Search results for: particle detector

Authors: M. Jalali Azizpour, H.Mohammadi Majd

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In this paper, the effect of WC-12Co particle Temperature in HVOF thermal spraying process on the coating thickness has been studied. The statistical results show that the spray distance and oxygen-to-fuel ratio are more effective factors on particle characterization and thickness of HVOF thermal spraying coatings. Spray Watch diagnostic system, scanning electron microscopy (SEM), X-ray diffraction and thickness measuring system were used for this purpose.

Keywords: HVOF, temperature, thickness, velocity, WC-12Co

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Authors: Sayed Hessam Bahmani, Rolsndo P. Orense

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From an engineering point of view, pumice particles are problematic because of their crushability and compressibility due to their vesicular nature. Currently, information on the geotechnical characteristics of pumice sands is limited. While extensive empirical and laboratory tests can be implemented to characterize their behavior, these are generally time-consuming and expensive. These drawbacks have motivated attempts to study the effects of particle breakage of pumice sand through the Discrete Element Method (DEM). This method provides insights into the behavior of crushable granular material at both the micro and macro-level. In this paper, the results of single-particle crushing tests conducted in the laboratory are simulated using DEM through the open-source code YADE. This is done to better understand the parameters necessary to represent the pumice microstructure that governs its crushing features, and to examine how the resulting microstructure evolution affects a particle’s properties. The DEM particle model is then used to simulate the behavior of pumice sand during consolidated drained triaxial tests. The results indicate the importance of incorporating particle porosity and unique surface textures in the material characterization and show that interlocking between the crushed particles significantly influences the drained behavior of the pumice specimen.

Keywords: pumice sand, triaxial compression, simulation, particle breakage

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Authors: E. Petrakis, V. Karmali, K. Komnitsas

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In this study grinding experiments were performed in a laboratory ball mill using Polish ferronickel slag in order to study the effect of the particle size on alkali activation and the properties of the produced alkali activated materials (AAMs). In this regard, the particle size distribution and the specific surface area of the grinding products in relation to grinding time were assessed. The experimental results show that products with high compressive strength, e.g. higher than 60 MPa, can be produced when the slag median size decreased from 39.9 μm to 11.9 μm. Also, finer fractions are characterized by higher reactivity and result in the production of AAMs with lower porosity and better mechanical properties.

Keywords: alkali activation, compressive strength, grinding time, particle size distribution, slag, structural integrity

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Authors: Asmaa Zaki M., Ahmed Abd El Aziz, Heba A. Fayed, Moustafa H. Aly

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ISLs are the most popular choice for deep space communications because these links are attractive alternatives to present day microwave links. This paper explored the allowable high data rate in this link over different orbits, which is affected by variation in modulation scheme and detector type. Moreover, the objective of this paper is to optimize and analyze the performance of ISL in terms of Q-factor and Minimum Bit Error Rate (Min-BER) based on different detectors comprising some parameters.

Keywords: free space optics (FSO), field of view (FOV), inter satellite link (ISL), optical wireless communication (OWC)

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Authors: S. Chockalingam, U. Natarajan, D. M. Santhoshsarang

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Particle damping is a promising vibration attenuating technique in boring tool than other type of damping with minimal effect on the strength, rigidity and stiffness ratio of the machine tool structure. Due to the cantilever nature of boring tool holder in operations, it suffers chatter when the slenderness ratio of the tool gets increased. In this study, Copper-Stainless steel (SS) particles were packed inside the boring tool which acts as a damper. Damper suppresses chatter generated during machining and also improves the machining efficiency of the tool with better slenderness ratio. In the first approach of particle damping, combined Cu-SS particles were packed inside the vibrating tool, whereas Copper and Stainless steel particles were selected separately and packed inside another tool and their effectiveness was analysed in this simulation. This study reveals that the efficiency of finite element simulation of the boring tools when equipped with particles such as copper, stainless steel and a combination of both. In this study, the newly modified boring tool holder with particle damping was simulated using ANSYS12.0 with and without particles. The aim of this study is to enhance the structural rigidity through particle damping thus avoiding the occurrence of resonance in the boring tool during machining.

