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Authors: S. Mahdavi, S.R. Allahkaram

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Electrodeposition is a simple and economic technique for precision coating of different shaped substrates with pure metal, alloy or composite films. Dc electrodeposition was used to produce Cr, Co-Cr and Co-Cr/TiO2 nano-composite coatings from Cr(III) based electrolytes onto 316L SS substrates. The effects of TiO2 nano-particles concentration on co-deposition of these particles along with Cr content and microhardness of the coatings were investigated. Morphology of the Cr, Co-Cr and Co-Cr/TiO2 coatings besides their tribological behavior were studied. The results showed that increment of TiO2 nano-particles concentration from 0 to 30 g L-1 in the bath increased their co-deposition and Cr content of the coatings from 0 to 3.5 wt.% and from 23.7 to 31.2 wt.%, respectively. Microhardness of Cr coating was about 920 Hv which was higher than Co-Cr and even Co-Cr/TiO2 films. Microhardness of Co-Cr and Co-Cr/TiO2 coatings were improved by increasing their Cr and TiO2 content. All the coatings had nodular morphology and contained microcracks. Nodules sizes and the number of microcracks in the alloy and composite coatings were lower than the Cr film. Wear results revealed that the Co-Cr/TiO2 coating had the lowest wear loss between all the samples, while the Cr film had the worst wear resistance.

Keywords: Co-Cr alloy, electrodeposition, nano-composite, tribological behavior, trivalent chromium

Procedia PDF Downloads 476

Authors: Kyung-Hoon Jang, Jae-Hyo Park, Kwang-Yeop Jang, Dongjin Kim

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The Tesla coil is an electrical resonant transformer circuit designed by inventor Nikola Tesla in 1891. It is used to produce high voltage, low current and high frequency alternating current electricity. Tesla experimented with a number of different configurations consisting of two or sometimes three coupled resonant electric circuits. This paper focuses on development and high voltage education to apply a Tesla coil to cuisine for high quality flavor and taste conditioning as well as high voltage education under 50 kV corona discharge. The result revealed that the velocity of roasted black belly pork by Tesla coil is faster than that of conventional methods such as hot grill and steel plate etc. depending on applied voltage level and applied voltage time. Besides, carbohydrate and crude protein increased, whereas natrium and saccharides significantly decreased after lightning surge by Tesla coil. This idea will be useful in high voltage education and high voltage application.

Keywords: corona discharge, Tesla coil, high voltage application, high voltage education

Procedia PDF Downloads 314

Authors: Ho-Won Jung, Donghun Lee, Hyung-Jin Kim

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Predictive analytics (data analysis) uses a subset of measurements (the features, predictor, or independent variable) to predict another measurement (the outcome, target, or dependent variable) on a single person or unit. It applies empirical methods in statistics, operations research, and machine learning to predict the future, or otherwise unknown events or outcome on a single or person or unit, based on patterns in data. Most analyses of metabolic syndrome are not predictive analytics but statistical explanatory studies that build a proposed model (theory building) and then validate metabolic syndrome predictors hypothesized (theory testing). A proposed theoretical model forms with causal hypotheses that specify how and why certain empirical phenomena occur. Predictive analytics and explanatory modeling have their own territories in analysis. However, predictive analytics can perform vital roles in explanatory studies, i.e., scientific activities such as theory building, theory testing, and relevance assessment. In the context, this study is to demonstrate how to use our predictive analytics to support theory building (i.e., hypothesis generation). For the purpose, this study utilized a big data predictive analytics platform TM based on a co-occurrence graph. The co-occurrence graph is depicted with nodes (e.g., items in a basket) and arcs (direct connections between two nodes), where items in a basket are fully connected. A cluster is a collection of fully connected items, where the specific group of items has co-occurred in several rows in a data set. Clusters can be ranked using importance metrics, such as node size (number of items), frequency, surprise (observed frequency vs. expected), among others. The size of a graph can be represented by the numbers of nodes and arcs. Since the size of a co-occurrence graph does not depend directly on the number of observations (transactions), huge amounts of transactions can be represented and processed efficiently. For a demonstration, a total of 13,254 metabolic syndrome training data is plugged into the analytics platform to generate rules (potential hypotheses). Each observation includes 31 predictors, for example, associated with sociodemographic, habits, and activities. Some are intentionally included to get predictive analytics insights on variable selection such as cancer examination, house type, and vaccination. The platform automatically generates plausible hypotheses (rules) without statistical modeling. Then the rules are validated with an external testing dataset including 4,090 observations. Results as a kind of inductive reasoning show potential hypotheses extracted as a set of association rules. Most statistical models generate just one estimated equation. On the other hand, a set of rules (many estimated equations from a statistical perspective) in this study may imply heterogeneity in a population (i.e., different subpopulations with unique features are aggregated). Next step of theory development, i.e., theory testing, statistically tests whether a proposed theoretical model is a plausible explanation of a phenomenon interested in. If hypotheses generated are tested statistically with several thousand observations, most of the variables will become significant as the p-values approach zero. Thus, theory validation needs statistical methods utilizing a part of observations such as bootstrap resampling with an appropriate sample size.

