Search results for: assembly feature

Authors: Sara Kamalisiahroudi, Jun Huang, Zhe Li, Jianbo Zhang

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Two types of commercial cylindrical lithium ion batteries (Panasonic 3.4 Ah NCR-18650B and Samsung 2.9 Ah INR-18650), were investigated experimentally. The capacities of these samples were individually measured using constant current-constant voltage (CC-CV) method at different ambient temperatures (-10 ℃, 0 ℃, 25 ℃). Their internal resistance was determined by electrochemical impedance spectroscopy (EIS) and pulse discharge methods. The cells with different configurations of parallel connection NCR-NCR, INR-INR and NCR-INR were charged/discharged at the aforementioned ambient temperatures. The results showed that the difference of internal resistance between cells much more evident at low temperatures. Furthermore, the parallel connection of NCR-NCR exhibits the most uniform temperature distribution in cells at -10 ℃, this feature is quite favorable for the safety of the battery pack.

Keywords: batteries in parallel connection, internal resistance, low temperature, temperature difference, current distribution

Procedia PDF Downloads 477

Authors: Lamyaa Gamal El-Deen Taha, Ashraf Sharawi

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China launched satellite GF-2 in 2014. This study deals with comparing nearest neighbor object-based classification and neural network classification methods for classification of the fused GF-2 image. Firstly, rectification of GF-2 image was performed. Secondly, a comparison between nearest neighbor object-based classification and neural network classification for classification of fused GF-2 was performed. Thirdly, the overall accuracy of classification and kappa index were calculated. Results indicate that nearest neighbor object-based classification is better than neural network classification for urban mapping.

Keywords: GF-2 images, feature extraction-rectification, nearest neighbour object based classification, segmentation algorithms, neural network classification, multilayer perceptron

Procedia PDF Downloads 387

Authors: Gaurav Shinde, Sai Charan Gongiguntla, Prajwal Shirur, Ahmed Hambaba

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Health issues are significantly increasing, putting a substantial strain on healthcare services. This has accelerated the integration of machine learning in healthcare, particularly following the COVID-19 pandemic. The utilization of machine learning in healthcare has grown significantly. We introduce DeClEx, a pipeline that ensures that data mirrors real-world settings by incorporating Gaussian noise and blur and employing autoencoders to learn intermediate feature representations. Subsequently, our convolutional neural network, paired with spatial attention, provides comparable accuracy to state-of-the-art pre-trained models while achieving a threefold improvement in training speed. Furthermore, we provide interpretable results using explainable AI techniques. We integrate denoising and deblurring, classification, and explainability in a single pipeline called DeClEx.

Keywords: machine learning, healthcare, classification, explainability

Procedia PDF Downloads 54

Authors: Lingling Shui, Shuting Xie

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As alternatives to electronic devices, optically active structures from responsive nanomaterials offer great opportunity buildup smart functional sensors. Hereby, we report on droplet microfluidics enabled construction and application of photonic microcapsules (PMCs) for colorimetric temperature microsensors, enabling miniaturization for injectable local micro-area sensing and integration for large-area sensing. Monodispersed PMCs are produced by in-situ photopolymerization of hydrogel shells of cholesteric liquid crystal (CLC)-in-water-in-oil double emulsion droplets prepared using microfluidic devices, with controllable physical structures and chemical compositions. Constructed PMCs exhibit thermal responsive structural color according to the selective Bragg reflection of CLC’s periodical helical structures within the microdroplet’s spherical confinement. Constructed PMCs with tunable size and composition have been successfully applied for monitoring the living cell extracellular temperature via co-incubation with cell suspension, and for detecting human body temperature via a flexible device from assembled PMCs. These PMCs could be flexibly applied in either micro-environment or large-area surface, enabling wide applications for precision temperature monitoring biological activities (e.g. cells or organs), optoelectronic devices working conditions (e.g. temperature indicators under extreme conditions), and etc.

