Search results for: failure detection and prediction

Authors: Rhea Kapoor

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Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

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Authors: Pavlina Capkova, Josef Srovnal, Vera Becvarova, Marie Trkova, Zuzana Capkova, Andrea Stefekova, Vaclava Curtisova, Alena Santava, Sarka Vejvalkova, Katerina Adamova, Radek Vodicka

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ASDs are heterogeneous and complex developmental diseases with a significant genetic background. Recurrent CNVs are known to be a frequent cause of ASD. These CNVs can have, however, a variable expressivity which results in a spectrum of phenotypes from asymptomatic to ID/DD/ASD. ASD is associated with ID in ~75% individuals. Various platforms are used to detect pathogenic mutations in the genome of these patients. The performed study is focused on a determination of the frequency of pathogenic mutations in a group of ASD patients and a group of ID/DD patients using various strategies along with a comparison of their detection rate. The possible role of the origin of these mutations in aetiology of ASD was assessed. The study included 35 individuals with ASD and 68 individuals with ID/DD (64 males and 39 females in total), who underwent rigorous genetic, neurological and psychological examinations. Screening for pathogenic mutations involved karyotyping, screening for FMR1 mutations and for metabolic disorders, a targeted MLPA test with probe mixes Telomeres 3 and 5, Microdeletion 1 and 2, Autism 1, MRX and a chromosomal microarray analysis (CMA) (Illumina or Affymetrix). Chromosomal aberrations were revealed in 7 (1 in the ASD group) individuals by karyotyping. FMR1 mutations were discovered in 3 (1 in the ASD group) individuals. The detection rate of pathogenic mutations in ASD patients with a normal karyotype was 15.15% by MLPA and CMA. The frequencies of the pathogenic mutations were 25.0% by MLPA and 35.0% by CMA in ID/DD patients with a normal karyotype. CNVs inherited from asymptomatic parents were more abundant than de novo changes in ASD patients (11.43% vs. 5.71%) in contrast to the ID/DD group where de novo mutations prevailed over inherited ones (26.47% vs. 16.18%). ASD patients shared more frequently their mutations with their fathers than patients from ID/DD group (8.57% vs. 1.47%). Maternally inherited mutations predominated in the ID/DD group in comparison with the ASD group (14.7% vs. 2.86 %). CNVs of an unknown significance were found in 10 patients by CMA and in 3 patients by MLPA. Although the detection rate is the highest when using CMA, recurrent CNVs can be easily detected by MLPA. CMA proved to be more efficient in the ID/DD group where a larger spectrum of rare pathogenic CNVs was revealed. This study determined that maternally inherited highly penetrant mutations and de novo mutations more often resulted in ID/DD without ASD in patients. The paternally inherited mutations could be, however, a source of the greater variability in the genome of the ASD patients and contribute to the polygenic character of the inheritance of ASD. As the number of the subjects in the group is limited, a larger cohort is needed to confirm this conclusion. Inherited CNVs have a role in aetiology of ASD possibly in combination with additional genetic factors - the mutations elsewhere in the genome. The identification of these interactions constitutes a challenge for the future. Supported by MH CZ – DRO (FNOl, 00098892), IGA UP LF_2016_010, TACR TE02000058 and NPU LO1304.

Keywords: autistic spectrum disorders, copy number variant, chromosomal microarray, intellectual disability, karyotyping, MLPA, multiplex ligation-dependent probe amplification

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Authors: Mohit Modi, Rajiv Kumar, Manojraj Saxena, G. Ravi Shankar

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Change detection of coastal ecosystem plays a vital role in monitoring and managing natural resources along the coastal regions. The present study mainly focuses on the decadal change in Kochi islands connecting the urban flatland areas and the coastal regions where sand deposits have taken place. With this, in view, the change detection has been monitored in the Kochi area to apprehend the urban growth and industrialization leading to decrease in the wetland ecosystem. The region lies between 76°11'19.134"E to 76°25'42.193"E and 9°52'35.719"N to 10°5'51.575"N in the south-western coast of India. The IRS LISS-IV satellite image has been processed using a rule-based algorithm to classify the LULC and to interpret the changes between 2005 & 2015. The approach takes two steps, i.e. extracting features as a single GIS vector layer using different parametric values and to dissolve them. The multi-resolution segmentation has been carried out on the scale ranging from 10-30. The different classes like aquaculture, agricultural land, built-up, wetlands etc. were extracted using parameters like NDVI, mean layer values, the texture-based feature with corresponding threshold values using a rule set algorithm. The objects obtained in the segmentation process were visualized to be overlaying the satellite image at a scale of 15. This layer was further segmented using the spectral difference segmentation rule between the objects. These individual class layers were dissolved in the basic segmented layer of the image and were interpreted in vector-based GIS programme to achieve higher accuracy. The result shows a rapid increase in an industrial area of 40% based on industrial area statistics of 2005. There is a decrease in wetlands area which has been converted into built-up. New roads have been constructed which are connecting the islands to urban areas as well as highways. The increase in coastal region has been visualized due to sand depositions. The outcome is well supported by quantitative assessments which will empower rich understanding of land use land cover change for appropriate policy intervention and further monitoring.

Keywords: land use land cover, multiresolution segmentation, NDVI, object based classification

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Authors: Keigo Nishitani, Kohei Mizuta Mizuta, Kazuyoshi Kurita, Yukinori Taniguchi

