Search results for: precision grinding
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 395

Search results for: precision grinding

305 Topographic Mapping of Farmland by Integration of Multiple Sensors on Board Low-Altitude Unmanned Aerial System

Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi

Abstract:

This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.

Keywords: Land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle.

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304 Improving the Voltage Level in High Voltage Direct Current Systems by Using Modular Multilevel Converter

Authors: G. Kishor Babu, B. Madhu Kiran

Abstract:

This paper presented an intend scheme of Modular-Multilevel-Converter (MMC) levels for move towering the practical conciliation flanked by the precision and divisional competence. The whole process is standard by a Thevenin-equivalent 133-level MMC model. Firstly the computation scheme of the fundamental limit imitation time step is offered to faithfully represent each voltage level of waveforms. Secondly the earlier industrial Improved Analytic Hierarchy Process (IAHP) is adopted to integrate the relative errors of all the input electrical factors interested in one complete virtual fault on each converter level. Thirdly the stable AC and DC ephemeral condition in virtual faults effects of all the forms stabilize and curve integral stand on the standard form. Finally the optimal MMC level will be obtained by the drown curves and it will give individual weights allowing for the precision and efficiency. And the competence and potency of the scheme are validated by model on MATLAB Simulink.

Keywords: Modular multilevel converter, improved analytic hierarchy process, ac and dc transient, high voltage direct current, voltage sourced converter.

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303 Void-Free Bonding of Si/Ti/Ni Power Integrated Circuit Chips with Direct Bonding Copper Alumina Substrates through Ag3Sn Intermetallic Interlayer

Authors: Kuan-Yu Chiu, Yin-Hsuan Chen, Tung-Han Chuang

Abstract:

Ti/Ni/Ag/Sn-metallized Si chips were bonded to Ni/Pd/Au-surface finished DBC (Direct Bonding Copper) alumina substrate through the formation of an Ag3Sn intermetallic interlayer by solid–liquid interdiffusion bonding method. The results indicated that the holes and gaps at the bonding interface could be effectively prevented. The intermetallic phases at the bonding interface between the Si/Ti/Ni/Ag/Sn wafer and the DBC substrate were identified as Ag3Sn, Ni3Sn4, and Ni3Sn2. The average bonding strength was about 19.75 MPa, and the maximum bonding strength reached 35.24 MPa.

Keywords: BGBM, Backside Grinding and Backside Metallization, SLID bonding, Solid–liquid Interdiffusion Bonding, Si/Ti/Ni/Sn, Si/Ti/Ni/Ag/Sn, intermetallic compound.

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302 Intelligent System and Renewable Energy: A Farming Platform in Precision Agriculture

Authors: Ryan B. Escorial, Elmer A. Maravillas, Chris Jordan G. Aliac

Abstract:

This study presents a small-scale water pumping system utilizing a fuzzy logic inference system attached to a renewable energy source. The fuzzy logic controller was designed and simulated in MATLAB fuzzy logic toolbox to examine the properties and characteristics of the input and output variables. The result of the simulation was implemented in a microcontroller, together with sensors, modules, and photovoltaic cells. The study used a grand rapid variety of lettuce, organic substrates, and foliar for observation of the capability of the device to irrigate crops. Two plant boxes intended for manual and automated irrigation were prepared with each box having 48 heads of lettuce. The observation of the system took 22-31 days, which is one harvest period of the crop. Results showed a 22.55% increase in agricultural productivity compared to manual irrigation. Aside from reducing human effort, and time, the smart irrigation system could help lessen some of the shortcomings of manual irrigations. It could facilitate the economical utilization of water, reducing consumption by 25%. The use of renewable energy could also help farmers reduce the cost of production by minimizing the use of diesel and gasoline.

Keywords: Fuzzy logic controller, intelligent system, precision agriculture, renewable energy.

