Search results for: particle detection

Authors: R. Z. Wang, B. C. Lin, C. H. Huang

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This study proposes a new method to simulate the crack propagation under mode-I loading using Vector Form Intrinsic Finite Element (VFIFE) method. A new idea which is expected to combine both VFIFE and J-integral is proposed to calculate the stress density factor as the crack critical in elastic crack. The procedure of implement the cohesive crack propagation in VFIFE based on the fictitious crack model is also proposed. In VFIFIE, the structure deformation is described by numbers of particles instead of elements. The strain energy density and the derivatives of the displacement vector of every particle is introduced to calculate the J-integral as the integral path is discrete by particles. The particle on the crack tip separated into two particles once the stress on the crack tip satisfied with the crack critical and then the crack tip propagates to the next particle. The internal force and the cohesive force is applied to the particles.

Keywords: VFIFE, crack propagation, fictitious crack model, crack critical

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Authors: K. E. Ch. Vidyasagar, M. Moghavvemi, T. S. S. T. Prabhat

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Epilepsy is a global problem, and with seizures eluding even the smartest of diagnoses a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Among a multitude of methods for automatic epilepsy detection, one should find the best method out, based on accuracy, for classification. This paper reasons out, and rationalizes, the best methods for classification. Accuracy is based on the classifier, and thus this paper discusses classifiers like quadratic discriminant analysis (QDA), classification and regression tree (CART), support vector machine (SVM), naive Bayes classifier (NBC), linear discriminant analysis (LDA), K-nearest neighbor (KNN) and artificial neural networks (ANN). Results show that ANN is the most accurate of all the above stated classifiers with 97.7% accuracy, 97.25% specificity and 98.28% sensitivity in its merit. This is followed closely by SVM with 1% variation in result. These results would certainly help researchers choose the best classifier for detection of epilepsy.

Keywords: classification, seizure, KNN, SVM, LDA, ANN, epilepsy

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Authors: Muhammad Hassan Khalil, Xu Jiadong

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Detection of malignant tumor inside the breast of women is a challenging field for the researchers. MWI (Microwave imaging) for breast cancer diagnosis has been of interest for last two decades, newly it suggested for finding cancerous tissues of women breast. A simple and basic idea of the mathematical modeling is used throughout this paper for imaging of malignant tumor. In this paper, the authors explained inverse scattering method in the microwave imaging and also present some simulation results.

Keywords: breast cancer detection, microwave imaging, tomography, tumor

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Authors: Mohammad Esmaeilpour

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One of the important open problems in the field of medical image processing is detection and quantification of small changes. In this poster, we try to investigate that, how the algebraic decomposition techniques can be used for semiautomatically detecting and quantifying subtle changes in Magnetic Resonance (MR) neuroimaging volumes. We mostly focus on the low-rank values of the matrices achieved from decomposing MR image pairs during a period of time. Besides, a skillful neuroradiologist will help the algorithm to distinguish between noises and small changes.

Keywords: magnetic resonance neuroimaging, subtle change detection and quantification, algebraic decomposition, basis functions

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Authors: Prikhil Agrawal, N. Priyanka

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With the increase of millions of users on Internet day by day, it is very essential to maintain highly reliable and secured data communication between various corporations. Although there are various traditional security imparting techniques such as antivirus software, password protection, data encryption, biometrics and firewall etc. But still network security has become the main issue in various leading companies. So IDSs have become an essential component in terms of security, as it can detect various network attacks and respond quickly to such occurrences. IDSs are used to detect unauthorized access to a computer system. This paper describes various intrusion detection techniques using GA approach. The intrusion detection problem has become a challenging task due to the conception of miscellaneous computer networks under various vulnerabilities. Thus the damage caused to various organizations by malicious intrusions can be mitigated and even be deterred by using this powerful tool.

Keywords: genetic algorithm (GA), intrusion detection system (IDS), dataset, network security

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Authors: Ahlem Abid, Farah Jemili

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Intrusion detection has been the subject of numerous studies in industry and academia, but cyber security analysts always want greater precision and global threat analysis to secure their systems in cyberspace. To improve intrusion detection system, the visualisation of the security events in form of graphs and diagrams is important to improve the accuracy of alerts. In this paper, we propose an approach of an IDS based on cloud computing, big data technique and using a machine learning graph algorithm which can detect in real time different attacks as early as possible. We use the MAWILab intrusion detection dataset . We choose Microsoft Azure as a unified cloud environment to load our dataset on. We implement the k2 algorithm which is a graphical machine learning algorithm to classify attacks. Our system showed a good performance due to the graphical machine learning algorithm and spark structured streaming engine.

