotani, Shunsuke Kanai, Hisaki Watari
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In recent years, global warming has become a worldwide problem. The reduction of carbon dioxide emissions is a top priority for many companies in the manufacturing industry. In the automobile industry as well, the reduction of carbon dioxide emissions is one of the most important issues. Technology to reduce the weight of automotive parts improves the fuel economy of automobiles, and is an important technology for reducing carbon dioxide. Also, even if this weight reduction technology is applied to electric automobiles rather than gasoline automobiles, reducing energy consumption remains an important issue. Plastic processing of hollow pipes is one important technology for realizing the weight reduction of automotive parts. Ohashi et al. [1],[2] present an example of research on pipe formation in which a process was carried out to enlarge a pipe diameter using a lost core, achieving the suppression of wall thickness reduction and greater pipe expansion than hydroforming. In this study, we investigated a method to increase the wall thickness of a pipe through pipe compression using planetary rolls. The establishment of a technology whereby the wall thickness of a pipe can be controlled without buckling the pipe is an important technology for the weight reduction of products. Using the finite element analysis method, we predicted that it would be possible to increase the compression of an aluminum pipe with a 3mm wall thickness by approximately 20%, and wall thickness by approximately 20% by pressing the hollow pipe with planetary rolls.Keywords: Pipe-Forming, Wall Thickness, Finite-element-method
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29902827 Reasons for the Slow Uptake of Embodied Carbon Estimation in the Sri Lankan Building Sector
Authors: Amalka Nawarathna, Nirodha Fernando, Zaid Alwan
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Global carbon reduction is not merely a responsibility of environmentally advanced developed countries, but also a responsibility of developing countries regardless of their less impact on global carbon emissions. In recognition of that, Sri Lanka as a developing country has initiated promoting green building construction as one reduction strategy. However, notwithstanding the increasing attention on Embodied Carbon (EC) reduction in the global building sector, they still mostly focus on Operational Carbon (OC) reduction (through improving operational energy). An adequate attention has not yet been given on EC estimation and reduction. Therefore, this study aims to identify the reasons for the slow uptake of EC estimation in the Sri Lankan building sector. To achieve this aim, 16 numbers of global barriers to estimate EC were identified through existing literature. They were then subjected to a pilot survey to identify the significant reasons for the slow uptake of EC estimation in the Sri Lankan building sector. A questionnaire with a three-point Likert scale was used to this end. The collected data were analysed using descriptive statistics. The findings revealed that 11 out of 16 challenges/ barriers are highly relevant as reasons for the slow uptake in estimating EC in buildings in Sri Lanka while the other five challenges/ barriers remain as moderately relevant reasons. Further, the findings revealed that there are no low relevant reasons. Eventually, the paper concluded that all the known reasons are significant to the Sri Lankan building sector and it is necessary to address them in order to upturn the attention on EC reduction.
Keywords: Embodied carbon emissions, embodied carbon estimation, global carbon reduction, Sri Lankan building sector.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8352826 Normalizing Flow to Augmented Posterior: Conditional Density Estimation with Interpretable Dimension Reduction for High Dimensional Data
Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L Duan
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The conditional density characterizes the distribution of a response variable y given other predictor x, and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts a motivating starting point. In this work, we extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zP , zN]. The zP component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zN component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach, coined Augmented Posterior CDE (AP-CDE), only requires a simple modification on the common normalizing flow framework, while significantly improving the interpretation of the latent component, since zP represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of x-related variations due to factors such as lighting condition and subject id, from the other random variations. Further, the experiments show that an unconditional NF neural network, based on an unsupervised model of z, such as Gaussian mixture, fails to generate interpretable results.
Keywords: Conditional density estimation, image generation, normalizing flow, supervised dimension reduction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1852825 Development of an Infrared Thermography Method with CO2 Laser Excitation, Applied to Defect Detection in CFRP
Authors: Sam-Ang Keo, Franck Brachelet, Florin Breaban, Didier Defer
Abstract:
This paper presents a NDT by infrared thermography with excitation CO2 Laser, wavelength of 10.6 μm. This excitation is the controllable heating beam, confirmed by a preliminary test on a wooden plate 1.2 m x 0.9 m x 1 cm. As the first practice, this method is applied to detecting the defect in CFRP heated by the Laser 300 W during 40 s. Two samples 40 cm x 40 cm x 4.5 cm are prepared, one with defect, another one without defect. The laser beam passes through the lens of a deviation device, and heats the samples placed at a determinate position and area. As a result, the absence of adhesive can be detected. This method displays prominently its application as NDT with the composite materials. This work gives a good perspective to characterize the laser beam, which is very useful for the next detection campaigns.
Keywords: CO2 LASER, Infrared Thermography, NDT, CFRP, Defect Detection.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30152824 Automatic Extraction of Arbitrarily Shaped Buildings from VHR Satellite Imagery
Authors: Evans Belly, Imdad Rizvi, M. M. Kadam
Abstract:
Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.Keywords: Building detection, shadow detection, landscape generation, label, partitioning, very high resolution satellite imagery.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8492823 M-ary Chaotic Sequence Based SLM-OFDM System for PAPR Reduction without Side-Information
Authors: A.Goel, M. Agrawal, P. Gupta Poddar
Abstract:
Selected Mapping (SLM) is a PAPR reduction technique, which converts the OFDM signal into several independent signals by multiplication with the phase sequence set and transmits one of the signals with lowest PAPR. But it requires the index of the selected signal i.e. side information (SI) to be transmitted with each OFDM symbol. The PAPR reduction capability of the SLM scheme depends on the selection of phase sequence set. In this paper, we have proposed a new phase sequence set generation scheme based on M-ary chaotic sequence and a mapping scheme to map quaternary data to concentric circle constellation (CCC) is used. It is shown that this method does not require SI and provides better SER performance with good PAPR reduction capability as compared to existing SLMOFDM methods.
Keywords: Orthogonal frequency division multiplexing (OFDM), Peak-to-average power ratio (PAPR), Selected mapping (SLM), Side information (SI)
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1968