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301 Influence of Environmental Temperature on Dairy Herd Performance and Behaviour

Authors: L. Krpalkova, N. O' Mahony, A. Carvalho, S. Campbell, S. Harapanahalli, J. Walsh

Abstract:

The objective of this study was to determine the effects of environmental stressors on the performance of lactating dairy cows and discuss some future trends. There exists a relationship between the meteorological data and milk yield prediction accuracy in pasture-based dairy systems. New precision technologies are available and are being developed to improve the sustainability of the dairy industry. Some of these technologies focus on welfare of individual animals on dairy farms. These technologies allow the automatic identification of animal behaviour and health events, greatly increasing overall herd health and yield while reducing animal health inspection demands and long-term animal healthcare costs. The data set consisted of records from 489 dairy cows at two dairy farms and temperature measured from the nearest meteorological weather station in 2018. The effects of temperature on milk production and behaviour of animals were analyzed. The statistical results indicate different effects of temperature on milk yield and behaviour. The “comfort zone” for animals is in the range 10 °C to 20 °C. Dairy cows out of this zone had to decrease or increase their metabolic heat production, and it affected their milk production and behaviour.

Keywords: Behaviour, milk yield, temperature, precision technologies.

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300 A Finite Precision Block Floating Point Treatment to Direct Form, Cascaded and Parallel FIR Digital Filters

Authors: Abhijit Mitra

Abstract:

This paper proposes an efficient finite precision block floating point (BFP) treatment to the fixed coefficient finite impulse response (FIR) digital filter. The treatment includes effective implementation of all the three forms of the conventional FIR filters, namely, direct form, cascaded and par- allel, and a roundoff error analysis of them in the BFP format. An effective block formatting algorithm together with an adaptive scaling factor is pro- posed to make the realizations more simple from hardware view point. To this end, a generic relation between the tap weight vector length and the input block length is deduced. The implementation scheme also emphasises on a simple block exponent update technique to prevent overflow even during the block to block transition phase. The roundoff noise is also investigated along the analogous lines, taking into consideration these implementational issues. The simulation results show that the BFP roundoff errors depend on the sig- nal level almost in the same way as floating point roundoff noise, resulting in approximately constant signal to noise ratio over a relatively large dynamic range.

Keywords: Finite impulse response digital filters, Cascade structure, Parallel structure, Block floating point arithmetic, Roundoff error.

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299 Optimization of Protein Hydrolysate Production Process from Jatropha curcas Cake

Authors: Waraporn Apiwatanapiwat, Pilanee Vaithanomsat, Phanu Somkliang, Taweesiri Malapant

Abstract:

This was the first document revealing the investigation of protein hydrolysate production optimization from J. curcas cake. Proximate analysis of raw material showed 18.98% protein, 5.31% ash, 8.52% moisture and 12.18% lipid. The appropriate protein hydrolysate production process began with grinding the J. curcas cake into small pieces. Then it was suspended in 2.5% sodium hydroxide solution with ratio between solution/ J. curcas cake at 80:1 (v/w). The hydrolysis reaction was controlled at temperature 50 °C in water bath for 45 minutes. After that, the supernatant (protein hydrolysate) was separated using centrifuge at 8000g for 30 minutes. The maximum yield of resulting protein hydrolysate was 73.27 % with 7.34% moisture, 71.69% total protein, 7.12% lipid, 2.49% ash. The product was also capable of well dissolving in water.

Keywords: Production, protein hydrolysate, Jatropha curcas cake, optimization.

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298 Experimental and Numerical Investigation of the Dispersion of Microparticles Emitted by Machining Operation

Authors: F. Tafnout, E. Belut, B. Oesterlé, J.R. Fontaine

Abstract:

As a part of the development of a numerical method of close capture exhausts systems for machining devices, a test rig recreating a situation similar to a grinding operation, but in a perfectly controlled environment, is used. The properties of the obtained spray of solid particles are initially characterized using particle tracking velocimetry (PTV), in order to obtain input and validation parameters for numerical simulations. The dispersion of a tracer gas (SF6) emitted simultaneously with the particle jet is then studied experimentally, as the dispersion of such a gas is representative of that of finer particles, whose aerodynamic response time is negligible. Finally, complete modeling of the test rig is achieved to allow comparison with experimental results and thus to progress towards validation of the models used to describe a twophase flow generated by machining operation.