Keywords: explanatory modeling, metabolic syndrome, predictive analytics, theory building

Procedia PDF Downloads 261

Authors: Shahrokh Ranjbar-Bahadori, Nima Farhadifar, Leila Mohammadyar

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Plant preparations from thyme and garlic have been shown to be effective acaricides against the poultry red mite, Dermanyssus gallinae. In a layer house with a history of D. gallinae problem, mites were detected in the monitoring traps for the first time and number of them was counted. Then, some rows of layer house was sprayed twice using a concentration of 0.21 mg/cm2 thyme essential oil and 0.07 mg/cm2 garlic juice and a similar row was used as an untreated control group. Red mite traps made of cardboard were used to assess the mite density during days 1 and 7 after treatment and always removed after 24 h. the collected mites were counted and the efficacy against all mite stages (larvae, nymphs and adults) was calculated. Results showed that on day 1 and 7 after the administration of garlic extract efficacy rate was 92.05% and 74.62%, respectively. Moreover, efficacy rate on day 1 and 7 was 89.4% and 95.37% when treatment was done with thyme essential oil. It is concluded that using garlic juice to control of D. gallinae is more effective on short time. But thyme essential oil has a long time effect in compare to garlic preparation.

Keywords: Dermanyssus gallinae, essential oil, garlic, thyme, efficacy

Procedia PDF Downloads 427

Authors: Pradthana Sianglam, Wittaya Ngeontae

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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 357

Authors: Mahdi Fakoor, Seyed Mohammad Navid Ghoreishi

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Composite patching is a common way for reinforcing the cracked pipes and cylinders. The effects of composite patch reinforcement on fracture parameters of a cracked pipe depend on a variety of parameters such as number of layers, angle, thickness, and material of each layer. Therefore, stacking sequence optimization of composite patch becomes crucial for the applications of cracked pipes. In this study, in order to obtain the optimal stacking sequence for a composite patch that has minimum weight and maximum resistance in propagation of cracks, a coupled Multi-Objective Genetic Algorithm (MOGA) and Finite Element Method (FEM) process is proposed. This optimization process has done for longitudinal and transverse semi-elliptical cracks and optimal stacking sequences and Pareto’s front for each kind of cracks are presented. The proposed algorithm is validated against collected results from the existing literature.

Keywords: multi objective optimization, pareto front, composite patch, cracked pipe

Procedia PDF Downloads 302

Authors: Omar Awad, R. Mamat, F. Yusop, M. M. Noor, I. M. Yusri

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Fusel oil is a by-product obtained through the fermentation of some agricultural products. The fusel oil properties are closer to other alternative combustible types and the limited number of studies on the use of fusel oil as an alcohol derivative in SI engines constitutes to the base of this study. This paper experimentally examined the impacts of a by-product of alcohol, which is fusel oil by blending it with gasoline, on engine performance, combustion characteristics, and emissions in a 4-cylinder SI engine. The test was achieved at different engine speeds and a 60 % throttle valve (load). As results, brake power, BTE, and BSFC of F10 are higher at all engine speeds. Maximum engine BTE was 33.9%, at the lowest BSFC with F10. Moreover, it is worth seeing that the F10 under rich air-fuel ratio has less variation of COVIMEP compared to the F20 and gasoline. F10 represents shorter combustion duration, thereby, the engine power increased. NOx emission for F10 at 4500 rpm was lower than gasoline. The highest value of HC emission is obtained with F10 compared to gasoline and F20 with an average increase of 11% over the engine speed range. CO and CO2 emissions increased when using fusel oil blends.