Keywords: Apache Spark Streaming, Graph, Intrusion detection, k2 algorithm, Machine Learning, MAWILab, Microsoft Azure Cloud

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Authors: Mefteh Bouhalleb

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With the recent progress in nanotechnology, nanofluids have excellent potentiality in many modern engineering processes, particularly for solar systems such as concentrated solar power plants (CSP). In this context, a numerical simulation is performed to investigate laminar natural convection nanofluids in an inclined rectangular enclosure. Mass conservation, momentum, and energy equations are numerically solved by the finite volume element method using the SIMPLER algorithm for pressure-velocity coupling. In this work, we tested the acting factors on the system response time, such as the particle volume fraction of nanoparticles, particle material, particle size, an inclination angle of enclosure and Rayleigh number. The results show that the diameter of solid particles and Rayleigh number plays an important role in the system response time. The orientation angle of the cavity affects the system response time. A phenomenon of hysteresis appears when the system does not return to its initial state.

Keywords: nanofluid, nanoparticles, heat transfer, time response

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Authors: Amer Dawoud, Jesy Motchaalangaram, Arati Biswakarma, Wujan Mio, Karl Wallace

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The development of an embedded miniaturized drone-based system for remote detection of Chemical Warfare Agents (CWA) is proposed. The paper focuses on the software/hardware system design of the electrochemical Cyclic Voltammetry (CV) and Differential Pulse Voltammetry (DPV) signal processing for future deployment on drones. The paper summarizes the progress made towards hardware and electrochemical signal processing for signature detection of CWA. Also, the miniature potentiostat signal is validated by comparing it with the high-end lab potentiostat signal.

Keywords: drone-based, remote detection chemical warfare agents, miniaturized, potentiostat

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Authors: Waqqas-ur-Rehman Butt, Martin Servin, Marion Pause

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In recent years, object detection has gained much attention and very encouraging research area in the field of computer vision. The robust object boundaries detection in an image is demanded in numerous applications of human computer interaction and automated surveillance systems. Many methods and approaches have been developed for automatic object detection in various fields, such as automotive, quality control management and environmental services. Inappropriately, to the best of our knowledge, object detection under illumination with shadow consideration has not been well solved yet. Furthermore, this problem is also one of the major hurdles to keeping an object detection method from the practical applications. This paper presents an approach to automatic object detection in images under non-standardized environmental conditions. A key challenge is how to detect the object, particularly under uneven illumination conditions. Image capturing conditions the algorithms need to consider a variety of possible environmental factors as the colour information, lightening and shadows varies from image to image. Existing methods mostly failed to produce the appropriate result due to variation in colour information, lightening effects, threshold specifications, histogram dependencies and colour ranges. To overcome these limitations we propose an object detection algorithm, with pre-processing methods, to reduce the interference caused by shadow and illumination effects without fixed parameters. We use the Y CrCb colour model without any specific colour ranges and predefined threshold values. The segmented object regions are further classified using morphological operations (Erosion and Dilation) and contours. Proposed approach applied on a large image data set acquired under various environmental conditions for wood stack detection. Experiments show the promising result of the proposed approach in comparison with existing methods.

Keywords: image processing, illumination equalization, shadow filtering, object detection

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Authors: M. Berrehail, F. Benamira

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We study the quantum motion of a particle in the presence of a time- dependent linear potential using an operator invariant that is quadratic in p and linear in q within the framework of the Lewis-Riesenfeld invariant, The special invariant operator proposed in this work is demonstrated to be an Hermitian operator which has an Airy wave packet as its Eigenfunction

Keywords: airy wave packet, ivariant, time-dependent linear potential, unitary transformation

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Authors: Ghebremedhin Tsegay, Weldu Tesfagaber, Yuanmao Zhu, Xijun He, Wan Wang, Zhenjiang Zhang, Encheng Sun, Jinya Zhang, Yuntao Guan, Fang Li, Renqiang Liu, Zhigao Bu, Dongming Zhao*

