Search results for: demonstration wildfire detection and action from space
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9311

Search results for: demonstration wildfire detection and action from space

8831 Video Text Information Detection and Localization in Lecture Videos Using Moments

Authors: Belkacem Soundes, Guezouli Larbi

Abstract:

This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time.

Keywords: text detection, text localization, lecture videos, pseudo zernike moments

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8830 Utilizing Public Spaces as a Precursor for Community Social Cohesion

Authors: Oloruntoba Kayode, Mohd Hisyam Rasidi, Ismail Said

Abstract:

This study investigates the influence of public space in developing social cohesion among residents in science cities. The study takes into consideration the need for social cohesion in knowledge-based development and focuses on Cyberjaya Malaysia being a science city that is characterized by public spaces. As such, we adopted validated measuring tools for this study we developed a theoretical framework that links public space utilization with people's social cohesion. A total of 211 survey questions were administered by the residents in the study area on public space utilization and their social cohesion potentials. The research framework was validated to confirm its fit using structural equation modeling (SEM). The findings indicated that the observed public space utilization variables significantly influenced people's social cohesion, while group social ties have a positive influence on their collective minds.

Keywords: public space, social cohesion, knowledge-based development, theoretical framework

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8829 Performance Comparison of Space-Time Block and Trellis Codes under Rayleigh Channels

Authors: Jing Qingfeng, Wu Jiajia

Abstract:

Due to the crowded orbits and shortage of frequency resources, utilizing of MIMO technology to improve spectrum efficiency and increase the capacity has become a necessary trend of broadband satellite communication. We analyze the main influenced factors and compare the BER performance of space-time block code (STBC) scheme and space-time trellis code (STTC) scheme. This paper emphatically studies the bit error rate (BER) performance of STTC and STBC under Rayleigh channel. The main emphasis is placed on the effects of the factors, such as terminal environment and elevation angles, on the BER performance of STBC and STTC schemes. Simulation results indicate that performance of STTC under Rayleigh channel is obviously improved with the increasing of transmitting and receiving antennas numbers, but the encoder state has little impact on the performance. Under Rayleigh channel, performance of Alamouti code is better than that of STTC.

Keywords: MIMO, space time block code (STBC), space time trellis code (STTC), Rayleigh channel

Procedia PDF Downloads 327
8828 Research on Space Discharge Flying Saucers Cruising Between Planets

Authors: Jiang Hua Zhou

Abstract:

According to the article "New Theoretical System of Physics in the 21st Century" published by the author, it is proposed to use the "scientific principle" of the "balanced distance" between "gravity" and "repulsion" between "planets" to "research" - "space flying saucer", and The formula for the law of universal repulsion between substances is proposed. Under the guidance of the new theoretical system, according to the principle of "planet" gravitational and repulsive force, the research and development idea of developing discharge-type "space flying saucer" is put forward. This paper expounds the reasons why flying saucers have the following characteristics: Flying Saucers can fly at high speed, change direction immediately, hover at any height on the earth, and there is no sound when flying. With the birth of the theoretical system of physics in the 21st century advocated by the author, a era of interstellar "space flying saucer" research will be created.

Keywords: planet, attraction, repulsive force, balance spacing, scientific principles, research, space, flying saucer

Procedia PDF Downloads 106
8827 Diffable’s Aspiration Dreams in Spatial Planning

Authors: Tety Widyaningrum, Sapnah Rahmawati, Abdulmuluk Attim

Abstract:

Space was a container that includes land space, sea space and air space, including space in the earth as a whole region, where humans and other living creatures, operate and maintain its survival. Whereas spatial planning was a form of the structure of space and spatial pattern. At this time, the arrangement of space became a matter of considerable concern because through spatial planning was what will determine how the future city hall, how the welfare of the population that is in it, and how space can be a comfortable space to live. This spatial arrangement became a subject that must be considered not only by the Government as policy makers but also of concern to the entire community in it. As a place to stay, this space should be able to ensure the safety and comfort of the whole community, even people with disabilities, though. For development and spatial planning in Indonesia. It was still very low which was still concerned about the disabled. The spatial arrangement made generalizations. This caused the right for disabled people was less fulfilled. In accordance with the Declaration on the Rights of Persons with Disabilities who explains that people with disabilities had the right to be able to facilitate their efforts to become self-sufficient or not depends on the other party. It was also strengthened by According to the Law of the Republic of Indonesia No. 4 of 1997 on Persons with Disabilities; disabilities were part of the Indonesian people who had the status, rights, obligations and the same role with other Indonesian community in all aspects of life and livelihood. As observed, during the disabled were still used as objects that hadn’t been involved in the formulation of development planning of space in Indonesia, so the infrastructure space was still very far from the concept of friendly to the disabled. As an example of a sidewalk in Indonesia were still in bad condition, potholes, and uneven and don’t meet the eligibility standards. In addition, there were sidewalks that abused become a trade causing run down and chaotic atmosphere. In addition, pedestrians are also disturbed because the sidewalks were often still used as a parking lot or flowers to decorate the layout of the city, so the legroom was becoming increasingly limited. The development of infrastructure for pedestrians was also still concerned with aspects of aesthetic than functional. Therefore, the participation of disabled people must be involved in spatial planning exist. It aims to achieve spatial and environmentally friendly to the disabled. These dream space activities carried out by giving questionnaires and the dream images to the disabled about how the layout of the space they want what they want and what development was also in line with the principle of their convenience. This then will be taken into consideration for government in planning layout that was friendly to the whole community.