Keywords: boring bar, copper-stainless steel, chatter, particle damping

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Authors: Arvind Srivastav, Tarun Kanti Bhattacharyya

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The north-eastern, Himalayan, and Eastern Ghats Belt of India comprise of earthquake-prone, remote, and hilly terrains. Earthquakes have caused enormous damages in these regions in the past. A wireless sensor network based earthquake early warning system (EEWS) is being developed to mitigate the damages caused by earthquakes. It consists of sensor nodes, distributed over the region, that perform majority voting of the output of the seismic sensors in the vicinity, and relay a message to a base station to alert the residents when an earthquake is detected. At the heart of the EEWS is a low-power two-stage seismic sensor that continuously tracks seismic events from incoming three-axis accelerometer signal at the first-stage, and, in the presence of a seismic event, triggers the second-stage P-wave detector that detects the onset of P-wave in an earthquake event. The parameters of the P-wave detector have been optimized for minimizing detection time and maximizing the accuracy of detection.Working of the sensor scheme has been verified with seven earthquakes data retrieved from IRIS. In all test cases, the scheme detected the onset of P-wave accurately. Also, it has been established that the P-wave onset detection time reduces linearly with the sampling rate. It has been verified with test data; the detection time for data sampled at 10Hz was around 2 seconds which reduced to 0.3 second for the data sampled at 100Hz.

Keywords: earthquake early warning system, EEWS, STA/LTA, polarization, wavelet, event detector, P-wave detector

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Authors: Daham Owaid Matrood, Naqaa Hussein Raheem

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Evolutionary algorithms and Artificial neural networks (ANN) are two relatively young research areas that were subject to a steadily growing interest during the past years. This paper examines the use of Particle Swarm Optimization (PSO) to train a multi-layer feed forward neural network for demand forecasting. We use in this paper weekly demand data for packed cement and towels, which have been outfitted by the Northern General Company for Cement and General Company of prepared clothes respectively. The results showed superiority of trained neural networks using particle swarm optimization on neural networks trained using error back propagation because their ability to escape from local optima.

Keywords: artificial neural network, demand forecasting, particle swarm optimization, weight optimization

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Authors: Siamack A. Shirazi, Farzin Darihaki

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Solid particles could be found in many multiphase flows, including transport pipelines and pipe fittings. Such particles interact with the pipe material and cause erosion which threats the integrity of the system. Therefore, predicting the erosion rate is an important factor in the design and the monitor of such systems. Mechanistic models can provide reliable predictions for many conditions while demanding only relatively low computational cost. Mechanistic models utilize a representative particle trajectory to predict the impact characteristics of the majority of the particle impacts that cause maximum erosion rate in the domain. The erosion caused by particle impacts is not only due to the direct impacts but also random impingements. In the present study, an alternative model has been introduced to describe the erosion due to random impingement of particles. The present model provides a realistic trend for erosion with changes in the particle size and particle Stokes number. The present model is examined against the experimental data and CFD simulation results and indicates better agreement with the data incomparison to the available models in the literature.

Keywords: erosion, mechanistic modeling, particles, multiphase flow, gas-liquid-solid

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Authors: Niddal Imam, Vassilios G. Vassilakis

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After analysing messages posted by health-related spam campaigns in Twitter Arabic hashtags, we found that these campaigns use unique hijacked accounts (we call them adversarial hijacked accounts) as adversarial examples to fool deployed ML-based spam detectors. Existing ML-based models build a behaviour profile for each user to detect hijacked accounts. This approach is not applicable for detecting spam in Twitter hashtags since they are computationally expensive. Hence, we propose an adversary-aware ML-based detector, which includes a newly designed feature (avg posts) to improve the detection of spam tweets posted by the adversarial hijacked accounts at a tweet-level in trending hashtags. The proposed detector was designed considering three key points: robustness, adaptability, and interpretability. The new feature leverages the account’s temporal patterns (i.e., account age and number of posts). It is faster to compute compared to features discussed in the literature and improves the accuracy of detecting the identified hijacked accounts by 73%.

