Search results for: thin layer chromatography-flame ionization detection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 6529

Search results for: thin layer chromatography-flame ionization detection

5719 Vibration Characteristics of Functionally Graded Thick Hollow Cylinders Using Galerkin Method

Authors: Pejman Daryabor, Kamal Mohammadi

Abstract:

In the present work, the study of vibration characteristics of a functionally graded thick hollow cylinder is investigated. The cylinder natural frequencies are obtained using Galerkin finite element method. The functionally graded cylinder is assumed to be made from many subcylinders. Each subcylinder is considered as an isotropic layer. Material’s properties in each layer are constant and functionally graded properties result by exponential function of layer radius in multilayer cylinder. To validate the FE results code, plane strain model of functionally graded cylinder are also modeled in ABAQUS. Analytical results are validated for both models. Also, a good agreement is found between the present results and those reported in the literature.

Keywords: natural frequency, functionally graded material, finite element method, thick cylinder

Procedia PDF Downloads 454
5718 Determination of Phytostearol in Serial Grains

Authors: Sumonthip Kongtun Janphuk

Abstract:

Ten cereal grains that usually used as ingredients in healthy products were studied for phytosteryl glucoside contents. β-sitosteryl glucoside in 10 cereal grains, including Phasecolus vulgaris L. (kidney bean), Sorghum bicolor (sorghum), Moringa oleifera Lam. (drumstick), Nelumbo nucifera (lotus), Vigna radiate L. (mung bean), Coix lacrymajobi (job’tears), Oryza sativa. (red rice), Glycine max L. Merrill. (soybean),Cucurbita maschata Decne (pumpkin) and Helianthas annuus (sunflower seeds), were analyzed using Thin-layer chromatography (TLC) and High-Performance liquid chromatography (HPLC). All grains were extracted with methanol before analysis. Red bean showed the maximum phytosteryl glucoside content of 0.42% w/w. The content of others were as follows: pumpkin seed 0.173%, mung bean 0.099 %, soybean 0.07%, dried moringa seed 0.067%, lotus seed 0.044%, sorghum 0.032%, sunflower seed 0.016%, Job's tears 0.012%, and brown rice 0.006%.

Keywords: cereal grains, phytosterol, β-sitosteryl glucoside, food analysis.

Procedia PDF Downloads 365
5717 A Review of Intelligent Fire Management Systems to Reduce Wildfires

Authors: Nomfundo Ngombane, Topside E. Mathonsi

Abstract:

Remote sensing and satellite imaging have been widely used to detect wildfires; nevertheless, the technologies present some limitations in terms of early wildfire detection as the technologies are greatly influenced by weather conditions and can miss small fires. The fires need to have spread a few kilometers for the technologies to provide accurate detection. The South African Advanced Fire Information System uses MODIS (Moderate Resolution Imaging Spectroradiometer) as satellite imaging. MODIS has limitations as it can exclude small fires and can fall short in validating fire vulnerability. Thus in the future, a Machine Learning algorithm will be designed and implemented for the early detection of wildfires. A simulator will be used to evaluate the effectiveness of the proposed solution, and the results of the simulation will be presented.

Keywords: moderate resolution imaging spectroradiometer, advanced fire information system, machine learning algorithm, detection of wildfires

Procedia PDF Downloads 65
5716 Facility Detection from Image Using Mathematical Morphology

Authors: In-Geun Lim, Sung-Woong Ra

Abstract:

As high resolution satellite images can be used, lots of studies are carried out for exploiting these images in various fields. This paper proposes the method based on mathematical morphology for extracting the ‘horse's hoof shaped object’. This proposed method can make an automatic object detection system to track the meaningful object in a large satellite image rapidly. Mathematical morphology process can apply in binary image, so this method is very simple. Therefore this method can easily extract the ‘horse's hoof shaped object’ from any images which have indistinct edges of the tracking object and have different image qualities depending on filming location, filming time, and filming environment. Using the proposed method by which ‘horse's hoof shaped object’ can be rapidly extracted, the performance of the automatic object detection system can be improved dramatically.

Keywords: facility detection, satellite image, object, mathematical morphology

Procedia PDF Downloads 361
5715 X-Corner Detection for Camera Calibration Using Saddle Points

Authors: Abdulrahman S. Alturki, John S. Loomis

Abstract:

This paper discusses a corner detection algorithm for camera calibration. Calibration is a necessary step in many computer vision and image processing applications. Robust corner detection for an image of a checkerboard is required to determine intrinsic and extrinsic parameters. In this paper, an algorithm for fully automatic and robust X-corner detection is presented. Checkerboard corner points are automatically found in each image without user interaction or any prior information regarding the number of rows or columns. The approach represents each X-corner with a quadratic fitting function. Using the fact that the X-corners are saddle points, the coefficients in the fitting function are used to identify each corner location. The automation of this process greatly simplifies calibration. Our method is robust against noise and different camera orientations. Experimental analysis shows the accuracy of our method using actual images acquired at different camera locations and orientations.