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To establish mass production process of Ti capsule which has Fe powder inside as magnetic hyperthermia implant, we assumed that Ti thin sheet can be drawn into a φ1.0 mm die hole through the medium of Fe Powder and becomes outer shell of capsule. This study discusses mechanism of powder assisted deep drawing process by both of numerical simulation and experiment. Ti thin sheet blank was placed on die, and was covered by Fe powder layer without pressurizing. Then upper punch was indented on the Fe powder layer, and the blank can be drawn into die cavity as pressurized powder particles were extruded into die cavity from behind of the drawn blank. Distinct Element Method (DEM) has been used to demonstrate the process. To identify bonding parameters on Fe particles which are cohesion, tensile bond stress and inter particle friction angle, axial and diametrical compression failure test of Fe powder compact was conducted. Several density ratios of powder compacts in range of 0.70 - 0.85 were investigated and relationship between mean stress and equivalent stress was calculated with consideration of critical state line which rules failure criterion in consolidation of Fe powder. Since variation of bonding parameters with density ratio has been experimentally identified, and good agreement has been recognized between several failure tests and its simulation, demonstration of powder assisted sheet forming by using DEM becomes applicable. Results of simulation indicated that indent/drawing length of Ti thin sheet is promoted by smaller Fe particle size, larger indent punch diameter, lower friction coefficient between die surface and Ti sheet and certain degrees of die inlet taper angle. In the deep drawing test, we have made die-set with φ2.4 mm punch and φ1.0 mm die bore diameter. Pure Ti sheet with 100 μm thickness, annealed at 650 deg. C has been tested. After indentation, indented/drawn capsule has been observed by microscope, and its length was measured to discuss the feasibility of this capsulation process. Longer drawing length exists on progressive loading pass comparing with the case of single stroke loading. It is expected that progressive loading has an advantage of which extrusion of powder particle into die cavity with Ti sheet is promoted since powder particle layer can be rebuilt while the punch is withdrawn from the layer in each loading steps. This capsulation phenomenon is qualitatively demonstrated by DEM simulation. Finally, we have fabricated Ti capsule which has Fe powder inside for magnetic hyperthermia cancer care treatment. It is concluded that suggested method is possible to use the manufacturing of Ti capsule implant for magnetic hyperthermia cancer care.

Keywords: metal powder compaction, metal forming, distinct element method, cancer care, magnetic hyperthermia

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Authors: Syeda Mainaaz Unnisa, Deepa Suresh

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Due to the increase in usage of public domain channels, such as the internet, and communication technology, there is a concern about the protection of intellectual property and security threats. This interest has led to growth in researching and implementing techniques for information hiding. Steganography is the art and science of hiding information in a private manner such that its existence cannot be recognized. Communication using steganographic techniques makes not only the secret message but also the presence of hidden communication, invisible. Steganalysis is the art of detecting the presence of this hidden communication. Parallel to steganography, steganalysis is also gaining prominence, since the detection of hidden messages can prevent catastrophic security incidents from occurring. Steganalysis can also be incredibly helpful in identifying and revealing holes with the current steganographic techniques, which makes them vulnerable to attacks. Through the formulation of new effective steganalysis methods, further research to improve the resistance of tested steganography techniques can be developed. Feature-based steganalysis method for JPEG images calculates the features of an image using the L1 norm of the difference between a stego image and the calibrated version of the image. This calibration can help retrieve some of the parameters of the cover image, revealing the variations between the cover and stego image and enabling a more accurate detection. Applying this method to various steganographic schemes, experimental results were compared and evaluated to derive conclusions and principles for more protected JPEG steganography.

Keywords: cover image, feature-based steganalysis, information hiding, steganalysis, steganography

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Authors: Houda Najeh, Mahendra Pratap Singh, Stéphane Ploix, Antoine Caucheteux, Karim Chabir, Mohamed Naceur Abdelkrim

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Building system is highly vulnerable to different kinds of faults and human misbehaviors. Energy efficiency and user comfort are directly targeted due to abnormalities in building operation. The available fault diagnosis tools and methodologies particularly rely on rules or pure model-based approaches. It is assumed that model or rule-based test could be applied to any situation without taking into account actual testing contexts. Contextual tests with validity domain could reduce a lot of the design of detection tests. The main objective of this paper is to consider fault validity when validate the test model considering the non-modeled events such as occupancy, weather conditions, door and window openings and the integration of the knowledge of the expert on the state of the system. The concept of heterogeneous tests is combined with test validity to generate fault diagnoses. A combination of rules, range and model-based tests known as heterogeneous tests are proposed to reduce the modeling complexity. Calculation of logical diagnoses coming from artificial intelligence provides a global explanation consistent with the test result. An application example shows the efficiency of the proposed technique: an office setting at Grenoble Institute of Technology.

Keywords: heterogeneous tests, validity, building system, sensor grids, sensor fault, diagnosis, fault detection and isolation

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Authors: S. Ajith Kumar, Vaisakh S. Rajan

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In external flows, vortex shedding behind the bluff bodies causes to experience unsteady loads on a large number of engineering structures, resulting in structural failure. Vortex shedding can even turn out to be disastrous like the Tacoma Bridge failure incident. We need to have control over vortex shedding to get rid of this untoward condition by reducing the unsteady forces acting on the bluff body. In circular cylinders, hydrophobic surface in an otherwise no-slip surface is found to be delaying separation and minimizes the effects of vortex shedding drastically. Flow over square cylinder stands different from this behavior as separation can takes place from either of the two corner separation points (front or rear). An attempt is made in this study to numerically elucidate the effect of hydrophobic surface in flow over a square cylinder. A 2D numerical simulation has been done to understand the effects of the slip surface on the flow past square cylinder. The details of the numerical algorithm will be presented at the time of the conference. A non-dimensional parameter, Knudsen number is defined to quantify the slip on the cylinder surface based on Maxwell’s equation. The slip surface condition of the wall affects the vorticity distribution around the cylinder and the flow separation. In the numerical analysis, we observed that the hydrophobic surface enhances the shedding frequency and damps down the amplitude of oscillations of the square cylinder. We also found that the slip has a negative effect on aerodynamic force coefficients such as the coefficient of lift (CL), coefficient of drag (CD) etc. and hence replacing the no slip surface by a hydrophobic surface can be treated as an effective drag reduction strategy and the introduction of hydrophobic surface could be utilized for reducing the vortex induced vibrations (VIV) and is found as an effective method in controlling VIV thereby controlling the structural failures.

