Search results for: scour detection
1513 3D Images Representation to Provide Information on the Type of Castella Beams Hole
Authors: Cut Maisyarah Karyati, Aries Muslim, Sulardi
Abstract:
Digital image processing techniques to obtain detailed information from an image have been used in various fields, including in civil engineering, where the use of solid beam profiles in buildings and bridges has often been encountered since the early development of beams. Along with this development, the founded castellated beam profiles began to be more diverse in shape, such as the shape of a hexagon, triangle, pentagon, circle, ellipse and oval that could be a practical solution in optimizing a construction because of its characteristics. The purpose of this research is to create a computer application to edge detect the profile of various shapes of the castella beams hole. The digital image segmentation method has been used to obtain the grayscale images and represented in 2D and 3D formats. This application has been successfully made according to the desired function, which is to provide information on the type of castella beam hole.Keywords: digital image, image processing, edge detection, grayscale, castella beams
Procedia PDF Downloads 1411512 Critical Analysis of Heat Exchanger Cycle for its Maintainability Using Failure Modes and Effect Analysis and Pareto Analysis
Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv
Abstract:
The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, pareto analysis, RPN (Risk Priority Number)
Procedia PDF Downloads 4021511 Performance Analysis of the Time-Based and Periodogram-Based Energy Detector for Spectrum Sensing
Authors: Sadaf Nawaz, Adnan Ahmed Khan, Asad Mahmood, Chaudhary Farrukh Javed
Abstract:
Classically, an energy detector is implemented in time domain (TD). However, frequency domain (FD) based energy detector has demonstrated an improved performance. This paper presents a comparison between the two approaches as to analyze their pros and cons. A detailed performance analysis of the classical TD energy-detector and the periodogram based detector is performed. Exact and approximate mathematical expressions for probability of false alarm (Pf) and probability of detection (Pd) are derived for both approaches. The derived expressions naturally lead to an analytical as well as intuitive reasoning for the improved performance of (Pf) and (Pd) in different scenarios. Our analysis suggests the dependence improvement on buffer sizes. Pf is improved in FD, whereas Pd is enhanced in TD based energy detectors. Finally, Monte Carlo simulations results demonstrate the analysis reached by the derived expressions.Keywords: cognitive radio, energy detector, periodogram, spectrum sensing
Procedia PDF Downloads 3771510 Networked Radar System to Increase Safety of Urban Railroad Crossing
Authors: Sergio Saponara, Luca Fanucci, Riccardo Cassettari, Ruggero Piernicola, Marco Righetto
Abstract:
The paper presents an innovative networked radar system for detection of obstacles in a railway level crossing scenario. This Monitoring System (MS) is able to detect moving or still obstacles within the railway level crossing area automatically, avoiding the need of human presence for surveillance. The MS is also connected to the National Railway Information and Signaling System to communicate in real-time the level crossing status. The architecture is compliant with the highest Safety Integrity Level (SIL4) of the CENELEC standard. The number of radar sensors used is configurable at set-up time and depends on how large the level crossing area can be. At least two sensors are expected and up four can be used for larger areas. The whole processing chain that elaborates the output sensor signals, as well as the communication interface, is fully-digital, was designed in VHDL code and implemented onto a Xilinx Virtex 6.Keywords: radar for safe mobility, railroad crossing, railway, transport safety
Procedia PDF Downloads 4801509 Supplementing Aerial-Roving Surveys with Autonomous Optical Cameras: A High Temporal Resolution Approach to Monitoring and Estimating Effort within a Recreational Salmon Fishery in British Columbia, Canada
Authors: Ben Morrow, Patrick O'Hara, Natalie Ban, Tunai Marques, Molly Fraser, Christopher Bone
Abstract:
Relative to commercial fisheries, recreational fisheries are often poorly understood and pose various challenges for monitoring frameworks. In British Columbia (BC), Canada, Pacific salmon are heavily targeted by recreational fishers while also being a key source of nutrient flow and crucial prey for a variety of marine and terrestrial fauna, including endangered Southern Resident killer whales (Orcinus orca). Although commercial fisheries were historically responsible for the majority of salmon retention, recreational fishing now comprises both greater effort and retention. The current monitoring scheme for recreational salmon fisheries involves aerial-roving creel surveys. However, this method has been identified as costly and having low predictive power as it is often limited to sampling fragments of fluid and temporally dynamic fisheries. This study used imagery from two shore-based autonomous cameras in a highly active recreational fishery around Sooke, BC, and evaluated their efficacy in supplementing existing aerial-roving surveys for monitoring a recreational salmon fishery. This study involved continuous monitoring and high temporal resolution (over one million images analyzed in a single fishing season), using a deep learning-based vessel detection algorithm and a custom image annotation tool to efficiently thin datasets. This allowed for the quantification of peak-season effort from a busy harbour, species-specific retention estimates, high levels of detected fishing events at a nearby popular fishing location, as well as the proportion of the fishery management area represented by cameras. Then, this study demonstrated how it could substantially enhance the temporal resolution of a fishery through diel activity pattern analyses, scaled monthly to visualize clusters of activity. This work also highlighted considerable off-season fishing detection, currently unaccounted for in the existing monitoring framework. These results demonstrate several distinct applications of autonomous cameras for providing enhanced detail currently unavailable in the current monitoring framework, each of which has important considerations for the managerial allocation of resources. Further, the approach and methodology can benefit other studies that apply shore-based camera monitoring, supplement aerial-roving creel surveys to improve fine-scale temporal understanding, inform the optimal timing of creel surveys, and improve the predictive power of recreational stock assessments to preserve important and endangered fish species.Keywords: cameras, monitoring, recreational fishing, stock assessment
Procedia PDF Downloads 1221508 Gene Names Identity Recognition Using Siamese Network for Biomedical Publications
Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu
Abstract:
As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Annotating pathway diagrams manually is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.Keywords: biological pathway, gene identification, object detection, Siamese network
Procedia PDF Downloads 2921507 Learning Example of a Biomedical Project from a Real Problem of Muscle Fatigue
Authors: M. Rezki, A. Belaidi
Abstract:
This paper deals with a method of learning to solve a real problem in biomedical engineering from a technical study of muscle fatigue. Electromyography (EMG) is a technique for evaluating and recording the electrical activity produced by skeletal muscles (viewpoint: anatomical and physiological). EMG is used as a diagnostics tool for identifying neuromuscular diseases, assessing low-back pain and muscle fatigue in general. In order to study the EMG signal for detecting fatigue in a muscle, we have taken a real problem which touches the tramway conductor the handle bar. For the study, we have used a typical autonomous platform in order to get signals at real time. In our case study, we were confronted with complex problem to do our experiments in a tram. This type of problem is recurring among students. To teach our students the method to solve this kind of problem, we built a similar system. Through this study, we realized a lot of objectives such as making the equipment for simulation, the study of detection of muscle fatigue and especially how to manage a study of biomedical looking.Keywords: EMG, health platform, conductor’s tram, muscle fatigue
Procedia PDF Downloads 3131506 Machine Learning Analysis of Eating Disorders Risk, Physical Activity and Psychological Factors in Adolescents: A Community Sample Study
Authors: Marc Toutain, Pascale Leconte, Antoine Gauthier
Abstract:
Introduction: Eating Disorders (ED), such as anorexia, bulimia, and binge eating, are psychiatric illnesses that mostly affect young people. The main symptoms concern eating (restriction, excessive food intake) and weight control behaviors (laxatives, vomiting). Psychological comorbidities (depression, executive function disorders, etc.) and problematic behaviors toward physical activity (PA) are commonly associated with ED. Acquaintances on ED risk factors are still lacking, and more community sample studies are needed to improve prevention and early detection. To our knowledge, studies are needed to specifically investigate the link between ED risk level, PA, and psychological risk factors in a community sample of adolescents. The aim of this study is to assess the relation between ED risk level, exercise (type, frequency, and motivations for engaging in exercise), and psychological factors based on the Jacobi risk factors model. We suppose that a high risk of ED will be associated with the practice of high caloric cost PA, motivations oriented to weight and shape control, and psychological