Search results for: lunar surface/subsurface detection
8039 Using T-Splines to Model Point Clouds from Terrestrial Laser Scanner
Authors: G. Kermarrec, J. Hartmann
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Spline surfaces are a major representation of freeform surfaces in the computer-aided graphic industry and were recently introduced in the field of geodesy for processing point clouds from terrestrial laser scanner (TLS). The surface fitting consists of approximating a trustworthy mathematical surface to a large numbered 3D point cloud. The standard B-spline surfaces lack of local refinement due to the tensor-product construction. The consequences are oscillating geometry, particularly in the transition from low-to-high curvature parts for scattered point clouds with missing data. More economic alternatives in terms of parameters on how to handle point clouds with a huge amount of observations are the recently introduced T-splines. As long as the partition of unity is guaranteed, their computational complexity is low, and they are flexible. T-splines are implemented in a commercial package called Rhino, a 3D modeler which is widely used in computer aided design to create and animate NURBS objects. We have applied T-splines surface fitting to terrestrial laser scanner point clouds from a bridge under load and a sheet pile wall with noisy observations. We will highlight their potential for modelling details with high trustworthiness, paving the way for further applications in terms of deformation analysis.Keywords: deformation analysis, surface modelling, terrestrial laser scanner, T-splines
Procedia PDF Downloads 1368038 Phytoplankton Community Structure in the Moroccan Coast of the Mediterranean Sea: Case Study of Saiidia, Three Forks Cape
Authors: H. Idmoussi, L. Somoue, O. Ettahiri, A. Makaoui, S. Charib, A. Agouzouk, A. Ben Mhamed, K. Hilmi, A. Errhif
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The study on the composition, abundance, and distribution of phytoplankton was conducted along the Moroccan coast of the Mediterranean Sea (Saiidia - Three Forks Cape) in April 2018. Samples were collected at thirteen stations using Niskin bottles within two layers (surface and deep layers). The identification and enumeration of phytoplankton were carried out according to the Utermöhl method (1958). A total number of 54 phytoplankton species were identified over the entire survey area. Thirty-six species could be found both in the surface and the deep layers while eleven species were observed only in the surface layer and seven in the deep layer. The phytoplankton throughout the study area was dominated by diatoms represented mainly by Nitzschia sp., Pseudonitzschia sp., Chaetoceros sp., Cylindrotheca closterium, Leptocylindrus minimus, Leptocylindrus danicus, Dactyliosolen fragilissimus. Dinoflagellates were dominated by Gymnodinium sp., Scrippsiella sp., Gyrodinium spirale, Noctulica sp, Prorocentrum micans. Euglenophyceae, Silicoflagellates and Raphidophyceae were present in low numbers. Most of the phytoplankton were concentrated in the surface layer, particularly towards the Three Forks Cape (25200 cells·l⁻¹). Shannon species diversity (ranging from 2 and 4 Bits) and evenness index (broadly > 0.7) suggested that phytoplankton community is generally diversified and structured in the studied area.Keywords: abundance, diversity, Mediterranean Sea, phytoplankton
Procedia PDF Downloads 1508037 Metal-Oxide-Semiconductor-Only Process Corner Monitoring Circuit
Authors: Davit Mirzoyan, Ararat Khachatryan
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A process corner monitoring circuit (PCMC) is presented in this work. The circuit generates a signal, the logical value of which depends on the process corner only. The signal can be used in both digital and analog circuits for testing and compensation of process variations (PV). The presented circuit uses only metal-oxide-semiconductor (MOS) transistors, which allow increasing its detection accuracy, decrease power consumption and area. Due to its simplicity the presented circuit can be easily modified to monitor parametrical variations of only n-type and p-type MOS (NMOS and PMOS, respectively) transistors, resistors, as well as their combinations. Post-layout simulation results prove correct functionality of the proposed circuit, i.e. ability to monitor the process corner (equivalently die-to-die variations) even in the presence of within-die variations.Keywords: detection, monitoring, process corner, process variation
Procedia PDF Downloads 5148036 Fault Diagnosis in Induction Motor
Authors: Kirti Gosavi, Anita Bhole
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The paper demonstrates simulation and steady-state performance of three phase squirrel cage induction motor and detection of rotor broken bar fault using MATLAB. This simulation model is successfully used in the fault detection of rotor broken bar for the induction machines. A dynamic model using PWM inverter and mathematical modelling of the motor is developed. The dynamic simulation of the small power induction motor is one of the key steps in the validation of the design process of the motor drive system and it is needed for eliminating advertent design errors and the resulting error in the prototype construction and testing. The simulation model will be helpful in detecting the faults in three phase induction motor using Motor current signature analysis.Keywords: squirrel cage induction motor, pulse width modulation (PWM), fault diagnosis, induction motor
Procedia PDF Downloads 6248035 Two-Dimensional Seismic Response of Concrete Gravity Dams Including Base Sliding
Authors: Djamel Ouzandja, Boualem Tiliouine
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The safety evaluation of the concrete gravity dams subjected to seismic excitations is really very complex as the earthquake response of the concrete gravity dam depends upon its contraction joints with foundation soil. This paper presents the seismic response of concrete gravity dams considering friction contact and welded contact. Friction contact is provided using contact elements. Two-dimensional (2D) finite element model of Oued Fodda concrete gravity dam, located in Chlef at the west of Algeria, is used for this purpose. Linear and nonlinear analyses considering dam-foundation soil interaction are performed using ANSYS software. The reservoir water is modeled as added mass using the Westergaard approach. The Drucker-Prager model is preferred for dam and foundation rock in nonlinear analyses. The surface-to-surface contact elements based on the Coulomb's friction law are used to describe the friction. These contact elements use a target surface and a contact surface to form a contact pair. According to this study, the seismic analysis of concrete gravity dams including base sliding. When the friction contact is considered in joints, the base sliding displacement occurs along the dam-foundation soil contact interface. Besides, the base sliding may generally decrease the principal stresses in the dam.Keywords: concrete gravity dam, dynamic soil-structure interaction, friction contact, sliding