Keywords: fusel oil, spark ignition engine, by-product alcohol, combustion characteristics, engine emissions, alternative fuel

Procedia PDF Downloads 463

Authors: Vivek Mahadev, Manoj Kumar, Neelu Mathur, Brahm Dutt Pandey

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Perimeter guarding and protection of critical installations require prompt intrusion detection and assessment to take effective countermeasures. Currently, visual and electronic surveillance are the primary methods used for perimeter guarding. These methods can be costly and complicated, requiring careful planning according to the location and terrain. Moreover, these methods often struggle to detect stealthy and camouflaged insurgents. The object of the present work is to devise a surveillance technique using seismic sensors that overcomes the limitations of existing systems. The aim is to improve intrusion detection, assessment, and characterization by utilizing seismic sensors. Most of the similar systems have only two types of intrusion detection capability viz., human or vehicle. In our work we could even categorize further to identify types of intrusion activity such as walking, running, group walking, fence jumping, tunnel digging and vehicular movements. A virtual fence of 60 meters at GCNEP, Bahadurgarh, Haryana, India, was created by installing four underground geophones at a distance of 15 meters each. The signals received from these geophones are then processed to find unique seismic signatures called features. Various feature optimization and selection methodologies, such as LightGBM, Boruta, Random Forest, Logistics, Recursive Feature Elimination, Chi-2 and Pearson Ratio were used to identify the best features for training the machine learning models. The trained models were developed using algorithms such as supervised support vector machine (SVM) classifier, kNN, Decision Tree, Logistic Regression, Naïve Bayes, and Artificial Neural Networks. These models were then used to predict the category of events, employing weighted ensemble voting to analyze and combine their results. The models were trained with 1940 training events and results were evaluated with 831 test events. It was observed that using the weighted ensemble voting increased the efficiency of predictions. In this study we successfully developed and deployed the virtual fence using geophones. Since these sensors are passive, do not radiate any energy and are installed underground, it is impossible for intruders to locate and nullify them. Their flexibility, quick and easy installation, low costs, hidden deployment and unattended surveillance make such systems especially suitable for critical installations and remote facilities with difficult terrain. This work demonstrates the potential of utilizing seismic sensors for creating better perimeter guarding and protection systems using multiple machine learning models in weighted ensemble voting. In this study the virtual fence achieved an intruder detection efficiency of over 97%.

Keywords: geophone, seismic perimeter surveillance, machine learning, weighted ensemble method

Procedia PDF Downloads 66

Authors: Alyona Gencheva

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The most common way to study diagnostic results is using specialized programs at a stationary workplace. Magnetic Resonance Imaging is presented in a two-dimensional (2D) format, and Computed Tomography sometimes looks like a three-dimensional (3D) model that can be interacted with. The main idea of the research is to compare ways of displaying diagnostic results in virtual reality that can help a surgeon during or before an operation in augmented reality. During the experiment, the medical staff examined liver vessels in the abdominal area and heart boundaries. The search time and detection accuracy were measured on black-and-white and coloured scans. Usability testing in virtual reality shows convenient ways of interaction like hand input, voice activation, displaying risk to the patient, and the required number of scans. The results of the experiment will be used in the new C# program based on Magic Leap technology.

Keywords: augmented reality, computed tomography, magic leap, magnetic resonance imaging, usability testing, VTE risk

Procedia PDF Downloads 96

Authors: M. Rahimi, F. Corman

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This paper study the travel behavior of passengers in a public transport disruption under information provision strategies. We develop a within-day approach for multi-agent simulation to evaluate the behavior of the agents, under comprehensive scenarios through various information exposure, equilibrium, and non-equilibrium scenarios. In particular, we quantify the effects of information strategies in disruption situation on passengers’ satisfaction, number of involved agents, and the caused delay. An agent-based micro-simulation model (MATSim) is applied for the city of Zürich, Switzerland, for the purpose of activity-based simulation in a multimodal network. Statistic outcome is analysed for all the agents who may be involved in the disruption. Agents’ movement in the public transport network illustrates agents’ adaptations to available information about the disruption. Agents’ delays and utility reveal that information significantly affects agents’ satisfaction and delay in public transport disruption. Besides, while the earlier availability of the information causes the fewer consequent delay for the involved agents, however, it also leads to more amount of affected agents.