disturbances. Method: An online survey destined for students has been sent to several middle schools and colleges in northwest France. This survey combined several questionnaires, the Eating Attitude Test-26 assessing ED risk; the Exercise Motivation Inventory–2 assessing motivations toward PA; the Hospital Anxiety and Depression Scale assessing anxiety and depression, the Contour Drawing Rating Scale; and the Body Esteem Scale assessing body dissatisfaction, Rosenberg Self-esteem Scale assessing self-esteem, the Exercise Dependence Scale-Revised assessing PA dependence, the Multidimensional Assessment of Interoceptive Awareness assessing interoceptive awareness and the Frost Multidimensional Perfectionism Scale assessing perfectionism. Machine learning analysis will be performed in order to constitute groups with a tree-based model clustering method, extract risk profile(s) with a bootstrap method comparison, and predict ED risk with a prediction method based on a decision tree-based model. Expected results: 1044 complete records have already been collected, and the survey will be closed at the end of May 2022. Records will be analyzed with a clustering method and a bootstrap method in order to reveal risk profile(s). Furthermore, a predictive tree decision method will be done to extract an accurate predictive model of ED risk. This analysis will confirm typical main risk factors and will give more data on presumed strong risk factors such as exercise motivations and interoceptive deficit. Furthermore, it will enlighten particular risk profiles with a strong level of proof and greatly contribute to improving the early detection of ED and contribute to a better understanding of ED risk factors.Keywords: eating disorders, risk factors, physical activity, machine learning
Procedia PDF Downloads 831505 Coal Mining Safety Monitoring Using Wsn
Authors: Somdatta Saha
Abstract:
The main purpose was to provide an implementable design scenario for underground coal mines using wireless sensor networks (WSNs). The main reason being that given the intricacies in the physical structure of a coal mine, only low power WSN nodes can produce accurate surveillance and accident detection data. The work mainly concentrated on designing and simulating various alternate scenarios for a typical mine and comparing them based on the obtained results to arrive at a final design. In the Era of embedded technology, the Zigbee protocols are used in more and more applications. Because of the rapid development of sensors, microcontrollers, and network technology, a reliable technological condition has been provided for our automatic real-time monitoring of coal mine. The underground system collects temperature, humidity and methane values of coal mine through sensor nodes in the mine; it also collects the number of personnel inside the mine with the help of an IR sensor, and then transmits the data to information processing terminal based on ARM.Keywords: ARM, embedded board, wireless sensor network (Zigbee)
Procedia PDF Downloads 3401504 3D-Mesh Robust Watermarking Technique for Ownership Protection and Authentication
Authors: Farhan A. Alenizi
Abstract:
Digital watermarking has evolved in the past years as an important means for data authentication and ownership protection. The images and video watermarking was well known in the field of multimedia processing; however, 3D objects' watermarking techniques have emerged as an important means for the same purposes, as 3D mesh models are in increasing use in different areas of scientific, industrial, and medical applications. Like the image watermarking techniques, 3D watermarking can take place in either space or transform domains. Unlike images and video watermarking, where the frames have regular structures in both space and temporal domains, 3D objects are represented in different ways as meshes that are basically irregular samplings of surfaces; moreover, meshes can undergo a large variety of alterations which may be hard to tackle. This makes the watermarking process more challenging. While the transform domain watermarking is preferable in images and videos, they are still difficult to implement in 3d meshes due to the huge number of vertices involved and the complicated topology and geometry, and hence the difficulty to perform the spectral decomposition, even though significant work was done in the field. Spatial domain watermarking has attracted significant attention in the past years; they can either act on the topology or on the geometry of the model. Exploiting the statistical characteristics in the 3D mesh models from both geometrical and topological aspects was useful in hiding data. However, doing that with minimal surface distortions to the mesh attracted significant research in the field. A 3D mesh blind watermarking technique is proposed in this research. The watermarking method depends on modifying the vertices' positions with respect to the center of the object. An optimal method