Keywords: camera calibration, corner detector, edge detector, saddle points

Procedia PDF Downloads 387
5714 Analysis of Facial Expressions with Amazon Rekognition

Authors: Kashika P. H.

Abstract:

The development of computer vision systems has been greatly aided by the efficient and precise detection of images and videos. Although the ability to recognize and comprehend images is a strength of the human brain, employing technology to tackle this issue is exceedingly challenging. In the past few years, the use of Deep Learning algorithms to treat object detection has dramatically expanded. One of the key issues in the realm of image recognition is the recognition and detection of certain notable people from randomly acquired photographs. Face recognition uses a way to identify, assess, and compare faces for a variety of purposes, including user identification, user counting, and classification. With the aid of an accessible deep learning-based API, this article intends to recognize various faces of people and their facial descriptors more accurately. The purpose of this study is to locate suitable individuals and deliver accurate information about them by using the Amazon Rekognition system to identify a specific human from a vast image dataset. We have chosen the Amazon Rekognition system, which allows for more accurate face analysis, face comparison, and face search, to tackle this difficulty.

Keywords: Amazon rekognition, API, deep learning, computer vision, face detection, text detection

Procedia PDF Downloads 87
5713 Improving Lane Detection for Autonomous Vehicles Using Deep Transfer Learning

Authors: Richard O’Riordan, Saritha Unnikrishnan

Abstract:

Autonomous Vehicles (AVs) are incorporating an increasing number of ADAS features, including automated lane-keeping systems. In recent years, many research papers into lane detection algorithms have been published, varying from computer vision techniques to deep learning methods. The transition from lower levels of autonomy defined in the SAE framework and the progression to higher autonomy levels requires increasingly complex models and algorithms that must be highly reliable in their operation and functionality capacities. Furthermore, these algorithms have no room for error when operating at high levels of autonomy. Although the current research details existing computer vision and deep learning algorithms and their methodologies and individual results, the research also details challenges faced by the algorithms and the resources needed to operate, along with shortcomings experienced during their detection of lanes in certain weather and lighting conditions. This paper will explore these shortcomings and attempt to implement a lane detection algorithm that could be used to achieve improvements in AV lane detection systems. This paper uses a pre-trained LaneNet model to detect lane or non-lane pixels using binary segmentation as the base detection method using an existing dataset BDD100k followed by a custom dataset generated locally. The selected roads will be modern well-laid roads with up-to-date infrastructure and lane markings, while the second road network will be an older road with infrastructure and lane markings reflecting the road network's age. The performance of the proposed method will be evaluated on the custom dataset to compare its performance to the BDD100k dataset. In summary, this paper will use Transfer Learning to provide a fast and robust lane detection algorithm that can handle various road conditions and provide accurate lane detection.

Keywords: ADAS, autonomous vehicles, deep learning, LaneNet, lane detection

Procedia PDF Downloads 79
5712 Design of Photonic Crystal with Defect Layer to Eliminate Interface Corrugations for Obtaining Unidirectional and Bidirectional Beam Splitting under Normal Incidence

Authors: Evrim Colak, Andriy E. Serebryannikov, Pavel V. Usik, Ekmel Ozbay

Abstract:

Working with a dielectric photonic crystal (PC) structure which does not include surface corrugations, unidirectional transmission and dual-beam splitting are observed under normal incidence as a result of the strong diffractions caused by the embedded defect layer. The defect layer has twice the period of the regular PC segments which sandwich the defect layer. Although the PC has even number of rows, the structural symmetry is broken due to the asymmetric placement of the defect layer with respect to the symmetry axis of the regular PC. The simulations verify that efficient splitting and occurrence of strong diffractions are related to the dispersion properties of the Floquet-Bloch modes of the photonic crystal. Unidirectional and bi-directional splitting, which are associated with asymmetric transmission, arise due to the dominant contribution of the first positive and first negative diffraction orders. The effect of the depth of the defect layer is examined by placing single defect layer in varying rows, preserving the asymmetry of PC. Even for deeply buried defect layer, asymmetric transmission is still valid even if the zeroth order is not coupled. This transmission is due to evanescent waves which reach to the deeply embedded defect layer and couple to higher order modes. In an additional selected performance, whichever surface is illuminated, i.e., in both upper and lower surface illumination cases, incident beam is split into two beams of equal intensity at the output surface where the intensity of the out-going beams are equal for both illumination cases. That is, although the structure is asymmetric, symmetric bidirectional transmission with equal transmission values is demonstrated and the structure mimics the behavior of symmetric structures. Finally, simulation studies including the examination of a coupled-cavity defect for two different permittivity values (close to the permittivity values of GaAs or Si and alumina) reveal unidirectional splitting for a wider band of operation in comparison to the bandwidth obtained in the case of a single embedded defect layer. Since the dielectric materials that are utilized are low-loss and weakly dispersive in a wide frequency range including microwave and optical frequencies, the studied structures should be scalable to the mentioned ranges.