Keywords: agent-based simulation, disruption management, passengers’ behavior simulation, public transport

Procedia PDF Downloads 129

Authors: M. Lghoul, N. El Goumi, M. Guernouche

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In order to predict the structural and tectonic framework of the Bahira basin and to have a 3D geological modeling of the basin, an integrated multidisciplinary work has been conducted using gravity, magnetic and geological data. The objective of the current study is delineating the subsurfacefeatures, faults, and geological limits, using airborne magnetic and gravity data analysis of the Bahira basin. To achieve our goal, we have applied different enhanced techniques on magnetic and gravity data: power spectral analysis techniques, reduction to pole (RTP), upward continuation, analytical signal, tilt derivative, total horizontal derivative, 3D Euler deconvolutionand source parameter imagining. The major lineaments/faults trend are: NE–SW, NW-SE, ENE–WSW, and WNW–ESE. The 3D Euler deconvolution analysis highlighted a number of fault trend, mainly in the ENE-WSW, WNW-ESE directions. The depth tothe top of the basement sources in the study area ranges between 200 m, in the southern and northern part of the Bahira basin, to 5000 m located in the Eastern part of the basin.

Keywords: magnetic, gravity, structural trend, depth to basement

Procedia PDF Downloads 118

Authors: Umair Rashid

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Normally softmax loss is used as the supervision signal in face recognition (FR) system, and it boosts the separability of features. In the last two years, a number of techniques have been proposed by reformulating the original softmax loss to enhance the discriminating power of Deep Convolutional Neural Networks (DCNNs) for FR system. To learn angularly discriminative features Cosine-Margin based softmax has been adjusted as monotonically decreasing angular function, that is the main challenge for angular based softmax. On that issue, we propose monotonically decreasing element for Cosine-Margin based softmax and also, we discussed the effect of different monotonically decreasing parameters on angular Margin softmax for FR system. We train the model on publicly available dataset CASIA- WebFace via our proposed monotonically decreasing parameters for cosine function and the tests on YouTube Faces (YTF, Labeled Face in the Wild (LFW), VGGFace1 and VGGFace2 attain the state-of-the-art performance.

Keywords: deep convolutional neural networks, cosine margin face recognition, softmax loss, monotonically decreasing parameter

Procedia PDF Downloads 82

Authors: Tahere Fazilat

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Caspian red deer or maral (Cervus elaphus maral) is the largest type of deer in iran. Maral in the past has lived in the north forests of Iran from the Caspian sea coast, Alborz mountains chain and oak forest of Zagros margin from the Azarbaijan up to fars province. However, the generation of them was completely destroyed in the north west and west of Iran. According to reports about 50 years and out of reach of humans. In the present studies, data were collected from 2004 to 2014 in the Mazandaran state Hyrcanian forest by means of guard of environment and justiciary office of department of environment of Mazandaran in this process the all arrested illegal hunting of red deer and the population census, estimation and the correlation of these data was assayed. We provide a first evaluation of how suitable these methods are by comparing the results with population estimates obtained using cohort analysis, and by analyzing the within-season variation in number of seen deer. The data gave us the future of red deer in northern forest of Iran and the results of policy of department of environment in Iran in red deer conservation.

Keywords: illegal hunting, red deer, census, concervation

Procedia PDF Downloads 540

Authors: K. Noah, F.-S. Lien

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In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.

Keywords: compressible lattice Boltzmann method, multiple relaxation times, large eddy simulation, turbulent jet flows

Procedia PDF Downloads 261

Authors: B. Makoudi, R. Ghanimi, M. Mouradi, A. Kabbadj, M. Farissi, J. J. Drevon, C. Ghoulam

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This work focuses on the responses of Vicia fabarhizobia symbiosis to phosphorus deficiency and their contribution to tolerate this constraint. The study was carried out on four faba bean varieties, Aguadulce, Alfia, Luz Otono, and Reina Mora submitted to two phosphorus treatments, deficient and sufficient and cultivated under field and greenhouse hydroaeroponic culture. Plants were harvested at flowering stage for growth, nodulation and phosphorus content assessment. Phosphatases in nodules and rhizospheric soil were analyzed. The impact of phosphorus deficiency on yield component was assessed at maturity stage. Under field conditions, phosphorus deficiency affected negatively nodule biomass and nodule phosphorus content with Alfia and Reina Mora showing the highest biomass reduction. The phosphatase activities in nodules and rhizospheric soil were increased under phosphorus deficiency. At maturity stage, under soil low available phosphorus, the pods number and 100 seeds weight were reduced. The genotypic variation was evident for almost all tested parameters.