will be developed to reduce the errors, minimizing the distortions that the 3d object may experience due to the watermarking process, and reducing the computational complexity due to the iterations and other factors. The technique relies on the displacement process of the vertices' locations depending on the modification of the variances of the vertices’ norms. Statistical analyses were performed to establish the proper distributions that best fit each mesh, and hence establishing the bins sizes. Several optimizing approaches were introduced in the realms of mesh local roughness, the statistical distributions of the norms, and the displacements in the mesh centers. To evaluate the algorithm's robustness against other common geometry and connectivity attacks, the watermarked objects were subjected to uniform noise, Laplacian smoothing, vertices quantization, simplification, and cropping. Experimental results showed that the approach is robust in terms of both perceptual and quantitative qualities. It was also robust against both geometry and connectivity attacks. Moreover, the probability of true positive detection versus the probability of false-positive detection was evaluated. To validate the accuracy of the test cases, the receiver operating characteristics (ROC) curves were drawn, and they’ve shown robustness from this aspect. 3D watermarking is still a new field but still a promising one.Keywords: watermarking, mesh objects, local roughness, Laplacian Smoothing
Procedia PDF Downloads 1601503 Segmentation of Gray Scale Images of Dropwise Condensation on Textured Surfaces
Authors: Helene Martin, Solmaz Boroomandi Barati, Jean-Charles Pinoli, Stephane Valette, Yann Gavet
Abstract:
In the present work we developed an image processing algorithm to measure water droplets characteristics during dropwise condensation on pillared surfaces. The main problem in this process is the similarity between shape and size of water droplets and the pillars. The developed method divides droplets into four main groups based on their size and applies the corresponding algorithm to segment each group. These algorithms generate binary images of droplets based on both their geometrical and intensity properties. The information related to droplets evolution during time including mean radius and drops number per unit area are then extracted from the binary images. The developed image processing algorithm is verified using manual detection and applied to two different sets of images corresponding to two kinds of pillared surfaces.Keywords: dropwise condensation, textured surface, image processing, watershed
Procedia PDF Downloads 2231502 Switching to the Latin Alphabet in Kazakhstan: A Brief Overview of Character Recognition Methods
Authors: Ainagul Yermekova, Liudmila Goncharenko, Ali Baghirzade, Sergey Sybachin
Abstract:
In this article, we address the problem of Kazakhstan's transition to the Latin alphabet. The transition process started in 2017 and is scheduled to be completed in 2025. In connection with these events, the problem of recognizing the characters of the new alphabet is raised. Well-known character recognition programs such as ABBYY FineReader, FormReader, MyScript Stylus did not recognize specific Kazakh letters that were used in Cyrillic. The author tries to give an assessment of the well-known method of character recognition that could be in demand as part of the country's transition to the Latin alphabet. Three methods of character recognition: template, structured, and feature-based, are considered through the algorithms of operation. At the end of the article, a general conclusion is made about the possibility of applying a certain method to a particular recognition process: for example, in the process of population census, recognition of typographic text in Latin, or recognition of photos of car numbers, store signs, etc.Keywords: text detection, template method, recognition algorithm, structured method, feature method
Procedia PDF Downloads 1871501 Child Sexual Abuse Prevention: Evaluation of the Program “Sharing Mouth to Mouth: My Body, Nobody Can Touch It”
Authors: Faride Peña, Teresita Castillo, Concepción Campo
Abstract:
Sexual violence, and particularly child sexual abuse, is a serious problem all over the world, México included. Given its importance, there are several preventive and care programs done by the government and the civil society all over the country but most of them are developed in urban areas even though these problems are especially serious in rural areas. Yucatán, a state in southern México, occupies one of the first places in child sexual abuse. Considering the above, the University Unit of Clinical Research and Victimological Attention (UNIVICT) of the Autonomous University of Yucatan, designed, implemented and is currently evaluating the program named “Sharing Mouth to Mouth: My Body, Nobody Can Touch It”, a program to prevent child sexual abuse in rural communities of Yucatán, México. Its aim