Keywords: Twitter spam detection, adversarial examples, evasion attack, adversarial concept drift, account hijacking, trending hashtag

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Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas

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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.

Keywords: biomass concentration, extended Kalman filter, particle filter, state estimation, specific growth rate

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Authors: Felix U. Asoiro, Daniel I. Eleazar, Peter O. Offor

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As a result of increasing energy demands, research in bioethanol has increased in recent years all through the world, in abide to partially or totally replace renewable energy supplies. The first and third generation feedstocks used for biofuel production have fundamental drawbacks. Waste rice straw and cake from second generation feedstock like Jatropha curcas l. kernel (JC) is seen as non-food feedstock and promising candidates for the industrial production of bioethanol. In this study, JC and rice husk (RH) wastes were characterized for proximate composition. Bioethanol was produced from the residual polysaccharides present in rice husk (RH) and Jatropha seed cake by sequential hydrolytic and fermentative processes at varying mixing proportions (50 g JC/50 g RH, 100 g JC/10 g RH, 100 g JC/20 g RH, 100 g JC/50 g RH, 100 g JC/100 g RH, 100 g JC/200 g RH and 200 g JC/100 g RH) and particle sizes (0.25, 0.5 and 1.00 mm). Mixing proportions and particle size significantly affected both bioethanol yield and some bioethanol properties. Bioethanol yield (%) increased with an increase in particle size. The highest bioethanol (8.67%) was produced at a mixing proportion of 100 g JC/50g RH at 0.25 mm particle size. The bioethanol had the lowest values of specific gravity and density of 1.25 and 0.92 g cm-3 and the highest values of 1.57 and 0.97 g cm-3 respectively. The highest values of viscosity (4.64 cSt) were obtained with 200 g JC/100 g RH, at 1.00 mm particle size. The maximum flash point and cloud point values were 139.9 oC and 23.7oC (100 g JC/200 g RH) at 1 mm and 0.5 mm particle sizes respectively. The maximum pour point value recorded was 3.85oC (100 g JC/50 g RH) at 1 mm particle size. The paper concludes that bioethanol can be recovered from JC and RH wastes. JC and RH blending proportions as well as particle sizes are important factors in bioethanol production.

Keywords: bioethanol, hydrolysis, Jatropha curcas l. kernel, rice husk, fermentation, proximate composition

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Authors: Han Joo Choe, Soon-Ho Kwon, Jung-Joong Lee

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Tin particles of various size and distribution were self-assembled by plasma treating tin film deposited on silicon oxide substrates. Plasma treatment was conducted using an inductively coupled plasma (ICP) source. A range of ICP power and topographic templated substrates were evaluated to observe changes in particle size and particle distribution. Scanning electron microscopy images of the particles were analyzed using computer software. The evolution of tin film dewetting into particles initiated from the hole nucleation in grain boundaries. Increasing ICP power during plasma treatment produced larger number of particles per area and smaller particle size and particle-size distribution. Topographic templates were also effective in positioning and controlling the size of the particles. By combining the effects of ICP power and topographic templates, particles of similar size and well-ordered distribution were obtained.