Keywords: diffable, aspiration, spatial, planning

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8826 Land Use Change Detection Using Satellite Images for Najran City, Kingdom of Saudi Arabia (KSA)

Authors: Ismail Elkhrachy

Abstract:

Determination of land use changing is an important component of regional planning for applications ranging from urban fringe change detection to monitoring change detection of land use. This data are very useful for natural resources management.On the other hand, the technologies and methods of change detection also have evolved dramatically during past 20 years. So it has been well recognized that the change detection had become the best methods for researching dynamic change of land use by multi-temporal remotely-sensed data. The objective of this paper is to assess, evaluate and monitor land use change surrounding the area of Najran city, Kingdom of Saudi Arabia (KSA) using Landsat images (June 23, 2009) and ETM+ image(June. 21, 2014). The post-classification change detection technique was applied. At last,two-time subset images of Najran city are compared on a pixel-by-pixel basis using the post-classification comparison method and the from-to change matrix is produced, the land use change information obtained.Three classes were obtained, urban, bare land and agricultural land from unsupervised classification method by using Erdas Imagine and ArcGIS software. Accuracy assessment of classification has been performed before calculating change detection for study area. The obtained accuracy is between 61% to 87% percent for all the classes. Change detection analysis shows that rapid growth in urban area has been increased by 73.2%, the agricultural area has been decreased by 10.5 % and barren area reduced by 7% between 2009 and 2014. The quantitative study indicated that the area of urban class has unchanged by 58.2 km〗^2, gained 70.3 〖km〗^2 and lost 16 〖km〗^2. For bare land class 586.4〖km〗^2 has unchanged, 53.2〖km〗^2 has gained and 101.5〖km〗^2 has lost. While agriculture area class, 20.2〖km〗^2 has unchanged, 31.2〖km〗^2 has gained and 37.2〖km〗^2 has lost.

Keywords: land use, remote sensing, change detection, satellite images, image classification

Procedia PDF Downloads 504
8825 Inheritance of Protein Content and Grain Yield in Half Diallel Maize (Zea mays L.) Populations

Authors: Gül Ebru Orhun

Abstract:

A half diallel crossing design was carried out during 2011 and 2012 growing seasons under Çanakkale-Turkey ecological conditions. In this research, 20 F1 maize hybrids obtained by 6x6 half diallel crossing were used. Gene action for protein content and grain yield traits were explored in half set involving six elite inbred lines. According to the results diallel analysis dominance and additive gene variances were determined for protein content. Variance/Co-variance graphs revealed for grain yield and protein content traits. In this study, inheritance of grain yield and protein content demonstrated over-dominance type of gene action.

Keywords: protein, maize, inheritance, gene action

Procedia PDF Downloads 500
8824 Studies on Space-Based Laser Targeting System for the Removal of Orbital Space Debris

Authors: Krima M. Rohela, Raja Sabarinath Sundaralingam

Abstract:

Humans have been launching rockets since the beginning of the space age in the late 1950s. We have come a long way since then, and the success rate for the launch of rockets has increased considerably. With every successful launch, there is a large amount of junk or debris which is released into the upper layers of the atmosphere. Space debris has been a huge concern for a very long time now. This includes the rocket shells released from the launch and the parts of defunct satellites. Some of this junk will come to fall towards the Earth and burn in the atmosphere. But most of the junk goes into orbit around the Earth, and they remain in orbits for at least 100 years. This can cause a lot of problems to other functioning satellites and may affect the future manned missions to space. The main concern of the space-debris is the increase in space activities, which leads to risks of collisions if not taken care of soon. These collisions may result in what is known as Kessler Syndrome. This debris can be removed by a space-based laser targeting system. Hence, the matter is investigated and discussed. The first step in this involves launching a satellite with a high-power laser device into space, above the debris belt. Then the target material is ablated with a focussed laser beam. This step of the process is highly dependent on the attitude and orientation of the debris with respect to the Earth and the device. The laser beam will cause a jet of vapour and plasma to be expelled from the material. Hence, the force is applied in the opposite direction, and in accordance with Newton’s third law of motion, this will cause the material to move towards the Earth and get pulled down due to gravity, where it will get disintegrated in the upper layers of the atmosphere. The larger pieces of the debris can be directed towards the oceans. This method of removal of the orbital debris will enable safer passage for future human-crewed missions into space.