Keywords: Pollutants, capture, tracer gas, SF6, PTV, numericalmodeling.

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297 Optimization of Control Parameters for EWR in Injection Flushing Type of EDM on Stainless Steel 304 Workpiece

Authors: M. S. Reza, M. Hamdi, S. H. Tomadi, A. R. Ismail

Abstract:

The operating control parameters of injection flushing type of electrical discharge machining process on stainless steel 304 workpiece using copper tools are being optimized according to its individual machining characteristic i.e. Electrode Wear Ratio (EWR). Higher EWR would give bad dimensional precision for the EDM machined workpiece because of high electrode wear. Hence, the quality characteristic for EWR is set to lower-the-better to achieve the optimum dimensional precision for the machined workpiece. Taguchi method has been used for the construction, layout and analysis of the experiment for EWR machining characteristic. The use of Taguchi method in the experiment saves a lot of time and cost of preparing and machining the experiment samples. Therefore, an L18 Orthogonal array which was the fundamental component in the statistical design of experiments has been used to plan the experiments and Analysis of Variance (ANOVA) is used to determine the optimum machining parameters for this machining characteristic. The control parameters selected for this optimization experiments are polarity, pulse on duration, discharge current, discharge voltage, machining depth, machining diameter and dielectric liquid pressure. The result had shown that negative polarity machining parameter setting will decreases EWR.

Keywords: ANOVA, EDM, Injection Flushing, L18Orthogonal Array, EWR, Stainless Steel 304

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296 Information System for Data Selection and New Information Acquisition for Reconfigurable Multifunctional Machine Tools

Authors: Sasho Guergov

Abstract:

The purpose of the paper is to develop an informationcontrol environment for overall management and self-reconfiguration of the reconfigurable multifunctional machine tool for machining both rotation and prismatic parts and high concentration of different technological operations - turning, milling, drilling, grinding, etc. For the realization of this purpose on the basis of defined sub-processes for the implementation of the technological process, architecture of the information-search system for machine control is suggested. By using the object-oriented method, a structure and organization of the search system based on agents and manager with central control are developed. Thus conditions for identification of available information in DBs, self-reconfiguration of technological system and entire control of the reconfigurable multifunctional machine tool are created.

Keywords: Information system, multifunctional machine tool, reconfigurable machine tool, search system.

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295 Development and Validation of a HPLC Method for 6-Gingerol and 6-Shogaol in Joint Pain Relief Gel Containing Ginger (Zingiber officinale)

Authors: Tanwarat Kajsongkram, Saowalux Rotamporn, Sirinat Limbunruang, Sirinan Thubthimthed

Abstract:

High Performance Liquid Chromatography (HPLC) method was developed and validated for simultaneous estimation of 6-Gingerol(6G) and 6-Shogaol(6S) in joint pain relief gel containing ginger extract. The chromatographic separation was achieved by using C18 column, 150 x 4.6mm i.d., 5μ Luna, mobile phase containing acetonitrile and water (gradient elution). The flow rate was 1.0 ml/min and the absorbance was monitored at 282 nm. The proposed method was validated in terms of the analytical parameters such as specificity, accuracy, precision, linearity, range, limit of detection (LOD), limit of quantification (LOQ), and determined based on the International Conference on Harmonization (ICH) guidelines. The linearity ranges of 6G and 6S were obtained over 20- 60 and 6-18 μg/ml respectively. Good linearity was observed over the above-mentioned range with linear regression equation Y= 11016x- 23778 for 6G and Y = 19276x-19604 for 6S (x is concentration of analytes in μg/ml and Y is peak area). The value of correlation coefficient was found to be 0.9994 for both markers. The limit of detection (LOD) and limit of quantification (LOQ) for 6G were 0.8567 and 2.8555 μg/ml and for 6S were 0.3672 and 1.2238 μg/ml respectively. The recovery range for 6G and 6S were found to be 91.57 to 102.36 % and 84.73 to 92.85 % for all three spiked levels. The RSD values from repeated extractions for 6G and 6S were 3.43 and 3.09% respectively. The validation of developed method on precision, accuracy, specificity, linearity, and range were also performed with well-accepted results.