Keywords: droplet, microfluidics, assembly, soft materials, microsensor

Procedia PDF Downloads 79

Authors: Salman Ali Nisar, Koshi Suzuki

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Precedence Diagram Method (PDM) with its additional relationships i.e., start-to-start, finish-to-finish, and start-to-finish, between activities provides more flexible schedule than traditional Critical Path Method (CPM). But, changing the duration of critical activities in PDM network will have anomalous effect on critical path. Researchers have proposed some classification of critical activity effects. In this paper, we do further study on classifications of critical activity effect and provide more information in detailed. Furthermore, we determine the maximum amount of time for each class of critical activity effect by which the project managers can control the dynamic feature (shortening/lengthening) of critical activities and project duration more efficiently.

Keywords: construction project management, critical path method, project scheduling, precedence diagram method

Procedia PDF Downloads 509

Authors: Tom Turner

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The recent financial crisis in 2008 and the growing inequality in developed industrial societies would appear to present significant challenges to capitalism and the free market. Yet there have been few substantial mainstream political or economic challenges to the dominant capitalist and market paradigm to-date. There is no dearth of critical and theoretical (academic) analyses regarding the prevailing systems failures. Yet despite the growing inequality in the developed industrial societies and the financial crisis in 2008 few commentators have advocated the comprehensive socialization or state ownership of the means of production to our knowledge – a core principle of radical Marxism in the 19th and early part of the 20th century. Undoubtedly the experience in the Soviet Union and satellite countries in the 20th century has cast a dark shadow over the notion of centrally controlled economies and state ownership of the means of production. In this paper, we explore the history of a doctrine advocating the socialization or state ownership of the means of production that was central to Marxism and socialism generally. Indeed this doctrine provoked an intense and often acrimonious debate especially for left-wing parties throughout the 20th century. The debate within the political economy tradition has historically tended to divide into a radical and a revisionist approach to changing or reforming capitalism. The radical perspective views the conflict of interest between capital and labor as a persistent and insoluble feature of a capitalist society and advocates the public or state ownership of the means of production. Alternatively, the revisionist perspective focuses on issues of distribution rather than production and emphasizes the possibility of compromise between capital and labor in capitalist societies. Over the 20th century, the radical perspective has faded and even the social democratic revisionist tradition has declined in recent years. We conclude with the major challenges that confront both the radical and revisionist perspectives in the development of viable policy agendas in mature developed democratic societies. Additionally, we consider whether state ownership of the means of production still has relevance in the 21st century and to what extent state ownership is off the agenda as a political issue in the political mainstream in developed industrial societies. A central argument in the paper is that state ownership of the means of production is unlikely to feature as either a practical or theoretical solution to the problems of capitalism post the financial crisis among mainstream political parties of the left. Although the focus here is solely on the shifting views of the radical and revisionist socialist perspectives in the western European tradition the analysis has relevance for the wider socialist movement.

Keywords: sate ownership, ownership means of production, radicals, revisionists

Procedia PDF Downloads 118

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

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The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

Procedia PDF Downloads 328

Authors: Amrane Meriem, Oukid Salyha

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The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

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Authors: E. H. Uguru, S. F. A. Sani, M. U. Khandaker, M. H. Rabir

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The beginning of cycle transient safety parameters is paramount for smooth reactor operation. The enhanced operational safety of UO₂ fuelled AP1000 reactor being the first using three fissile enrichment zones motivated this research for (Th, U)O₂ fuel. This study evaluated the impact of fissile enrichment, soluble boron, and gadolinia on the transient safety parameters to determine the basis for choosing the three fissile enrichment zones. Fuel assembly and core model of Westinghouse small modular reactor were investigated using different fuel and reactivity control arrangements. The Monte Carlo N-Particle eXtended (MCNPX) integrated with CINDER90 burn-up code was used for the calculations. The results show that the moderator temperature coefficient of reactivity (MTC) and the fuel temperature coefficient of reactivity (FTC) were respectively negative and decreased with increasing fissile enrichment. Soluble boron significantly decreased the MTC but slightly increased FTC while gadolinia followed the same trend with a minor impact. However, the MTC and FTC respectively decreased significantly with increasing change in temperature. These results provide a guide on the considerable factors in choosing the three fissile enrichment zones for (Th, U)O₂ fuel in anticipation of their impact on safety parameters. Therefore, this study provides foundational results on the factors that must be considered in choosing three fissile arrangement zones for (Th, U)O₂ fuel.