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African swine fever (ASF) is a highly infectious viral disease of pigs, resulting in significant economic loss worldwide. As there is no approved vaccines and treatments, the control of ASF entirely depends on early diagnosis and culling of infected pigs. Thus, highly specific and sensitive diagnostic assays are required for accurate and early diagnosis of ASF virus (ASFV). Currently, only a few recombinant proteins have been tested and validated for use as reagents in ASF diagnostic assays. The most promising ones for ASFV antibody detection were p72, p30, p54, and pp62. So far, three ELISA kits based on these recombinant proteins have been commercialized. Due to the complex nature of the virus and variety forms of the disease, robust serodiagnostic assays are still required. ASFV p22 protein, encoded by KP177R gene, is located in the inner membrane of viral particle and appeared transiently in the plasma membrane early after virus infection. The p22 protein interacts with numerous cellular proteins, involved in processes of phagocytosis and endocytosis through different cellular pathways. However, p22 does not seem to be involved in virus replication or swine pathogenicity. In this study, E.coli expressed recombinant p22 protein was used to generate a monoclonal antibody (mAb), and its potential use for the development of blocking ELISA (bELISA) was evaluated. A total of 806 pig serum samples were tested to evaluate the bELISA. Acording the ROC (Reciever operating chracteristic) analysis, 100% sensitivity and 98.10% of specificity was recorded when the PI cut-off value was set at 47%. The novel assay was able to detect the antibodies as early as 9 days post infection. Finaly, a highly sensitive, specific and rapid novel p22-mAb based bELISA assay was developed, and optimized for detection of antibodies against genotype I and II ASFVs. It is a promising candidate for an early and acurate detection of the antibodies and is highly expected to have a valuable role in the containment and prevention of ASF.

Keywords: ASFV, blocking ELISA, diagnosis, monoclonal antibodies, sensitivity, specificity

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Authors: Mahmut Yildirim

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This paper proposed the bidirectional long short-term memory (Bi-LSTM) network-aided deep learning (DL)-based signal detection for Orthogonal frequency division multiplexing with all index modulation (OFDM-AIM), namely Bi-DeepAIM. OFDM-AIM is developed to increase the spectral efficiency of OFDM with index modulation (OFDM-IM), a promising multi-carrier technique for communication systems beyond 5G. In this paper, due to its strong classification ability, Bi-LSTM is considered an alternative to the maximum likelihood (ML) algorithm, which is used for signal detection in the classical OFDM-AIM scheme. The performance of the Bi-DeepAIM is compared with LSTM network-aided DL-based OFDM-AIM (DeepAIM) and classic OFDM-AIM that uses (ML)-based signal detection via BER performance and computational time criteria. Simulation results show that Bi-DeepAIM obtains better bit error rate (BER) performance than DeepAIM and lower computation time in signal detection than ML-AIM.

Keywords: bidirectional long short-term memory, deep learning, maximum likelihood, OFDM with all index modulation, signal detection

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Authors: Tomáš Dyk, Stanislav Procházka, Martin Drahanský

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The article proposes a new algorithm for detecting damaged areas of the tank barrel based on the image of the inner surface of the tank barrel. Damage position is calculated using image processing techniques such as edge detection, discrete wavelet transformation and image segmentation for accurate contour detection. The algorithm can detect surface damage in smoothbore and even in rifled tank barrels. The algorithm also calculates the volume of the detected damage from the depth map generated, for example, from the distance measurement unit. The proposed method was tested on data obtained by a tank barrel scanning device, which generates both surface image data and depth map. The article also discusses tank barrel scanning devices and how damaged surface impacts material resistance.

Keywords: barrel, barrel diagnostic, image processing, surface damage detection, tank

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Authors: Jianrong Wu, Xuan Fu, Akihiro Higashi, Zhiming Tan

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CMOS image sensors with a rolling shutter are used broadly in the digital cameras embedded in mobile devices. The rolling shutter suffers the flicker artifacts from the fluorescent lamp, and it could be observed easily. In this paper, the characteristics of illumination flicker in motion case were analyzed, and two efficient detection methods based on matching fragment selection were proposed. According to the experimental results, our methods could achieve as high as 100% accuracy in static scene, and at least 97% in motion scene.

Keywords: illumination flicker, embedded camera, rolling shutter, detection

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Authors: R. Rezaeipour, A. R. Mehrabi

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Recent increase of the DGs and microgrids in distribution systems, disturbs the tradition structure of the system. Coordination between protection devices in such a system becomes the concern of the network operators. This paper presents a new method for fault location detection in the active distribution networks, independent of the fault type or its resistance. The method uses synchronized voltage and current measurements at the interconnection of DG units and is able to adapt to changes in the topology of the system. The method has been tested on a 38-bus distribution system, with very encouraging results.