Keywords: asymmetric transmission, beam deflection, blazing, bi-directional splitting, defect layer, dual beam splitting, Floquet-Bloch modes, isofrequency contours, line defect, oblique incidence, photonic crystal, unidirectionality

Procedia PDF Downloads 170
5711 BodeACD: Buffer Overflow Vulnerabilities Detecting Based on Abstract Syntax Tree, Control Flow Graph, and Data Dependency Graph

Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

Abstract:

As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

Procedia PDF Downloads 150
5710 Manufacturing Anomaly Detection Using a Combination of Gated Recurrent Unit Network and Random Forest Algorithm

Authors: Atinkut Atinafu Yilma, Eyob Messele Sefene

Abstract:

Anomaly detection is one of the essential mechanisms to control and reduce production loss, especially in today's smart manufacturing. Quick anomaly detection aids in reducing the cost of production by minimizing the possibility of producing defective products. However, developing an anomaly detection model that can rapidly detect a production change is challenging. This paper proposes Gated Recurrent Unit (GRU) combined with Random Forest (RF) to detect anomalies in the production process in real-time quickly. The GRU is used as a feature detector, and RF as a classifier using the input features from GRU. The model was tested using various synthesis and real-world datasets against benchmark methods. The results show that the proposed GRU-RF outperforms the benchmark methods with the shortest time taken to detect anomalies in the production process. Based on the investigation from the study, this proposed model can eliminate or reduce unnecessary production costs and bring a competitive advantage to manufacturing industries.

Keywords: anomaly detection, multivariate time series data, smart manufacturing, gated recurrent unit network, random forest

Procedia PDF Downloads 87
5709 Using Bidirectional Encoder Representations from Transformers to Extract Topic-Independent Sentiment Features for Social Media Bot Detection

Authors: Maryam Heidari, James H. Jones Jr.

Abstract:

Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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5708 Plate-Laminated Slotted-Waveguide Fed 2×3 Planar Inverted F Antenna Array

Authors: Badar Muneer, Waseem Shabir, Faisal Karim Shaikh

Abstract:

Substrate Integrated waveguide based 6-element array of Planar Inverted F antenna (PIFA) has been presented and analyzed parametrically in this paper. The antenna is fed with coupled transverse slots on a plate laminated waveguide cavity to ensure wide bandwidth and simplicity of feeding network. The two-layer structure has one layer dedicated for feeding network and the top layer dedicated for radiating elements. It has been demonstrated that the presented feeding technique for feeding such class of array antennas can be far simple in structure and miniaturized in size when it comes to designing large phased array antenna systems. A good return loss and standing wave ratio of 2:1 has been achieved while maintaining properties of typical PIFA.

Keywords: feeding network, laminated waveguide, PIFA, transverse slots

Procedia PDF Downloads 288
5707 A Variable Structural Control for a Flexible Lamina

Authors: Xuezhang Hou

Abstract:

A control problem of a flexible Lamina formulated by partial differential equations with viscoelastic boundary conditions is studied in this paper. The problem is written in standard form of linear infinite dimensional system in an appropriate energy Hilbert space. The semigroup approach of linear operators is adopted in investigating wellposedness of the closed loop system. A variable structural control for the system is proposed, and meanwhile an equivalent control method is applied to the thin plate system. A significant result on control theory that the thin plate can be approximated by ideal sliding mode in any accuracy in terms of semigroup approach is obtained.