Keywords: reactivity, safety parameters, small modular reactor, soluble boron, thorium fuel cycle

Procedia PDF Downloads 129

Authors: Ahmad Umar, Sheikh Akbar, Ahmed A. Ibrahim, Mohsen A. Alhamami

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The development of advanced materials for energy storage and gas sensing applications has gained significant attention in recent years. In this study, we synthesized and characterized PANI@MnO2@rGO ternary nanocomposites (NCs) to explore their potential in supercapacitors and gas sensing devices. The ternary NCs were synthesized through a multi-step process involving the hydrothermal synthesis of MnO2 nanoparticles, preparation of PANI@rGO composites and the assembly to the ternary PANI@MnO2@rGO ternary NCs. The structural, morphological, and compositional characteristics of the materials were thoroughly analyzed using techniques such as XRD, FESEM, TEM, FTIR, and Raman spectroscopy. In the realm of gas sensing, the ternary NCs exhibited excellent performance as NH3 gas sensors. The optimized operating temperature of 100 °C yielded a peak response of 15.56 towards 50 ppm NH3. The nanocomposites demonstrated fast response and recovery times of 6 s and 10 s, respectively, and displayed remarkable selectivity for NH3 gas over other tested gases. For supercapacitor applications, the electrochemical performance of the ternary NCs was evaluated using cyclic voltammetry and galvanostatic charge-discharge techniques. The composites exhibited pseudocapacitive behavior, with the capacitance reaching up to 185 F/g at 1 A/g and excellent capacitance retention of approximately 88.54% over 4000 charge-discharge cycles. The unique combination of rGO, PANI, and MnO2 nanoparticles in these ternary NCs offer synergistic advantages, showcasing their potential to address challenges in energy storage and gas sensing technologies.

Keywords: paniI@mnO2@rGO ternary NCs, synergistic effects, supercapacitors, gas sensing, energy storage

Procedia PDF Downloads 70

Authors: Srinivasapriyan Vijayan

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Phenol is one of the most vital chemical in industry. Nowadays, phenol production is based upon the three-step cumene process, which involves a hazardous cumene hydroperoxide intermediate and produces nearly equimolar amounts of acetone as a coproduct. An attractive route in phenol production is the direct one-step selective hydroxylation of benzene using eco-friendly oxidants such as O2, N2O, and H2O2. In particular, the direct hydroxylation of benzene to form phenol with O2 has recently attracted extensive research attention because this process is green clean and eco-friendly. However, most of the catalytic systems involving O2 have a low rate of hydroxylation because the direct introduction of hydroxyl functionality into benzene is challenging. Almost all the developed catalytic systems require an elevated temperature and suffer from low conversion because of the notoriously low reactivity of aromatic C–H bonds. Moreover, increased reactivity of phenol relative to benzene makes the selective oxidation of benzene to phenol very difficult, especially under heating conditions. Hollow spheres, a very fascinating class of materials with good permeation and low density, highly monodisperse MOF hollow sandwich spheres have been rationally synthesized using monodisperse polystyrene (PS) nanoparticles as templates through a versatile step-by-step self-assembly strategy. So, our findings could pave the way toward highly efficient nonprecious catalysts for low-temperature oxidation reactions in heterogeneous catalysis. Because it is easy post-reaction separation, its cheap, green and recyclable.

