Search results for: train fire

Authors: J. K. Alhassan, C. S. Actsu

Abstract:

This study is on the prediction of feature performance of undergraduate students with Artificial Neural Networks (ANN). With the growing decline in the quality academic performance of undergraduate students, it has become essential to predict the students’ feature academic performance early in their courses of first and second years and to take the necessary precautions using such prediction-based information. The feed forward multilayer neural network model was used to train and develop a network and the test carried out with some of the input variables. A result of 80% accuracy was obtained from the test which was carried out, with an average error of 0.009781.

Keywords: academic performance, artificial neural network, prediction, students

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Authors: Vinayak Malhotra, Samanyu Raina, Ajinkya Vajurkar

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Enhancing the rocket efficiency by controlling the external factors in solid rockets motors has been an active area of research for most of the terrestrial and extra-terrestrial system operations. Appreciable work has been done, but the complexity of the problem has prevented thorough understanding due to heterogenous heat and mass transfer. On record, severe issues have surfaced amounting to irreplaceable loss of mankind, instruments, facilities, and huge amount of money being invested every year. The coupled effect of an external heat source and external heat sink is an aspect yet to be articulated in combustion. Better understanding of this coupled phenomenon will induce higher safety standards, efficient missions, reduced hazard risks, with better designing, validation, and testing. The experiment will help in understanding the coupled effect of an external heat sink and heat source on the burning process, contributing in better combustion and fire safety, which are very important for efficient and safer rocket flights and space missions. Safety is the most prevalent issue in rockets, which assisted by poor combustion efficiency, emphasizes research efforts to evolve superior rockets. This signifies real, engineering, scientific, practical, systems and applications. One potential application is Solid Rocket Motors (S.R.M). The study may help in: (i) Understanding the effect on efficiency of core engines due to the primary boosters if considered as source, (ii) Choosing suitable heat sink materials for space missions so as to vary the efficiency of the solid rocket depending on the mission, (iii) Giving an idea about how the preheating of the successive stage due to previous stage acting as a source may affect the mission. The present work governs the temperature (resultant) and thus the heat transfer which is expected to be non-linear because of heterogeneous heat and mass transfer. The study will deepen the understanding of controlled inter-energy conversions and the coupled effect of external source/sink(s) surrounding the burning fuel eventually leading to better combustion thus, better propulsion. The work is motivated by the need to have enhanced fire safety and better rocket efficiency. The specific objective of the work is to understand the coupled effect of external heat source and sink on propellant burning and to investigate the role of key controlling parameters. Results as of now indicate that there exists a singularity in the coupled effect. The dominance of the external heat sink and heat source decides the relative rocket flight in Solid Rocket Motors (S.R.M).

Keywords: coupled effect, heat transfer, sink, solid rocket motors, source

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Authors: Vinicius G. Goecks, Gregory M. Gremillion, William D. Nothwang

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Modern approaches to train intelligent agents rely on prolonged training sessions, high amounts of input data, and multiple interactions with the environment. This restricts the application of these learning algorithms in robotics and real-world applications, in which there is low tolerance to inadequate actions, interactions are expensive, and real-time processing and action are required. This paper addresses this issue introducing CyberSteer, a novel approach to efficiently design intrinsic reward functions based on human intention to guide deep reinforcement learning agents with no environment-dependent rewards. CyberSteer uses non-expert human operators for initial demonstration of a given task or desired behavior. The trajectories collected are used to train a behavior cloning deep neural network that asynchronously runs in the background and suggests actions to the deep reinforcement learning module. An intrinsic reward is computed based on the similarity between actions suggested and taken by the deep reinforcement learning algorithm commanding the agent. This intrinsic reward can also be reshaped through additional human demonstration or critique. This approach removes the need for environment-dependent or hand-engineered rewards while still being able to safely shape the behavior of autonomous robotic agents, in this case, based on human intention. CyberSteer is tested in a high-fidelity unmanned aerial vehicle simulation environment, the Microsoft AirSim. The simulated aerial robot performs collision avoidance through a clustered forest environment using forward-looking depth sensing and roll, pitch, and yaw references angle commands to the flight controller. This approach shows that the behavior of robotic systems can be shaped in a reduced amount of time when guided by a non-expert human, who is only aware of the high-level goals of the task. Decreasing the amount of training time required and increasing safety during training maneuvers will allow for faster deployment of intelligent robotic agents in dynamic real-world applications.