Keywords: dewetting, particles, plasma, tin

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Authors: Ryan Maclellan

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EXO-200 has provided one of the most sensitive searches for neutrinoless double-beta decay utilizing 175 kg of enriched liquid xenon in an ultra-low background time projection chamber. This detector has demonstrated excellent energy resolution and background rejection capabilities. Using the first two years of data, EXO-200 has set a limit of 1.1x10^25 years at 90% C.L. on the neutrinoless double-beta decay half-life of Xe-136. The experiment has experienced a brief hiatus in data taking during a temporary shutdown of its host facility: the Waste Isolation Pilot Plant. EXO-200 expects to resume data taking in earnest this fall with upgraded detector electronics. Results from the analysis of EXO-200 data and an update on the current status of EXO-200 will be presented.

Keywords: double-beta, Majorana, neutrino, neutrinoless

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Authors: R. Alias, A. Kasa, M. R. Taha

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The effect of particle size on shear strength of granular materials are investigated using direct shear tests. Small direct shear test (60 mm by 60 mm by 24 mm deep) were conducted for particles passing the sieves with opening size of 2.36 mm. Meanwhile, particles passing the standard 20 mm sieves were tested using large direct shear test (300 mm by 300 mm by 200 mm deep). The large direct shear tests and the small direct shear tests carried out using the same shearing rate of 0.09 mm/min and similar normal stresses of 100, 200, and 300 kPa. The results show that the peak and residual shear strength decreases as particle size increases.

Keywords: particle size, shear strength, granular material, direct shear test

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Authors: E. Accomando, L. Delle Rose, S. Moretti, E. Olaiya, C. Shepherd-Themistocleous

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Heavy sterile neutrinos are almost ubiquitous in the class of Beyond Standard Model scenarios aimed at addressing the puzzle that emerged from the discovery of neutrino flavour oscillations, hence the need to explain their masses. In particular, they are necessary in a U(1)’ enlarged Standard Model (SM). We show that these heavy neutrinos can be rather long-lived producing distinctive displaced vertices and tracks. Indeed, depending on the actual decay length, they can decay inside a Large Hadron Collider (LHC) detector far from the main interaction point and can be identified in the inner tracking system or the muon chambers, emulated here through the Compact Muon Solenoid (CMS) detector parameters. Among the possible production modes of such heavy neutrino, we focus on their pair production mechanism in the SM Higgs decay, eventually yielding displaced lepton signatures following the heavy neutrino decays into weak gauge bosons. By employing well-established triggers available for the CMS detector and using the data collected by the end of the LHC Run 2, these signatures would prove to be accessible with negligibly small background. Finally, we highlight the importance that the exploitation of new triggers, specifically, displaced tri-lepton ones, could have for this displaced vertex search.

Keywords: beyond the standard model, displaced vertex, Higgs physics, neutrino physics

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Authors: Lina Pan

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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

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Authors: Alexander Mikkelsen, Khobaib Khobaib, Zbigniew Rozynek

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Drops covered by particles have found important uses in various fields, ranging from stabilization of emulsions to production of new advanced materials. Particles at drop interfaces can be interlocked to form solid capsules with properties tailored for a myriad of applications. Despite the huge potential of particle-laden drops and capsules, the knowledge of their deformation and stability are limited. In this regard, we contribute with experimental studies on the deformation and manipulation of silicone oil drops covered with micrometer-sized particles subjected to electric fields. A mixture of silicone oil and particles were immersed in castor oil using a mechanical pipette, forming millimeter sized drops. The particles moved and adsorbed at the drop interfaces by sedimentation, and were structured at the interface by electric field-induced electrohydrodynamic flows. When applying a direct current electric field, free charges accumulated at the drop interfaces, yielding electric stress that deformed the drops. In our experiments, we investigated how particle properties affected drop deformation, break-up, and particle structuring. We found that by increasing the size of weakly-conductive clay particles, the drop shape can go from compressed to stretched out in the direction of the electric field. Increasing the particle size and electrical properties were also found to weaken electrohydrodynamic flows, induce break-up of drops at weaker electric field strengths and structure particles in chains. These particle parameters determine the dipolar force between the interfacial particles, which can yield particle chaining. We conclude that the balance between particle chaining and electrohydrodynamic flows governs the observed drop mechanics.