Keywords: faba bean, phosphorus, rhizobia, yield

Procedia PDF Downloads 436

Authors: Cui Long (Allen)

Abstract:

The role of the Arctic in world politics and international relations has increased significantly over the past decades. With its large natural resources, the Arctic region has important geopolitical, strategic, and economic significance. All this determines the interest in it not only of the Arctic states but also of states located far from the Arctic. One of these states is the People's Republic of China. Relations between China and Russia in recent decades have been built on the basis of strategic partnership. Joint projects in the Arctic have become the most important priority area of this partnership. These are projects in the transport and energy fields. A large number of works by Russian scientists are devoted to the Sino-Russian Arctic cooperation. Most authors consider cooperation as a guarantee of stability for China and Russia in a globalized world. However, there are authors who believe that there are separate contradictions in the relations between the Arctic and non-Arctic countries. In their opinion, China sometimes acts as a competitor, and its activities become expansionist. In general, according to the Russian authors, Sino-Russian cooperation is mutually beneficial and is under development. China and Russia have a long way to go in the issue of sustainable development of the Arctic.

Keywords: People’s Republic of China, Russian Federation, Arctic, historiography

Procedia PDF Downloads 55

Authors: Enes Furkan Erkan, Özer Uygun, Halil Ibrahim Demir, Zeynep Demir

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Companies require increase in quality perception level of their products due to competitive conditions. As a result, the tendency to quality and researches to develop the quality are increasing day by day. Cost and time constraints are the biggest problems that companies face in their quality improvement efforts. In this study, factors that affect the porosity of ceramic products are determined and analyzed in a factory producing ceramic tiles. Then, Taguchi method is used in the design phase in order to decrease the number of tests to be performed by means of orthogonal sequences. The most important factors affecting the porosity of ceramic tiles are determined using Taguchi and ANOVA analysis. Based on the analyses, the most affecting factors are determined to be used in the fuzzy implementation stage. Then, the fuzzy rules were established with the factors affecting porosity by the experts’ opinion. Thus, porosity result could be obtained not only for the specified factor levels but also for intermediate values. In this way, it has been provided convenience to the factory in terms of cost and quality improvement.

Keywords: fuzzy, porosity, Taguchi Method, Taguchi-Fuzzy

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Authors: Mehdi Assefi, Keihan Hataminezhad

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One of the efficient architectures for exploring the resources in wireless ad-hoc networks is contact-based architecture. In this architecture, each node assigns a unique zone for itself and each node keeps all information from inside the zone, as well as some from outside the zone, which is called contact. Reducing the overlap between different zones of a node and its contacts increases its performance, therefore Edge Method (EM) is designed for this purpose. Contacts selected by EM do not have any overlap with their sources, but for choosing the contact a vast amount of information must be transmitted. In this article, we will offer a new protocol for contact selection, which is called PEM. The objective would be reducing the volume of transmitted information, using Non-Uniform Dissemination Probabilistic Protocols. Consumed energy for contact selection is a function of the size of transmitted information between nodes. Therefore, by reducing the content of contact selection message using the PEM will decrease the consumed energy. For evaluation of the PEM we applied the simulation method. Results indicated that PEM consumes less energy compared to EM, and by increasing the number of nodes (level of nodes), performance of PEM will improve in comparison with EM.

Keywords: wireless ad-hoc networks, contact selection, method for CARD, energy-efficient

Procedia PDF Downloads 275

Authors: Ambuj Kumar Gautam, V. Vasu

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This paper introduces a head movement based Human Machine Interface (HMI) that uses the right and left movements of head to control a robot motion. Here we present an approach for making an effective technique for real-time face orientation information system, to control a robot which can be efficiently used for Electrical Powered Wheelchair (EPW). Basically this project aims at application related to HMI. The system (machine) identifies the orientation of the face movement with respect to the pixel values of image in a certain areas. Initially we take an image and divide that whole image into three parts on the basis of its number of columns. On the basis of orientation of face, maximum pixel value of approximate same range of (R, G, and B value of a pixel) lie in one of divided parts of image. This information we transfer to the microcontroller through serial communication port and control the motion of robot like forward motion, left and right turn and stop in real time by using head movements.