Keywords: Ginger, 6-gingerol, HPLC, 6-shogaol.

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294 Calibration of Syringe Pumps Using Interferometry and Optical Methods

Authors: E. Batista, R. Mendes, A. Furtado, M. C. Ferreira, I. Godinho, J. A. Sousa, M. Alvares, R. Martins

Abstract:

Syringe pumps are commonly used for drug delivery in hospitals and clinical environments. These instruments are critical in neonatology and oncology, where any variation in the flow rate and drug dosing quantity can lead to severe incidents and even death of the patient. Therefore it is very important to determine the accuracy and precision of these devices using the suitable calibration methods. The Volume Laboratory of the Portuguese Institute for Quality (LVC/IPQ) uses two different methods to calibrate syringe pumps from 16 nL/min up to 20 mL/min. The Interferometric method uses an interferometer to monitor the distance travelled by a pusher block of the syringe pump in order to determine the flow rate. Therefore, knowing the internal diameter of the syringe with very high precision, the travelled distance, and the time needed for that travelled distance, it was possible to calculate the flow rate of the fluid inside the syringe and its uncertainty. As an alternative to the gravimetric and the interferometric method, a methodology based on the application of optical technology was also developed to measure flow rates. Mainly this method relies on measuring the increase of volume of a drop over time. The objective of this work is to compare the results of the calibration of two syringe pumps using the different methodologies described above. The obtained results were consistent for the three methods used. The uncertainties values were very similar for all the three methods, being higher for the optical drop method due to setup limitations.

Keywords: Calibration, interferometry, syringe pump, optical method, uncertainty.

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293 Taguchi-Based Optimization of Surface Roughness and Dimensional Accuracy in Wire EDM Process with S7 Heat Treated Steel

Authors: Joseph C. Chen, Joshua Cox

Abstract:

This research focuses on the use of the Taguchi method to reduce the surface roughness and improve dimensional accuracy of parts machined by Wire Electrical Discharge Machining (EDM) with S7 heat treated steel material. Due to its high impact toughness, the material is a candidate for a wide variety of tooling applications which require high precision in dimension and desired surface roughness. This paper demonstrates that Taguchi Parameter Design methodology is able to optimize both dimensioning and surface roughness successfully by investigating seven wire-EDM controllable parameters: pulse on time (ON), pulse off time (OFF), servo voltage (SV), voltage (V), servo feed (SF), wire tension (WT), and wire speed (WS). The temperature of the water in the Wire EDM process is investigated as the noise factor in this research. Experimental design and analysis based on L18 Taguchi orthogonal arrays are conducted. This paper demonstrates that the Taguchi-based system enables the wire EDM process to produce (1) high precision parts with an average of 0.6601 inches dimension, while the desired dimension is 0.6600 inches; and (2) surface roughness of 1.7322 microns which is significantly improved from 2.8160 microns.

Keywords: Taguchi parameter design, surface roughness, dimensional accuracy, Wire EDM.