Keywords: altitude, Kessler syndrome, laser ablation, Newton’s third law of motion, satellites, Space debris

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8823 Improving Early Detection, Diagnosis And Intervention For Children With Autism Spectrum Disorder: A Cross-sectional Survey In China

Authors: Yushen Dai, Tao Deng, Miaoying Chen, Baoqin Huang, Yan Ji, Yongshen Feng, Shaofei Liu, Dongmei Zhong, Tao Zhang, Lifeng Zhang

Abstract:

Background: Detection and diagnosis are prerequisites for early interventions in the care of children with Autism Spectrum Disorder (ASD). However, few studies have focused on this topic. Aim: This study aims to characterize the timing from symptom detection to intervention in children with ASD and to identify the potential predictors of early detection, diagnosis, and intervention. Methods and procedures: A cross-sectional survey was conducted with 314 parents of children with ASD in Guangzhou, China. Outcomes and Results: This study found that most children (76.24%) were diagnosed within one year after detection, and 25.8% of them did not receive the intervention after diagnosis. Predictors to ASD diagnosis included ASD-related symptoms identified at a younger age, more serious symptoms, and initial symptoms with abnormal development and sensory anomalies. ASD-related symptoms observed at an older age, initial symptoms with the social deficit, sensory anomalies, and without language impairment, parents as the primary caregivers, family with lower income and less social support utilization increased the odds of the time lag between detection and diagnosis. Children whose fathers had a lower level of education were less likely to receive the intervention. Conclusions and Implications: The study described the time for detection, diagnosis, and interventions of children with ASD. Findings suggest that the ASD-related symptoms, the timing at which symptoms first become a concern, primary caregivers’ roles, father’s educational level, and the family economic status should be considered when offering support to improve early detection, diagnosis, and intervention. Helping children and their families take full advantage of support is also important.

Keywords: autism spectrum disorder, child, detection, diagnosis, intervention, social support

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8822 Fully Automated Methods for the Detection and Segmentation of Mitochondria in Microscopy Images

Authors: Blessing Ojeme, Frederick Quinn, Russell Karls, Shannon Quinn

Abstract:

The detection and segmentation of mitochondria from fluorescence microscopy are crucial for understanding the complex structure of the nervous system. However, the constant fission and fusion of mitochondria and image distortion in the background make the task of detection and segmentation challenging. In the literature, a number of open-source software tools and artificial intelligence (AI) methods have been described for analyzing mitochondrial images, achieving remarkable classification and quantitation results. However, the availability of combined expertise in the medical field and AI required to utilize these tools poses a challenge to its full adoption and use in clinical settings. Motivated by the advantages of automated methods in terms of good performance, minimum detection time, ease of implementation, and cross-platform compatibility, this study proposes a fully automated framework for the detection and segmentation of mitochondria using both image shape information and descriptive statistics. Using the low-cost, open-source python and openCV library, the algorithms are implemented in three stages: pre-processing, image binarization, and coarse-to-fine segmentation. The proposed model is validated using the mitochondrial fluorescence dataset. Ground truth labels generated using a Lab kit were also used to evaluate the performance of our detection and segmentation model. The study produces good detection and segmentation results and reports the challenges encountered during the image analysis of mitochondrial morphology from the fluorescence mitochondrial dataset. A discussion on the methods and future perspectives of fully automated frameworks conclude the paper.

Keywords: 2D, binarization, CLAHE, detection, fluorescence microscopy, mitochondria, segmentation

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8821 The Terminology of Mandatory Mediation on Commercial Disputes in Türkiye and the Differences from England and Wales’s Approaches

Authors: Sevgi Karaca

Abstract:

Since December 6, 2018, mediation has become mandatory for commercial disputes under the Turkish Commercial Code. Mandatory mediation became one of the “causes of action”, and being compulsory means starting the mediation process before going to court. As it contemplates looking at “the causes of the action”, the terminology may lead to misinterpretation of the core of the phrases. However, the terms pertain to a prerequisite for starting the lawsuit. The court will examine failure to comply with such requirements, and the case will be dismissed without further action. Türkiye’s use of obligatory mediation is highly unusual. It is neither judge-led nor judge-assisted mediation but rather a mediation conducted outside of court with the participation of a third party (mediators). What distinguishes it is the incorporation of obligatory mediation into the causes of actions listed in the Code of Civil Procedure. Being one of the causes of action in a legal case implies that the absence of any of them may result in the procedural dismissal of the case without any further action. The case must be presented to the mediator first, and if the parties are unable to reach an agreement, they must deliver the results of the mediation session. Other than submitting the minutes, parties are ineligible to file a lawsuit. However, despite a lengthy history of use in England and Wales, there are considerable reservations about making mediation mandatory. The Civil Procedure Code does not explicitly mention making mediation mandatory. For the time being, there is no Mediation Code, and case law limits the growth of obligatory mediation. Some renowned judges voiced their desire to re-evaluate the notion of required mediation, prompting the Civil Justice Council to release a study in 2021 on the significance of amending case law and the high value of mandatory mediation. By contrasting the approaches to mandatory mediation in England and Wales, the study will investigate the method of controlled mandatory mediation and its effects on the success of mediation in Türkiye.

Keywords: alternative dispute resolution, case law, cause of action, litigation process, mandatory mediation

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8820 Improvement of Brain Tumors Detection Using Markers and Boundaries Transform

Authors: Yousif Mohamed Y. Abdallah, Mommen A. Alkhir, Amel S. Algaddal

Abstract:

This was experimental study conducted to study segmentation of brain in MRI images using edge detection and morphology filters. For brain MRI images each film scanned using digitizer scanner then treated by using image processing program (MatLab), where the segmentation was studied. The scanned image was saved in a TIFF file format to preserve the quality of the image. Brain tissue can be easily detected in MRI image if the object has sufficient contrast from the background. We use edge detection and basic morphology tools to detect a brain. The segmentation of MRI images steps using detection and morphology filters were image reading, detection entire brain, dilation of the image, filling interior gaps inside the image, removal connected objects on borders and smoothen the object (brain). The results of this study were that it showed an alternate method for displaying the segmented object would be to place an outline around the segmented brain. Those filters approaches can help in removal of unwanted background information and increase diagnostic information of Brain MRI.

Keywords: improvement, brain, matlab, markers, boundaries

Procedia PDF Downloads 494
8819 Feasibility of Weakly Interacting Massive Particles as Dark Matter Candidates: Exploratory Study on The Possible Reasons for Lack of WIMP Detection

Authors: Sloka Bhushan

Abstract:

Dark matter constitutes a majority of matter in the universe, yet very little is known about it due to its extreme lack of interaction with regular matter and the fundamental forces. Weakly Interacting Massive Particles, or WIMPs, have been contested to be one of the strongest candidates for dark matter due to their promising theoretical properties. However, various endeavors to detect these elusive particles have failed. This paper explores the various particles which may be WIMPs and the detection techniques being employed to detect WIMPs (such as underground detectors, LHC experiments, and so on). There is a special focus on the reasons for the lack of detection of WIMPs so far, and the possibility of limits in detection being a reason for the lack of physical evidence of the existence of WIMPs. This paper also explores possible inconsistencies within the WIMP particle theory as a reason for the lack of physical detection. There is a brief review on the possible solutions and alternatives to these inconsistencies. Additionally, this paper also reviews the supersymmetry theory and the possibility of the supersymmetric neutralino (A possible WIMP particle) being detectable. Lastly, a review on alternate candidates for dark matter such as axions and MACHOs has been conducted. The explorative study in this paper is conducted through a series of literature reviews.

Keywords: dark matter, particle detection, supersymmetry, weakly interacting massive particles

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8818 Selective Circular Dichroism Sensor Based on the Generation of Quantum Dots for Cadmium Ion Detection

Authors: Pradthana Sianglam, Wittaya Ngeontae

Abstract:

A new approach for the fabrication of cadmium ion (Cd2+) sensor is demonstrated. The detection principle is based on the in-situ generation of cadmium sulfide quantum dots (CdS QDs) in the presence of chiral thiol containing compound and detection by the circular dichroism spectroscopy (CD). Basically, the generation of CdS QDs can be done in the presence of Cd2+, sulfide ion and suitable capping compounds. In addition, the strong CD signal can be recorded if the generated QDs possess chiral property (from chiral capping molecule). Thus, the degree of CD signal change depends on the number of the generated CdS QDs which can be related to the concentration of Cd2+ (excess of other components). In this work, we use the mixture of cysteamine (Cys) and L-Penicillamine (LPA) as the capping molecules. The strong CD signal can be observed when the solution contains sodium sulfide, Cys, LPA, and Cd2+. Moreover, the CD signal is linearly related to the concentration of Cd2+. This approach shows excellence selectivity towards the detection of Cd2+ when comparing to other cation. The proposed CD sensor provides low limit detection limits around 70 µM and can be used with real water samples with satisfactory results.