Keywords: drag reduction, flow past square cylinder, flow control, hydrophobic surfaces, vortex shedding

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Authors: Shahrzad Zolfagharnassab, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo

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Conventional methods for nutrient soil mapping are based on laboratory tests of samples that are obtained from surveys. The time and cost involved in gathering and analyzing soil samples are the reasons that researchers use Predictive Soil Mapping (PSM). PSM can be defined as the development of a numerical or statistical model of the relationship among environmental variables and soil properties, which is then applied to a geographic database to create a predictive map. Kriging is a group of geostatistical techniques to spatially interpolate point values at an unobserved location from observations of values at nearby locations. The main problem with using kriging as an interpolator is that it is excessively data-dependent and requires a large number of closely spaced data points. Hence, there is a need to minimize the number of data points without sacrificing the accuracy of the results. In this paper, an Artificial Neural Networks (ANN) scheme was used to predict macronutrient values at un-sampled points. ANN has become a popular tool for prediction as it eliminates certain difficulties in soil property prediction, such as non-linear relationships and non-normality. Back-propagation multilayer feed-forward network structures were used to predict nitrogen, phosphorous and potassium values in the soil of the study area. A limited number of samples were used in the training, validation and testing phases of ANN (pattern reconstruction structures) to classify soil properties and the trained network was used for prediction. The soil analysis results of samples collected from the soil survey of block C of Sawah Sempadan, Tanjung Karang rice irrigation project at Selangor of Malaysia were used. Soil maps were produced by the Kriging method using 236 samples (or values) that were a combination of actual values (obtained from real samples) and virtual values (neural network predicted values). For each macronutrient element, three types of maps were generated with 118 actual and 118 virtual values, 59 actual and 177 virtual values, and 30 actual and 206 virtual values, respectively. To evaluate the performance of the proposed method, for each macronutrient element, a base map using 236 actual samples and test maps using 118, 59 and 30 actual samples respectively produced by the Kriging method. A set of parameters was defined to measure the similarity of the maps that were generated with the proposed method, termed the sample reduction method. The results show that the maps that were generated through the sample reduction method were more accurate than the corresponding base maps produced through a smaller number of real samples. For example, nitrogen maps that were produced from 118, 59 and 30 real samples have 78%, 62%, 41% similarity, respectively with the base map (236 samples) and the sample reduction method increased similarity to 87%, 77%, 71%, respectively. Hence, this method can reduce the number of real samples and substitute ANN predictive samples to achieve the specified level of accuracy.

Keywords: artificial neural network, kriging, macro nutrient, pattern recognition, precision farming, soil mapping

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Authors: Farshid Marbouti, Jale Ulas, Julia Thompson

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The main sources of stress among college students are: changes in sleeping and eating habits, undertaking new responsibilities, and financial difficulties as the most common sources of stress, exams, meeting new people, career decisions, fear of failure, and pressure from parents, transition to university especially if it requires leaving home, working with people that they do not know, trouble with parents, and relationship with the opposite sex. The students use a variety of stress coping strategies, including talking to family and friends, leisure activities and exercising. The Yerkes–Dodson law indicates while a moderate amount of stress may be beneficial for performance, too high stress will result in weak performance. In other words, if students are too stressed, they are likely to have low academic performance. In a preliminary study conducted in 2017 with engineering students enrolled in three high failure rate classes, the majority of the students stated that they have high levels of stress mainly for academic, financial, or family-related reasons. As the second stage of the study, the main purpose of this research is to investigate the students’ level of stress, sources of stress, their relationship with student demographic background, students’ coping strategies, and academic performance. A device is being developed to gather data from students breathing patterns and measure their stress levels. In addition, all participants are asked to fill out a survey. The survey under development has the following categories: exam stressor, study-related stressors, financial pressures, transition to university, family-related stress, student response to stress, and stress management. After the data collection, Structural Equation Modeling (SEM) analysis will be conducted in order to identify the relationship among students’ level of stress, coping strategies, and academic performance.

Keywords: college student stress, coping strategies, academic performance, measuring stress

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Authors: Nassima Noufail, Sara Bouhali

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In this work, we develop a semi-supervised solution for the purpose of action detection in videos and propose an efficient algorithm for video segmentation. The approach is divided into video segmentation, feature extraction, and classification. In the first part, a video is segmented into clips, and we used the K-means algorithm for this segmentation; our goal is to find groups based on similarity in the video. The application of k-means clustering into all the frames is time-consuming; therefore, we started by the identification of transition frames where the scene in the video changes significantly, and then we applied K-means clustering into these transition frames. We used two image filters, the gaussian filter and the Laplacian of Gaussian. Each filter extracts a set of features from the frames. The Gaussian filter blurs the image and omits the higher frequencies, and the Laplacian of gaussian detects regions of rapid intensity changes; we then used this vector of filter responses as an input to our k-means algorithm. The output is a set of cluster centers. Each video frame pixel is then mapped to the nearest cluster center and painted with a corresponding color to form a visual map. The resulting visual map had similar pixels grouped. We then computed a cluster score indicating how clusters are near each other and plotted a signal representing frame number vs. clustering score. Our hypothesis was that the evolution of the signal would not change if semantically related events were happening in the scene. We marked the breakpoints at which the root mean square level of the signal changes significantly, and each breakpoint is an indication of the beginning of a new video segment. In the second part, for each segment from part 1, we randomly selected a 16-frame clip, then we extracted spatiotemporal features using convolutional 3D network C3D for every 16 frames using a pre-trained model. The C3D final output is a 512-feature vector dimension; hence we used principal component analysis (PCA) for dimensionality reduction. The final part is the classification. The C3D feature vectors are used as input to a multi-class linear support vector machine (SVM) for the training model, and we used a multi-classifier to detect the action. We evaluated our experiment on the UCF101 dataset, which consists of 101 human action categories, and we achieved an accuracy that outperforms the state of art by 1.2%.

Keywords: video segmentation, action detection, classification, Kmeans, C3D

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Authors: Anita, Sari Septiani Tangke, Rusdina Bte Ladju, Nasrum Massi

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New diagnostic tools are urgently needed to interrupt the transmission of tuberculosis and multidrug-resistant tuberculosis. The microscopic-observation drug-susceptibility (MODS) assay is a rapid, accurate and simple liquid culture method to detect multidrug-resistant tuberculosis (MDR-TB). MODS were evaluated to determine a lower and same concentration of isoniazid and rifampin for detection of MDR-TB. Direct drug-susceptibility testing was performed with the use of the MODS assay. Drug-sensitive control strains were tested daily. The drug concentrations that used for both isoniazid and rifampin were at the same concentration: 0.16, 0.08 and 0.04μg per milliliter. We tested 56 M. tuberculosis clinical isolates and the control strains M. tuberculosis H37RV. All concentration showed same result. Of 53 M. tuberculosis clinical isolates, 14 were MDR-TB, 38 were susceptible with isoniazid and rifampin, 1 was resistant with isoniazid only. Drug-susceptibility testing was performed with the use of the proportion method using Mycobacteria Growth Indicator Tube (MGIT) system as reference. The result of MODS assay using lower concentration was significance (P<0.001) compare with the reference methods. A lower and same concentration of isoniazid and rifampin can be used to detect MDR-TB. Operational cost and application can be more efficient and easier in resource-limited environments. However, additional studies evaluating the MODS using lower and same concentration of isoniazid and rifampin must be conducted with a larger number of clinical isolates.