Keywords: fault location detection, active distribution system, micro grids, network operators

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Authors: Zhongfei Cai, Hui He, Changsheng Li

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This paper studied in the automatic repeat request (ARQ) transmission technique in Mars detection telecommunications system. An ARQ method applied to proximity-1 space link protocol was proposed by this paper. In order to ensure the efficiency of data reliable transmission, this ARQ method combined these different ARQ maneuvers characteristics. Considering the Mars detection communication environments, this paper analyzed the characteristics of the saturation throughput rate, packet dropping probability, average delay and energy efficiency with different ARQ algorithms. Combined thus results with the theories of ARQ transmission technique, an ARQ transmission project in Mars detection telecommunications system was established. The simulation results showed that this algorithm had excellent saturation throughput rate and energy efficiency with low complexity.

Keywords: ARQ, mars, CCSDS, proximity-1, deepspace

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Authors: R. S. Yadav, J. Havlica, I. Kuřitka, Z. Kozakova, J. Masilko, L. Kalina, M. Hajdúchová, V. Enev, J. Wasserbauer

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Nickel spinel ferrite NiFe2O4 nanoparticles with different particle size at different annealing temperature were synthesized using the starch-assisted sol-gel auto-combustion method. The synthesized nanoparticles were characterized by conventional powder X-ray diffraction (XRD) spectroscopy, Raman Spectroscopy, Fourier Transform Infrared Spectroscopy, Field-Emission Scanning Electron Microscopy, X-ray Photoelectron Spectroscopy and Vibrating Sample Magnetometer. The XRD patterns confirmed the formation of NiFe2O4 spinel ferrite nanoparticles. Field-Emission Scanning Electron Microscopy revealed that particles are of spherical morphology with particle size 5-20 nm at lower annealing temperature. An infrared spectroscopy study showed the presence of two principal absorption bands in the frequency range around 525 cm-1 (ν1) and around 340 cm-1 (ν2); which indicate the presence of tetrahedral and octahedral group complexes, respectively, within the spinel ferrite nanoparticles. Raman spectroscopy study also indicated the change in octahedral and tetrahedral site related Raman modes in nickel ferrite nanoparticles with change of particle size. This change in magnetic behavior with change of particle size of NiFe2O4 nanoparticles was observed.

Keywords: nickel ferrite, nanoparticles, magnetic property, NiFe2O4

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Authors: Ahmed Soliman Nagiub, Mahmoud Fayez, Heba Khaled, Said Ghoniemy

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Accurate perception is a critical component in enabling autonomous vehicles to understand their driving environment. The acquisition of 3D information about objects, including their location and pose, is essential for achieving this understanding. This survey paper presents a comprehensive review of 3D object detection techniques specifically tailored for autonomous vehicles. The survey begins with an introduction to 3D object detection, elucidating the significance of the third dimension in perceiving the driving environment. It explores the types of sensors utilized in this context and the corresponding data extracted from these sensors. Additionally, the survey investigates the different types of datasets employed, including their formats, sizes, and provides a comparative analysis. Furthermore, the paper categorizes and thoroughly examines the perception methods employed for 3D object detection based on the diverse range of sensors utilized. Each method is evaluated based on its effectiveness in accurately detecting objects in a three-dimensional space. Additionally, the evaluation metrics used to assess the performance of these methods are discussed. By offering a comprehensive overview of 3D object detection techniques for autonomous vehicles, this survey aims to advance the field of perception systems. It serves as a valuable resource for researchers and practitioners, providing insights into the techniques, sensors, and evaluation metrics employed in 3D object detection for autonomous vehicles.

Keywords: computer vision, 3D object detection, autonomous vehicles, deep learning

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Authors: Muhammad Arif Jalil, Xaythavay Luangvilay, Montree Bunruangses, Somchat Sonasang, Preecha Yupapin

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Black and white holes form the entangled pair⟨BH│WH⟩, where a white hole occurs when the particle moves at the same speed as light. The entangled black-white hole pair is at the center with the radian between the gap. When the speed of particle motion is slower than light, the black hole is gravitational (positive gravity), where the white hole is smaller than the black hole. On the downstream side, the entangled pair appears to have a black hole outside the gap increases until the white holes disappear, which is the emptiness paradox. On the upstream side, when moving faster than light, white holes form times tunnels, with black holes becoming smaller. It will continue to move faster and further when the black hole disappears and becomes a wormhole (Singularity) that is only a white hole in emptiness (Emptiness). This research studies use of black and white holes generated by a two-level circuit for communication transmission carriers, in which high ability and capacity of data transmission can be obtained. The black and white hole pair can be generated by the two-level system circuit when the speech of a particle on the circuit is equal to the speed of light. The black hole forms when the particle speed has increased from slower to equal to the light speed, while the white hole is established when the particle comes down faster than light. They are bound by the entangled pair, signal and idler, ⟨Signal│Idler⟩, and the virtual ones for the white hole, which has an angular displacement of half of π radian. A two-level system is made from an electronic circuit to create black and white holes bound by the entangled bits that are immune or cloning-free from thieves. Start by creating a wave-particle behavior when its speed is equal to light black hole is in the middle of the entangled pair, which is the two bit gate. The required information can be input into the system and wrapped by the black hole carrier. A timeline (Tunnel) occurs when the wave-particle speed is faster than light, from which the entangle pair is collapsed. The transmitted information is safely in the time tunnel. The required time and space can be modulated via the input for the downlink operation. The downlink is established when the particle speed is given by a frequency(energy) form is down and entered into the entangled gap, where this time the white hole is established. The information with the required destination is wrapped by the white hole and retrieved by the clients at the destination. The black and white holes are disappeared, and the information can be recovered and used.