Keywords: electrical powered wheelchair (EPW), human machine interface (HMI), robotics, microcontroller

Procedia PDF Downloads 278

Authors: Eun Ho Kim

Abstract:

Innovations have conjured up a mode of treating GBM cancer cells in the newly diagnosed patients in a period of 4.9 months at an improved median OS, which brings along only a few minor side effects in the phase III of the clinical trial. This mode has been termed the Alternating Electric Fields (AEF). The study at hand is aimed at determining whether the AEF treatment is beneficial in sensitizing the GBM cancer cells through the process of increasing the AEF –induced senescence. The methodology to obtain the findings for this research ranged across various components, such as obtaining and testing SA-β-gal staining, flow cytometry, Western blotting, morphology, and Positron Emission Tomography (PET) / Computed Tomography (CT), immunohistochemical staining and microarray. The number of cells that displayed a senescence-specific morphology and positive SA-ß-Gal activity gradually increased up to 5 days. These results suggest that p16, p21 and p27 are essential regulators of AEF -induced senescence via NF-κB activation. The results showed that the AEF treatment is functional in enhancing the AEF –induced senescence in the GBM cells via an apoptosis- independent mechanism. This research concludes that this mode of treatment is a trustworthy protocol that can be effectively employed to overcome the limitations of the conventional mode of treatment on GBM.

Keywords: alternating electric fields, senescence, glioblastoma, cell death

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Authors: S. Bayona, J. Nunez, D. Paez, C. Diaz

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The application of Lean manufacturing tools continues to be an effective solution for increasing productivity, reducing costs and eliminating waste in the manufacture of goods and services. This article analyzes the production process of a hot asphalt manufacturing company from an administrative and technical perspective. Three main phases were analyzed, the first phase was related to the determination of the risk priority number of the main operations in asphalt mix production process by an FMEA (Failure Mode Effects Analysis), in the second phase the Value Stream Mapping (VSM) of the production line was performed and in the third phase a SWOT (Strengths, Weaknesses Opportunities, Threats) matrix was constructed. Among the most valued failure modes were the lack training of workers in occupational safety and health issues, the lack of signaling and classification of granulated material, and the overweight of vehicles loaded. The analysis of the results in the three phases agree on the importance of training operational workers, improve communication with external actors in order to minimize delays in material orders and strengthen control suppliers.

Keywords: asphalt, lean manufacturing, productivity, process

Procedia PDF Downloads 105

Authors: Zhifeng Kong

Abstract:

Over-parameterized neural networks have attracted a great deal of attention in recent deep learning theory research, as they challenge the classic perspective of over-fitting when the model has excessive parameters and have gained empirical success in various settings. While a number of theoretical works have been presented to demystify properties of such models, the convergence properties of such models are still far from being thoroughly understood. In this work, we study the convergence properties of training two-hidden-layer partially over-parameterized fully connected networks with the Rectified Linear Unit activation via gradient descent. To our knowledge, this is the first theoretical work to understand convergence properties of deep over-parameterized networks without the equally-wide-hidden-layer assumption and other unrealistic assumptions. We provide a probabilistic lower bound of the widths of hidden layers and proved linear convergence rate of gradient descent. We also conducted experiments on synthetic and real-world datasets to validate our theory.

Keywords: over-parameterization, rectified linear units ReLU, convergence, gradient descent, neural networks

Procedia PDF Downloads 131

Authors: Vidhya Venugopal, Jeremiah Chinnadurai, Rebekah A. I. Lucas, Tord Kjellstrom, Bruno Lemke