Keywords: circular dichroism sensor, quantum dots, enaniomer, in-situ generation, chemical sensor, heavy metal ion

Procedia PDF Downloads 346
8817 Material Detection by Phase Shift Cavity Ring-Down Spectroscopy

Authors: Rana Muhammad Armaghan Ayaz, Yigit Uysallı, Nima Bavili, Berna Morova, Alper Kiraz

Abstract:

Traditional optical methods for example resonance wavelength shift and cavity ring-down spectroscopy used for material detection and sensing have disadvantages, for example, less resistance to laser noise, temperature fluctuations and extraction of the required information can be a difficult task like ring downtime in case of cavity ring-down spectroscopy. Phase shift cavity ring down spectroscopy is not only easy to use but is also capable of overcoming the said problems. This technique compares the phase difference between the signal coming out of the cavity with the reference signal. Detection of any material is made by the phase difference between them. By using this technique, air, water, and isopropyl alcohol can be recognized easily. This Methodology has far-reaching applications and can be used in air pollution detection, human breath analysis and many more.

Keywords: materials, noise, phase shift, resonance wavelength, sensitivity, time domain approach

Procedia PDF Downloads 132
8816 Development of Star Image Simulator for Star Tracker Algorithm Validation

Authors: Zoubida Mahi

Abstract:

A successful satellite mission in space requires a reliable attitude and orbit control system to command, control and position the satellite in appropriate orbits. Several sensors are used for attitude control, such as magnetic sensors, earth sensors, horizon sensors, gyroscopes, and solar sensors. The star tracker is the most accurate sensor compared to other sensors, and it is able to offer high-accuracy attitude control without the need for prior attitude information. There are mainly three approaches in star sensor research: digital simulation, hardware in the loop simulation, and field test of star observation. In the digital simulation approach, all of the processes are done in software, including star image simulation. Hence, it is necessary to develop star image simulation software that could simulate real space environments and various star sensor configurations. In this paper, we present a new stellar image simulation tool that is used to test and validate the stellar sensor algorithms; the developed tool allows to simulate of stellar images with several types of noise, such as background noise, gaussian noise, Poisson noise, multiplicative noise, and several scenarios that exist in space such as the presence of the moon, the presence of optical system problem, illumination and false objects. On the other hand, we present in this paper a new star extraction algorithm based on a new centroid calculation method. We compared our algorithm with other star extraction algorithms from the literature, and the results obtained show the star extraction capability of the proposed algorithm.

Keywords: star tracker, star simulation, star detection, centroid, noise, scenario

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8815 Consideration of Starlight Waves Redshift as Produced by Friction of These Waves on Its Way through Space

Authors: Angel Pérez Sánchez

Abstract:

In 1929, a light redshift was discovered in distant galaxies and was interpreted as produced by galaxies moving away from each other at high speed. This interpretation led to the consideration of a new source of energy, which was called Dark Energy. Redshift is a loss of light wave frequency produced by galaxies moving away at high speed, but the loss of frequency can also be produced by the friction of light waves on their way to Earth. This friction is impossible because outer space is empty, but if it were not empty and a medium existed in this empty space, it would be possible. The consequences would be extraordinary because Universe acceleration and Dark Energy would be in doubt. This article presents evidence that empty space is actually a medium occupied by different particles, among them the most significant would-be Graviton or Higgs Boson, because let's not forget that gravity also affects empty space.

Keywords: Big Bang, dark energy, doppler effect, redshift, starlight frequency reduction, universe acceleration

Procedia PDF Downloads 48
8814 A Comprehensive Survey of Artificial Intelligence and Machine Learning Approaches across Distinct Phases of Wildland Fire Management

Authors: Ursula Das, Manavjit Singh Dhindsa, Kshirasagar Naik, Marzia Zaman, Richard Purcell, Srinivas Sampalli, Abdul Mutakabbir, Chung-Horng Lung, Thambirajah Ravichandran

Abstract:

Wildland fires, also known as forest fires or wildfires, are exhibiting an alarming surge in frequency in recent times, further adding to its perennial global concern. Forest fires often lead to devastating consequences ranging from loss of healthy forest foliage and wildlife to substantial economic losses and the tragic loss of human lives. Despite the existence of substantial literature on the detection of active forest fires, numerous potential research avenues in forest fire management, such as preventative measures and ancillary effects of forest fires, remain largely underexplored. This paper undertakes a systematic review of these underexplored areas in forest fire research, meticulously categorizing them into distinct phases, namely pre-fire, during-fire, and post-fire stages. The pre-fire phase encompasses the assessment of fire risk, analysis of fuel properties, and other activities aimed at preventing or reducing the risk of forest fires. The during-fire phase includes activities aimed at reducing the impact of active forest fires, such as the detection and localization of active fires, optimization of wildfire suppression methods, and prediction of the behavior of active fires. The post-fire phase involves analyzing the impact of forest fires on various aspects, such as the extent of damage in forest areas, post-fire regeneration of forests, impact on wildlife, economic losses, and health impacts from byproducts produced during burning. A comprehensive understanding of the three stages is imperative for effective forest fire management and mitigation of the impact of forest fires on both ecological systems and human well-being. Artificial intelligence and machine learning (AI/ML) methods have garnered much attention in the cyber-physical systems domain in recent times leading to their adoption in decision-making in diverse applications including disaster management. This paper explores the current state of AI/ML applications for managing the activities in the aforementioned phases of forest fire. While conventional machine learning and deep learning methods have been extensively explored for the prevention, detection, and management of forest fires, a systematic classification of these methods into distinct AI research domains is conspicuously absent. This paper gives a comprehensive overview of the state of forest fire research across more recent and prominent AI/ML disciplines, including big data, classical machine learning, computer vision, explainable AI, generative AI, natural language processing, optimization algorithms, and time series forecasting. By providing a detailed overview of the potential areas of research and identifying the diverse ways AI/ML can be employed in forest fire research, this paper aims to serve as a roadmap for future investigations in this domain.

Keywords: artificial intelligence, computer vision, deep learning, during-fire activities, forest fire management, machine learning, pre-fire activities, post-fire activities

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8813 Simulations of High-Intensity, Thermionic Electron Guns for Electron Beam Thermal Processing Including Effects of Space Charge Compensation

Authors: O. Hinrichs, H. Franz, G. Reiter

Abstract:

Electron guns have a key function in a series of thermal processes, like EB (electron beam) melting, evaporation or welding. These techniques need a high-intensity continuous electron beam that defocuses itself due to high space charge forces. A proper beam transport throughout the magnetic focusing system can be ensured by a space charge compensation via residual gas ions. The different pressure stages in the EB gun cause various degrees of compensation. A numerical model was installed to simulate realistic charge distributions within the beam by using CST-Particle Studio code. We will present current status of beam dynamic simulations. This contribution will focus on the creation of space charge ions and their influence on beam and gun components. Furthermore, the beam transport in the gun will be shown for different beam parameters. The electron source allows to produce beams with currents of 3 A to 15 A and energies of 40 keV to 45 keV.

Keywords: beam dynamic simulation, space charge compensation, thermionic electron source, EB melting, EB thermal processing

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8812 Proposed Fault Detection Scheme on Low Voltage Distribution Feeders

Authors: Adewusi Adeoluwawale, Oronti Iyabosola Busola, Akinola Iretiayo, Komolafe Olusola Aderibigbe

Abstract:

The complex and radial structure of the low voltage distribution network (415V) makes it vulnerable to faults which are due to system and the environmental related factors. Besides these, the protective scheme employed on the low voltage network which is the fuse cannot be monitored remotely such that in the event of sustained fault, the utility will have to rely solely on the complaint brought by customers for loss of supply and this tends to increase the length of outages. A microcontroller based fault detection scheme is hereby developed to detect low voltage and high voltage fault conditions which are common faults on this network. Voltages below 198V and above 242V on the distribution feeders are classified and detected as low voltage and high voltages respectively. Results shows that the developed scheme produced a good response time in the detection of these faults.

Keywords: fault detection, low voltage distribution feeders, outage times, sustained faults

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8811 Verifying the Performance of the Argon-41 Monitoring System from Fluorine-18 Production for Medical Applications

Authors: Nicole Virgili, Romolo Remetti

Abstract:

The aim of this work is to characterize, from radiation protection point of view, the emission into the environment of air contaminated by argon-41. In this research work, 41Ar is produced by a TR19PET cyclotron, operated at 19 MeV, installed at 'A. Gemelli' University Hospital, Rome, Italy, for fluorine-18 production. The production rate of 41Ar has been calculated on the basis of the scheduled operation cycles of the cyclotron and by utilising proper production algorithms. Then extensive Monte Carlo calculations, carried out by MCNP code, have allowed to determine the absolute detection efficiency to 41Ar gamma rays of a Geiger Muller detector placed in the terminal part of the chimney. Results showed unsatisfactory detection efficiency values and the need for integrating the detection system with more efficient detectors.

Keywords: Cyclotron, Geiger Muller detector, MCNPX, argon-41, emission of radioactive gas, detection efficiency determination

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8810 A Unified Deep Framework for Joint 3d Pose Estimation and Action Recognition from a Single Color Camera

Authors: Huy Hieu Pham, Houssam Salmane, Louahdi Khoudour, Alain Crouzil, Pablo Zegers, Sergio Velastin

Abstract:

We present a deep learning-based multitask framework for joint 3D human pose estimation and action recognition from color video sequences. Our approach proceeds along two stages. In the first, we run a real-time 2D pose detector to determine the precise pixel location of important key points of the body. A two-stream neural network is then designed and trained to map detected 2D keypoints into 3D poses. In the second, we deploy the Efficient Neural Architecture Search (ENAS) algorithm to find an optimal network architecture that is used for modeling the Spatio-temporal evolution of the estimated 3D poses via an image-based intermediate representation and performing action recognition. Experiments on Human3.6M, Microsoft Research Redmond (MSR) Action3D, and Stony Brook University (SBU) Kinect Interaction datasets verify the effectiveness of the proposed method on the targeted tasks. Moreover, we show that our method requires a low computational budget for training and inference.