was to develop skills for the detection of risk situations, providing protection strategies and mechanisms for prevention through culturally relevant psycho-educative strategies to increase personal resources in children, in collaboration with parents, teachers, police and municipal authorities. The diagnosis identified that a particularly vulnerable population were children between 4 and 10 years. The program run during 2015 in primary schools in the municipality whose inhabitants are mostly Mayan. The aim of this paper is to present its evaluation in terms of its effectiveness and efficiency. This evaluation included documental analysis of the work done in the field, psycho-educational and recreational activities with children, evaluation of knowledge by participating children and interviews with parents and teachers. The results show high efficiency in fulfilling the tasks and achieving primary objectives. The efficiency shows satisfactory results but also opportunity areas that can be resolved with minor adjustments to the program. The results also show the importance of including culturally relevant strategies and activities otherwise it minimizes possible achievements. Another highlight is the importance of participatory action research in preventive approaches to child sexual abuse since by becoming aware of the importance of the subject people participate more actively; in addition to design culturally appropriate strategies and measures so that the proposal may not be distant to the people. Discussion emphasizes the methodological implications of prevention programs (convenience of using participatory action research (PAR), importance of monitoring and mediation during implementation, developing detection skills tools in creative ways using psycho-educational interactive techniques and working assessment issued by the participants themselves). As well, it is important to consider the holistic character this type of program should have, in terms of incorporating social and culturally relevant characteristics, according to the community individuality and uniqueness, consider type of communication to be used and children’ language skills considering that there should be variations strongly linked to a specific cultural context.Keywords: child sexual abuse, evaluation, PAR, prevention
Procedia PDF Downloads 2951500 Right Atrial Tissue Morphology in Acquired Heart Diseases
Authors: Edite Kulmane, Mara Pilmane, Romans Lacis
Abstract:
Introduction: Acquired heart diseases remain one of the leading health care problems in the world. Changes in myocardium of the diseased hearts are complex and pathogenesis is still not fully clear. The aim of this study was to identify appearance and distribution of apoptosis, homeostasis regulating factors, and innervation and ischemia markers in right atrial tissue in different acquired heart diseases. Methods: During elective open heart surgery were taken right atrial tissue fragments from 12 patients. All patients were operated because of acquired heart diseases- aortic valve stenosis (5 patients), coronary heart disease (5 patients), coronary heart disease and secondary mitral insufficiency (1 patient) and mitral disease (1 patient). The mean age was (mean±SD) 70,2±7,0 years (range 58-83 years). The tissues were stained with haematoxylin and eosin methods for routine light-microscopical examination and for immunohistochemical detection of protein gene peptide 9.5 (PGP 9.5), human atrial natriuretic peptide (hANUP), vascular endothelial growth factor (VEGF), chromogranin A and endothelin. Apoptosis was detected by TUNEL method. Results: All specimens showed degeneration of cardiomyocytes with lysis of myofibrils, diffuse vacuolization especially in perinuclear region, different size of cells and their nuclei. The severe invasion of connective tissue was observed in main part of all fragments. The apoptotic index ranged from 24 to 91%. One specimen showed region of newly performed microvessels with cube shaped endotheliocytes that were positive for PGP 9.5, endothelin, chromogranin A and VEGF. From all fragments, taken from patients with coronary heart disease, there were observed numerous PGP 9.5-containing nerve fibres, except in patient with secondary mitral insufficiency, who showed just few PGP 9.5 positive nerves. In majority of specimens there were regions observed with cube shaped mixed -VEGF immunoreactive endocardial and epicardial cells. Only VEGF positive endothelial cells were observed just in few specimens. There was no significant difference of hANUP secreting cells among all specimens. All patients operated due to the coronary heart disease moderate to numerous number of chromogranin A positive cells were seen while in patients with aortic valve stenosis tissue demonstrated just few factor positive cells. Conclusions: Complex detection of different factors may indicate selectively disordered morphopathogenetical event of heart disease: decrease of PGP 9.5 nerves suggests the decreased innervation of organ; increased apoptosis indicates the cell death without ingrowth of connective tissue; persistent presence of hANUP proves the unchanged homeostasis of cardiomyocytes probably supported by expression of chromogranins. Finally, decrease of VEGF detects the regions of affected blood vessels in heart affected by acquired heart disease.Keywords: heart, apoptosis, protein-gene peptide 9.5, atrial natriuretic peptide, vascular endothelial growth factor, chromogranin A, endothelin