Keywords: partial differential equations, flexible lamina, variable structural control, semigroup of linear operators

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5706 Highly Responsive p-NiO/n-rGO Heterojunction Based Self-Powered UV Photodetectors

Authors: P. Joshna, Souvik Kundu

Abstract:

Detection of ultraviolet (UV) radiation is very important as it has exhibited a profound influence on humankind and other existences, including military equipment. In this work, a self-powered UV photodetector was reported based on oxides heterojunctions. The thin films of p-type nickel oxide (NiO) and n-type reduced graphene oxide (rGO) were used for the formation of p-n heterojunction. Low-Cost and low-temperature chemical synthesis was utilized to prepare the oxides, and the spin coating technique was employed to deposit those onto indium doped tin oxide (ITO) coated glass substrates. The top electrode platinum was deposited utilizing physical vapor evaporation technique. NiO offers strong UV absorption with high hole mobility, and rGO prevents the recombination rate by separating electrons out from the photogenerated carriers. Several structural characterizations such as x-ray diffraction, atomic force microscope, scanning electron microscope were used to study the materials crystallinity, microstructures, and surface roughness. On one side, the oxides were found to be polycrystalline in nature, and no secondary phases were present. On the other side, surface roughness was found to be low with no pit holes, which depicts the formation of high-quality oxides thin films. Whereas, x-ray photoelectron spectroscopy was employed to study the chemical compositions and oxidation structures. The electrical characterizations such as current-voltage and current response were also performed on the device to determine the responsivity, detectivity, and external quantum efficiency under dark and UV illumination. This p-n heterojunction device offered faster photoresponse and high on-off ratio under 365 nm UV light illumination of zero bias. The device based on the proposed architecture shows the efficacy of the oxides heterojunction for efficient UV photodetection under zero bias, which opens up a new path towards the development of self-powered photodetector for environment and health monitoring sector.

Keywords: chemical synthesis, oxides, photodetectors, spin coating

Procedia PDF Downloads 107
5705 Fully Eulerian Finite Element Methodology for the Numerical Modeling of the Dynamics of Heart Valves

Authors: Aymen Laadhari

Abstract:

During the last decade, an increasing number of contributions have been made in the fields of scientific computing and numerical methodologies applied to the study of the hemodynamics in the heart. In contrast, the numerical aspects concerning the interaction of pulsatile blood flow with highly deformable thin leaflets have been much less explored. This coupled problem remains extremely challenging and numerical difficulties include e.g. the resolution of full Fluid-Structure Interaction problem with large deformations of extremely thin leaflets, substantial mesh deformations, high transvalvular pressure discontinuities, contact between leaflets. Although the Lagrangian description of the structural motion and strain measures is naturally used, many numerical complexities can arise when studying large deformations of thin structures. Eulerian approaches represent a promising alternative to readily model large deformations and handle contact issues. We present a fully Eulerian finite element methodology tailored for the simulation of pulsatile blood flow in the aorta and sinus of Valsalva interacting with highly deformable thin leaflets. Our method enables to use a fluid solver on a fixed mesh, whilst being able to easily model the mechanical properties of the valve. We introduce a semi-implicit time integration scheme based on a consistent NewtonRaphson linearization. A variant of the classical Newton method is introduced and guarantees a third-order convergence. High-fidelity computational geometries are built and simulations are performed under physiological conditions. We address in detail the main features of the proposed method, and we report several experiments with the aim of illustrating its accuracy and efficiency.

Keywords: eulerian, level set, newton, valve

Procedia PDF Downloads 259
5704 The Role of Poling Protocol on Augmentation of Magnetoelectricity in BCZT/NZFO Layered Composites

Authors: Pankhuri Bansal, Sanjeev Kumar

Abstract:

We examined the exotic role of electrical poling of layered BCZT-NZFO bulk composite for sustainable advancement of magnetoelectric (ME) technology. Practically, it seems quite difficult to access the full potential of ME composites due to their weak ME coupling performances. Using a standard poling protocol, we successfully deployed the coupling performance of laminated ME composite, comprised of a ferroelectric (FE) layer of BCZT and a ferrite layer of NZFO. However, the ME coupling constant of laminated composite is optimized by lowering the volume fraction of the FE component to strengthen the mechanical strain in the piezoelectric layer while fixing the thickness of the magnetostrictive ferrite layer. Here, we employed systematic zero field cooled (ZFC) and field cooled (FC) electrical poling protocol on morphotropic phase boundary (MPB) based BCZT composition, well-appreciated for it’s remarkable electromechanical activity. We report a record augmentation in magnetoelectric coupling as a consequence of a prudent field-cooled poling mechanism. On the basis of our findings, we emphasize that the degree of magnetoelectricity may be significantly improved for the miniaturization of efficient devices via proper execution of the poling technique.