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Introduction: The effects of climate change (CC) are largely discussed across the globe in terms of impacts on the environment and the general population, but the impacts on workers remain largely unexplored. The predicted rise in temperatures and heat events in the CC scenario have health implications on millions of workers in physically exerting jobs. The current health and productivity risks associated with heat exposures are characterized, future risk estimates as temperature rises and recommendations towards developing protective and preventive occupational health and safety guidelines for India are discussed. Methodology: Cross-sectional studies were conducted in several occupational sectors with workers engaged in moderate to heavy labor (n=1580). Quantitative data on heat exposures (WBGT°C), physiological heat strain indicators viz., Core temperature (CBT), Urine specific gravity (USG), Sweat rate (SwR) and qualitative data on heat-related health symptoms and productivity losses were collected. Data were analyzed for associations between heat exposures, health and productivity outcomes related to heat stress. Findings: Heat conditions exceeded the Threshold Limit Value (TLV) for safe manual work in 66% of the workers across several sectors (Avg.WBGT of 28.7°C±3.1°C). Widespread concerns about heat-related health outcomes (86%) were prevalent among workers exposed to high TLVs, with excessive sweating, fatigue and tiredness being commonly reported by workers. The heat stress indicators, core temperature (14%), Sweat rate (8%) and USG (9%), were above normal levels in the study population. A significant association was found between rise in Core Temperatures and WBGT exposures (p=0.000179) Elevated USG and SwR in the worker population indicate moderate dehydration, with potential risks of developing heat-related illnesses. In a steel industry with high heat exposures, an alarming 9% prevalence of kidney/urogenital anomalies was observed in a young workforce. Heat exposures above TLVs were associated with significantly increased odds of various adverse health outcomes (OR=2.43, 95% CI 1.88 to 3.13, p-value = <0.0001) and productivity losses (OR=1.79, 95% CI 1.32 to 2.4, p-value = 0.0002). Rough estimates for the number of workers who would be subjected to higher than TLV levels in the various RCP scenarios are RCP2.6 =79%, RCP4.5 & RCP6 = 81% and at RCP 8.5 = 85%. Rising temperatures due to CC has the capacity to further reduce already compromised health and productivity by subjecting the workers to increased heat exposures in the RCP scenarios are of concern for the country’s occupational health and economy. Conclusion: The findings of this study clearly identify that health protection from hot weather will become increasingly necessary in the Indian subcontinent and understanding the various adaptation techniques needs urgent attention. Further research with a multi-targeted approach to develop strategies for implementing interventions to protect the millions of workers is imperative. Approaches to include health aspects of climate change within sectoral and climate change specific policies should be encouraged, via a number of mechanisms, such as the “Health in All Policies” approach to avert adverse health and productivity consequences as climate change proceeds.

Keywords: heat stress, occupational health, productivity loss, heat strain, adverse health outcomes

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Authors: Shweta Pinjarkar, Shrutika Yawale, Mayuri Patil, Reshma Adagale

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Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this, demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application. Face recognition is the technique which can be applied to the wide variety of problems like image and film processing, human computer interaction, criminal identification etc. This has motivated researchers to develop computational models to identify the faces, which are easy and simple to implement. In this , demonstrates the face recognition system in android device using eigenface. The system can be used as the base for the development of the recognition of human identity. Test images and training images are taken directly with the camera in android device.The test results showed that the system produces high accuracy. The goal is to implement model for particular face and distinguish it with large number of stored faces. face recognition system detects the faces in picture taken by web camera or digital camera and these images then checked with training images dataset based on descriptive features. Further this algorithm can be extended to recognize the facial expressions of a person.recognition could be carried out under widely varying conditions like frontal view,scaled frontal view subjects with spectacles. The algorithm models the real time varying lightning conditions. The implemented system is able to perform real-time face detection, face recognition and can give feedback giving a window with the subject's info from database and sending an e-mail notification to interested institutions using android application.

Keywords: face detection, face recognition, eigen faces, algorithm

Procedia PDF Downloads 344

Authors: Caroline Jones

Abstract:

Research over the last decade suggests that there have been distinct changes in both women’s sexual behaviour and attitudes towards female sexuality in the UK. Areas such as discussing sex, participating in sexual activity outside of traditional monogamous relationships, and engaging in boudoir photography have all been explored by researchers. Women’s participation in tantric practices, however, is a relatively unexplored area of sexuality, despite an increasing number of Tantra schools opening in the UK. Tantra is a practice in which women are considered to have a higher consciousness than men, where the sexual role of women is deemed to be very different to a traditional Western sexually passive role. This research looks at this area, and is based on in-depth, semi-structured, thematically analysed interviews with women who have participated in tantric workshops and/or retreats across the country. The interviews investigate why women engage with such practices, what they feel they gain from the experience, and how shifting notions of appropriate sexual roles for women impact on their sexuality and life generally. While Tantra is still a minority activity in the UK, the findings shed light on not only these areas but also on women’s constructions of their sexuality, their relationships with their bodies and sexualities, and ways in which they express and engage with changing notions of female sexuality.

Keywords: sexuality, Tantra, gender, Shakti

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Authors: Rajamani Doraiswami, Lahouari Cheded

Abstract:

Fault diagnosis of Linear Parameter-Varying (LPV) system using an adaptive Kalman filter is proposed. The LPV model is comprised of scheduling parameters, and the emulator parameters. The scheduling parameters are chosen such that they are capable of tracking variations in the system model as a result of changes in the operating regimes. The emulator parameters, on the other hand, simulate variations in the subsystems during the identification phase and have negligible effect during the operational phase. The nominal model and the influence vectors, which are the gradient of the feature vector respect to the emulator parameters, are identified off-line from a number of emulator parameter perturbed experiments. A Kalman filter is designed using the identified nominal model. As the system varies, the Kalman filter model is adapted using the scheduling variables. The residual is employed for fault diagnosis. The proposed scheme is successfully evaluated on simulated system as well as on a physical process control system.