Keywords: human-robot interaction, intelligent robots, robot learning, semisupervised learning, unmanned aerial vehicles

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Authors: Minal Jain, Vinayak Malhotra

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Solid Propellant ignition consists of rapid and complex events comprising of heat generation and transfer of heat with spreading of flames over the entire burning surface area. Proper combustion and thus propulsion depends heavily on the modes of heat transfer characteristics and cavity volume. Fire safety is an integral component of a successful rocket flight failing to which may lead to overall failure of the rocket. This leads to enormous forfeiture in resources viz., money, time, and labor involved. When the propellant is ignited, thrust is generated and the casing gets heated up. This heat adds on to the propellant heat and the casing, if not at proper orientation starts burning as well, leading to the whole rocket being completely destroyed. This has necessitated active research efforts emphasizing a comprehensive study on the inter-energy relations involved for effective utilization of the solid rocket motors for better space missions. Present work is focused on one of the major influential aspects of this detrimental burning which is the presence of an external heat source, in addition to a potential heat source which is already ignited. The study is motivated by the need to ensure better combustion and fire safety presented experimentally as a simplified small-scale mode of a rocket carrying a solid propellant inside a cavity. The experimental setup comprises of a paraffin wax candle as the pilot fuel and incense stick as the external heat source. The candle is fixed and the incense stick position and location is varied to investigate the find the influence of the pilot heat source. Different configurations of the external heat source presence with separation distance are tested upon. Regression rates of the pilot thin solid fuel are noted to fundamentally understand the non-linear heat and mass transfer which is the governing phenomenon. An attempt is made to understand the phenomenon fundamentally and the mechanism governing it. Results till now indicate non-linear heat transfer assisted with the occurrence of flaming transition at selected critical distances. With an increase in separation distance, the effect is noted to drop in a non-monotonic trend. The parametric study results are likely to provide useful physical insight about the governing physics and utilization in proper testing, validation, material selection, and designing of solid rocket motors with enhanced safety.

Keywords: combustion, propellant, regression, safety

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Authors: Soo-Yeon Seo, Jong-Wook Lim, Se-Ki Song

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Currently, FRP (Fiber Reinforced Polymer) materials have been widely used for reinforcement of building structural members. However, since the FRP and the epoxy material for attaching it have very low resistance to heat, there is a problem in application where high temperature is an issue. In this paper, the resistance performance of FRP member made of carbon fiber at high temperature was investigated through experiment under temperature change. As a result, epoxy encapsulating FRP is damaged at not high temperatures, and the fibers are degraded. Therefore, when reinforcing a structure using FRP, a separate refractory heat treatment is necessary. The use of a 30 mm thick calcium silicate board as a fireproofing method can protect FRP up to 600ᵒC outside temperature.

Keywords: FRP (Fiber Reinforced Polymer), high temperature, experiment under temperature change, calcium silicate board

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Authors: Malathi Iyer, Jayesh Vaidya

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The demographic dividend of India will last for thirty years from now. However, reduction in birth rate, an increase in working population, improvements in medicine and better health practices lead to an ever-expanding elderly population, bringing additional burden to the economy and putting an end to the demographic dividend. To reap the dividend India needs to train the youth for employability. The need of the hour is to improve their life skills which lead the youth to become industrious and have continuous employment. The study will be conducted in perceiving the skill gaps that exist in commerce students for employability. The analysis results indicate the relation between the core study and the right skills for the workforce, with the steps that are taken to open the window for the demographic dividend.

Keywords: demographic dividend, life skills, employability, workforce

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Authors: Ross Goroshin, Joan Bruna, Jonathan Tompson, David Eigen, Yann LeCun

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Current state-of-the-art classification and detection algorithms rely on supervised training. In this work we study unsupervised feature learning in the context of temporally coherent video data. We focus on feature learning from unlabeled video data, using the assumption that adjacent video frames contain semantically similar information. This assumption is exploited to train a convolutional pooling auto-encoder regularized by slowness and sparsity. We establish a connection between slow feature learning to metric learning and show that the trained encoder can be used to define a more temporally and semantically coherent metric.