Keywords: cloning free, time machine, teleportation, two-level system

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Authors: M. Ardelean, F. Manea, A. Pop, J. Schoonman

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The presence of pharmaceuticals in the environment and especially in water has gained increasing attention. They are included in emerging class of pollutants, and for most of them, legal limits have not been set-up due to their impact on human health and ecosystem was not determined and/or there is not the advanced analytical method for their quantification. In this context, the development of various advanced analytical methods for the quantification of pharmaceuticals in water is required. The electrochemical methods are known to exhibit the great potential for high-performance analytical methods but their performance is in direct relation to the electrode material and the operating techniques. In this study, two types of carbon-based electrodes materials, i.e., boron-doped diamond (BDD) and carbon nanofiber (CNF)-epoxy composite electrodes have been investigated through voltammetric techniques for the detection of naproxen in water. The comparative electrochemical behavior of naproxen (NPX) on both BDD and CNF electrodes was studied by cyclic voltammetry, and the well-defined peak corresponding to NPX oxidation was found for each electrode. NPX oxidation occurred on BDD electrode at the potential value of about +1.4 V/SCE (saturated calomel electrode) and at about +1.2 V/SCE for CNF electrode. The sensitivities for NPX detection were similar for both carbon-based electrode and thus, CNF electrode exhibited superiority in relation to the detection potential. Differential-pulsed voltammetry (DPV) and square-wave voltammetry (SWV) techniques were exploited to improve the electroanalytical performance for the NPX detection, and the best results related to the sensitivity of 9.959 µA·µM^-1 were achieved using DPV. In addition, the simultaneous detection of NPX and fluoxetine -a very common antidepressive drug, also present in water, was studied using CNF electrode and very good results were obtained. The detection potential values that allowed a good separation of the detection signals together with the good sensitivities were appropriate for the simultaneous detection of both tested pharmaceuticals. These results reclaim CNF electrode as a valuable tool for the individual/simultaneous detection of pharmaceuticals in water.

Keywords: boron-doped diamond electrode, carbon nanofiber-epoxy composite electrode, emerging pollutans, pharmaceuticals

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Authors: Andrii Natochii

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The UA9 collaboration in the last two years has installed two different types of detectors to investigate the channeling effect in the bent silicon crystals with high-energy particles beam on the CERN accelerator facilities: Cherenkov detector CpFM and silicon pixel detector Timepix. In the current work, we describe the main performances of the Timepix detector operation at the SPS and H8 extracted beamline at CERN. We are presenting some detector calibration results and tuning. Our research topics also cover a cluster analysis algorithm for the particle hits reconstruction. We describe the optimal acquisition setup for the Timepix device and the edges of its functionality for the high energy and flux beam monitoring. The measurements of the crystal parameters are very important for the future bent crystal applications and needs a track reconstruction apparatus. Thus, it was decided to construct a short range (1.2 m long) particle telescope based on the Timepix sensors and test it at H8 SPS extraction beamline. The obtained results will be shown as well.