Keywords: drop deformation, electric field induced stress, electrohydrodynamic flows, particle structuring at drop interfaces

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Authors: Hugo Lefeuvre, Jerôme Donnard, Michael Descostes, Sophie Billon, Samuel Duval, Tugdual Oger, Herve Toubon, Paul Sardini

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Spectroscopic autoradiography is a method of interest for geological sample analysis. Indeed, researchers may face different issues such as radioelement identification and quantification in the field of environmental studies. Imaging gaseous ionization detectors find their place in geosciences for conducting specific measurements of radioactivity to improve the monitoring of natural processes using naturally-occurring radioactive tracers, but also for the nuclear industry linked to the mining sector. In geological samples, the location and identification of the radioactive-bearing minerals at the thin-section scale remains a major challenge as the detection limit of the usual elementary microprobe techniques is far higher than the concentration of most of the natural radioactive decay products. The spatial distribution of each decay product in the case of uranium in a geomaterial is interesting for relating radionuclides concentration to the mineralogy. The present study aims to provide spectroscopic autoradiography analysis method for measuring the initial energy of alpha particles with a parallel ionization multiplier gaseous detector. The analysis method has been developed thanks to Geant4 modelling of the detector. The track of alpha particles recorded in the gas detector allow the simultaneous measurement of the initial point of emission and the reconstruction of the initial particle energy by a selection based on the linear energy distribution. This spectroscopic autoradiography method was successfully used to reproduce the alpha spectra from a 238U decay chain on a geological sample at the thin-section scale. The characteristics of this measurement are an energy spectrum resolution of 17.2% (FWHM) at 4647 keV and a spatial resolution of at least 50 µm. Even if the efficiency of energy spectrum reconstruction is low (4.4%) compared to the efficiency of a simple autoradiograph (50%), this novel measurement approach offers the opportunity to select areas on an autoradiograph to perform an energy spectrum analysis within that area. This opens up possibilities for the detailed analysis of heterogeneous geological samples containing natural alpha emitters such as uranium-238 and radium-226. This measurement will allow the study of the spatial distribution of uranium and its descendants in geo-materials by coupling scanning electron microscope characterizations. The direct application of this dual modality (energy-position) of analysis will be the subject of future developments. The measurement of the radioactive equilibrium state of heterogeneous geological structures, and the quantitative mapping of 226Ra radioactivity are now being actively studied.

Keywords: alpha spectroscopy, digital autoradiography, mining activities, natural decay products

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Authors: T. Kobayashi, K. Shiba, T. Kaburagi, Y. Kurihara

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For the elderly living alone, falls can be a serious problem encountered in daily life. Some elderly people are unable to stand up without the assistance of a caregiver. They may become unconscious after a fall, which can lead to serious aftereffects such as hypothermia, dehydration, and sometimes even death. We treat the subject as an inverted pendulum and model its angle from the equilibrium position and its angular velocity. As the model is non-linear, we implement the filtering method with a particle filter which can estimate true states of the non-linear model. In order to evaluate the accuracy of the particle filter estimation results, we calculate the root mean square error (RMSE) between the estimated angle/angular velocity and the true values generated by the simulation. The experimental results give the highest accuracy RMSE of 0.0141 rad and 0.1311 rad/s for the angle and angular velocity, respectively.

Keywords: fall, microwave Doppler sensor, non-linear dynamics model, particle filter

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Authors: Chih-Yi Ho, Tzu-Fang Chang, Chih-Chia Huang, Chia-Yen Lee