Keywords: machine learning, pattern clustering, pooling, classification

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Authors: Mohammadamin Abbasnejad

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The analysis of expression and facial Action Units (AUs) detection are very important tasks in fields of computer vision and Human Computer Interaction (HCI) due to the wide range of applications in human life. Many works have been done during the past few years which has their own advantages and disadvantages. In this work, we present a new model based on Gaussian Conditional Random Field. We solve our objective problem using ADMM and we show how well the proposed model works. We train and test our work on two facial expression datasets, CK+, and RU-FACS. Experimental evaluation shows that our proposed approach outperform state of the art expression recognition.

Keywords: Gaussian Conditional Random Field, ADMM, convergence, gradient descent

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Authors: Yashfeen Khan, Anees Ahmad

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In the last few decades, nano-composites have been the topic of interest. Presently, the modern era enlightens the synthesis of hybrid nano-composites over their individual counterparts because of higher application potentials and synergism. Recently, CNT hybrids have demonstrated their pronounced capability as effective sorbents for the removal of heavy metal ions (the root trouble) and organic contaminants due to their high specific surface area, enhanced reactivity, and sequestration characteristics. The present abstract discusses removal efficiencies of organic, inorganic pollutants through CNT/PANI/ composites. It also represents the widespread applications of CNT like monitoring biological systems, biosensors, as heat resources for treating cancer, fire retardant applications of polymer/CNT composites etc. And considering the same, this article aims to brief the scenario of CNT-PANI nano-composites.

Keywords: biosensors, CNT, hybrids, polyaniline, synergism

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Authors: Toan Vo

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Electronic attacks, illegal drones, interference, and jamming are no longer capabilities reserved for a state-sponsored, near-peer adversary. The proliferation of jammers on auction websites has lowered the price of entry for electronics hobbyists and nefarious actors. To enable local authorities and enforcement bodies to keep up with these challenges, this paper proposes a training as a service model to quickly and economically train and equip police departments and local law enforcement agencies. Using the U.S Department of Defense’s investment in Electronic Warfare as a guideline, a large number of personnel can be trained on effective spectrum monitoring techniques using commercial equipment readily available on the market. Finally, this paper will examine the economic benefits to the test and measurement industry if the TaaS model is applied.

Keywords: training, electronic warfare, economics, law enforcement

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Authors: Kemal Polat

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In this study, it has been estimated whether there is skin by using RBG values obtained from the camera and k-nearest neighbor (k-NN) classifier. The dataset used in this study has an unbalanced distribution and a linearly non-separable structure. This problem can also be called a big data problem. The Skin dataset was taken from UCI machine learning repository. As the classifier, we have used the k-NN method to handle this big data problem. For k value of k-NN classifier, we have used as 1. To train and test the k-NN classifier, 50-50% training-testing partition has been used. As the performance metrics, TP rate, FP Rate, Precision, recall, f-measure and AUC values have been used to evaluate the performance of k-NN classifier. These obtained results are as follows: 0.999, 0.001, 0.999, 0.999, 0.999, and 1,00. As can be seen from the obtained results, this proposed method could be used to predict whether the image is skin or not.

Keywords: k-NN classifier, skin or non-skin classification, RGB values, classification

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Authors: Proud Arunrangsiwed

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This study analyzes the crisis management and image repair strategies during the crisis of Mahidol Wittayanusorn School (MWIT) library burning. The library of this school was burned by a 16-year-old-male student on June 6th, 2010. This student blamed the school that the lesson was difficult, and other students were selfish. Although no one was in the building during the fire, it had caused damage to the building, books and electronic supplies around 130 million bahts (4.4 million USD). This event aroused many discourses arguing about the education system and morality. The strategies which were used during crisis were denial, shift the blame, bolstering, minimization, and uncertainty reduction. The results of using these strategies appeared after the crisis. That was the numbers of new students, who registered for the examination to get into this school in the later years, have remained the same.