Keywords: isoniazid, MODS assay, MDR-TB, rifampin

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Authors: S. Mousavian, F. Mousavian, V. Nikkhah Rashidabad

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Cubic equations of state like Redlich–Kwong (RK) EOS have been proved to be very reliable tools in the prediction of phase behavior. Despite their good performance in compositional calculations, they usually suffer from weaknesses in the predictions of saturated liquid density. In this research, RK equation was modified. The result of this study shows that modified equation has good agreement with experimental data.

Keywords: equation of state, modification, ammonia, genetic algorithm

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Authors: Nonde Lushinga, Jiang Xin, Danstan Chiponde, Lawrence P. Mutale

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In this paper, falling weight deflectometer (FWD) was used to determine the bonding condition of a newly constructed semi-rigid base pavement. Using Evercal back-calculation computer programme, it was possible to quickly and accurately determine the structural condition of the pavement system of FWD test data. The bonding condition of the pavement layers was determined from calculated shear stresses and strains (relative horizontal displacements) on the interface of pavement layers from BISAR 3.0 pavement computer programmes. Thus, by using non-linear layered elastic theory, a pavement structure is analysed in the same way as other civil engineering structures. From non-destructive FWD testing, the required bonding condition of pavement layers was quantified from soundly based principles of Goodman’s constitutive models shown in equation 2, thereby producing the shear reaction modulus (Ks) which gives an indication of bonding state of pavement layers. Furthermore, a Tack coat failure Ratio (TFR) which has long being used in the USA in pavement evaluation was also used in the study in order to give validity to the study. According to research [39], the interface between two asphalt layers is determined by use of Tack Coat failure Ratio (TFR) which is the ratio of the stiffness of top layer asphalt layers over the stiffness of the second asphalt layer (E1/E2) in a slipped pavement. TFR gives an indication of the strength of the tack coat which is the main determinants of interlayer slipping. The criteria is that if the interface was in the state full bond, TFR would be greater or equals to 1 and that if the TFR was 0, meant full slip. Results of the calculations showed that TFR value was 1.81 which re-affirmed the position that the pavement under study was in the state of full bond because the value was greater than 1. It was concluded that FWD can be used to determine bonding condition of existing and newly constructed pavements.

Keywords: falling weight deflectometer (FWD), backcaluclation, semi-rigid base pavement, shear reaction modulus

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Authors: Ghada A. Gamea, Nabila A. Yaseen, Ahmed A. Othman, Ahmed S. Tawfik

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Infection with Toxoplasma gondii can cause serious complications in pregnant women, leading to abortion, stillbirth, and congenital anomalies in the fetus. Definitive diagnosis of T. gondii acute infection is therefore critical for the clinical management of a mother and her fetus. This study was conducted on 250 pregnant females in the first trimester who were inpatients or outpatients at Obstetrics and Gynaecology Department at Tanta University Hospital. Screening of the selected females was done for the detection of immunoglobulin (IgG and IgM), and all subjects were submitted to history taking through a questionnaire including personal data, risk factors for Toxoplasma, complaint and history of the present illness. Thirty-eight samples, including 18 IgM +ve and 20 IgM-ve cases were further investigated by the avidity and IgE ELISA tests. The seroprevalence of toxoplasmosis in pregnant women was (42.8%) based on the presence of IgG antibodies in their sera. Contact with cats and consumption of raw or undercooked meat are important risk factors that were associated with toxoplasmosis in pregnant women. By serology, it could be observed that in the IgM +ve group, only one case (5.6%) showed an acute pattern by using the avidity test, though 10 (55.6%) cases were found to be acute by the IgE assay. On the other hand, in the IgM –ve group, 3 (15%) showed low avidity, but none of them was positive by using the IgE assay. In conclusion, there is no single serological test that can be used to confirm whether T. gondii infection is recent or was acquired in the distant past. A panel of tests for detection of toxoplasmosis will certainly have higher discriminatory power than any test alone.

Keywords: diagnosis, serology, seroprevalence, toxoplasmosis

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Authors: Selim M. Khan, Aaron A. Goodarzi, Joshua M. Taron, Tryggve Rönnqvist

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Indoor air quality, a prime determinant of health, is strongly influenced by the presence of hazardous radon gas within the built environment. As a health issue, dangerously high indoor radon arose within the 20th century to become the 2nd leading cause of lung cancer. While the 21st century building metrics and human behaviors have captured, contained, and concentrated radon to yet higher and more hazardous levels, the issue is rapidly worsening in Canada. It is established that Canadians in the Prairies are the 2nd highest radon-exposed population in the world, with 1 in 6 residences experiencing 0.2-6.5 millisieverts (mSv) radiation per week, whereas the Canadian Nuclear Safety Commission sets maximum 5-year occupational limits for atomic workplace exposure at only 20 mSv. This situation is also deteriorating over time within newer housing stocks containing higher levels of radon. Deep machine learning (LSTM) algorithms were applied to analyze multiple quantitative and qualitative features, determine the most important contributory factors, and predicted radon levels in the known past (1990-2020) and projected future (2021-2050). The findings showed gradual downwards patterns in Sweden, whereas it would continue to go from high to higher levels in Canada over time. The contributory factors found to be the basement porosity, roof insulation depthness, R-factor, and air dynamics of the indoor environment related to human window opening behaviour. Building codes must consider including these factors to ensure adequate indoor ventilation and healthy living that can prevent lung cancer in non-smokers.