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In dental clinics, the dentists use the periapical radiography image to assess the effectiveness of endodontic treatment of teeth with chronic apical periodontitis. Periapical radiography images are taken at different times to assess alveolar bone variation before and after the root canal treatment, and furthermore to judge whether the treatment was successful. Current clinical assessment of apical tissue recovery relies only on dentist personal experience. It is difficult to have the same standard and objective interpretations due to the dentist or radiologist personal background and knowledge. If periapical radiography images at the different time could be registered well, the endodontic treatment could be evaluated. In the image registration area, it is necessary to assign representative control points to the transformation model for good performances of registration results. However, detection of representative control points (feature points) on periapical radiography images is generally very difficult. Regardless of which traditional detection methods are practiced, sufficient feature points may not be detected due to the low-contrast characteristics of the x-ray image. Barnard detector is an algorithm for feature point detection based on grayscale value gradients, which can obtain sufficient feature points in the case of gray-scale contrast is not obvious. However, the Barnard detector would detect too many feature points, and they would be too clustered. This study uses the local extrema of clustering feature points and the suppression radius to overcome the problem, and compared different feature point detection methods. In the preliminary result, the feature points could be detected as representative control points by the proposed method.

Keywords: feature detection, Barnard detector, registration, periapical radiography image, endodontic treatment

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Authors: A. A. Abid

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Wave-particle interactions are considered to be the paramount in the transmission of energy in collisionless space plasmas, where electromagnetic fields confined the charged particles movement. One of the distinct features of energy transfer in collisionless plasma is wave-particle interaction which is ubiquitous in space plasmas. The three essential populations of the inner magnetosphere are cold plasmaspheric plasmas, ring-currents, and radiation belts high energy particles. The transition region amid such populations initiates wave-particle interactions among distinct plasmas and the wave mode perceived in the magnetosphere is the electromagnetic ion cyclotron (EMIC) wave. These waves can interact with numerous particle species resonantly, accompanied by plasma particle heating is still in debate. In this work we paid particular attention to how EMIC waves impact plasma species, specifically how they affect the heating of electrons and ions during storm and substorm in the Magnetosphere. Using Magnetospheric Multiscale (MMS) mission and electromagnetic hybrid simulation, this project will investigate the energy transfer mechanism (e.g., Landau interactions, bounce resonance interaction, cyclotron resonance interaction, etc.) between EMIC waves and cold-warm plasma populations. Other features such as the production of EMIC waves and the importance of cold plasma particles in EMIC wave-particle interactions will also be worth exploring. Wave particle interactions, electromagnetic hybrid simulation, electromagnetic ion cyclotron (EMIC) waves, Magnetospheric Multiscale (MMS) mission, space plasmas, inner magnetosphere

Keywords: MMS, magnetosphere, wave particle interraction, non-maxwellian distribution

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Authors: Ebrahim Ghasemi Ardi, Ai Bing Yu, Run Yu Yang

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Current study is aimed to develop an available in-house discrete element method (DEM) code and link it with direct breakage event. So, it became possible to determine the particle breakage and then its fragments size distribution, simultaneous with DEM simulation. It directly applies the particle breakage inside the DEM computation algorithm and if any breakage happens the original particle is replaced with daughters. In this way, the calculation will be followed based on a new updated particles list which is very similar to the real grinding environment. To validate developed model, a grinding ball impacting an unconfined particle bed was simulated. Since considering an entire ball mill would be too computationally demanding, this method provided a simplified environment to test the model. Accordingly, a representative volume of the ball mill was simulated inside a box, which could emulate media (ball)–powder bed impacts in a ball mill and during particle bed impact tests. Mono, binary and ternary particle beds were simulated to determine the effects of granular composition on breakage kinetics. The results obtained from the DEM simulations showed a reduction in the specific breakage rate for coarse particles in binary mixtures. The origin of this phenomenon, commonly known as cushioning or decelerated breakage in dry milling processes, was explained by the DEM simulations. Fine particles in a particle bed increase mechanical energy loss, and reduce and distribute interparticle forces thereby inhibiting the breakage of the coarse component. On the other hand, the specific breakage rate of fine particles increased due to contacts associated with coarse particles. Such phenomenon, known as acceleration, was shown to be less significant, but should be considered in future attempts to accurately quantify non-linear breakage kinetics in the modeling of dry milling processes.