Keywords: human action recognition, pose estimation, D-CNN, deep learning

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8809 Deep Learning Based Road Crack Detection on an Embedded Platform

Authors: Nurhak Altın, Ayhan Kucukmanisa, Oguzhan Urhan

Abstract:

It is important that highways are in good condition for traffic safety. Road crashes (road cracks, erosion of lane markings, etc.) can cause accidents by affecting driving. Image processing based methods for detecting road cracks are available in the literature. In this paper, a deep learning based road crack detection approach is proposed. YOLO (You Look Only Once) is adopted as core component of the road crack detection approach presented. The YOLO network structure, which is developed for object detection, is trained with road crack images as a new class that is not previously used in YOLO. The performance of the proposed method is compared using different training methods: using randomly generated weights and training their own pre-trained weights (transfer learning). A similar training approach is applied to the simplified version of the YOLO network model (tiny yolo) and the results of the performance are examined. The developed system is able to process 8 fps on NVIDIA Jetson TX1 development kit.

Keywords: deep learning, embedded platform, real-time processing, road crack detection

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8808 The Development of a Miniaturized Raman Instrument Optimized for the Detection of Biosignatures on Europa

Authors: Aria Vitkova, Hanna Sykulska-Lawrence

Abstract:

In recent years, Europa has been one of the major focus points in astrobiology due to its high potential of harbouring life in the vast ocean underneath its icy crust. However, the detection of life on Europa faces many challenges due to the harsh environmental conditions and mission constraints. Raman spectroscopy is a highly capable and versatile in-situ characterisation technique that does not require any sample preparation. It has only been used on Earth to date; however, recent advances in optical and laser technology have also allowed it to be considered for extraterrestrial exploration. So far, most efforts have been focused on the exploration of Mars, the most imminent planetary target. However, as an emerging technology with high miniaturization potential, Raman spectroscopy also represents a promising tool for the exploration of Europa. In this study, the capabilities of Raman technology in terms of life detection on Europa are explored and assessed. Spectra of biosignatures identified as high priority molecular targets for life detection on Europa were acquired at various excitation wavelengths and conditions analogous to Europa. The effects of extremely low temperatures and low concentrations in water ice were explored and evaluated in terms of the effectiveness of various configurations of Raman instruments. Based on the findings, a design of a miniaturized Raman instrument optimized for in-situ detection of life on Europa is proposed.

Keywords: astrobiology, biosignatures, Europa, life detection, Raman Spectroscopy

Procedia PDF Downloads 186
8807 Intrusion Detection in Computer Networks Using a Hybrid Model of Firefly and Differential Evolution Algorithms

Authors: Mohammad Besharatloo

Abstract:

Intrusion detection is an important research topic in network security because of increasing growth in the use of computer network services. Intrusion detection is done with the aim of detecting the unauthorized use or abuse in the networks and systems by the intruders. Therefore, the intrusion detection system is an efficient tool to control the user's access through some predefined regulations. Since, the data used in intrusion detection system has high dimension, a proper representation is required to show the basis structure of this data. Therefore, it is necessary to eliminate the redundant features to create the best representation subset. In the proposed method, a hybrid model of differential evolution and firefly algorithms was employed to choose the best subset of properties. In addition, decision tree and support vector machine (SVM) are adopted to determine the quality of the selected properties. In the first, the sorted population is divided into two sub-populations. These optimization algorithms were implemented on these sub-populations, respectively. Then, these sub-populations are merged to create next repetition population. The performance evaluation of the proposed method is done based on KDD Cup99. The simulation results show that the proposed method has better performance than the other methods in this context.

Keywords: intrusion detection system, differential evolution, firefly algorithm, support vector machine, decision tree

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8806 Fast Accurate Detection of Frequency Jumps Using Kalman Filter with Non Linear Improvements

Authors: Mahmoud E. Mohamed, Ahmed F. Shalash, Hanan A. Kamal

Abstract:

In communication systems, frequency jump is a serious problem caused by the oscillators used. Kalman filters are used to detect that jump, Despite the tradeoff between the noise level and the speed of the detection. In this paper, An improvement is introduced in the Kalman filter, Through a nonlinear change in the bandwidth of the filter. Simulation results show a considerable improvement in the filter speed with a very low noise level. Additionally, The effect on the response to false alarms is also presented and false alarm rate show improvement.