Keywords: beam monitoring, channeling, particle tracking, Timepix detector

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Authors: Moumen Abdelhafidh, Stribu Bogdan, Laboureur Delphine, Gallant Johan, Hendrick Patrick

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This study is part of an ongoing effort to improve the understanding of phenomena occurring during the intermediate ballistic phase, such as muzzle flows. A thorough comprehension of muzzle flow fields is essential for optimizing muzzle device and projectile design. This flow characterization has heretofore been almost entirely limited to local and intrusive measurement techniques such as pressure measurements using pencil probes. Consequently, the body of quantitative experimental data is limited, so is the number of numerical codes validated in this field. The objective of the work presented here is to demonstrate the applicability of the Particle Image Velocimetry (PIV) technique in the challenging environment of the propellant flow of a .300 blackout weapon to provide accurate velocity measurements. The key points of a successful PIV measurement are the selection of the particle tracer, their seeding technique, and their tracking characteristics. We have experimentally investigated the aforementioned points by evaluating the resistance, gas dispersion, laser light reflection as well as the response to a step change across the Mach disk for five different solid tracers using two seeding methods. To this end, an experimental setup has been performed and consisted of a PIV system, the combustion chamber pressure measurement, classical high-speed schlieren visualization, and an aerosol spectrometer. The latter is used to determine the particle size distribution in the muzzle flow. The experimental results demonstrated the ability of PIV to accurately resolve the salient features of the propellant flow, such as the under the expanded jet and vortex rings, as well as the instantaneous velocity field with maximum centreline velocities of more than 1000 m/s. Besides, naturally present unburned particles in the gas and solid ZrO₂ particles with a nominal size of 100 nm, when coated on the propellant powder, are suitable as tracers. However, the TiO₂ particles intended to act as a tracer, surprisingly not only melted but also functioned as a combustion accelerator and decreased the number of particles in the propellant gas.

Keywords: intermediate ballistic, muzzle flow fields, particle image velocimetry, propellant gas, particle size distribution, under expanded jet, solid particle tracers

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Authors: Yu-Hsuan Liu, Ying-Fang Wang

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The objectives of the present study are to characterize nanoparticles generated from the laser metal deposition (LMD) process and to estimate particle concentrations deposited in the head (H), that the tracheobronchial (TB) and alveolar (A) regions, respectively. The studied LMD chamber (3.6m × 3.8m × 2.9m) is installed with a robot laser metal deposition machine. Direct-reading instrument of a scanning mobility particle sizer (SMPS, Model 3082, TSI Inc., St. Paul, MN, USA) was used to conduct static sampling inside the chamber for nanoparticle number concentration and particle size distribution measurements. The SMPS obtained particle number concentration at every 3 minutes, the diameter of the SMPS ranged from 11~372 nm when the aerosol and sheath flow rates were set at 0.6 and 6 L / min, respectively. The resultant size distributions were used to predict depositions of nanoparticles at the H, TB, and A regions of the respiratory tract using the UK National Radiological Protection Board’s (NRPB’s) LUDEP Software. Result that the number concentrations of nanoparticles in indoor background and LMD chamber were 4.8×10³ and 4.3×10⁵ # / cm³, respectively. However, the nanoparticles emitted from the LMD process was in the form of the uni-modal with number median diameter (NMD) and geometric standard deviation (GSD) as 142nm and 1.86, respectively. The fractions of the nanoparticles deposited on the alveolar region (A: 69.8%) were higher than the other two regions of the head region (H: 10.9%), tracheobronchial region (TB: 19.3%). This study conducted static sampling to measure the nanoparticles in the LMD process, and the results show that the fraction of particles deposited on the A region was higher than the other two regions. Therefore, applying the characteristics of nanoparticles emitted from LMD process could be provided valuable scientific-based evidence for exposure assessments in the future.

Keywords: exposure assessment, laser metal deposition process, nanoparticle, respiratory region

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Authors: A. Sacko, H. Nyoni, T. A. M. Msagati, B. Ntsendwana

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Carbon based materials to target environmental pollutants have become increasingly recognized in science. Electrochemical methods using carbon based materials are notable methods for high sensitive detection of organic pollutants in air. It is therefore in this light that exfoliated graphite electrode was fabricated for electrochemical analysis of PAHs in urban atmospheric air. The electrochemical properties of the graphite electrode were studied using CV and EIS in the presence of acetate buffer supporting electrolyte with 2 Mm ferricyanide as a redox probe. The graphite electrode showed enhanced current response which confirms facile kinetics and enhanced sensitivity. However, the peak to peak (DE) separation increased as a function of scan rate. The EIS showed a high charger transfer resistance. The detection phenanthrene on the exfoliated graphite was studied in the presence of acetate buffer solution at PH 3.5 using DPV. The oxidation peak of phenanthrene was observed at 0.4 V. Under optimized conditions (supporting electrolyte, pH, deposition time, etc.). The detection limit observed was at 5x 10⁻⁸ M. Thus the results demonstrate with further optimization and modification lower concentration detection can be achieved.