Keywords: particle bed, breakage models, breakage kinetic, discrete element method

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

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

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

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Authors: Maru Chetan, Desai Abhilash

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The structural characteristics & application of TiO2 powder with different phases are study by various techniques in this paper. TTIP, EG and citric acid use as Ti source and catalyst respectively synthesis for sol gel synthesis of TiO2 powder. To replace sol gel method we develop the new method of making nano particle of TiO2 powder. It is two route method one is physical and second one is chemical route. Specific aim to this process is to minimize the production cost and the large scale production of nano particle The synthesis product work characterize by EDAX, SEM, XRD tests.

Keywords: mortal and pestle, nano particle , TiO2, TTIP

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Authors: Jeremy Jenrette, Z. Y. C. Liu, Pranav Chimote, Edward Fox, Trevor Hastie, Francesco Ferretti

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Suitable shark conservation depends on well-informed population assessments. Direct methods such as scientific surveys and fisheries monitoring are adequate for defining population statuses, but species-specific indices of abundance and distribution coming from these sources are rare for most shark species. We can rapidly fill these information gaps by boosting media-based remote monitoring efforts with machine learning and automation. We created a database of shark images by sourcing 24,546 images covering 219 species of sharks from the web application spark pulse and the social network Instagram. We used object detection to extract shark features and inflate this database to 53,345 images. We packaged object-detection and image classification models into a Shark Detector bundle. We developed the Shark Detector to recognize and classify sharks from videos and images using transfer learning and convolutional neural networks (CNNs). We applied these models to common data-generation approaches of sharks: boosting training datasets, processing baited remote camera footage and online videos, and data-mining Instagram. We examined the accuracy of each model and tested genus and species prediction correctness as a result of training data quantity. The Shark Detector located sharks in baited remote footage and YouTube videos with an average accuracy of 89\%, and classified located subjects to the species level with 69\% accuracy (n =\ eight species). The Shark Detector sorted heterogeneous datasets of images sourced from Instagram with 91\% accuracy and classified species with 70\% accuracy (n =\ 17 species). Data-mining Instagram can inflate training datasets and increase the Shark Detector’s accuracy as well as facilitate archiving of historical and novel shark observations. Base accuracy of genus prediction was 68\% across 25 genera. The average base accuracy of species prediction within each genus class was 85\%. The Shark Detector can classify 45 species. All data-generation methods were processed without manual interaction. As media-based remote monitoring strives to dominate methods for observing sharks in nature, we developed an open-source Shark Detector to facilitate common identification applications. Prediction accuracy of the software pipeline increases as more images are added to the training dataset. We provide public access to the software on our GitHub page.

Keywords: classification, data mining, Instagram, remote monitoring, sharks

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Authors: Ejay Nsugbe, Andrew Starr, Ian Jennions, Cristobal Ruiz-Carcel

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This works investigates the possibility of using Acoustic Emissions (AE) to estimate the Particle Size Distribution (PSD) of a mixture of particles that comprise of particles of different densities and geometry. The experiments carried out involved the mixture of a set of glass and polyethylene particles that ranged from 150-212 microns and 150-250 microns respectively and an experimental rig that allowed the free fall of a continuous stream of particles on a target plate which the AE sensor was placed. By using a time domain based multiple threshold method, it was observed that the PSD of the particles in the mixture could be estimated.

Keywords: acoustic emissions, particle sizing, process monitoring, signal processing

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Authors: Seong Woo Kwak, Jung-Min Yang

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A strategy of fault diagnosis and tolerance for asynchronous sequential machines is discussed in this paper. With no synchronizing clock, it is difficult to diagnose an occurrence of permanent or stuck-in faults in the operation of asynchronous machines. In this paper, we present a fault detector comprised of a timer and a set of static functions to determine the occurrence of faults. In order to realize immediate fault tolerance, corrective control theory is applied to designing a dynamic feedback controller. Existence conditions for an appropriate controller and its construction algorithm are presented in terms of reachability of the machine and the feature of fault occurrences.