Keywords: school, crisis management, violence, image repair strategies, uncertainty, burn

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Authors: Butchi Kameswara Rao Chittem, Rooban Kumar

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Cement concrete is a complex mixture of different materials. Concrete is believed to have a good fire resistance. Behaviour of concrete depends on its mix proportions and its constituent materials when it is subjected to elevated temperatures. Loss in compressive strength, loss in weight or mass, change in colour and spall of concrete are reported in literature as effects of elevated temperature on concrete. In this paper results are reported on the behaviour of normal strength concrete and high strength concrete subjected to temperatures 200°C, 400°C, 600°C, and 800°C and different cooling regimes viz. air cooling, water quenching. Rebound hammer test was also conducted to study the changes in surface hardness of concrete specimens subjected to elevated temperatures.

Keywords: normal strength concrete, high-strength concrete, temperature, NDT

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Authors: Sharon Garyn-Tal, Shoshana Shahrabani

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Military service in general, and in combat units in particular, can be physically and psychologically stressful. Therefore, type of service may have significant implications for soldiers during and after their military service including emotions, judgments and risk perceptions. Previous studies have focused on risk propensity and risky behavior among soldiers, however there is still lack of knowledge on the impact of type of army service on risk perceptions. The current study examines the effect of type of army service (combat versus non-combat service) and negative incidental emotions on risk perceptions. In 2014 a survey was conducted among 153 combat and non-combat Israeli soldiers. The survey was distributed in train stations and central bus stations in various places in Israel among soldiers waiting for the train/bus. Participants answered questions related to the levels of incidental negative emotions they felt, to their risk perceptions (chances to be hurt by terror attack, by violent crime and by car accident), and personal details including type of army service. The data in this research is unique because military service in Israel is compulsory, so that the Israeli population serving in the army is wide and diversified. The results indicate that currently serving combat participants were more pessimistic in their risk perceptions (for all type of risks) compared to the currently serving non-combat participants. Since combat participants probably experienced severe and distressing situations during their service, they became more pessimistic regarding their probabilities of being hurt in different situations in life. This result supports the availability heuristic theory and the findings of previous studies indicating that those who directly experience distressing events tend to overestimate danger. The findings also indicate that soldiers who feel higher levels of incidental fear and anger have pessimistic risk perceptions. In addition, respondents who experienced combat army service also have pessimistic risk perceptions if they feel higher levels of fear. In addition, the findings suggest that higher levels of the incidental emotions of fear and anger are related to more pessimistic risk perceptions. These results can be explained by the compulsory army service in Israel that constitutes a focused threat to soldiers' safety during their period of service. Thus, in this stressful environment, negative incidental emotions even during routine times correlate with higher risk perceptions. In conclusion, the current study results suggest that combat army service shapes risk perceptions and the way young people control their negative incidental emotions in everyday life. Recognizing the factors affecting risk perceptions among soldiers is important for better understanding the impact of army service on young people.

Keywords: army service, combat soldiers, incidental emotions, risk perceptions

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Authors: Pelangi Wiyantika

Abstract:

Sustainable energy is the main concern in According to solve any problems on energy sectors. One of the sustainable energy that has lack of presentation is Geothermal energy which has developed lately as the new promising sustainable energy. Indonesia as country that has been passed by the ring of fire zone has many geothermal sources. This is the good opportunity to elaborate and learn more about geothermal as sustainable and renewable energy. Geothermal systems have special characteristic whom the zone of sources can be detected by measuring the resistivity of the subsurface. There are many methods to measuring the anomaly of the systems. One of the best method is Magnetotelluric approchment. Magnetotelluric is the passive method which the resistivity is obtained by injecting the eddy current of rocks in the subsurface with the sources. The sources of Magnetotelluric method can be obtained from lightning or solar wind which has the frequencies each below 1 Hz and above 1 Hz.

Keywords: geothermal, magnetotelluric, renewable energy, resistivity, sustainable energy

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Authors: Gabriel Calvo, Carmen Armero, Luigi Spezia

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A basketball player is said to have a hot hand if his/her performance is better than expected in different periods of time. A way to deal with this phenomenon is to make use of latent variables, which can indicate whether the player is ‘on fire’ or not. This work aims to model the hot hand phenomenon through a Bayesian hidden Markov model (HMM) with two states (cold and hot) and two different probability of success depending on the corresponding hidden state. This task is illustrated through a comprehensive simulation study. The simulated data sets emulate the field goal attempts in an NBA season from different profile players. This model can be a powerful tool to assess the ‘streakiness’ of each player, and it provides information about the general performance of the players during the match. Finally, the Bayesian HMM allows computing the posterior probability of any type of streak.