Procedia PDF Downloads 4018034 Abnormality Detection of Persons Living Alone Using Daily Life Patterns Obtained from Sensors
Authors: Ippei Kamihira, Takashi Nakajima, Taiyo Matsumura, Hikaru Miura, Takashi Ono
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In this research, the goal was construction of a system by which multiple sensors were used to observe the daily life behavior of persons living alone (while respecting their privacy). Using this information to judge such conditions as a bad physical condition or falling in the home, etc., so that these abnormal conditions can be made known to relatives and third parties. The daily life patterns of persons living alone are expressed by the number of responses of sensors each time that a set time period has elapsed. By comparing data for the prior two weeks, it was possible to judge a situation as 'normal' when the person was in a good physical condition or as 'abnormal' when the person was in a bad physical condition.Keywords: sensors, elderly living alone, abnormality detection, iifestyle habit
Procedia PDF Downloads 2458033 Recommendations Using Online Water Quality Sensors for Chlorinated Drinking Water Monitoring at Drinking Water Distribution Systems Exposed to Glyphosate
Authors: Angela Maria Fasnacht
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Detection of anomalies due to contaminants’ presence, also known as early detection systems in water treatment plants, has become a critical point that deserves an in-depth study for their improvement and adaptation to current requirements. The design of these systems requires a detailed analysis and processing of the data in real-time, so it is necessary to apply various statistical methods appropriate to the data generated, such as Spearman’s Correlation, Factor Analysis, Cross-Correlation, and k-fold Cross-validation. Statistical analysis and methods allow the evaluation of large data sets to model the behavior of variables; in this sense, statistical treatment or analysis could be considered a vital step to be able to develop advanced models focused on machine learning that allows optimized data management in real-time, applied to early detection systems in water treatment processes. These techniques facilitate the development of new technologies used in advanced sensors. In this work, these methods were applied to identify the possible correlations between the measured parameters and the presence of the glyphosate contaminant in the single-pass system. The interaction between the initial concentration of glyphosate and the location of the sensors on the reading of the reported parameters was studied.Keywords: glyphosate, emergent contaminants, machine learning, probes, sensors, predictive
Procedia PDF Downloads 1108032 Real-Time Quantitative Polymerase Chain Reaction Assay for the Detection of microRNAs Using Bi-Directional Extension Sequences
Authors: Kyung Jin Kim, Jiwon Kwak, Jae-Hoon Lee, Soo Suk Lee
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MicroRNAs (miRNA) are a class of endogenous, single-stranded, small, and non-protein coding RNA molecules typically 20-25 nucleotides long. They are thought to regulate the expression of other genes in a broad range by binding to 3’- untranslated regions (3’-UTRs) of specific mRNAs. The detection of miRNAs is very important for understanding of the function of these molecules and in the diagnosis of variety of human diseases. However, detection of miRNAs is very challenging because of their short length and high sequence similarities within miRNA families. So, a simple-to-use, low-cost, and highly sensitive method for the detection of miRNAs is desirable. In this study, we demonstrate a novel bi-directional extension (BDE) assay. In the first step, a specific linear RT primer is hybridized to 6-10 base pairs from the 3’-end of a target miRNA molecule and then reverse transcribed to generate a cDNA strand. After reverse transcription, the cDNA was hybridized to the 3’-end which is BDE sequence; it played role as the PCR template. The PCR template was amplified in an SYBR green-based quantitative real-time PCR. To prove the concept, we used human brain total RNA. It could be detected quantitatively in the range of seven orders of magnitude with excellent linearity and reproducibility. To evaluate the performance of BDE assay, we contrasted sensitivity and specificity of the BDE assay against a commercially available poly (A) tailing method using miRNAs for let-7e extracted from A549 human epithelial lung cancer cells. The BDE assay displayed good performance compared with a poly (A) tailing method in terms of specificity and sensitivity; the CT values differed by 2.5 and the melting curve showed a sharper than poly (A) tailing methods. We have demonstrated an innovative, cost-effective BDE assay that allows improved sensitivity and specificity in detection of miRNAs. Dynamic range of the SYBR green-based RT-qPCR for miR-145 could be represented quantitatively over a range of 7 orders of magnitude from 0.1 pg to 1.0 μg of human brain total RNA. Finally, the BDE assay for detection of miRNA species such as let-7e shows good performance compared with a poly (A) tailing method in terms of specificity and sensitivity. Thus BDE proves a simple, low cost, and highly sensitive assay for various miRNAs and should provide significant contributions in research on miRNA biology and application of disease diagnostics with miRNAs as targets.Keywords: bi-directional extension (BDE), microRNA (miRNA), poly (A) tailing assay, reverse transcription, RT-qPCR
Procedia PDF Downloads 1598031 High Friction Surface Treatment Highway Safety Improvement Program Funded Pilot Project Maricopa County D. O. T.