Keywords: electrochemical detection, exfoliated graphite, PAHs (polycyclic aromatic hydrocarbons), urban air

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Authors: Sri Satya Antarlina, Elok Zubaidah, Teti Istiana, Harijono

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Sorghum bicolor (Sorghum bicolor L. Moench) has the potential as a flour for gluten-free food products. Sorghum flour production needs grain soaking treatment. Soaking can reduce the tannin content which is an anti-nutrient, so it can increase the protein digestibility. Fine particle size decreases the yield of flour, so it is necessary to study various particle sizes to increase the yield. This study aims to determine the characteristics of sorghum flour in the treatment of soaking peeled grain and particle size. The material of white sorghum varieties KD-4 from farmers in East Java, Indonesia. Factorial randomized factorial design (two factors), repeated three times, factor I were the time of grain soaking (five levels) that were 0, 12, 24, 36, and 48 hours, factor II was the size of the starch particles sifted with a fineness level of 40, 60, 80, and 100 mesh. The method of making sorghum flour is grain peeling, soaking peeled grain, drying using the oven at 60ᵒC, milling, and sieving. Physico-chemical analysis of sorghum flour. The results show that there is an interaction between soaking time of grain with the size of sorghum flour particles. Interaction in yield of flour, L* color (brightness level), whiteness index, paste properties, amylose content, protein content, bulk density, and protein digestibility. The method of making sorghum flour through the soaking of peeled grain and the difference in particle size has an important role in producing the physicochemical properties of the specific flour. Based on the characteristics of sorghum flour produced, it is determined the method of making sorghum flour through sorghum grain soaking for 24 hours, the particle size of flour 80 mesh. The sorghum flour with characteristic were 24.88% yield of flour, 88.60 color L* (brightness level), 69.95 whiteness index, 3615 Cp viscosity, 584.10 g/l of bulk density, 24.27% db protein digestibility, 90.02% db starch content, 23.4% db amylose content, 67.45% db amylopectin content, 0.22% db crude fiber content, 0.037% db tannin content, 5.30% db protein content, ash content 0.18% db, carbohydrate content 92.88 % db, and 1.94% db fat content. The sorghum flour is recommended for cookies products.

Keywords: characteristic, sorghum (Sorghum bicolor L. Moench) flour, grain soaking, particle size, physicochemical properties

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Authors: Xu Jinsheng, Tong Xin, Zheng Jian, Zhou Changsheng

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The NEPE (nitrate ester plasticized polyether) propellant is a kind of particle filling material with relatively high filling fraction. The experimental results show that the microcracks, microvoids and dewetting can cause the stress softening of the material. In this paper, a series of mechanical testing in inclusion with CCD technique were conducted to analyze the evolution of internal defects of propellant. The volume expansion function of the particle filling material was established by measuring of longitudinal and transverse strain with optical deformation measurement system. By analyzing the defects and internal damages of the material, a visco-hyperelastic constitutive model based on free energy theory was proposed incorporating damage function. The proposed constitutive model could accurately predict the mechanical properties of uniaxial tensile tests and tensile-relaxation tests.

Keywords: dewetting, constitutive model， uniaxial tensile tests, visco-hyperelastic, nonlinear

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Authors: C. R. Stein; K. Skeff Neto, K. L. C. Miranda, P. P. C. Sartoratto, M. E. Xavier, Z. G. M. Lacava, S. M. De Freita, P. C. Morais

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In this study, static magnetic birefringence (SMB) and transmission electron microscopy (TEM) were used to investigate the self-assembling of maghemite nanoparticles suspended as biocompatible magnetic fluid (BMF) while incubated or not with the Black Eyed–Pea Trypsin Chymotripsin Inhibitor–BTCI protein. The stock samples herein studied are dextran coated maghemite nanoparticles (average core diameter of 7.1 nm, diameter dispersion of 0.26, and containing 4.6×1016 particle/mL) and the dextran coated maghemite nanoparticles associated with the BTCI protein. Several samples were prepared by diluting the stock samples with deionized water while following their colloidal stability. The diluted samples were investigated using SMB measurements to assess the average sizes of the self-assembled and suspended mesoscopic structures whereas the TEM micrographs provide the morphology of the as-suspended units. The SMB data were analyzed using a model that includes the particle-particle interaction within the mean field model picture.