Keywords: magnetoelectric, lead-free, ferroelctric, ferromagnetic, energy harvesting

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5703 Controlling the Surface Morphology of the Biocompatible Hydroxyapatite Layer Deposited by Using a Flame-Coating

Authors: Nabaa M. Abdul Rahim, Mohammed A.Kadhim, Fadhil K. Fuliful

Abstract:

A biocompatible layer is prepared from calcium phosphate, which plays a role in building damaged bones and is used in many applications. In this research, calcium phosphate is coated on stainless steel substrates (SS 316) by using the flame coating. FE-SEM images show that the behavior of the sample surfaces varies with distance, at 3cm, appeared with nanostructures of bumps shaped of diameter about 317 nm. The contents of the elements are analyzed by energy-dispersive X-ray spectroscopy (EDX). The chemical elements C, Ca, Fe, Ni, Cr, Mn and O corresponding to calcium phosphate and the alloy are revealed by EDX analysis of the coating layer. XRD patterns for the calcium phosphate layers indicate the formation of the Hap layer on the deposited layers. The samples are immersed in a solution of simulated body fluids (SBF) for 21 days to examine the biocompatibility, as the tests show that the calcium phosphate ratio of 1.65 is the appropriate and biocompatible ratio in the human body. The assays show antibacterial activity using the diffusion disk procedure. On the surface of the agar, observed infested E.coli bacteria and incubated for 24 hours at 37°C. Bacteria grow on the entire agar rather than in some areas around some samples at a distance of 3 cm from the flame hole.

Keywords: biomaterial, flame coating, antibacterial activity, stainless steel

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5702 Determination of the Inhibitory Effects of N-Methylpyrrole Derivatives on Glutathione Reductase Enzyme

Authors: Esma Kocaoglu, Oktay Talaz, Huseyin Cavdar, Murat Senturk, Deniz Eki̇nci̇

Abstract:

Glutathione reductase (GR) is a crucial antioxidant enzyme which is responsible for the maintenance of the antioxidant GSH (glutathione) molecule. Antimalarial effects of some chemical molecules are attributed to their inhibition of GR; thus inhibitors of this enzyme are expected to be promising candidates for the treatment of malaria. In this work, GR inhibitory properties of N-Methylpyrrole derivatives are reported. Firstly, GR was purified by means of affinity chromatography using 2’,5’-ADP-Sepharose 4B as ligand. Enzymatic activity was measured by Beutler’s method. Synthesis of the compounds was approved by thin layer chromatography and column chromatography. Different inhibitor concentrations were used and all compounds were tested in triplicate at each concentration used. It was found that all compounds have better inhibitory activity than the strong GR inhibitor N,N-bis(2-chloroethyl)-N-nitrosourea, especially three molecules, 8m, 8n, and 8q, are the best among them with low micromolar I₅₀ values. Findings of our study indicate that these Schiff base derivatives are strong GR inhibitors which can be used as leads for designation of novel antimalaria candidates.

Keywords: glutathione reductase, antimalaria, inhibitor, enzyme

Procedia PDF Downloads 251
5701 Evaluation of DNA Oxidation and Chemical DNA Damage Using Electrochemiluminescent Enzyme/DNA Microfluidic Array

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

Abstract:

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 342
5700 TiO2/PDMS Coating With Minimum Solar Absorption Loss for Passive Daytime Radiative Cooling

Authors: Bhrigu Rishi Mishra, Sreerag Sundaram, Nithin Jo Varghese, Karthik Sasihithlu

Abstract:

We have designed a TiO2/PDMS coating with 94% solar reflection, 96% IR emission, and 81.8 W/m2 cooling power for passive daytime radiative cooling using Kubelka Munk theory and CST microwave studio. To reduce solar absorption loss in 0.3-0.39 m wavelength region, a TiO2 thin film on top of the coating is used. Simulation using Ansys Lumerical shows that for a 20 m thick TiO2/PDMS coating, a TiO2 thin film of 84 nm increases the coating's reflectivity by 11% in the solar region.

Keywords: passive daytime radiative cooling, disordered metamaterial, Kudelka Munk theory, solar reflectivity

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5699 An Energy Detection-Based Algorithm for Cooperative Spectrum Sensing in Rayleigh Fading Channel

Authors: H. Bakhshi, E. Khayyamian

Abstract:

Cognitive radios have been recognized as one of the most promising technologies dealing with the scarcity of the radio spectrum. In cognitive radio systems, secondary users are allowed to utilize the frequency bands of primary users when the bands are idle. Hence, how to accurately detect the idle frequency bands has attracted many researchers’ interest. Detection performance is sensitive toward noise power and gain fluctuation. Since signal to noise ratio (SNR) between primary user and secondary users are not the same and change over the time, SNR and noise power estimation is essential. In this paper, we present a cooperative spectrum sensing algorithm using SNR estimation to improve detection performance in the real situation.