Authors: Maz Muradvich
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The Federal Highway Administration's Everyday Counts (EDC) initiative is designed to identify and deploy innovations, enhancing the safety of our roadways. According to and as referenced in FHWA everyday counts (2) website, High friction surface treatment (HFST) is an emerging surface application that has been proven to reduce crashes. High Friction Surface Treatment involves the application of Calcined Bauxite, very high-quality aggregate to the pavement using a polymer binder to restore and maintain pavement friction at existing or potentially high crash areas. Bauxite is a byproduct of manufacturing aluminum resulting in very hard aggregate and is abrasion and polish resistant. HFST is an approach that has been recognized nationally and internationally and has provided considerable increases in friction for curves and intersections spot applications. Maricopa County qualified and received HSIP (Highway Safety Improvement Program) funding that was applied towards HFST application on 2 locations in Maricopa County. The project was successfully completed in December 2019. Four years later MCDOT continues to conduct wet and dry ABS and Non-ABS friction coefficient testing in pursuit of after studies evaluation of HFST application.Keywords: roadway departure, sever crashes, coefficient of friction, break meter technology
Procedia PDF Downloads 368030 Video Heart Rate Measurement for the Detection of Trauma-Related Stress States
Authors: Jarek Krajewski, David Daxberger, Luzi Beyer
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Finding objective and non-intrusive measurements of emotional and psychopathological states (e.g., post-traumatic stress disorder, PTSD) is an important challenge. Thus, the proposed approach here uses Photoplethysmographic imaging (PPGI) applying facial RGB Cam videos to estimate heart rate levels. A pipeline for the signal processing of the raw image has been proposed containing different preprocessing approaches, e.g., Independent Component Analysis, Non-negative Matrix factorization, and various other artefact correction approaches. Under resting and constant light conditions, we reached a sensitivity of 84% for pulse peak detection. The results indicate that PPGI can be a suitable solution for providing heart rate data derived from these indirectly post-traumatic stress states.Keywords: heart rate, PTSD, PPGI, stress, preprocessing
Procedia PDF Downloads 1218029 Mike Hat: Coloured-Tape-in-Hat as a Head Circumference Measuring Instrument for Early Detection of Hydrocephalus in an Infant
Authors: Nyimas Annissa Mutiara Andini
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Every year, children develop hydrocephalus during the first year of life. If it is not treated, hydrocephalus can lead to brain damage, a loss in mental and physical abilities, and even death. To be treated, first, we have to do a proper diagnosis using some examinations especially to detect hydrocephalus earlier. One of the examination that could be done is using a head circumference measurement. Increased head circumference is a first and main sign of hydrocephalus, especially in infant (0-1 year age). Head circumference is a measurement of a child's head largest area. In this measurement, we want to get the distance from above the eyebrows and ears and around the back of the head using a measurement tape. If the head circumference of an infant is larger than normal, this infant might potentially suffer hydrocephalus. If early diagnosis and timely treatment of hydrocephalus could be done most children can recover successfully. There are some problems with early detection of hydrocephalus using regular tape for head circumference measurement. One of the problem is the infant’s comfort. We need to make the infant feel comfort along the head circumference measurement to get a proper result of the examination. For that, we can use a helpful stuff, like a hat. This paper is aimed to describe the possibility of using a head circumference measuring instrument for early detection of hydrocephalus in an infant with a mike hat, coloured-tape-in-hat. In the first life, infants’ head size is about 35 centimeters. First three months after that infants will gain 2 centimeters each month. The second three months, infant’s head circumference will increase 1 cm each month. And for the six months later, the rate is 0.5 cm per month, and end up with an average of 47 centimeters. This formula is compared to the WHO’s head circumference growth chart. The shape of this tape-in-hat is alike an upper arm measurement. This tape-in-hat diameter is about 47 centimeters. It contains twelve different colours range by age. If it is out of the normal colour, the infant potentially suffers hydrocephalus. This examination should be done monthly. If in two times of measurement there still in the same range abnormal of head circumference, or a rapid growth of the head circumference size, the infant should be referred to a pediatrician. There are the pink hat for girls and blue hat for boys. Based on this paper, we know that this measurement can be used to help early detection of hydrocephalus in an infant.Keywords: head circumference, hydrocephalus, infant, mike hat
Procedia PDF Downloads 2628028 Performance Assessment of Carbon Nano Tube Based Cutting Fluid in Machining Process
Authors: Alluru Gopala Krishna, Thella Babu Rao