Keywords: asynchronous sequential machines, corrective control, fault diagnosis and tolerance, fault detector

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Authors: Nanditha Rajamani, Anirudhaa R. Rao, Divya Sriram

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One of the greatest difficulties in treating patients with pain is the highly subjective nature of pain sensation. The measurement of pain intensity is primarily dependent on the patient’s report, often with little physical evidence to provide objective corroboration. This is also complicated by the fact that there are only few and expensive existing technologies (Functional Magnetic Resonance Imaging-fMRI). The need is thus clear and urgent for a reliable, non-invasive, non-painful, objective, readily adoptable, and coefficient diagnostic platform that provides additional diagnostic information to supplement its current regime with more information to assist doctors in diagnosing these patients. Thus, our idea of developing a pain detector was conceived to take a step further the detection and diagnosis of chronic and acute pain.

Keywords: pain sensor, microwave radiometery, pain sensation, fMRI

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Authors: Samindi Samarakoon, Ørjan Sletbakk Vie, Remi Kleiven Fjelldal

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White concrete facade elements are widely used in construction industry. It is challenging to achieve the desired workability in casting of white concrete elements. Particle Matrix model was used for proportioning the self-compacting white concrete (SCWC) to control segregation and bleeding and to improve workability. The paper presents how to reach the target slump flow while controlling bleeding and segregation in SCWC. The amount of aggregates, binders and mixing water, as well as type and dosage of superplasticizer (SP) to be used are the major factors influencing the properties of SCWC. Slump flow and compressive strength tests were carried out to examine the performance of SCWC, and the results indicate that the particle matrix model could produce successfully SCWC controlling segregation and bleeding.

Keywords: white concrete, particle matrix model, mix design, construction industry

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Authors: Xinghui Wu, Chun Yang

Abstract:

Inertial microfluidics is a competitive fluidic method with applications in separation of particles, cells and bacteria. In contrast to traditional microfluidic devices with low Reynolds number, inertial microfluidics works in the intermediate Re number range which brings about several intriguing inertial effects on particle separation/focusing to meet the throughput requirement in the real-world. Geometric modifications to make channels become irregular shapes can leverage fluid inertia to create complex secondary flow for adjusting the particle equilibrium positions and thus enhance the separation resolution and throughput. Although inertial microfluidics has been extensively studied by experiments, our current understanding of its mechanisms is poor, making it extremely difficult to build rational-design guidelines for the particle focusing locations, especially for irregularly shaped microfluidic channels. Inertial particle microfluidics in irregularly shaped channels were investigated in our group. There are several fundamental issues that require us to address. One of them is about the balance between the inertial lift forces and the secondary drag forces. Also, it is critical to quantitatively describe the dependence of the life forces on particle-particle interactions in irregularly shaped channels, such as a rectangular one. To provide physical insights into the inertial microfluidics in channels of irregular shapes, in this work the immersed boundary-lattice Boltzmann method (IB-LBM) was introduced and validated to explore the transport characteristics and the underlying mechanisms of an inertial focusing single particle in a rectangular microchannel. The transport dynamics of a finitesized particle were investigated over wide ranges of Reynolds number (20 < Re < 500) and particle size. The results show that the inner equilibrium positions are more difficult to occur in the rectangular channel, which can be explained by the secondary flow caused by the presence of a finite-sized particle. Furthermore, force decoupling analysis was utilized to study the effect of each type of lift force on the inertia migration, and a theoretical model for the lateral lift force of a finite-sized particle in the rectangular channel was established. Such theoretical model can be used to provide theoretical guidance for the design and operation of inertial microfluidics.

Keywords: inertial microfluidics, particle focuse, life force, IB-LBM

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