Keywords: benzene hydroxylation, Fe-based metal organic frameworks, molecular oxygen, phenol

Procedia PDF Downloads 213

Authors: Kaouther Bergaui, Nafaa Reguigui, Charles Gary

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Characterization and the applications of deuterium-deuterium (DD) neutron generator developed by Adelphie technology and acquired by the National Centre of Nuclear Science and Technology (NCNST) were presented in this work. We study the performance of the neutron generator in terms of neutron yield, production efficiency, and the ionic current as a function of the acceleration voltage at various RF powers. We provide the design and optimization of the PGNAA chamber and thus give insight into the capabilities of the planned PGNAA facility. Additional non-destructive techniques were studied employing the DD neutron generator, such as PGNAA and neutron radiography: The PGNAA is used for determining the concentration of 10B in Si and SiO2 matrices by using a germanium detector HPGe and the results obtained are compared with PGNAA system using a Sodium Iodide detector (NaI (Tl)); Neutron radiography facility was tested and simulated, using a camera device CCD and simulated by the Monte Carlo code; and the explosive detection system (EDS) also simulated using the Monte Carlo code. The study allows us to show that the new models of DD neutron generators are feasible and that superior-quality neutron beams could be produced and used for various applications. The feasibility of Boron neutron capture therapy (BNCT) for cancer treatment using a neutron generator was assessed by optimizing Beam Shaping Assembly (BSA) on a phantom using Monte-Carlo (MCNP6) simulations.

Keywords: neutron generator deuterium-deuterium, Monte Carlo method, radiation, neutron flux, neutron activation analysis, born, neutron radiography, explosive detection, BNCT

Procedia PDF Downloads 191

Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 250

Authors: Li Ji, Kaiwei Chu, Shibo Kuang, Aibing Yu

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Hydrocyclones are widely used to classify particles by size in industries such as mineral processing and chemical processing. The particles to be handled usually have a broad range of size distributions and sometimes density distributions, which has to be properly considered, causing challenges in the modelling of hydrocyclone. The combined approach of Computational Fluid Dynamics (CFD) and Discrete Element Method (DEM) offers convenience to model particle size/density distribution. However, its direct application to hydrocyclones is computationally prohibitive because there are billions of particles involved. In this work, a CFD-DEM model with the concept of the coarse-grained (CG) model is developed to model the solid-fluid flow in a hydrocyclone. The DEM is used to model the motion of discrete particles by applying Newton’s laws of motion. Here, a particle assembly containing a certain number of particles with same properties is treated as one CG particle. The CFD is used to model the liquid flow by numerically solving the local-averaged Navier-Stokes equations facilitated with the Volume of Fluid (VOF) model to capture air-core. The results are analyzed in terms of fluid and solid flow structures, and particle-fluid, particle-particle and particle-wall interaction forces. Furthermore, the calculated separation performance is compared with the measurements. The results obtained from the present study indicate that this approach can offer an alternative way to examine the flow and performance of hydrocyclones

Keywords: computational fluid dynamics, discrete element method, hydrocyclone, multiphase flow

Procedia PDF Downloads 405

Authors: Elena E. Lyakso, Olga V. Frolova, Yuri N. Matveev, Aleksey S. Grigorev, Alexander S. Nikolaev, Viktor A. Gorodnyi