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In machining, there is always a problem with heat generation and friction produced during the process as they consequently affect tool wear and surface finish. An instant heat transfer mechanism could protect the cutting tool edge and enhance the tool life by cooling the cutting edge of the tool. In the present work, carbon nanotube (CNT) based nano-cutting fluid is proposed for machining a hard-to-cut material. Tool wear and surface roughness are considered for the evaluation of the nano-cutting fluid in turning process. The performance of nanocoolant is assessed against the conventional coolant and dry machining conditions and it is observed that the proposed nanocoolant has produced better performance than the conventional coolant.Keywords: CNT based nano cutting fluid, tool wear, turning, surface roughness
Procedia PDF Downloads 2588027 Electrical Decomposition of Time Series of Power Consumption
Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats
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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).Keywords: electrical disaggregation, DTW, general appliance modeling, event detection
Procedia PDF Downloads 688026 Synergistic Studies of Multi-Flame Retarders Using Silica Nanoparticles, and Nitrogen and Phosphorus-Based Compounds for Polystyrene Using Response Surface Methodology
Authors: Florencio D. De Los Reyes, Magdaleno R. Vasquez Jr., Mark Daniel G. De Luna, Peerasak Paoprasert
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The effect of adding silica nanoparticles (SiNPs) obtained from rice husk, and phosphorus and nitrogen based compounds namely 9,10-dihydro-9-oxa-10-phosphaphenantrene-10-oxide (DOPO) and melamine, respectively, on the flammability of polystyrene (PS) was studied using response surface methodology (RSM). The flammability of PS was reduced as the limiting oxygen index (LOI) values increased when the flame retardant additives were added. DOPO exhibited the best retarding property increasing the LOI value of PS by 42.4%. A quadratic model for LOI was obtained from the RSM results, with percent loading of SiNPs, DOPO, and melamine, as independent variables. The observed increase in the LOI value as the percent loading of the flame retardant additives is increased, was attributed both to the main effects and synergistic effects of the parameters, as the LOI response of SiNPs is greatly enhanced by the addition of DOPO and melamine, as shown by the response surface plots. This indicates the potential of producing a cheaper, effective, and non-toxic multi-flame retardant system for the polymeric system via different flame retarding mechanisms.Keywords: flame retardancy, polystyrene, response surface methodology, rice husk, silica nanoparticle
Procedia PDF Downloads 2808025 Double Functionalization of Magnetic Colloids with Electroactive Molecules and Antibody for Platelet Detection and Separation
Authors: Feixiong Chen, Naoufel Haddour, Marie Frenea-Robin, Yves MéRieux, Yann Chevolot, Virginie Monnier
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Neonatal thrombopenia occurs when the mother generates antibodies against her baby’s platelet antigens. It is particularly critical for newborns because it can cause coagulation troubles leading to intracranial hemorrhage. In this case, diagnosis must be done quickly to make platelets transfusion immediately after birth. Before transfusion, platelet antigens must be tested carefully to avoid rejection. The majority of thrombopenia (95 %) are caused by antibodies directed against Human Platelet Antigen 1a (HPA-1a) or 5b (HPA-5b). The common method for antigen platelets detection is polymerase chain reaction allowing for identification of gene sequence. However, it is expensive, time-consuming and requires significant blood volume which is not suitable for newborns. We propose to develop a point-of-care device based on double functionalized magnetic colloids with 1) antibodies specific to antigen platelets and 2) highly sensitive electroactive molecules in order to be detected by an electrochemical microsensor. These magnetic colloids will be used first to isolate platelets from other blood components, then to capture specifically platelets bearing HPA-1a and HPA-5b antigens and finally to attract them close to sensor working electrode for improved electrochemical signal. The expected advantages are an assay time lower than 20 min starting from blood volume smaller than 100 µL. Our functionalization procedure based on amine dendrimers and NHS-ester modification of initial carboxyl colloids will be presented. Functionalization efficiency was evaluated by colorimetric titration of surface chemical groups, zeta potential measurements, infrared spectroscopy, fluorescence scanning and cyclic voltammetry. Our results showed that electroactive molecules and antibodies can be immobilized successfully onto magnetic colloids. Application of a magnetic field onto working electrode increased the detected electrochemical signal. Magnetic colloids were able to capture specific purified antigens extracted from platelets.Keywords: Magnetic Nanoparticles , Electroactive Molecules, Antibody, Platelet
Procedia PDF Downloads 2628024 Automatic Motion Trajectory Analysis for Dual Human Interaction Using Video Sequences
Authors: Yuan-Hsiang Chang, Pin-Chi Lin, Li-Der Jeng