Keywords: radon, building metrics, deep learning, LSTM prediction model, lung cancer, canada, sweden

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Authors: Judy M. Obliosca, Olivia Vest, Sandra Poulos, Kelsi Smith, Tammy Ferguson, Abigail Powers Lott, Alicia K. Smith, Yang Xu, Christopher K. Tison

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Post-Traumatic Stress Disorder (PTSD) is a mental health problem that people may develop after experiencing traumatic events such as combat, natural disasters, and major emotional challenges. Tragically, the number of military personnel with PTSD correlates directly with the number of veterans who attempt suicide, with the highest rate in the Army. Research has shown epigenetic risks in those who are prone to several psychiatric dysfunctions, particularly PTSD. Once initiated in response to trauma, epigenetic alterations in particular, the DNA methylation in the form of 5-methylcytosine (5mC) alters chromatin structure and represses gene expression. Current methods to detect DNA methylation, such as bisulfite-based genomic sequencing techniques, are laborious and have massive analysis workflow while still having high error rates. A faster and simpler detection method of high sensitivity and precision would be useful in a clinical setting to confirm potential PTSD etiologies, prevent other psychiatric disorders, and improve military health. A nano-enhanced Surface Plasmon Resonance imaging (SPRi)-based assay that simultaneously detects site-specific 5mC base (termed as PTSD base) in methylated genes related to PTSD is being developed. The arrays on a sensing chip were first constructed for parallel detection of PTSD bases using synthetic and genomic DNA (gDNA) samples. For the gDNA sample extracted from the whole blood of a PTSD patient, the sample was first digested using specific restriction enzymes, and fragments were denatured to obtain single-stranded methylated target genes (ssDNA). The resulting mixture of ssDNA was then injected into the assay platform, where targets were captured by specific DNA aptamer probes previously immobilized on the surface of a sensing chip. The PTSD bases in targets were detected by anti-5-methylcytosine antibody (anti-5mC), and the resulting signals were then enhanced by the universal nanoenhancer. Preliminary results showed successful detection of a PTSD base in a gDNA sample. Brighter spot images and higher delta values (control-subtracted reflectivity signal) relative to those of the control were observed. We also implemented the in-house surface activation system for detection and developed SPRi disposable chips. Multiplexed PTSD base detection of target methylated genes in blood DNA from PTSD patients of severity conditions (asymptomatic and severe) was conducted. This diagnostic capability being developed is a platform technology, and upon successful implementation for PTSD, it could be reconfigured for the study of a wide variety of neurological disorders such as traumatic brain injury, Alzheimer’s disease, schizophrenia, and Huntington's disease and can be extended to the analyses of other sample matrices such as urine and saliva.

Keywords: epigenetic assay, DNA methylation, PTSD, whole blood, multiplexing

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Authors: Moroof, O. Oloruntola, Sunday Oladele, Daniel, O. Obasaju, Victor, O Ojekunle, Olateju, O. Bayewu, Ganiyu, O. Mosuro

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Integrated geophysical methods involving Vertical Electrical Sounding (VES) and 2D resistivity survey were deployed to gain an insight into the influence of the two varying rock types (mica-schist and granite gneiss) underlying the road alignment to the incessant highway failure along Ajaokuta-Anyigba, North-central Nigeria. The highway serves as a link-road for the single largest cement factory in Africa (Dangote Cement Factory) and two major ceramic industries to the capital (Abuja) via Lokoja. 2D Electrical Resistivity survey (Dipole-Dipole Array) and Vertical Electrical Sounding (VES) (Schlumberger array) were employed. Twenty-two (22) 2D profiles were occupied, twenty (20) conducted about 1 m away from the unstable section underlain by mica-schist with profile length each of approximately 100 m. Two (2) profiles were conducted about 1 m away from the stable section with a profile length of 100 m each due to barriers caused by the drainage system and outcropping granite gneiss at the flanks of the road. A spacing of 2 m was used for good image resolution of the near-surface. On each 2D profile, a range of 1-3 VES was conducted; thus, forty-eight (48) soundings were acquired. Partial curve matching and WinResist software were used to obtain the apparent and true resistivity values of the 1D survey, while DiprofWin software was used for processing the 2-D survey. Two exposed lithologic sections caused by abandoned river channels adjacent to two profiles as well as the knowledge of the geology of the area helped to constrain the VES and 2D processing and interpretation. Generally, the resistivity values obtained reflect the parent rock type, degree of weathering, moisture content and competency of the tested area. Resistivity values < 100; 100 – 950; 1000 – 2000 and > 2500 ohms-m were interpreted as clay, weathered layer, partly weathered layer and fresh basement respectively. The VES results and 2-D resistivity structures along the unstable segment showed similar lithologic characteristics and sequences dominated by clayey substratum for depths range of 0 – 42.2 m. The clayey substratum is a product of intensive weathering of the parent rock (mica-schist) and constitutes weak foundation soils, causing highway failure. This failure is further exacerbated by several heavy-duty trucks which ply the section round the clock due to proximity to two major ceramic industries in the state and lack of drainage system. The two profiles on the stable section show 2D structures that are remarkably different from those of the unstable section with very thin topsoils, higher resistivity weathered substratum (indicating the presence of coarse fragments from the parent rock) and shallow depth to the basement (1.0 – 7. 1 m). Also, the presence of drainage and lower volume of heavy-duty trucks are contributors to the pavement stability of this section of the highway. The resistivity surveys effectively delineated two contrasting soil profiles of the subbase/subgrade that reflect variation in the mineralogy of underlying parent rocks.

Keywords: clay, geophysical methods, pavement, resistivity

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Authors: Muhamad Aris Burhanudin, Angga Firmansyas, Bagus Jaya Santosa

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Earthquakes are natural hazard that can trigger the most dangerous hazard, tsunami. 26 December 2004, a giant earthquake occurred in north-west Andalas Island. It made giant tsunami which crushed Sumatra, Bangladesh, India, Sri Lanka, Malaysia and Singapore. More than twenty thousand people dead. The occurrence of earthquake and tsunami can not be avoided. But this hazard can be mitigated by earthquake forecasting. Early preparation is the key factor to reduce its damages and consequences. We aim to investigate quantitatively on pattern of earthquake. Then, we can know the trend. We study about earthquake which has happened in Andalas island, Indonesia one last decade. Andalas is island which has high seismicity, more than a thousand event occur in a year. It is because Andalas island is in tectonic subduction zone of Hindia sea plate and Eurasia plate. A tsunami forecasting is needed to mitigation action. Thus, a Tsunami Forecasting Method is presented in this work. Neutral Network has used widely in many research to estimate earthquake and it is convinced that by using Backpropagation Method, earthquake can be predicted. At first, ANN is trained to predict Tsunami 26 December 2004 by using earthquake data before it. Then after we get trained ANN, we apply to predict the next earthquake. Not all earthquake will trigger Tsunami, there are some characteristics of earthquake that can cause Tsunami. Wrong decision can cause other problem in the society. Then, we need a method to reduce possibility of wrong decision. Fuzzy TOPSIS is a statistical method that is widely used to be decision seconder referring to given parameters. Fuzzy TOPSIS method can make the best decision whether it cause Tsunami or not. This work combines earthquake prediction using neural network method and using Fuzzy TOPSIS to determine the decision that the earthquake triggers Tsunami wave or not. Neural Network model is capable to capture non-linear relationship and Fuzzy TOPSIS is capable to determine the best decision better than other statistical method in tsunami prediction.