Keywords: identification, linear parameter-varying systems, least-squares estimation, fault diagnosis, Kalman filter, emulators

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Authors: R. Kiran, B. R. Lakshmikantha, R. V. Parimala

Abstract:

Secure operation of power systems requires monitoring of the system operating conditions. Phasor measurement units (PMU) are the device, which uses synchronized signals from the GPS satellites, and provide the phasors information of voltage and currents at a given substation. The optimal locations for the PMUs must be determined, in order to avoid redundant use of PMUs. The objective of this paper is to make system observable by using minimum number of PMUs & the implementation of stability software at 22OkV grid for on-line estimation of the power system transfer capability based on voltage and thermal limitations and for security monitoring. This software utilizes State Estimator (SE) and synchrophasor PMU data sets for determining the power system operational margin under normal and contingency conditions. This software improves security of transmission system by continuously monitoring operational margin expressed in MW or in bus voltage angles, and alarms the operator if the margin violates a pre-defined threshold.

Keywords: state estimator (SE), flexible ac transmission systems (FACTS), optimal location, phasor measurement units (PMU)

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Authors: Pham Ngoc Thang, Le Thai Hung, Nguyen Quang Bau

Abstract:

The influence of confined acoustic phonons on the Shubnikov – de Haas magnetoresistance oscillations in a doped semiconductor superlattice (DSSL), subjected in a magnetic field, DC electric field, and a laser radiation, has been theoretically studied based on quantum kinetic equation method. The analytical expression for the magnetoresistance in a DSSL has been obtained as a function of external fields, DSSL parameters, and especially the quantum number m characterizing the effect of confined acoustic phonons. When m goes to zero, the results for bulk phonons in a DSSL could be achieved. Numerical calculations are also achieved for the GaAs:Si/GaAs:Be DSSL and compared with other studies. Results show that the Shubnikov – de Haas magnetoresistance oscillations amplitude decrease as the increasing of phonon confinement effect.

Keywords: Shubnikov–de Haas magnetoresistance oscillations, quantum kinetic equation, confined acoustic phonons, laser radiation, doped semiconductor superlattices

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Authors: Peter Temitope Agboola

Abstract:

Food insecurity continues to affect a large number of U.S households during this coronavirus COVID-19 pandemic. The pandemic has threatened the livelihoods of people, making them vulnerable to severe hardship and has had an unanticipated impact on the U.S economy. This study attempts to identify the food insecurity status of households and the determinant factors driving household food insecurity. Additionally, it attempts to discover the mitigation measures adopted by households during the pandemic in the city of Huntsville, Texas. A structured online sample survey was used to collect data, with a household expenditures survey used in evaluating the food security status of the household. Most survey respondents disclosed that the COVID-19 pandemic had affected their life and source of income. Furthermore, the main analytical tool used for the study is descriptive statistics and logistic regression modeling. A logistic regression model was used to determine the factors responsible for food insecurity in the study area. The result revealed that most households in the study area are food secure, with the remainder being food insecure.

Keywords: food insecurity, household expenditure survey, COVID-19, coping strategies, food pantry

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Authors: Hestika D. Waraningrum, Indriani N. Khairunnisa, Nabila Isnandini, Nadine Yasminah, Sekar A. Winesa

Abstract:

Each individual’s ability to recall, whether they are male or female, is allegedly influenced by the environmental circumstances during the recalling process. The presence of a distraction is one of the environmental variables that affect recall ability in its capacity in the Short Term Memory. This study was made to see the difference in number of words that was successfully recalled by male participants and female participants with the presence of music as a distraction and also without music as a distraction. Data was taken using an experimental procedure from 75 female and male undergraduate students of Universitas Indonesia. The study design used was a 2x2 Factorial ANOVA, which aimed to see the difference between two variables, which were gender (male vs female) and the presence of a distraction (music serving as a distraction vs absence of music). The results indicated that there were no significant mean differences in the ability to recall between male and female participants. There are no significant mean differences between the presence and the absence of music as a distraction, but a significant interaction was found between gender and distraction with the ability to recall.

Keywords: college, gender, music, recall

Procedia PDF Downloads 223