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Advance in techniques of image and video processing has enabled the development of intelligent video surveillance systems. This study was aimed to automatically detect moving human objects and to analyze events of dual human interaction in a surveillance scene. Our system was developed in four major steps: image preprocessing, human object detection, human object tracking, and motion trajectory analysis. The adaptive background subtraction and image processing techniques were used to detect and track moving human objects. To solve the occlusion problem during the interaction, the Kalman filter was used to retain a complete trajectory for each human object. Finally, the motion trajectory analysis was developed to distinguish between the interaction and non-interaction events based on derivatives of trajectories related to the speed of the moving objects. Using a database of 60 video sequences, our system could achieve the classification accuracy of 80% in interaction events and 95% in non-interaction events, respectively. In summary, we have explored the idea to investigate a system for the automatic classification of events for interaction and non-interaction events using surveillance cameras. Ultimately, this system could be incorporated in an intelligent surveillance system for the detection and/or classification of abnormal or criminal events (e.g., theft, snatch, fighting, etc.).Keywords: motion detection, motion tracking, trajectory analysis, video surveillance
Procedia PDF Downloads 5418023 Subpixel Corner Detection for Monocular Camera Linear Model Research
Authors: Guorong Sui, Xingwei Jia, Fei Tong, Xiumin Gao
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Camera calibration is a fundamental issue of high precision noncontact measurement. And it is necessary to analyze and study the reliability and application range of its linear model which is often used in the camera calibration. According to the imaging features of monocular cameras, a camera model which is based on the image pixel coordinates and three dimensional space coordinates is built. Using our own customized template, the image pixel coordinate is obtained by the subpixel corner detection method. Without considering the aberration of the optical system, the feature extraction and linearity analysis of the line segment in the template are performed. Moreover, the experiment is repeated 11 times by constantly varying the measuring distance. At last, the linearity of the camera is achieved by fitting 11 groups of data. The camera model measurement results show that the relative error does not exceed 1%, and the repeated measurement error is not more than 0.1 mm magnitude. Meanwhile, it is found that the model has some measurement differences in the different region and object distance. The experiment results show this linear model is simple and practical, and have good linearity within a certain object distance. These experiment results provide a powerful basis for establishment of the linear model of camera. These works will have potential value to the actual engineering measurement.Keywords: camera linear model, geometric imaging relationship, image pixel coordinates, three dimensional space coordinates, sub-pixel corner detection
Procedia PDF Downloads 2718022 Assay for SARS-Cov-2 on Chicken Meat
Authors: R. Mehta, M. Ghogomu, B. Schoel
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Reports appeared in 2020 about China detecting SARS-Cov-2 (Covid-19) on frozen meat, shrimp, and food packaging material. In this study, we examined the use of swabs for the detection of Covid-19 on meat samples, and chicken breast (CB) was used as a model. Methods: Heat inactivated SARS-Cov-2 virus (IV) from Microbiologics was loaded onto the CB, swabbing was done, and the recovered inactivated virus was subjected to the Machery & Nagel NucleoSpin RNAVirus kit for RNA isolation according to manufacturer's instructions. For RT-PCR, the IDT 2019-nCoV RUO Covid-19 test kit was used with the Taqman Fast Virus 1-step master mix. The limit of detection (LOD) of viral load recovered from the CB was determined under various conditions: first on frozen CB where the IV was introduced on a defined area, then on frozen CB, with IV spread-out, and finally, on thawed CB. Results: The lowest amount of IV which can be reliably detected on frozen CB was a load of 1,000 - 2,000 IV copies where the IV was loaded on one spot of about 1 square inch. Next, the IV was spread out over a whole frozen CB about 16 square inches. The IV could be recovered at a lowest load of 4,000 to 8,000 copies. Furthermore, the effects of temperature change on viral load recovery was investigated i.e., if raw unfrozen meat became contaminated and remains for 1 hour at 4°C or gets refrozen. The amount of IV recovered successfully from CB kept at 4°C and the refrozen CB was similar to the recovery gotten from loading the IV directly on the frozen CB. In conclusion, an assay using swabs was successfully established for the detection of SARS-Cov-2 on frozen or raw (unfrozen) CB with a minimal load of up to 8,000 copies spread over 16 square inches.Keywords: assay, COVID-19, meat, SARS-Cov-2
Procedia PDF Downloads 1988021 Clinical Efficacy of Indigenous Software for Automatic Detection of Stages of Retinopathy of Prematurity (ROP)
Authors: Joshi Manisha, Shivaram, Anand Vinekar, Tanya Susan Mathews, Yeshaswini Nagaraj
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Retinopathy of prematurity (ROP) is abnormal blood vessel development in the retina of the eye in a premature infant. The principal object of the invention is to provide a technique for detecting demarcation line and ridge detection for a given ROP image that facilitates early detection of ROP in stage 1 and stage 2. The demarcation line is an indicator of Stage 1 of the ROP and the ridge is the hallmark of typically Stage 2 ROP. Thirty Retcam images of Asian Indian infants obtained during routine ROP screening have been used for the analysis. A graphical user interface has been developed to detect demarcation line/ridge and to extract ground truth. This novel algorithm uses multilevel vessel enhancement to enhance tubular structures in the digital ROP images. It has been observed that the orientation of the demarcation line/ridge is normal to the direction of the blood vessels, which is used for the identification of the ridge/ demarcation line. Quantitative analysis has been presented based on gold standard images marked by expert ophthalmologist. Image based analysis has been based on the length and the position of the detected ridge. In image based evaluation, average sensitivity and positive predictive value was found to be 92.30% and 85.71% respectively. In pixel based evaluation, average sensitivity, specificity, positive predictive value and negative predictive value achieved were 60.38%, 99.66%, 52.77% and 99.75% respectively.Keywords: ROP, ridge, multilevel vessel enhancement, biomedical