Keywords: Bernoulli trials, field goals, latent variables, posterior distribution

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Authors: Andrey Norov

Abstract:

Based on the generalization of scientific and production experience and the latest developments of JSC “NIUIF”, the oldest (founded in September 1919) and the only Russian research institute for phosphorus-containing fertilizers, this paper shows the factors that determine the reasonable choice of a method for processing phosphate raw materials into complex fertilizers. These factors primarily include the composition of phosphate raw materials and the impurities contained in it, as well as some parameters of the process mode, wastelessness, ecofriendliness, energy saving, maximum use of the heat of chemical reactions, fire and explosion safety, efficiency, productive capacity, the required product range and the possibility of creating flexible technologies, compliance with BAT principles, etc. The presented data allow to choose the right technology for complex granular fertilizers, depending on the abovementioned factors.

Keywords: BAT, ecofriendliness, energy saving, phosphate raw materials, wastelessness

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Authors: Chang Su Woo, Hyun Sung Park

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Air spring system is widely accepted for railway vehicle secondary suspension to reduce and absorb the vibration and noise. The low natural frequency ensures a comfortable ride and an invariably good stiffness. In this paper, the characteristic and durability test was conducted in laboratory by using servo-hydraulic fatigue testing system to reliability evaluation of air spring for electric railway vehicle. The experimental results show that the characteristics and durability of domestically developed products are excellent. Moreover, to guarantee the adaption of air spring, the ride comfort and air pressure variation were measured in train test on subway line. Air spring developed by this study for railway vehicles can guarantee the reliability of average usage of 1 million times at 90% confidence level.

Keywords: air spring, reliability, railway, service lifetime

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Authors: Xiaoqi Jia, Qing Zhu, Hao Zhang, Su Yang

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A gender recognition system is able to tell the gender of the given person through a few of frontal facial images. An effective gender recognition approach enables to improve the performance of many other applications, including security monitoring, human-computer interaction, image or video retrieval and so on. In this paper, we present an effective method for gender classification task in frontal facial images based on deep belief networks (DBNs), which can pre-train model and improve accuracy a little bit. Our experiments have shown that the pre-training method with DBNs for gender classification task is feasible and achieves a little improvement of accuracy on FERET and CAS-PEAL-R1 facial datasets.

Keywords: gender recognition, beep belief net-works, semi-supervised learning, greedy-layer wise RBMs

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Authors: Oke Oktavianty, Tadayuki Kyoutani, Shigeyuki Haruyama, Ken Kaminishi

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For advancing the experiment system standard of Inkjet printer that is being developed, the actual natural period, fire limitation number in droplet weight measurement and observation distance in droplet velocity measurement was investigated. In another side, the study to control the droplet volume in inkjet printer with negative actuating waveform method is still limited. Therefore, the effect of negative waveform with preliminary and suppressing vibration addition on the droplet formation process, droplet shape, volume and velocity were evaluated. The different voltage and print-head temperature were exerted to obtain the optimum preliminary and suppressing vibration. The mechanism of different phenomenon from each waveform was also discussed.

Keywords: inkjet printer, DoD, waveform, preliminary and suppressing vibration

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Authors: Hamed Zolfaghari, Mojtaba Kord

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After feasibility study the design phase is started and the rest of other phases are highly dependent on this phase. forecasting the duration of design phase could do a miracle and would save a lot of time. This study provides a fast and accurate Machine learning (ML) and optimization framework, which allows a quick duration estimation of project design phase, hence improving operational efficiency and competitiveness of a design construction company. 3 data sets of three years composed of daily time spent for different design projects are used to train and validate the ML models to perform multiple projects. Our study concluded that Artificial Neural Network (ANN) performed an accuracy of 0.94.

Keywords: time estimation, machine learning, Artificial neural network, project design phase

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Authors: Yang Zhuo

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This study explores the integration of MIDI technology as one of the important digital technologies in music teaching, from the perspective of teaching practice, into the process of cultivating students' teaching skills. At the same time, the framework elements of the learning environment for music education students are divided into four aspects: digital technology supported learning space, new knowledge learning, teaching methods, and teaching evaluation. In teaching activities, more attention should be paid to students' subjectivity and interaction between them so as to enhance their emotional experience in teaching practice simulation. In the process of independent exploration and cooperative interaction, problems should be discovered and solved, and basic knowledge of music and teaching methods should be exercised in practice.