Keywords: earthquake, fuzzy TOPSIS, neural network, tsunami

Procedia PDF Downloads 503

Authors: Sanela Slavkovic, Congor Nad, Spela Golubovic

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Background: The diagnosis of multiple sclerosis (MS) is a major life challenge and has repercussions on all aspects of the daily functioning of those attained by it – personal activities, social participation, and quality of life. Regular follow-up of only the neurological status is not informative enough so that it could provide data on the sort of support and rehabilitation that is required. Objective: The aim of this study was to establish the current level of functioning of persons attained by MS and the factors that influence it. Methods: The study was conducted in Serbia, on a sample of 108 persons with relapse-remitting form of MS, aged 20 to 53 (mean 39.86 years; SD 8.20 years). All participants were fully ambulatory. Methods applied in the study include Expanded Disability Status Scale-EDSS and World Health Organization Disability Assessment Schedule, WHODAS 2.0 (36-item version, self-administered). Results: Participants were found to experience the most problems in the domains of Participation, Mobility, Life activities and Cognition. The least difficulties were found in the domain of Self-care. Symptom duration was the only control variable with a significant partial contribution to the prediction of the WHODAS scale score (β=0.30, p < 0.05). The total EDSS score correlated with the total WHODAS 2.0 score (r=0.34, p=0.00). Statistically significant differences in the domain of EDSS 0-5.5 were found within categories (0-1.5; 2-3.5; 4-5.5). The more pronounced a participant’s EDSS score was, although not indicative of large changes in the neurological status, the more apparent the changes in the functional domain, i.e. in all areas covered by WHODAS 2.0. Pyramidal (β=0.34, p < 0.05) and Bowel and bladder (β=0.24, p < 0.05) functional systems were found to have a significant partial contribution to the prediction of the WHODAS score. Conclusion: Measuring functioning and disability is important in the follow-up of persons suffering from MS in order to plan rehabilitation and define areas in which additional support is needed.

Keywords: disability, functionality, multiple sclerosis, rehabilitation

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Authors: Lopita Pal, Suresh V. Madha

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Wetlands are areas of marsh, fen, peat land or water, whether natural or artificial, permanent or temporary, with water that is static or flowing, fresh, brackish or salt, including areas of marine water the depth of which at low tide does not exceed six metres. The rapidly expanding human population, large scale changes in land use/land cover, burgeoning development projects and improper use of watersheds all has caused a substantial decline of wetland resources in the world. Major degradations have been impacted from agricultural, industrial and urban developments leading to various types of pollutions and hydrological perturbations. Regular fishing activities and unsustainable grazing of animals are degrading the wetlands in a slow pace. The paper focuses on the spatio-temporal change detection of the area of the water body and the main cause of this depletion. The total area under study (22°19’87’’ N, 88°20’23’’ E) is a wetland region in West Bengal of 213 sq.km. The procedure used is the Normalized Difference Water Index (NDWI) from multi-spectral imagery and Landsat to detect the presence of surface water, and the datasets have been compared of the years 2016, 2006 and 1996. The result shows a sharp decline in the area of water body due to a rapid increase in the agricultural practices and the growing urbanization.

Keywords: spatio-temporal change, NDWI, urbanization, wetland

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Authors: Mostafa Firoozabadi, Alireza Foroughi Nematollahi

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Wet mills are one of the most important equipment in the mining industries and any defect occurrence in them can stop the production line and it can make some irrecoverable damages to the system. Electromotors are the significant parts of a mill and their monitoring is a necessary process to prevent unwanted defects. The purpose of this study is to investigate the Electromotor bearing defects, theoretically and practically, using the vibration analysis method. When a defect happens in a bearing, it can be transferred to the other parts of the equipment like inner ring, outer ring, balls, and the bearing cage. The electromotor defects source can be electrical or mechanical. Sometimes, the electrical and mechanical defect frequencies are modulated and the bearing defect detection becomes difficult. In this paper, to detect the electromotor bearing defects, the electrical and mechanical defect frequencies are extracted firstly. Then, by calculating the bearing defect frequencies, and the spectrum and time signal analysis, the bearing defects are detected. In addition, the obtained frequency determines that the bearing level in which the defect has happened and by comparing this level to the standards it determines the bearing remaining lifetime. Finally, the defect length is calculated by theoretical equations to demonstrate that there is no need to replace the bearing. The results of the proposed method, which has been implemented on the wet mills in the Golgohar mining and industrial company in Iran, show that this method is capable of detecting the electromotor bearing defects accurately and on time.

Keywords: bearing defect length, defect frequency, electromotor defects, vibration analysis

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Authors: Aniket S. Joshi, Aditya R. Mane, Arjun Tukaram

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In the 21st century, in the era of e-world, people are continuously getting updated by daily information such as weather conditions, news, stock exchange market updates, new projects, cricket updates, sports and other such applications. In the busy situation, they want this information on the little use of keyboard, time. Today in order to get such information user have to repeat same mouse and keyboard actions which includes time and inconvenience. In India due to rural background many people are not much familiar about the use of computer and internet also. Also in small clinics, small offices, and hotels and in the airport there should be a system which retrieves daily information with the minimum use of keyboard and mouse actions. We plan to design application based project that can easily retrieve information with minimum use of keyboard and mouse actions and make our task more convenient and easier. This can be possible with an image processing application which takes real time hand gestures which will get matched by system and retrieve information. Once selected the functions with hand gestures, the system will report action information to user. In this project we use real time hand gesture movements to select required option which is stored on the screen in the form of RSS Feeds. Gesture will select the required option and the information will be popped and we got the information. A real time hand gesture makes the application handier and easier to use.