Keywords: biocompatible magnetic fluid, maghemite nanoparticles, self-assembling

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Authors: Yu-Kuei Hsu, Yan-Gu Lin

Abstract:

A facile and simple fabrication of copper(II) oxide (CuO) nanosheet on copper foil as nanoelectrode for H2O2 sensing application was proposed in this study. The spontaneous formation of CuO nanosheets by immersing the copper foil into 0.1 M NaOH aqueous solution for 48 hrs was carried out at room temperature. The sheet-like morphology with several ten nanometers in thickness and ~500 nm in width was observed by SEM. Those nanosheets were confirmed the monoclinic-phase CuO by the structural analysis of XRD and Raman spectra. The directly grown CuO nanosheets film is mechanically stable and offers an excellent electrochemical sensing platform. The CuO nanosheets electrode shows excellent electrocatalytic response to H2O2 with significantly lower overpotentials for its oxidation and reduction and also exhibits a fast response and high sensitivity for the amperometric detection of H2O2. The novel spontaneously grown CuO nanosheets electrode is readily applicable to other analytes and has great potential applications in the electrochemical detection.

Keywords: CuO, nanosheets, H2O2 detection, Cu foil

Procedia PDF Downloads 288

Authors: V. Rashtchi, H. Bizhani, F. R. Tatari

Abstract:

This paper presents a new online loss minimization for an induction motor drive. Among the many loss minimization algorithms (LMAs) for an induction motor, a particle swarm optimization (PSO) has the advantages of fast response and high accuracy. However, the performance of the PSO and other optimization algorithms depend on the accuracy of the modeling of the motor drive and losses. In the development of the loss model, there is always a trade off between accuracy and complexity. This paper presents a new online optimization to determine an optimum flux level for the efficiency optimization of the vector-controlled induction motor drive. An induction motor (IM) model in d-q coordinates is referenced to the rotor magnetizing current. This transformation results in no leakage inductance on the rotor side, thus the decomposition into d-q components in the steady-state motor model can be utilized in deriving the motor loss model. The suggested algorithm is simple for implementation.

Keywords: induction machine, loss minimization, magnetizing current, particle swarm optimization

Procedia PDF Downloads 630

Authors: Amos Olajide Oluyege, Akpanobong Akpan Ekong, Emmanuel Uchechukwu Opara, Sunday Adeniyi Adedutan, Joseph Adeola Fuwape, Olawale John Olukunle

Abstract:

This study was carried out to evaluate the influence of wood species and wood plastic ratio on the physical and mechanical properties of wood plastic composites (WPCs) produced from polyethylene terephthalate (PET) plastic bottle wastes and sawdust from three hardwood species, namely, Terminalia superba, Gmelina arborea, and Ceiba pentandra. The experimental WPCs were prepared from sawdust particle size classes of ≤ 0.5, 0.5 – 1.0, and 1.0 – 2.0 mm at wood/plastic ratios of 40:60, 50:50 and 60:40 (percentage by weight). The WPCs for each study variable combination were prepared in 3 replicates and laid out in a randomized complete block design (RCBD). The physical properties investigated water absorption (WA), linear expansion (LE) and thickness swelling (TS) while the mechanical properties evaluated were Modulus of Elasticity (MOE) and Modulus of Rupture (MOR). The mean values for WA, LE and TS ranged from 1.07 to 34.04, 0.11 to 1.76 and 0.11 to 4.05 %, respectively. The mean values of the three physical properties increased with decrease in wood plastic ratio. Wood plastic ratio of 40:60 at each particle size class generally resulted in the lowest values while wood plastic ratio of 60:40 had the highest values for each of the three species. For each of the physical properties, T. superba had the least mean values followed by G. arborea, while the highest values were observed C. pentandra. The mean values for MOE and MOR ranged from 458.17 to 1875.67 and 2.64 to 18.39 N/mm2, respectively. The mean values of the two mechanical properties decreased with increase in wood plastic ratio. Wood plastic ratio of 40:60 at each wood particle size class generally had the highest values while wood plastic ratio of 60:40 had the least values for each of the three species. For each of the mechanical properties, C. pentandra had the highest mean values followed by G. arborea, while the least values were observed T. superba. There were improvements in both the physical and mechanical properties due to decrease in sawdust particle size class with the particle size class of ≤ 0.5 mm giving the best result. The results of the Analysis of variance revealed significant (P < 0.05) effects of the three study variables – wood species, sawdust particle size class and wood/plastic ratio on all the physical and mechanical properties of the WPCs. It can be concluded from the results of this study that wood plastic composites from sawdust particle size ≤ 0.5 and PET plastic bottle wastes with acceptable physical and mechanical properties are better produced using 40:60 wood/plastic ratio, and that at this ratio, all the three species are suitable for the production of wood plastic composites.

Keywords: polyethylene terephthalate plastic bottle wastes, wood plastic composite, physical properties, mechanical properties

Procedia PDF Downloads 201