Procedia PDF Downloads 2951499 A Weighted Approach to Unconstrained Iris Recognition
Authors: Yao-Hong Tsai
Abstract:
This paper presents a weighted approach to unconstrained iris recognition. Nowadays, commercial systems are usually characterized by strong acquisition constraints based on the subject’s cooperation. However, it is not always achievable for real scenarios in our daily life. Researchers have been focused on reducing these constraints and maintaining the performance of the system by new techniques at the same time. With large variation in the environment, there are two main improvements to develop the proposed iris recognition system. For solving extremely uneven lighting condition, statistic based illumination normalization is first used on eye region to increase the accuracy of iris feature. The detection of the iris image is based on Adaboost algorithm. Secondly, the weighted approach is designed by Gaussian functions according to the distance to the center of the iris. Furthermore, local binary pattern (LBP) histogram is then applied to texture classification with the weight. Experiment showed that the proposed system provided users a more flexible and feasible way to interact with the verification system through iris recognition.Keywords: authentication, iris recognition, adaboost, local binary pattern
Procedia PDF Downloads 2251498 Application of the MOOD Technique to the Steady-State Euler Equations
Authors: Gaspar J. Machado, Stéphane Clain, Raphael Loubère
Abstract:
The goal of the present work is to numerically study steady-state nonlinear hyperbolic equations in the context of the finite volume framework. We will consider the unidimensional Burgers' equation as the reference case for the scalar situation and the unidimensional Euler equations for the vectorial situation. We consider two approaches to solve the nonlinear equations: a time marching algorithm and a direct steady-state approach. We first develop the necessary and sufficient conditions to obtain the existence and unicity of the solution. We treat regular examples and solutions with a steady shock and to provide very-high-order finite volume approximations we implement a method based on the MOOD technology (Multi-dimensional Optimal Order Detection). The main ingredient consists in using an 'a posteriori' limiting strategy to eliminate non physical oscillations deriving from the Gibbs phenomenon while keeping a high accuracy for the smooth part.Keywords: Euler equations, finite volume, MOOD, steady-state
Procedia PDF Downloads 2771497 miR-200c as a Biomarker for 5-FU Chemosensitivity in Colorectal Cancer
Authors: Rezvan Najafi, Korosh Heydari, Massoud Saidijam
Abstract:
5-FU is a chemotherapeutic agent that has been used in colorectal cancer (CRC) treatment. However, it is usually associated with the acquired resistance, which decreases the therapeutic effects of 5-FU. miR-200c is involved in chemotherapeutic drug resistance, but its mechanism is not fully understood. In this study, the effect of inhibition of miR-200c in sensitivity of HCT-116 CRC cells to 5-FU was evaluated. HCT-116 cells were transfected with LNA-anti- miR-200c for 48 h. mRNA expression of miR-200c was evaluated using quantitative real- time PCR. The protein expression of phosphatase and tensin homolog (PTEN) and E-cadherin were analyzed by western blotting. Annexin V and propidium iodide staining assay were applied for apoptosis detection. The caspase-3 activation was evaluated by an enzymatic assay. The results showed LNA-anti-miR-200c inhibited the expression of PTEN and E-cadherin protein, apoptosis and activation of caspase 3 compared with control cells. In conclusion, these results suggest that miR-200c as a prognostic marker can overcome to 5-FU chemoresistance in CRC.Keywords: colorectal cancer, miR-200c, 5-FU resistance, E-cadherin, PTEN
Procedia PDF Downloads 1661496 Impact of Flavor on Food Product Quality, A Case Study of Vanillin Stability during Biscuit Preparation
Authors: N. Yang, R. Linforth, I. Fisk
Abstract:
The influence of food processing and choice of flavour solvent was investigated using biscuits prepared with vanillin flavour as an example. Powder vanillin either was added directly into the dough or dissolved into flavour solvent then mixed into the dough. The impact of two commonly used flavour solvents on food quality was compared: propylene glycol (PG) or triacetin (TA). The analytical approach for vanillin detection was developed by chromatography (HPLC-PDA), and the standard extraction method for vanillin was also established. The results indicated the impact of solvent choice on vanillin level during biscuit preparation. After baking, TA as a more heat resistant solvent retained more vanillin than PG, so TA is a better solvent for products that undergo a heating process. The results also illustrated the impact of mixing and baking on vanillin stability in the matrices. The average loss of vanillin was 33% during mixing and 13% during baking, which indicated that the binding of vanillin to fat or flour before baking might cause larger loss than evaporation loss during baking.Keywords: biscuit, flavour stability, food quality, vanillin
Procedia PDF Downloads 5081495 Microbiological Analysis, Cytotoxic and Genotoxic Effects from Material Captured in PM2.5 and PM10 Filters Used in the Aburrá Valley Air Quality Monitoring Network (Colombia)
Authors: Carmen E. Zapata, Juan Bautista, Olga Montoya, Claudia Moreno, Marisol Suarez, Alejandra Betancur, Duvan Nanclares, Natalia A. Cano
Abstract:
This study aims to evaluate the diversity of microorganisms in filters PM2.5 and PM10; and determine the genotoxic and cytotoxic activity of the complex mixture present in PM2.5 filters used in the Aburrá Valley Air Quality Monitoring Network (Colombia). The research results indicate that particulate matter PM2.5 of different monitoring stations are bacteria; however, this study of detection of bacteria and their phylogenetic relationship is not complete evidence to connect the microorganisms with pathogenic or degrading activities of compounds present in the air. Additionally, it was demonstrated the damage induced by the particulate material in the cell membrane, lysosomal and endosomal membrane and in the mitochondrial metabolism; this damage was independent of the PM2.5 concentrations in almost all the cases.Keywords: cytotoxic, genotoxic, microbiological analysis, PM10, PM2.5
Procedia PDF Downloads 3481494 Detection of Respiratory Syncytial Virus (hRSV) by PCR Technique in Lower Respiratory Tract Infection (LRTI) in Babylon City
Authors: Amal Raqib Shameran, Ghanim Aboud Al-Mola
Abstract:
Respiratory syncytial virus (hRSV) is the major pathogens of respiratory tract infections (RTI) among infants and children in the world. They are classified in family Paramyxoviridae and sub-family Pneumovirinae. The current work aimed to detect the role of RSV in the lower respiratory tract infection (LRTI) in Hilla, Iraq. The samples were collected from 50 children who were admitted to hospital suffering from lower respiratory tract infections (LRTI). 50 nasal and pharyngeal swabs were taken from patients at the period from January 2010 till April 2011, hospitalized in Hilla Maternity and Children Hospital. The results showed that the proportion of children infected with hRSV accounted for 24% 12/50 with lower respiratory tract infections (LRTI) when they tested by polymerase chain reaction (RT-PCR).Keywords: respiratory syncytial virus, respiratory tract infections, infants, polymerase chain reaction (PCR)
Procedia PDF Downloads 3561493 Detection of COVID-19 Cases From X-Ray Images Using Capsule-Based Network
Authors: Donya Ashtiani Haghighi, Amirali Baniasadi
Abstract:
Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.Keywords: capsule network, dropout, hyperparameter tuning, classification
Procedia PDF Downloads 781492 Improving Detection of Illegitimate Scores and Assessment in Most Advantageous Tenders
Authors: Hao-Hsi Tseng, Hsin-Yun Lee
Abstract:
The Most Advantageous Tender (MAT) has been criticized for its susceptibility to dictatorial situations and for its processing of same score, same rank issues. This study applies the four criteria from Arrow's Impossibility Theorem to construct a mechanism for revealing illegitimate scores in scoring methods. While commonly be used to improve on problems resulting from extreme scores, ranking methods hide significant defects, adversely affecting selection fairness. To address these shortcomings, this study relies mainly on the overall evaluated score method, using standardized scores plus normal cumulative distribution function conversion to calculate the evaluation of vender preference. This allows for free score evaluations, which reduces the influence of dictatorial behavior and avoiding same score, same rank issues. Large-scale simulations confirm that this method outperforms currently used methods using the Impossibility Theorem.Keywords: Arrow’s impossibility theorem, cumulative normal distribution function, most advantageous tender, scoring method
Procedia PDF Downloads 4641491 Assessing Musculoskeletal Disorder Prevalence and Heat-Related Symptoms: A Cross-sectional Comparison in Indian Farmers
Authors: Makkhan Lal Meena, R. C. Bairwa, G. S. Dangayach, Rahul Jain
Abstract:
The current study looked at the frequency of chronic illness conditions, accidents, health complaints, and ergonomic issues among 100 conventional and 100 greenhouse farmers. Data related to the health symptoms and ergonomic problems were collected through questionnaires by conducting direct interviews of farmers. According to the findings, symptoms of heat exposure (skin rashes, headache, dizziness, and lack of appetite) were substantially higher among conventional farmers than greenhouse farmers. The greenhouse farmers reported much more pain, numbness, or weakness in wrists/hands, fingers, upper back, hips, and ankles/feet than conventional farmers. The findings of the study suggest that suitable ergonomic knowledge and awareness campaign programs concentrating on safety at work, particularly low back pain, should be implemented in workplaces to allow for earlier detection of symptoms among the greenhouse farmers.Keywords: accident, conventional farmer, ergonomics, health symptoms, greenhouse farmers, pesticide
Procedia PDF Downloads 2711490 Crystallography Trials of Escherichia coli Nitrate Transporter, NarU
Authors: Naureen Akhtar
Abstract:
The stability of the protein in detergent-containing solution is the key for its successful crystallisation. Fluorescence-detection size-exclusion chromatography (FSEC) is a potential approach for screening monodispersity as well as the stability of protein in a detergent-containing-solution. In this present study, covalently linked Green Fluorescent Protein (GFP) to bacterial nitrate transporter, NarU from Escherichia coli was studied for pre-crystallisation trials by FSEC. Immobilised metal ion affinity chromatography (IMAC) and gel filtration were employed for their purification. The main objectives of this study were over-expression, detergent screening and crystallisation of nitrate transporter proteins. This study could not produce enough proteins that could realistically be taken forward to achieve the objectives set for this particular research. In future work, different combinations of variables like vectors, tags, creation of mutant proteins, host cells, position of GFP (N- or C-terminal) and/or membrane proteins would be tried to determine the best combination as the principle of technique is still promising.Keywords: transporters, detergents, over-expression, crystallography
Procedia PDF Downloads 4771489 3D Building Model Utilizing Airborne LiDAR Dataset and Terrestrial Photographic Images
Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal
Abstract:
The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.Keywords: LiDAR datasets, DSM, DTM, 3D building models
Procedia PDF Downloads 3201488 Efficient Feature Fusion for Noise Iris in Unconstrained Environment
Authors: Yao-Hong Tsai
Abstract:
This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.Keywords: image fusion, iris recognition, local binary pattern, wavelet
Procedia PDF Downloads 3671487 Empowering a New Frontier in Heart Disease Detection: Unleashing Quantum Machine Learning
Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz
Abstract:
Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.Keywords: quantum machine learning, SVM, QSVM, matrix product state
Procedia PDF Downloads 941486 A Facile and Room Temperature Growth of Pd-Pt Decorated Hexagonal-ZnO Framework and Their Selective H₂ Gas Sensing Properties
Authors: Gaurav Malik, Satyendra Mourya, Jyoti Jaiswal, Ramesh Chandra
Abstract:
The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor
Procedia PDF Downloads 3921485 The Nature and Impact of Trojan Horses in Cybersecurity
Authors: Mehrab Faraghti
Abstract:
Trojan horses, a form of malware masquerading as legitimate software, pose significant cybersecurity threats. These malicious programs exploit user trust, infiltrate systems, and can lead to data breaches, financial loss, and compromised privacy. This paper explores the mechanisms through which Trojan horses operate, including delivery methods such as phishing and software vulnerabilities. It categorizes various types of Trojan horses and their specific impacts on individuals and organizations. Additionally, the research highlights the evolution of Trojan threats and the importance of user awareness and proactive security measures. By analyzing case studies of notable Trojan attacks, this study identifies common vulnerabilities that can be exploited and offers insights into effective countermeasures, including behavioral analysis, anomaly detection, and robust incident response strategies. The findings emphasize the need for comprehensive cybersecurity education and the implementation of advanced security protocols to mitigate the risks associated with Trojan horses.Keywords: Trojan horses, cybersecurity, malware, data breach
Procedia PDF Downloads 101484 The Effect of Closed Circuit Television Image Patch Layout on Performance of a Simulated Train-Platform Departure Task
Authors: Aaron J. Small, Craig A. Fletcher
Abstract:
This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.Keywords: rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design
Procedia PDF Downloads 168