Keywords: hand detection, hand tracking, hand gesture recognition, HSV color model, Blob detection

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Authors: Lily Ranjbar, Haori Yang

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Online education has been around for several decades, but the importance of online education became evident after the COVID-19 pandemic. Eventhough the online delivery approach works well for knowledge building through delivering content and oversight processes, it has limitations in developing hands-on laboratory skills, especially in the STEM field. During the pandemic, many education institutions faced numerous challenges in delivering lab-based courses, especially in the STEM field. Also, many students worldwide were unable to practice working with lab equipment due to social distancing or the significant cost of highly specialized equipment. The laboratory plays a crucial role in nuclear science and engineering education. It can engage students and improve their learning outcomes. In addition, online education and virtual labs have gained substantial popularity in engineering and science education. Therefore, developing virtual labs is vital for institutions to deliver high-class education to their students, including their online students. The School of Nuclear Science and Engineering (NSE) at Oregon State University, in partnership with SpectralLabs company, has developed an Advanced Virtual Radiation Detection and Measurement Lab (AVR-DML) to offer a fully online Master of Health Physics program. It was essential for us to use a system that could simulate nuclear modules that accurately replicate the underlying physics, the nature of radiation and radiation transport, and the mechanics of the instrumentations used in the real radiation detection lab. It was all accomplished using a Realistic, Adaptive, Interactive Learning System (RAILS). RAILS is a comprehensive software simulation-based learning system for use in training. It is comprised of a web-based learning management system that is located on a central server, as well as a 3D-simulation package that is downloaded locally to user machines. Users will find that the graphics, animations, and sounds in RAILS create a realistic, immersive environment to practice detecting different radiation sources. These features allow students to coexist, interact and engage with a real STEM lab in all its dimensions. It enables them to feel like they are in a real lab environment and to see the same system they would in a lab. Unique interactive interfaces were designed and developed by integrating all the tools and equipment needed to run each lab. These interfaces provide students full functionality for data collection, changing the experimental setup, and live data collection with real-time updates for each experiment. Students can manually do all experimental setups and parameter changes in this lab. Experimental results can then be tracked and analyzed in an oscilloscope, a multi-channel analyzer, or a single-channel analyzer (SCA). The advanced virtual radiation detection and measurement laboratory developed in this study enabled the NSE school to offer a fully online MHP program. This flexibility of course modality helped us to attract more non-traditional students, including international students. It is a valuable educational tool as students can walk around the virtual lab, make mistakes, and learn from them. They have an unlimited amount of time to repeat and engage in experiments. This lab will also help us speed up training in nuclear science and engineering.

Keywords: advanced radiation detection and measurement, virtual laboratory, realistic adaptive interactive learning system (rails), online education in stem fields, student engagement, stem online education, stem laboratory, online engineering education

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Authors: John E. Foley, Martin Miele, Raul Fonda, Jon Jacobson

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This paper presents development and implementation of new and innovative data collection and analysis methodologies based on deployment of total field magnetometer arrays. Our research has focused on the development of a vertically-integrated suite of platforms all utilizing common data acquisition, data processing and analysis tools. These survey platforms include low-altitude helicopters and ground-based vehicles, including robots, for terrestrial mapping applications. For marine settings the sensor arrays are deployed from either a hydrodynamic bottom-following wing towed from a surface vessel or from a towed floating platform for shallow-water settings. Additionally, sensor arrays are deployed from tethered remotely operated vehicles (ROVs) for underwater settings where high maneuverability is required. While the primary application of these systems is the detection and mapping of unexploded ordnance (UXO), these system are also used for various infrastructure mapping and geologic investigations. For each application, success is driven by the integration of magnetometer arrays, accurate geo-positioning, system noise mitigation, and stable deployment of the system in appropriate proximity of expected targets or features. Each of the systems collects geo-registered data compatible with a web-enabled data management system providing immediate access of data and meta-data for remote processing, analysis and delivery of results. This approach allows highly sophisticated magnetic processing methods, including classification based on dipole modeling and remanent magnetization, to be efficiently applied to many projects. This paper also briefly describes the initial development of magnetometer-based detection systems deployed from low-altitude helicopter platforms and the subsequent successful transition of this technology to the marine environment. Additionally, we present examples from a range of terrestrial and marine settings as well as ongoing research efforts related to sensor miniaturization for unmanned aerial vehicle (UAV) magnetic field mapping applications.

Keywords: dipole modeling, magnetometer mapping systems, sub-surface infrastructure mapping, unexploded ordnance detection

Procedia PDF Downloads 468

Authors: Sebastian Töpfer, Jorge Fuenzalida, Marta Gilaberte Basset, Juan P. Torres, Markus Gräfe

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This work presents an experimental and theoretical study about the noise resilience of quantum holography with undetected photons. Quantum imaging has become an important research topic in the recent years after its first publication in 2014. Following this research, advances towards different spectral ranges in detection and different optical geometries have been made. Especially an interest in the field of near infrared to mid infrared measurements has developed, because of the unique characteristic, that allows to sample a probe with photons in a different wavelength than the photons arriving at the detector. This promising effect can be used for medical applications, to measure in the so-called molecule fingerprint region, while using broadly available detectors for the visible spectral range. Further advance the development of quantum imaging methods have been made by new measurement and detection schemes. One of which is quantum holography with undetected light. It combines digital phase shifting holography with quantum imaging to extent the obtainable sample information, by measuring not only the object transmission, but also its influence on the phase shift experienced by the transmitted light. This work will present extended research for the quantum holography with undetected light scheme regarding the influence of external noise. It is shown experimentally and theoretically that the samples information can still be at noise levels of 250 times higher than the signal level, because of its information being transmitted by the interferometric pattern. A detailed theoretic explanation is also provided.