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The study of the children’s emotional sphere depending on age and psychoneurological state is of great importance for the design of educational programs for children and their social adaptation. Atypical development may be accompanied by violations or specificities of the emotional sphere. To study characteristics of the emotional state reflection in the voice and speech features of children, the perceptual study with the participation of adults and the automatic recognition of speech were conducted. Speech of children with typical development (TD), with Down syndrome (DS), and with autism spectrum disorders (ASD) aged 6-12 years was recorded. To obtain emotional speech in children, model situations were created, including a dialogue between the child and the experimenter containing questions that can cause various emotional states in the child and playing with a standard set of toys. The questions and toys were selected, taking into account the child’s age, developmental characteristics, and speech skills. For the perceptual experiment by adults, test sequences containing speech material of 30 children: TD, DS, and ASD were created. The listeners were 100 adults (age 19.3 ± 2.3 years). The listeners were tasked with determining the children’s emotional state as “comfort – neutral – discomfort” while listening to the test material. Spectrographic analysis of speech signals was conducted. For automatic recognition of the emotional state, 6594 speech files containing speech material of children were prepared. Automatic recognition of three states, “comfort – neutral – discomfort,” was performed using automatically extracted from the set of acoustic features - the Geneva Minimalistic Acoustic Parameter Set (GeMAPS) and the extended Geneva Minimalistic Acoustic Parameter Set (eGeMAPS). The results showed that the emotional state is worse determined by the speech of TD children (comfort – 58% of correct answers, discomfort – 56%). Listeners better recognized discomfort in children with ASD and DS (78% of answers) than comfort (70% and 67%, respectively, for children with DS and ASD). The neutral state is better recognized by the speech of children with ASD (67%) than by the speech of children with DS (52%) and TD children (54%). According to the automatic recognition data using the acoustic feature set GeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.687; children with DS – 0.725; TD children – 0.641. When using the acoustic feature set eGeMAPSv01b, the accuracy of automatic recognition of emotional states for children with ASD is 0.671; children with DS – 0.717; TD children – 0.631. The use of different models showed similar results, with better recognition of emotional states by the speech of children with DS than by the speech of children with ASD. The state of comfort is automatically determined better by the speech of TD children (precision – 0.546) and children with ASD (0.523), discomfort – children with DS (0.504). The data on the specificities of recognition by adults of the children’s emotional state by their speech may be used in recruitment for working with children with atypical development. Automatic recognition data can be used to create alternative communication systems and automatic human-computer interfaces for social-emotional learning. Acknowledgment: This work was financially supported by the Russian Science Foundation (project 18-18-00063).

Keywords: autism spectrum disorders, automatic recognition of speech, child’s emotional speech, Down syndrome, perceptual experiment

Procedia PDF Downloads 186

Authors: Aida Sheeta, M. Nashat Fors, Sherwet El Gholmy, Marwa Issa

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Globalization has raised the customer preferences not only towards the high-quality garments but also the right fitting, comfort and aesthetic apparels. This only can be accomplished by the good interaction between fabric mechanical and physical properties as well as the required style. Consequently, this paper provides an integrated review of the fabric drape terminology because it is considered as an essential feature in which the fabric can form folds with the help of the gravity. Moreover, an instrument has been fabricated in order to analyze the static and dynamic drape behaviors using different fabric types. In addition, the obtained results find out the parameters affecting the drape coefficient using digital image processing for various kind of commercial fabrics. This was found to be an essential first step in order to analyze the behavior of this fabric when it is fabricated in a certain 3-D garment design.

Keywords: cloth fitting, fabric drape nodes, garment silhouette, image processing

Procedia PDF Downloads 183

Authors: Z. S. Yip, T. K. Tan, C. C. Geh, T. T. Ting

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The mobile phone is an indispensable device in today’s daily living. The arising new brands in the market with different specification are targeting at the different population. The most promising market would be the younger generation who are IT savvy. Therefore, it is beneficial to find out their factors of consideration in purchasing a mobile phone. A survey is carried out in Malaysia to discover the current youngster’s mobile phone buying behavior. This study has found that the most influencing factor of consideration is Price, followed by Feature, and Battery Lifespan. Gender and Income have no relationship with certain factors of consideration. It is important to discover the factors of consideration in order to provide industry insight into the current trend of smartphone in Malaysia.

Keywords: buying behavior, smart phone, mobile brand, mobile operating system, specification, battery lifespan

Procedia PDF Downloads 354

Authors: Tugba Ayas Onol

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The paper revisits Jean-François Lyotard’s interpretation of the Kantian Sublime as a tool for understanding politics after modernity. In 1985 Lyotard announces the end of rational politics based on consensus and claims that new strategies are urged to recognize the political imperatives of marginalized groups. The charm of the sublime as a reflective judgment is grounded on the fact that the judgment of sublime is free from any notion of consensus or common sense in particular. Lyotard interprets this feature of the sublime as a respect for heterogeneity and for him aesthetic judgments can be a model for understanding justice in postmodern times, in which it seems hard to follow a single universal law among different phrase regimes. More importantly, the Kantian sublime speaks to what Lyotard addresses as the incommensurability of phase genres. The present paper shall try to evaluate Lyotard’s employment of the Kantian notion of the sublime in relation to its possible political import.