Keywords: cognitive radio, cooperative spectrum sensing, energy detection, SNR estimation, spectrum sensing, rayleigh fading channel

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5698 Possibility of Creating Polygon Layers from Raster Layers Obtained by using Classic Image Processing Software: Case of Geological Map of Rwanda

Authors: Louis Nahimana

Abstract:

Most maps are in a raster or pdf format and it is not easy to get vector layers of published maps. Faced to the production of geological simplified map of the northern Lake Tanganyika countries without geological information in vector format, I tried a method of obtaining vector layers from raster layers created from geological maps of Rwanda and DR Congo in pdf and jpg format. The procedure was as follows: The original raster maps were georeferenced using ArcGIS10.2. Under Adobe Photoshop, map areas with the same color corresponding to a lithostratigraphic unit were selected all over the map and saved in a specific raster layer. Using the same image processing software Adobe Photoshop, each RGB raster layer was converted in grayscale type and improved before importation in ArcGIS10. After georeferencing, each lithostratigraphic raster layer was transformed into a multitude of polygons with the tool "Raster to Polygon (Conversion)". Thereafter, tool "Aggregate Polygons (Cartography)" allowed obtaining a single polygon layer. Repeating the same steps for each color corresponding to a homogeneous rock unit, it was possible to reconstruct the simplified geological constitution of Rwanda and the Democratic Republic of Congo in vector format. By using the tool «Append (Management)», vector layers obtained were combined with those from Burundi to achieve vector layers of the geology of the « Northern Lake Tanganyika countries ».

Keywords: creating raster layer under image processing software, raster to polygon, aggregate polygons, adobe photoshop

Procedia PDF Downloads 425
5697 Structural Determination of Nanocrystalline Si Films Using Raman Spectroscopy and the Ellipsometry

Authors: K. Kefif, Y. Bouizem, A. Belfedal, D. J. Sib, K. Zellama, l. Chahed

Abstract:

Hydrogenated microcrystalline silicon (μc-Si:H) thin films were prepared by radio frequency magnetron sputtering at relatively low growth temperatures (Ts=100 °C). The films grown on glass substrate in order to use the new generation of substrates sensitive to elevated temperatures. Raman spectroscopy was applied to investigate the effect of the argon gas diluted in hydrogen, on the structural properties and the evolution of the micro structure in the films. Raman peak position, intensity and line width were used to characterize the quality and the percentage of the crystallites in the films. The results of this investigation suggest the existence of a threshold dilution around a gas mixture of argon (40%) and hydrogen (60%) for which the crystallization occurs, even at low deposition temperatures. The difference between the amorphous and the crystallized structures is well confirmed by spectroscopic ellipsometry (SE) technique.

Keywords: Silicon, Thin films, Structural properties, Raman spectroscopy, Ellipsometry

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5696 Data-Centric Anomaly Detection with Diffusion Models

Authors: Sheldon Liu, Gordon Wang, Lei Liu, Xuefeng Liu

Abstract:

Anomaly detection, also referred to as one-class classification, plays a crucial role in identifying product images that deviate from the expected distribution. This study introduces Data-centric Anomaly Detection with Diffusion Models (DCADDM), presenting a systematic strategy for data collection and further diversifying the data with image generation via diffusion models. The algorithm addresses data collection challenges in real-world scenarios and points toward data augmentation with the integration of generative AI capabilities. The paper explores the generation of normal images using diffusion models. The experiments demonstrate that with 30% of the original normal image size, modeling in an unsupervised setting with state-of-the-art approaches can achieve equivalent performances. With the addition of generated images via diffusion models (10% equivalence of the original dataset size), the proposed algorithm achieves better or equivalent anomaly localization performance.

Keywords: diffusion models, anomaly detection, data-centric, generative AI

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5695 2,7-Diazaindole as a Photophysical Probe for Excited State Hydrogen/Proton Transfer

Authors: Simran Baweja, Bhavika Kalal, Surajit Maity

Abstract:

Photoinduced tautomerization reactions have been the centre of attention among the scientific community over the past several decades because of their significance in various biological systems. 7-azaindole (7AI) is considered a model system for DNA base pairing and to understand the role of such tautomerization reactions in mutations. To the best of our knowledge, extensive studies have been carried out on 7-azaindole and its solvent clusters exhibiting proton/ hydrogen transfer in both solution as well as gas phases. Derivatives of the above molecule, like 2,7- and 2,6-diazaindoles are proposed to have even better photophysical properties due to the presence of -aza group on the 2nd position. However, there are studies in the solution phase that suggest the relevance of these molecules, but there are no experimental studies reported in the gas phase yet. In our current investigation, we present the first gas phase spectroscopic data of 2,7-diazaindole (2,7-DAI) and its solvent cluster (2,7-DAI-H2O). In this, we have employed state-of-the-art laser spectroscopic methods such as fluorescence excitation (LIF), dispersed fluorescence (DF), resonant two-photon ionization-time of flight mass spectrometry (2C-R2PI), photoionization efficiency spectroscopy (PIE), IR-UV double resonance spectroscopy, i.e., fluorescence-dip infrared spectroscopy (FDIR) and resonant ion-dip infrared spectroscopy (IDIR) to understand the electronic structure of the molecule. The origin band corresponding to the S1 ← S0 transition of the bare 2,7-DAI is found to be positioned at 33910 cm-1, whereas the origin band corresponding to S1 ← S0 transition of the 2,7-DAI-H2O is positioned at 33074 cm-1. The red-shifted transition in the case of solvent cluster suggests the enhanced feasibility of excited state hydrogen/ proton transfer. The ionization potential for the 2,7-DAI molecule is found to be 8.92 eV which is significantly higher than the previously reported 7AI (8.11 eV) molecule, making it a comparatively complex molecule to study. The ionization potential is reduced by 0.14 eV in the case of 2,7-DAI-H2O (8.78 eV) cluster compared to that of 2,7-DAI. Moreover, on comparison with the available literature values of 7AI, we found the origin band of 2,7-DAI and 2,7-DAI-H2O to be red-shifted by -729 and -280 cm-1 respectively. The ground and excited state N-H stretching frequencies of the 27DAI molecule were determined using fluorescence-dip infrared spectra (FDIR) and resonant ion dip infrared spectroscopy (IDIR), obtained at 3523 and 3467 cm-1, respectively. The lower value of vNH in the electronically excited state of 27DAI implies the higher acidity of the group compared to the ground state. Moreover, we have done extensive computational analysis, which suggests that the energy barrier in the excited state reduces significantly as we increase the number of catalytic solvent molecules (S= H2O, NH3) as well as the polarity of solvent molecules. We found that the ammonia molecule is a better candidate for hydrogen transfer compared to water because of its higher gas-phase basicity. Further studies are underway to understand the excited state dynamics and photochemistry of such N-rich chromophores.

Keywords: excited state hydrogen transfer, supersonic expansion, gas phase spectroscopy, IR-UV double resonance spectroscopy, laser induced fluorescence, photoionization efficiency spectroscopy

Procedia PDF Downloads 53
5694 Adaptive Target Detection of High-Range-Resolution Radar in Non-Gaussian Clutter

Authors: Lina Pan

Abstract:

In non-Gaussian clutter of a spherically invariant random vector, in the cases that a certain estimated covariance matrix could become singular, the adaptive target detection of high-range-resolution radar is addressed. Firstly, the restricted maximum likelihood (RML) estimates of unknown covariance matrix and scatterer amplitudes are derived for non-Gaussian clutter. And then the RML estimate of texture is obtained. Finally, a novel detector is devised. It is showed that, without secondary data, the proposed detector outperforms the existing Kelly binary integrator.

Keywords: non-Gaussian clutter, covariance matrix estimation, target detection, maximum likelihood

Procedia PDF Downloads 447
5693 Forced Convection Boundary Layer Flow of a Casson Fluid over a Moving Permeable Flat Plate beneath a Uniform Free Stream

Authors: N. M. Arifin, S. P. M. Isa, R. Nazar, N. Bachok, F. M. Ali, I. Pop

Abstract:

In this paper, the steady forced convection boundary layer flow of a Casson fluid past a moving permeable semi-infinite flat plate beneath a uniform free stream is investigated. The mathematical problem reduces to a pair of noncoupled ordinary differential equations by similarity transformation, which is then solved numerically using the shooting method. Both the cases when the plate moves into or out of the origin are considered. Effects of the non-Newtonian (Casson) parameter, moving parameter, suction or injection parameter and Eckert number on the flow and heat transfer characteristics are thoroughly examined. Dual solutions are found to exist for each value of the governing parameters.