Keywords: distillation, quantum holography, quantum imaging, quantum metrology

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Authors: Lakhoua Najeh

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Aims of the work: The aim of this paper is to improve the reliability and the availability of a Packer production line of cigarettes based on two methods: The SADT method (Structured Analysis Design Technique) and the FMECA approach (Failure Mode Effects and Critically Analysis). The first method enables us to describe the functionality of the Packer production line of cigarettes and the second method enables us to establish an FMECA analysis. Methods: The methodology adopted in order to contribute to the improvement of the reliability and the availability of a Packer production line of cigarettes has been proposed in this paper, and it is based on the use of Structured Analysis Design Technique (SADT) and Failure mode, effects, and criticality analysis (FMECA) methods. This methodology consists of using a diagnosis of the existing of all of the equipment of a production line of a factory in order to determine the most critical machine. In fact, we use, on the one hand, a functional analysis based on the SADT method of the production line and on the other hand, a diagnosis and classification of mechanical and electrical failures of the line production by their criticality analysis based on the FMECA approach. Results: Based on the methodology adopted in this paper, the results are the creation and the launch of a preventive maintenance plan. They contain the different elements of a Packer production line of cigarettes; the list of the intervention preventive activities and their period of realization. Conclusion: The diagnosis of the existing state helped us to found that the machine of cigarettes used in the Packer production line of cigarettes is the most critical machine in the factory. Then this enables us in the one hand, to describe the functionality of the production line of cigarettes by SADT method and on the other hand, to study the FMECA machine in order to improve the availability and the performance of this machine.

Keywords: production system, diagnosis, SADT method, FMECA method

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Authors: Abdelmessih Malak Sadek Labib

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The Stability in harsh environments thanks to excellent electrical, mechanical and thermal properties is what ceramics are all about selected materials for many applications despite advent of new materials such as plastics and composites. However, ceramic materials have disadvantages, including brittleness. Fragility is often attributed to pottery strong covalent and ionic bonds in the ceramic body. There is still much to learn about brittle cracks in a attention to detail, hence the fragility of the ceramic and its catastrophic failure of a frequently studied topic, particularly in charging applications. One of the most commonly used ceramics for load-bearing applications such as veneers is porcelain. Porcelain is a type of traditional pottery. Traditional pottery consists mainly of three basic ingredients: clay, which gives plasticity; silica which maintains the shape and stability of the ceramic body over temperature high temperature; and feldspar affecting glazing. In traditional pottery, the inversion of quartz during cooling the process can create microcracks that act as a stress concentration centers. Consequently, subcritical crack growth is caused due to quartz inversion origins unpredictable catastrophic failure of the work of ceramic bodies when reloading. In the case of porcelain, however, this is what the mullite hypothesis says the strength of porcelain can be significantly increased with felt Interlocking of mullite needles in the ceramic body.in this way realistic assessment of the role of quartz and mullite Porcelain with a strength of is needed to grow stronger and smaller fragile porcelain. Currently,the lack of reports on Young's moduli in the literature leads to erroneous conclusions in this regard mechanical behavior of porcelain. Therefore, the current project uses the Young's modulus approach for the investigation the role of quartz and mullite on the mechanical strength of various porcelains, in addition to reducing particle size, flexural strength fractographic forces and techniques.

Keywords: materials, technical, ceramics, properties, thermal, stability, advantages

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Authors: Rudzani Manafe, Ezekiel Green

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Brucella, has many different virulence factors that act as a causative agent of brucellosis, depending on the environment and other factors, some factors may play a role more than others during infection and as a result, play a role in becoming a causative agent for pathogenesis. Brucella melitensis and Brucella abortus are considered to be pathogenic to humans. The genetic regularity of nine potential causes of virulence of two Brucella species in Eastern Cape livestock have been examined. A hundred and twenty isolates obtained from Molecular Pathogenesis and Molecular Epidemiology Research Group (MPMERG) were used for this study. All isolates were grown on Brucella agar medium. Nine primer pairs were used for the detection of virB2, virB5, vceC, btpA, btpB, prpA, betB, bpe275, and bspB virulence factors using Polymerase chain reaction (PCR). Approximately 100% was observed for genes BecC and BetB from B. arbotus. While the lowest gene observed was PrpA at 4.6% from B. arbotus. BetB was detected in 34.7%, while virB2 and prpA (0%) were not detected in B. melitensis. The results from this research suggest that most isolates of Brucella have virulence-related genes associated with disease pathogenesis. Finally, our findings showed that Brucella strains in the Eastern Cape Province are extremely virulent as virulence characteristics exist in most strains investigated.

Keywords: putative virulence genes, brucella, polymerase chain reaction, milk

Procedia PDF Downloads 146

Authors: Wei Zhao, Yuxuan Yao, Hao Chen

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In order to find out the mechanical properties and failure behavior of lithium-ion batteries, drop hammer impact experiments and finite element simulations are carried out on batteries with different packed angles. Firstly, a drop hammer impact experiment system, which is based on the DHR-1808 drop hammer and oscilloscope, is established, and then a drop test of individual batteries and packed angles of 180 ° and 120 ° are carried out. The image of battery deformation, force-time curve and voltage-time curve are recorded. Secondly, finite element models of individual batteries and two packed angles are established, and the results of the test and simulation are compared. Finally, the mechanical characteristics and failure behavior of lithium-ion battery modules with the packed arrangement of 6 * 6 and packing angles of 180 °, 120 °, 90 ° and 60 ° are analyzed under the same velocity with different battery packing angles, and the same impact energy with different impact velocity and different packing angles. The result shows that the individual battery is destroyed completely in the drop hammer impact test with an initial impact velocity of 3m/s and drop height of 459mm, and the voltage drops to close to 0V when the test ends. The voltage drops to 12V when packed angle of 180°, and 3.6V when packed angle of 120°. It is found that the trend of the force-time curve between simulation and experiment is generally consistent. The difference in maximum peak value is 3.9kN for a packing angle of 180° and 1.3kN for a packing angle of 120°. Under the same impact velocity and impact energy, the strain rate of the battery module with a packing angle of 180° is the lowest, and the maximum stress can reach 26.7MPa with no battery short-circuited. The research under our experiment and simulation shows that the lithium-ion battery module with a packing angle of 180 ° is the least likely to be damaged, which can sustain the maximum stress under the same impact load.

Keywords: battery module, finite element simulation, power battery, packing angle

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Authors: Etienne Gaborit, Dorothy Durnford, Daniel Deacu, Marco Carrera, Nathalie Gauthier, Camille Garnaud, Vincent Fortin

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A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model.

Keywords: assimilation system, distributed physical model, offline hydro-meteorological chain, short-term streamflow forecasts

Procedia PDF Downloads 135