Keywords: Kant, Lyotard, sublime, politics

Procedia PDF Downloads 380

Authors: Hefzollah Mohammadiyan, Mohammad Bagher Heidari, Ensiyeh Hajeb

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In this paper investigates and analyses the structure of nano sensors will be discussed. The structure can be classified based of nano sensors: quantum points, carbon nanotubes and nano tools, which details into each other and in turn are analyzed. Then will be fully examined to the Carbon nanotubes as chemical and mechanical sensors. The following discussion, be examined compares the advantages and disadvantages as different types of sensors and also it has feature and a wide range of applications in various industries. Finally, the structure and application of Chemical sensor transistors and the sensors will be discussed in air pollution control.

Keywords: carbon nanotubes, quantum points, chemical sensors, mechanical sensors, chemical sensor transistors, single walled nanotube (SWNT), atomic force microscope (AFM)

Procedia PDF Downloads 448

Authors: Anqi Wang, Linye Zhang

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With the proliferation and development of mobile devices, various mobile apps have appeared to satisfy people’s needs. Metro, with the feature of convenient, punctuality and economic, is one of the most popular modes of transportation in cities. Yet, there are still some inconveniences brought by various factors, impacting tourists’ riding experience. The aim of this study is to help tourists to shorten the time of purchasing tickets, to provide them clear metro information and direct navigation, detailed schedule as well as a way to collect metro cards as souvenir. The study collects data through three phases, including observation, survey and test. Data collected from 106 tourists totally in Wuhan metro stations are discussed in the study. The result reflects tourists’ demand when they take the metro. It also indicates the feasibility of using mobile technology to improve passenger’s experience.

Keywords: mobile app, metro, public transportation, ticket, mobile payment, indoors positioning, tourists

Procedia PDF Downloads 140

Authors: Yoftahe Nigussie

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This report presents a final year project pertaining to the design of Fire tube boiler for the purpose of producing saturated steam. The objective of the project is to produce saturated steam for different purpose with a capacity of 2000kg/h at 12bar design pressure by performing a design of a higher performance fire tube boiler that considered the requirements of cost minimization and parameters improvement. This is mostly done in selection of appropriate material for component parts, construction materials and production methods in different steps of analysis. In the analysis process, most of the design parameters are obtained by iterating with related formulas like selection of diameter of tubes with overall heat transfer coefficient optimization, and the other selections are also as like considered. The number of passes is two because of the size and area of the tubes and shell. As the analysis express by using heavy oil fuel no6 with a higher heating value of 44000kJ/kg and lower heating value of 41300kJ/kg and the amount of fuel consumed 140.37kg/hr. and produce 1610kw of heat with efficiency of 85.25%. The flow of the fluid is a cross flow because of its own advantage and the arrangement of the tube in-side the shell is welded with the tube sheet, and the tube sheet is attached with the shell and the end by using a gasket and weld. The design of the shell, using European Standard code section, is as like pressure vessel by considering the weight, including content and the supplementary accessories such as lifting lugs, openings, ends, man hole and supports with detail and assembly drawing.

Keywords: steam generation, external treatment, internal treatment, steam velocity

Procedia PDF Downloads 95

Authors: Shabir Ahmad Sofi, Shubham Aggarwal, Sanyam Singhal, Roohie Naaz

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Biometric recognition refers to an automatic recognition of individuals based on a feature vector(s) derived from their physiological and/or behavioral characteristic. Biometric recognition systems should provide a reliable personal recognition schemes to either confirm or determine the identity of an individual. These features are used to provide an authentication for computer based security systems. Applications of such a system include computer systems security, secure electronic banking, mobile phones, credit cards, secure access to buildings, health and social services. By using biometrics a person could be identified based on 'who she/he is' rather than 'what she/he has' (card, token, key) or 'what she/he knows' (password, PIN). In this paper, a brief overview of biometric methods, both unimodal and multimodal and their advantages and disadvantages, will be presented.