Keywords: Kalman filter, innovation, false detection, improvement

Procedia PDF Downloads 577
8805 Detecting Venomous Files in IDS Using an Approach Based on Data Mining Algorithm

Authors: Sukhleen Kaur

Abstract:

In security groundwork, Intrusion Detection System (IDS) has become an important component. The IDS has received increasing attention in recent years. IDS is one of the effective way to detect different kinds of attacks and malicious codes in a network and help us to secure the network. Data mining techniques can be implemented to IDS, which analyses the large amount of data and gives better results. Data mining can contribute to improving intrusion detection by adding a level of focus to anomaly detection. So far the study has been carried out on finding the attacks but this paper detects the malicious files. Some intruders do not attack directly, but they hide some harmful code inside the files or may corrupt those file and attack the system. These files are detected according to some defined parameters which will form two lists of files as normal files and harmful files. After that data mining will be performed. In this paper a hybrid classifier has been used via Naive Bayes and Ripper classification methods. The results show how the uploaded file in the database will be tested against the parameters and then it is characterised as either normal or harmful file and after that the mining is performed. Moreover, when a user tries to mine on harmful file it will generate an exception that mining cannot be made on corrupted or harmful files.

Keywords: data mining, association, classification, clustering, decision tree, intrusion detection system, misuse detection, anomaly detection, naive Bayes, ripper

Procedia PDF Downloads 395
8804 Ultra-High Frequency Passive Radar Coverage for Cars Detection in Semi-Urban Scenarios

Authors: Pedro Gómez-del-Hoyo, Jose-Luis Bárcena-Humanes, Nerea del-Rey-Maestre, María-Pilar Jarabo-Amores, David Mata-Moya

Abstract:

A study of achievable coverages using passive radar systems in terrestrial traffic monitoring applications is presented. The study includes the estimation of the bistatic radar cross section of different commercial vehicle models that provide challenging low values which make detection really difficult. A semi-urban scenario is selected to evaluate the impact of excess propagation losses generated by an irregular relief. A bistatic passive radar exploiting UHF frequencies radiated by digital video broadcasting transmitters is assumed. A general method of coverage estimation using electromagnetic simulators in combination with estimated car average bistatic radar cross section is applied. In order to reduce the computational cost, hybrid solution is implemented, assuming free space for the target-receiver path but estimating the excess propagation losses for the transmitter-target one.

Keywords: bistatic radar cross section, passive radar, propagation losses, radar coverage

Procedia PDF Downloads 315
8803 Refined Edge Detection Network

Authors: Omar Elharrouss, Youssef Hmamouche, Assia Kamal Idrissi, Btissam El Khamlichi, Amal El Fallah-Seghrouchni

Abstract:

Edge detection is represented as one of the most challenging tasks in computer vision, due to the complexity of detecting the edges or boundaries in real-world images that contains objects of different types and scales like trees, building as well as various backgrounds. Edge detection is represented also as a key task for many computer vision applications. Using a set of backbones as well as attention modules, deep-learning-based methods improved the detection of edges compared with the traditional methods like Sobel and Canny. However, images of complex scenes still represent a challenge for these methods. Also, the detected edges using the existing approaches suffer from non-refined results while the image output contains many erroneous edges. To overcome this, n this paper, by using the mechanism of residual learning, a refined edge detection network is proposed (RED-Net). By maintaining the high resolution of edges during the training process, and conserving the resolution of the edge image during the network stage, we make the pooling outputs at each stage connected with the output of the previous layer. Also, after each layer, we use an affined batch normalization layer as an erosion operation for the homogeneous region in the image. The proposed methods are evaluated using the most challenging datasets including BSDS500, NYUD, and Multicue. The obtained results outperform the designed edge detection networks in terms of performance metrics and quality of output images.

Keywords: edge detection, convolutional neural networks, deep learning, scale-representation, backbone

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8802 Induction Machine Bearing Failure Detection Using Advanced Signal Processing Methods

Authors: Abdelghani Chahmi

Abstract:

This article examines the detection and localization of faults in electrical systems, particularly those using asynchronous machines. First, the process of failure will be characterized, relevant symptoms will be defined and based on those processes and symptoms, a model of those malfunctions will be obtained. Second, the development of the diagnosis of the machine will be shown. As studies of malfunctions in electrical systems could only rely on a small amount of experimental data, it has been essential to provide ourselves with simulation tools which allowed us to characterize the faulty behavior. Fault detection uses signal processing techniques in known operating phases.

Keywords: induction motor, modeling, bearing damage, airgap eccentricity, torque variation

Procedia PDF Downloads 117