Keywords: music education, educational technology, MIDI, teacher training

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Authors: Martin Kendra, Jaroslav Mašek, Juraj Čamaj, Matej Babin

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The railway transport is considered as a one of the most environmentally friendly mode of transport. With future prediction of increasing of freight transport there are lines facing problems with demanded capacity. Increase of the track capacity could be achieved by infrastructure constructive adjustments. The contribution shows how the travel time can be minimized and the track capacity increased by changing some of the basic infrastructure and operation parameters, for example, the minimal curve radius of the track, the number of tracks, or the usable track length at stations. Calculation of the necessary parameter changes is based on the fundamental physical laws applied to the train movement, and calculation of the occupation time is dependent on the changes of controlling the traffic between the stations.

Keywords: curve radius, maximum curve speed, track mass capacity, reconstruction

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Authors: Xinli Chen, Xue Su

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In the urban rail transit CBTC system, interlocking is considered one of the most basic sys-tems, which has the characteristics of logical complexity and high-security requirements. The development and verification of traditional interlocking subsystems are entirely manual pro-cesses and rely too much on the designer, which often hides many uncertain factors. In order to solve this problem, this article is based on the multi-template nib tracking algorithm for model construction and verification, achieving the main safety attributes and using SCADE for formal verification. Experimental results show that this method helps to improve the quality and efficiency of interlocking software.

Keywords: computer interlocking subsystem, penpoint tracking, communication-based train control system, multi-template tip tracking

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Authors: Keyi Wang

Abstract:

Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

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Authors: S. Dhivya, M. Abirami, M. Farjana Parveen, M. Keerthiga

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The development of high-speed railway makes people’s lives more and more convenient; meanwhile, handover is the major problem on high-speed railway communication services. In order to overcome that drawback the architecture of Long-Term Evolution (LTE) femtocell networks is used to improve network performance, and the deployment of a femtocell is a key for bandwidth limitation and coverage issues in conventional mobile network system. To increase the handover performance this paper proposed a multiple input multiple output (MIMO) assisted handoff (MAHO) algorithm. It is a technique used in mobile telecom to transfer a mobile phone to a new radio channel with stronger signal strength and improved channel quality.

Keywords: flawless handover, high-speed train, home evolved Node B, LTE, mobile femtocell, RSS

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Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

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In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: segmentation, color-texture, neural networks, fractal, watershed

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Thuy Bui Anh, Ngan Nguyen Thi Thanh

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Currently, social work in Vietnam is entering the first step in the development process to become a true profession with a strong position in society. However, Spirit of helping and sharing of social work has already existed in the daily life of Vietnamese people for a very long time, becoming a precious heritage passed down from ancestors to the next generations while expanding the territory, building and defending for the country. Following the stream of history, charity work in Vietnam has gradually transformed itself towards a more professional work, especially in the last 2 decades. Accordingly, more than 50 universities and educational institutions in Vietnam have been licensed to train social work, ensuring a stronger foundation on human resources working in this field. Despite the strong growth, social work profession, social work education and the recognition of the role of the social workers still need to be fueled to develop, responded to the increasing demand of Vietnam society.

Keywords: education, history, recognition, social work, Vietnam

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Authors: Jamison Duckworth, Shankarachary Ragi

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Detection and segmentation of wildfire smoke plumes from remote sensing imagery are being pursued as a solution for early fire detection and response. Smoke plume detection can be automated and made robust by the application of artificial intelligence methods. Specifically, in this study, the deep learning approach Mask Region-based Convolutional Neural Network (RCNN) is being proposed to learn smoke patterns across different spectral bands. This method is proposed to separate the smoke regions from the background and return masks placed over the smoke plumes. Multispectral data was acquired using NASA’s Earthdata and WorldView and services and satellite imagery. Due to the use of multispectral bands along with the three visual bands, we show that Mask R-CNN can be applied to distinguish smoke plumes from clouds and other landscape features that resemble smoke.

Keywords: deep learning, mask-RCNN, smoke plumes, spectral bands

Procedia PDF Downloads 106