Keywords: biometric, DNA, fingerprint, ear, face, retina scan, gait, iris, voice recognition, unimodal biometric, multimodal biometric

Procedia PDF Downloads 752

Authors: Wei Li, Tuo Yang

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In order to satisfy the real-time and accurate requirements of cigarette smoke detection in complex scenes, a cigarette smoke detection technology based on the combination of deep learning and color features was proposed. Firstly, based on the color features of cigarette smoke, the suspicious cigarette smoke area in the image is extracted. Secondly, combined with the efficiency of cigarette smoke detection and the problem of network overfitting, a network model for cigarette smoke detection was designed according to YOLOV3 algorithm to reduce the false detection rate. The experimental results show that the method is feasible and effective, and the accuracy of cigarette smoke detection is up to 99.13%, which satisfies the requirements of real-time cigarette smoke detection in complex scenes.

Keywords: deep learning, computer vision, cigarette smoke detection, YOLOV3, color feature extraction

Procedia PDF Downloads 84

Authors: Itti Bist, Snehasis Bhakta, Di Jiang, Tia E. Keyes, Aaron Martin, Robert J. Forster, James F. Rusling

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DNA damage from metabolites of lipophilic drugs and pollutants, generated by enzymes, represents a major toxicity pathway in humans. These metabolites can react with DNA to form either 8-oxo-7,8-dihydro-2-deoxyguanosine (8-oxodG), which is the oxidative product of DNA or covalent DNA adducts, both of which are genotoxic and hence considered important biomarkers to detect cancer in humans. Therefore, detecting reactions of metabolites with DNA is an effective approach for the safety assessment of new chemicals and drugs. Here we describe a novel electrochemiluminescent (ECL) sensor array which can detect DNA oxidation and chemical DNA damage in a single array, facilitating a more accurate diagnostic tool for genotoxicity screening. Layer-by-layer assembly of DNA and enzyme are assembled on the pyrolytic graphite array which is housed in a microfluidic device for sequential detection of two type of the DNA damages. Multiple enzyme reactions are run on test compounds using the array, generating toxic metabolites in situ. These metabolites react with DNA in the films to cause DNA oxidation and chemical DNA damage which are detected by ECL generating osmium compound and ruthenium polymer, respectively. The method is further validated by the formation of 8-oxodG and DNA adduct using similar films of DNA/enzyme on magnetic bead biocolloid reactors, hydrolyzing the DNA, and analyzing by liquid chromatography-mass spectrometry (LC-MS). Hence, this combined DNA/enzyme array/LC-MS approach can efficiently explore metabolic genotoxic pathways for drugs and environmental chemicals.

Keywords: biosensor, electrochemiluminescence, DNA damage, microfluidic array

Procedia PDF Downloads 365

Authors: Maha Jazouli

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Suicide is one of the most important causes of death in the prison environment, both in Canada and internationally. Rates of attempts of suicide and self-harm have been on the rise in recent years, with hangings being the most frequent method resorted to. The objective of this article is to propose a method to automatically detect in real time suicidal behaviors. We present a gesture recognition system that consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using machine learning algorithms (MLA). Our proposed system gives us satisfactory results. This smart video surveillance system can help assist staff responsible for the safety and health of inmates by alerting them when suicidal behavior is detected, which helps reduce mortality rates and save lives.

Keywords: suicide detection, Kinect azure, RGB-D camera, SVM, machine learning, gesture recognition

Procedia PDF Downloads 187

Authors: Bhupeshwaran Mani, S. Radha, A. Jawahar, A. Sivasubramanian

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Here, we study the characteristic feature of conventional (ON-OFF keying) and soliton based transmission system. We consider 20 Gbps transmission system implemented with Conventional Single Mode Fiber (C-SMF) to examine the role of Gaussian pulse which is the characteristic of conventional propagation and hyperbolic-secant pulse which is the characteristic of soliton propagation in it. We note the influence of these pulses with respect to different dispersion lengths and soliton period in conventional and soliton system, respectively, and evaluate the system performance in terms of quality factor. From the analysis, we could prove that the soliton pulse has more consistent performance even for long distance without dispersion compensation than the conventional system as it is robust to dispersion. For the length of transmission of 200 Km, soliton system yielded Q of 33.958 while the conventional system totally exhausted with Q=0.