Procedia PDF Downloads 3958020 Impact of Landuse Change on Surface Temperature in Ibadan, Nigeria
Authors: Abegunde Linda, Adedeji Oluwatola
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It has become increasingly evident that large developments influence the climate within the immediate region and there are concerns that rising temperatures over developed areas could have negative impact and increase living discomfort within city boundaries. Temperature trends in Ibadan city have received minor attention, yet the area has experienced heavy urban expansion between 1972 and 2014. This research aims at examining the impact of landuse change on temperature knowing that the built environment absorbs and stores solar energy, the temperature in cities can be several degrees higher than in adjacent rural areas. This is known as the urban heat island (UHI) effect. The Landsat imagery were used to examine the landuse change for a time period of 42years (1972-2014) and Land surface temperature (LST) was obtained by converting the thermal band to a surface temperature map and zonal statistic analyses was further used to examine the relationship between landuse and temperature emission. The results showed that the settlement area increased by 200km2 while the area covered by vegetation also reduced to about 42.6% during the study period. The spatial and temporal trends of temperature are related to the gradual change in urban landcover and the settlement area has the highest emission of land surface temperature. This research provides useful insight into the temporal behavior of the Ibadan city.Keywords: landuse, LST, remote sensing, UHI
Procedia PDF Downloads 2658019 Real-Time Optimisation and Minimal Energy Use for Water and Environment Efficient Irrigation
Authors: Kanya L. Khatri, Ashfaque A. Memon, Rod J. Smith, Shamas Bilal
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The viability and sustainability of crop production is currently threatened by increasing water scarcity. Water scarcity problems can be addressed through improved water productivity and the options usually presumed in this context are efficient water use and conversion of surface irrigation to pressurized systems. By replacing furrow irrigation with drip or centre pivot systems, the water efficiency can be improved by up to 30 to 45%. However, the installation and application of pumps and pipes, and the associated fuels needed for these alternatives increase energy consumption and cause significant greenhouse gas emissions. Hence, a balance between the improvement in water use and the potential increase in energy consumption is required keeping in view adverse impact of increased carbon emissions on the environment. When surface water is used, pressurized systems increase energy consumption substantially, by between 65% to 75%, and produce greenhouse gas emissions around 1.75 times higher than that of gravity based irrigation. With gravity based surface irrigation methods the energy consumption is assumed to be negligible. This study has shown that a novel real-time infiltration model REIP has enabled implementation of real-time optimization and control of surface irrigation and surface irrigation with real-time optimization has potential to bring significant improvements in irrigation performance along with substantial water savings of 2.92 ML/ha which is almost equivalent to that given by pressurized systems. Thus real-time optimization and control offers a modern, environment friendly and water efficient system with close to zero increase in energy consumption and minimal greenhouse gas emissions.Keywords: pressurised irrigation, carbon emissions, real-time, environmentally-friendly, REIP
Procedia PDF Downloads 4918018 Analysis of a IncResU-Net Model for R-Peak Detection in ECG Signals
Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar
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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks
Procedia PDF Downloads 1748017 EQMamba - Method Suggestion for Earthquake Detection and Phase Picking
Authors: Noga Bregman
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Accurate and efficient earthquake detection and phase picking are crucial for seismic hazard assessment and emergency response. This study introduces EQMamba, a deep-learning method that combines the strengths of the Earthquake Transformer and the Mamba model for simultaneous earthquake detection and phase picking. EQMamba leverages the computational efficiency of Mamba layers to process longer seismic sequences while maintaining a manageable model size. The proposed architecture integrates convolutional neural networks (CNNs), bidirectional long short-term memory (BiLSTM) networks, and Mamba blocks. The model employs an encoder composed of convolutional layers and max pooling operations, followed by residual CNN blocks for feature extraction. Mamba blocks are applied to the outputs of BiLSTM blocks, efficiently capturing long-range dependencies in seismic data. Separate decoders are used for earthquake detection, P-wave picking, and S-wave picking. We trained and evaluated EQMamba using a subset of the STEAD dataset, a comprehensive collection of labeled seismic waveforms. The model was trained using a weighted combination of binary cross-entropy loss