Keywords: forced convection, Casson fluids, moving flat plate, boundary layer

Procedia PDF Downloads 438
5692 USBware: A Trusted and Multidisciplinary Framework for Enhanced Detection of USB-Based Attacks

Authors: Nir Nissim, Ran Yahalom, Tomer Lancewiki, Yuval Elovici, Boaz Lerner

Abstract:

Background: Attackers increasingly take advantage of innocent users who tend to use USB devices casually, assuming these devices benign when in fact they may carry an embedded malicious behavior or hidden malware. USB devices have many properties and capabilities that have become the subject of malicious operations. Many of the recent attacks targeting individuals, and especially organizations, utilize popular and widely used USB devices, such as mice, keyboards, flash drives, printers, and smartphones. However, current detection tools, techniques, and solutions generally fail to detect both the known and unknown attacks launched via USB devices. Significance: We propose USBWARE, a project that focuses on the vulnerabilities of USB devices and centers on the development of a comprehensive detection framework that relies upon a crucial attack repository. USBWARE will allow researchers and companies to better understand the vulnerabilities and attacks associated with USB devices as well as providing a comprehensive platform for developing detection solutions. Methodology: The framework of USBWARE is aimed at accurate detection of both known and unknown USB-based attacks by a process that efficiently enhances the framework's detection capabilities over time. The framework will integrate two main security approaches in order to enhance the detection of USB-based attacks associated with a variety of USB devices. The first approach is aimed at the detection of known attacks and their variants, whereas the second approach focuses on the detection of unknown attacks. USBWARE will consist of six independent but complimentary detection modules, each detecting attacks based on a different approach or discipline. These modules include novel ideas and algorithms inspired from or already developed within our team's domains of expertise, including cyber security, electrical and signal processing, machine learning, and computational biology. The establishment and maintenance of the USBWARE’s dynamic and up-to-date attack repository will strengthen the capabilities of the USBWARE detection framework. The attack repository’s infrastructure will enable researchers to record, document, create, and simulate existing and new USB-based attacks. This data will be used to maintain the detection framework’s updatability by incorporating knowledge regarding new attacks. Based on our experience in the cyber security domain, we aim to design the USBWARE framework so that it will have several characteristics that are crucial for this type of cyber-security detection solution. Specifically, the USBWARE framework should be: Novel, Multidisciplinary, Trusted, Lightweight, Extendable, Modular and Updatable and Adaptable. Major Findings: Based on our initial survey, we have already found more than 23 types of USB-based attacks, divided into six major categories. Our preliminary evaluation and proof of concepts showed that our detection modules can be used for efficient detection of several basic known USB attacks. Further research, development, and enhancements are required so that USBWARE will be capable to cover all of the major known USB attacks and to detect unknown attacks. Conclusion: USBWARE is a crucial detection framework that must be further enhanced and developed.

Keywords: USB, device, cyber security, attack, detection

Procedia PDF Downloads 376
5691 A Study on Implementation of Optimal Soldering Temperature Profile through Deformation Analysisin Infrared Lamp Soldering of Photovoltaic Cells

Authors: Taejung Lho, Jonghwan Lee

Abstract:

Most of the photovoltaic (PV) module manufacturers have recently interested in reducing the manufacturing cost. One of available solution is the use of the thin photovoltaic cell because of reducing of raw material cost. Thin PV cells, however, are damaged large deformation which causes possible microcracks inside PV cell, leading to failure problem. In this paper, deformation characteristics by heat conduction in soldering process of PV cells are analyzed through ANSYS software tool. They have been tested for different PV cell thickness and soldering temperature profile. Accordingly optimal soldering process to minimize the deformation of PV cell has been suggested.

Keywords: photovoltaic (PV) cell, infrared(IR) lamp soldering, optimal soldering temperature profile, deformation, temperature distribution, 3D scanner, ANSYS

Procedia PDF Downloads 385
5690 Fully Printed Strain Gauges: A Comparison of Aerosoljet-Printing and Micropipette-Dispensing

Authors: Benjamin Panreck, Manfred Hild

Abstract:

Strain sensors based on a change in resistance are well established for the measurement of forces, stresses, or material fatigue. Within the scope of this paper, fully additive manufactured strain sensors were produced using an ink of silver nanoparticles. Their behavior was evaluated by periodic tensile tests. Printed strain sensors exhibit two advantages: Their measuring grid is adaptable to the use case and they do not need a carrier-foil, as the measuring structure can be printed directly onto a thin sprayed varnish layer on the aluminum specimen. In order to compare quality characteristics, the sensors have been manufactured using two different technologies, namely aerosoljet-printing and micropipette-dispensing. Both processes produce structures which exhibit continuous features (in contrast to what can be achieved with droplets during inkjet printing). Briefly summarized the results show that aerosoljet-printing is the preferable technology for specimen with non-planar surfaces whereas both technologies are suitable for flat specimen.

Keywords: aerosoljet-printing, micropipette-dispensing, printed electronics, printed sensors, strain gauge

Procedia PDF Downloads 185