Keywords: dispersion length, retrun-to-zero (rz), soliton, soliton period, q-factor

Procedia PDF Downloads 342

Authors: Arpit Patil, Atharav Bhagwat, Rajas Bhope, Pramod Bide

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This research integrates IoT and ML to predict heart failure risks, utilizing the Framingham dataset. IoT devices gather real-time physiological data, focusing on heart rate dynamics, while ML, specifically Random Forest, predicts heart failure. Rigorous feature selection enhances accuracy, achieving over 90% prediction rate. This amalgamation marks a transformative step in proactive healthcare, highlighting early detection's critical role in cardiovascular risk mitigation. Challenges persist, necessitating continual refinement for improved predictive capabilities.

Keywords: cardiovascular diseases, internet of things, machine learning, cardiac risk assessment, heart failure prediction, early detection, cardio data analysis

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Authors: Akram Hatami, Naser Firoozi, Vesa Puhakka

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Ethics and responsibility are rapidly becoming a distinguishing feature of organizations. In this paper, we analyze ethics and responsibility in shadow factories in China. We engage ourselves with Bauman’s moral impulse perspective because his idea can contextualize ethics and responsibility. Moral impulse is a feeling of a selfless, infinite and unconditional responsibility towards, and care for, Others. We analyze a case study from a secondary data source because, for such a critical phenomenon as business ethics in shadow factories, collecting primary data is difficult, since they are unregistered factories. We argue that there has not been enough attention given to the ethics and responsibility in shadow factories in China. Our main goal is to demonstrate that, considering the Other, more importantly the employees, in ethical decision-making is a simple instruction beyond the narrow version of ethics by ethical codes and rules.

Keywords: moral impulse, responsibility, shadow factories, Bauman’s moral impulse

Procedia PDF Downloads 327

Authors: Mohammed Alhammad

Abstract:

The movement towards the inclusion of students with special educational needs (SEN) in mainstream schools has become widely accepted practice in many countries. However in Saudi Arabia, this is not happening. Instead the practice for students with learning difficulties (LD) is to study in special classrooms in mainstream schools and they are not included with their peers, except at break times and morning assembly, and on school trips. There are a number of barriers that face implementing inclusion for students with LD in mainstream classrooms: one such barrier is the training of teachers. The training, either pre- or in-service, that teachers receive is seen as playing an important role in leading to the successful implementation of inclusion. The aim of this presentation is to explore how pre-service training and in-service training are acting as barriers for implementing inclusion of students with LD in mainstream primary schools in Saudi Arabia from the perspective of teachers. The qualitative research approach was used to explore this barrier. Twenty-four teachers (general education teachers, special education teachers) were interviewed using semi-structured interview and a number of documents were used as method of data collection. The result showed teachers felt that not much attention was paid to inclusion in pre-services training for general education teachers and special education teachers in Saudi Arabia. In addition, pre-service training for general education teachers does not normally including modules on special education. Regarding the in-service training, no courses at all about inclusion are provided for teachers. Furthermore, training courses in special education are few. As result, the knowledge and skills required to implemented inclusion successfully.

Keywords: inclusion, learning difficulties, Saudi Arabia, training

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Authors: Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Michel Dhome

Abstract:

In this paper, we handle the problem of real time localization and mapping in indoor environment assisted by a partial prior 3D model, using an RGBD sensor. The proposed solution relies on a feature-based RGBD SLAM algorithm to localize the camera and update the 3D map of the scene. To improve the accuracy and the robustness of the localization, we propose to combine in a local bundle adjustment process, geometric information provided by a prior coarse 3D model of the scene (e.g. generated from the 2D floor plan of the building) along with RGBD data from a Kinect camera. The proposed approach is evaluated on a public benchmark dataset as well as on real scene acquired by a Kinect sensor.

Keywords: SLAM, global localization, 3D sensor, bundle adjustment, 3D model

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