functions for each task, with the Adam optimizer and a scheduled learning rate. Data augmentation techniques were employed to enhance the model's robustness. Performance comparisons were conducted between EQMamba and the EQTransformer over 20 epochs on this modest-sized STEAD subset. Results demonstrate that EQMamba achieves superior performance, with higher F1 scores and faster convergence compared to EQTransformer. EQMamba reached F1 scores of 0.8 by epoch 5 and maintained higher scores throughout training. The model also exhibited more stable validation performance, indicating good generalization capabilities. While both models showed lower accuracy in phase-picking tasks compared to detection, EQMamba's overall performance suggests significant potential for improving seismic data analysis. The rapid convergence and superior F1 scores of EQMamba, even on a modest-sized dataset, indicate promising scalability for larger datasets. This study contributes to the field of earthquake engineering by presenting a computationally efficient and accurate method for simultaneous earthquake detection and phase picking. Future work will focus on incorporating Mamba layers into the P and S pickers and further optimizing the architecture for seismic data specifics. The EQMamba method holds the potential for enhancing real-time earthquake monitoring systems and improving our understanding of seismic events.Keywords: earthquake, detection, phase picking, s waves, p waves, transformer, deep learning, seismic waves
Procedia PDF Downloads 248016 Approximating a Funicular Shape with a Translational Surface, Example of a Glass Canopy
Authors: Raphaël Menard, Etienne Fayette, Paul Azzopardi
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This paper presents the method to generate the geometry of an actual glass canopy project in Rennes, France, by architect Bruno Gaudin, with aim to achieve the best structural efficiency possible using only quadrangle meshing. The paper includes equation of the translational surface generated, the level of accuracy in approximating the funicular shape and the method of constructive implementation.Keywords: funicular shape, glass canopy, glass panels, lowered arches, mathematics, penalization, shell structure
Procedia PDF Downloads 5438015 Viability of Irrigation Water Conservation Practices in the Low Desert of California
Authors: Ali Montazar
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California and the Colorado River Basin are facing increasing uncertainty concerning water supplies. The Colorado River is the main source of irrigation water in the low desert of California. Currently, due to an increasing water-use competition and long-term drought at the Colorado River Basin, efficient use of irrigation water is one of the highest conservation priorities in the region. This study aims to present some of current irrigation technologies and management approaches in the low desert and assess the viability and potential of these water management practices. The results of several field experiments are used to assess five water conservation practices of sub-surface drip irrigation, automated surface irrigation, sprinkler irrigation, tail-water recovery system, and deficit irrigation strategy. The preliminary results of several ongoing studies at commercial fields are presented, particularly researches in alfalfa, sugar beets, kliengrass, sunflower, and spinach fields. The findings indicate that all these practices have significant potential to conserve water (an average of 1 ac-ft/ac) and enhance the efficiency of water use (15-25%). Further work is needed to better understand the feasibility of each of these applications and to help maintain profitable and sustainable agricultural production system in the low desert as water and labor costs, and environmental issues increase.Keywords: automated surface irrigation, deficit irrigation, low desert of California, sprinkler irrigation, sub-surface drip irrigation, tail-water recovery system
Procedia PDF Downloads 1478014 Finite Element Modelling and Analysis of Human Knee Joint
Authors: R. Ranjith Kumar
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Computer modeling and simulation of human movement is playing an important role in sports and rehabilitation. Accurate modeling and analysis of human knee join is more complex because of complicated structure whose geometry is not easily to represent by a solid model. As part of this project, from the number of CT scan images of human knee join surface reconstruction is carried out using 3D slicer software, an open source software. From this surface reconstruction model, using mesh lab (another open source software) triangular meshes are created on reconstructed surface. This final triangular mesh model is imported to Solid Works, 3D mechanical CAD modeling software. Finally this CAD model is imported to ABAQUS, finite element analysis software for analyzing the knee joints. The results obtained are encouraging and provides an accurate way of modeling and analysis of biological parts without human intervention.Keywords: solid works, CATIA, Pro-e, CAD
Procedia PDF Downloads 1178013 Signal Processing of Barkhausen Noise Signal for Assessment of Increasing Down Feed in Surface Ground Components with Poor Micro-Magnetic Response
Authors: Tanmaya Kumar Dash, Tarun Karamshetty, Soumitra Paul
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The Barkhausen Noise Analysis (BNA) technique has been utilized to assess surface integrity of steels. But the BNA technique is not very successful in evaluating surface integrity of ground steels that exhibit poor micro-magnetic response. A new approach has been proposed for the processing of BN signal with Fast Fourier transforms while Wavelet transforms has been used to remove noise from the BN signal, with judicious choice of the ‘threshold’ value, when the micro-magnetic response of the work material is poor. In the present study, the effect of down feed induced upon conventional plunge surface grinding of hardened bearing steel has been investigated along with an ultrasonically cleaned, wet polished and a sample ground with spark out technique for benchmarking. Moreover, the FFT analysis has been established, at different sets of applied voltages and applied frequency and the pattern of the BN signal in the frequency domain is analyzed. The study also depicts the wavelet transforms technique with different levels of decomposition and different mother wavelets, which has been used to reduce the noise value in BN signal of materials with poor micro-magnetic response, in order to standardize the procedure for all BN signals depending on the frequency of the applied voltage.Keywords: barkhausen noise analysis, grinding, magnetic properties, signal processing, micro-magnetic response
Procedia PDF Downloads 6618012 A Simple Approach to Reliability Assessment of Structures via Anomaly Detection
Authors: Rims Janeliukstis, Deniss Mironovs, Andrejs Kovalovs
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Operational Modal Analysis (OMA) is widely applied as a method for Structural Health Monitoring for structural damage identification and assessment by tracking the changes of the identified modal parameters over time. Unfortunately, modal parameters also depend on such external factors as temperature and loads. Any structural condition assessment using modal parameters should be done taking into consideration those external factors, otherwise there is a high chance of false positives. A method of structural reliability assessment based on anomaly detection technique called Machalanobis Squared Distance (MSD) is proposed. It requires a set of reference conditions to learn healthy state of a structure, which all future parameters are compared to. In this study, structural modal parameters (natural frequency and mode shape), as well as ambient temperature and loads acting on the structure are used as features. Numerical tests were performed on a finite element model of a carbon fibre reinforced polymer composite beam with delamination damage at various locations and of various severities. The advantages of the demonstrated approach include relatively few computational steps, ability to distinguish between healthy and damaged conditions and discriminate between different damage severities. It is anticipated to be promising in reliability assessment of massively produced structural parts.Keywords: operational modal analysis, reliability assessment, anomaly detection, damage, mahalanobis squared distance
Procedia PDF Downloads 1058011 Contact Temperature of Sliding Surfaces in AISI 316 Austenitic Stainless Steel During PIN on Disk Dry Wear Testing
Authors: Dler Abdullah Ahmed, Zozan Ahmed Mohammed
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This study looked into contact surface temperature during a pin-on-disk test. Friction and wear between sliding surfaces raised the temperature differential between the contact surface and ambient temperatures Tdiff. Tdiff was significantly influenced by wear test variables. Tdiff rose with the increase of sliding speed and applied load while dropped with the increase in ambient temperature. The highest Tdiff was 289°C during the tests at room temperature and 2.5 m/s sliding speed, while the minimum was only 24 °C during the tests at 400°C and 0.5 m/s. However, the maximum contact temperature Tmax was found during tests conducted at high ambient temperatures. The Tmax was estimated based on the theoretical equation. The comparison of experimental and theoretical Tmax data revealed good agreement.Keywords: pin on disk test, contact temperature, wear, sliding surface, friction, ambient temperature
Procedia PDF Downloads 658010 Synergetic Effects of Water and Sulfur Dioxide Treatments on Wear of Soda Lime Silicate Glass
Authors: Qian Qiao, Tongjin Xiao, Hongtu He, Jiaxin Yu
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This study is focused on the synergetic effects of water and sulfur dioxide treatments (SO₂ treatments) on the mechanochemical wear of SLS glass. It is found that the wear behavior of SLS glass in humid air is very sensitive to the water and SO₂ treatment environments based on the wear test using a ball-on-flat reciprocation tribometer. When SLS glass is treated with SO₂-without, the presence of water, the wear resistance of SLS glass in humid air becomes significantly higher compared to the pristine glass. However, when SLS glass is treated with SO₂ with the presence of water, the wear resistance of SLS glass decreases remarkably with increasing in the relative humidity (RH) from 0% to 90%. Further analyses indicate that when sodium ions are leached out of SLS glass surface via the water and SO₂ treatments, the mechanochemical properties of SLS glass surface become different depending on the RH. At lower humidity, the nano hardness of the Na⁺-leached surface is higher, and it can contribute to the enhanced wear resistance of SLS glass. In contrast, at higher humidity conditions, the SLS glass surface is more hydrophilic, and substantial wear debris can be found inside the wear track of SLS glass. Those phenomena suggest that adhesive wear and abrasive wear dominate the wear mechanism of SLS glass in humid air, causing the decreased wear resistance of SLS glass with increasing the RH. These results may not only provide a deep understanding of the wear mechanism of SLS glass but also helpful for operation process of functional and engineering glasses.Keywords: soda lime silicate glass, wear, water, SO₂
Procedia PDF Downloads 166