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292 Theoretical and Experimental Analysis of Hard Material Machining

Authors: Rajaram Kr. Gupta, Bhupendra Kumar, T. V. K. Gupta, D. S. Ramteke

Abstract:

Machining of hard materials is a recent technology for direct production of work-pieces. The primary challenge in machining these materials is selection of cutting tool inserts which facilitates an extended tool life and high-precision machining of the component. These materials are widely for making precision parts for the aerospace industry. Nickel-based alloys are typically used in extreme environment applications where a combination of strength, corrosion resistance and oxidation resistance material characteristics are required. The present paper reports the theoretical and experimental investigations carried out to understand the influence of machining parameters on the response parameters. Considering the basic machining parameters (speed, feed and depth of cut) a study has been conducted to observe their influence on material removal rate, surface roughness, cutting forces and corresponding tool wear. Experiments are designed and conducted with the help of Central Composite Rotatable Design technique. The results reveals that for a given range of process parameters, material removal rate is favorable for higher depths of cut and low feed rate for cutting forces. Low feed rates and high values of rotational speeds are suitable for better finish and higher tool life.

Keywords: Speed, feed, depth of cut, roughness, cutting force, flank wear.

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291 Spacecraft Neural Network Control System Design using FPGA

Authors: Hanaa T. El-Madany, Faten H. Fahmy, Ninet M. A. El-Rahman, Hassen T. Dorrah

Abstract:

Designing and implementing intelligent systems has become a crucial factor for the innovation and development of better products of space technologies. A neural network is a parallel system, capable of resolving paradigms that linear computing cannot. Field programmable gate array (FPGA) is a digital device that owns reprogrammable properties and robust flexibility. For the neural network based instrument prototype in real time application, conventional specific VLSI neural chip design suffers the limitation in time and cost. With low precision artificial neural network design, FPGAs have higher speed and smaller size for real time application than the VLSI and DSP chips. So, many researchers have made great efforts on the realization of neural network (NN) using FPGA technique. In this paper, an introduction of ANN and FPGA technique are briefly shown. Also, Hardware Description Language (VHDL) code has been proposed to implement ANNs as well as to present simulation results with floating point arithmetic. Synthesis results for ANN controller are developed using Precision RTL. Proposed VHDL implementation creates a flexible, fast method and high degree of parallelism for implementing ANN. The implementation of multi-layer NN using lookup table LUT reduces the resource utilization for implementation and time for execution.

Keywords: Spacecraft, neural network, FPGA, VHDL.

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290 Refining Waste Spent Hydroprocessing Catalyst and Their Metal Recovery

Authors: Meena Marafi, Mohan S. Rana

Abstract:

Catalysts play an important role in producing valuable fuel products in petroleum refining; but, due to feedstock’s impurities catalyst gets deactivated with carbon and metal deposition. The disposal of spent catalyst falls under the category of hazardous industrial waste that requires strict agreement with environmental regulations. The spent hydroprocessing catalyst contains Mo, V and Ni at high concentrations that have been found to be economically significant for recovery. Metal recovery process includes deoiling, decoking, grinding, dissolving and treatment with complexing leaching agent such as ethylene diamine tetra acetic acid (EDTA). The process conditions have been optimized as a function of time, temperature and EDTA concentration in presence of ultrasonic agitation. The results indicated that optimum condition established through this approach could recover 97%, 94% and 95% of the extracted Mo, V and Ni, respectively, while 95% EDTA was recovered after acid treatment.

Keywords: Spent catalyst, deactivation, hydrotreating, spent catalyst.

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289 Effects of used Engine Oil in Reinforced Concrete Beams: The Structural Behaviour

Authors: S.C. Chin, N. Shafiq, M.F. Nuruddin

Abstract:

In the modern construction practices, industrial wastes or by-products are largely used as raw materials in cement and concrete. These impart many benefits to the environment and bringabout an economic impact because the cost of waste disposal is constantly increasing due to strict environmental regulations. It was reported in literature that the leakage of oil onto concrete element in older cement grinding unit resulted in concrete with greater resistance to freezing and thawing. This effect was thought to be similar to adding an air-entraining chemical admixture to concrete. This paper presents an investigation on the load deflection behaviour and crack patterns of reinforced concrete (RC) beams subjected to four point loading. Ten 120x260x1900 mm beams were cast with 100% ordinary Portland cement (OPC) concrete, 20% fly ash (FA) and 20% rice husk ash (RHA) blended cement concrete. 0.15% dosage of admixtures (used engine oil, new engine oil, and superplasticizer) was used throughout the experiment. Results show that OPC and OPC/RHA RC beams containing used engine oil and superplasticizer exhibit higher capacity, 18-26% than their corresponding control mix.

Keywords: by-products, RC beams, superplasticizer, used engine oil

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288 Feasibility of Ground Alkali-Active Sandstone Powder for Use in Concrete as Mineral Admixture

Authors: Xia Chen, Hua-Quan Yang, Shi-Hua Zhou

Abstract:

Alkali-active sandstone aggregate was ground by vertical and ball mill into particles with residue over 45 μm less than 12%, and investigations have been launched on particles distribution and characterization of ground sandstone powder, fluidity, heat of hydration, strength as well as hydration products morphology of pastes with incorporation of ground sandstone powder. Results indicated that ground alkali-active sandstone powder with residue over 45 μm less than 8% was easily obtainable, and specific surface area was more sensitive to characterize its fineness with extension of grinding length. Incorporation of sandstone powder resulted in higher water demand and lower strength, advanced hydration of C3A and C2S within 3days and refined pore structure. Based on its manufacturing, characteristics and influence on properties of pastes, it was concluded that sandstone powder was a good selection for use in concrete as mineral admixture.

Keywords: Concrete, mineral admixture, hydration, structure.

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287 Evolutionary Approach for Automated Discovery of Censored Production Rules

Authors: Kamal K. Bharadwaj, Basheer M. Al-Maqaleh

Abstract:

In the recent past, there has been an increasing interest in applying evolutionary methods to Knowledge Discovery in Databases (KDD) and a number of successful applications of Genetic Algorithms (GA) and Genetic Programming (GP) to KDD have been demonstrated. The most predominant representation of the discovered knowledge is the standard Production Rules (PRs) in the form If P Then D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski & Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: If P Then D Unless C, where C (Censor) is an exception to the rule. Such rules are employed in situations, in which the conditional statement 'If P Then D' holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the 'If P Then D' part of the CPR expresses important information, while the Unless C part acts only as a switch and changes the polarity of D to ~D. This paper presents a classification algorithm based on evolutionary approach that discovers comprehensible rules with exceptions in the form of CPRs. The proposed approach has flexible chromosome encoding, where each chromosome corresponds to a CPR. Appropriate genetic operators are suggested and a fitness function is proposed that incorporates the basic constraints on CPRs. Experimental results are presented to demonstrate the performance of the proposed algorithm.

Keywords: Censored Production Rule, Data Mining, MachineLearning, Evolutionary Algorithms.

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286 Bioleaching of Spent Catalyst using Moderate Thermophiles with Different Pulp Densities and Varying Size Fractions without Fe Supplemented Growth Medium

Authors: Haragobinda Srichandan, Chandra Sekhar Gahan, Dong-Jin Kim, Seoung-Won Lee

Abstract:

Bioleaching of spent catalyst using moderate thermophilic chemolithotrophic acidophiles in growth medium without Fe source was investigated with two different pulp densities and three different size fractions. All the experiments were conducted on shake flasks at a temperature of 65 °C. The leaching yield of Ni and Al was found to be promising with very high leaching yield of 92-96% followed by Al as 41-76%, which means both Ni and Al leaching were favored by the moderate thermophilic bioleaching compared to the mesophilic bioleaching. The acid consumption was comparatively higher for the 10% pulp density experiments. Comparatively minimal difference in the leaching yield with different size fractions and different pulp densities show no requirement of grinding and using low pulp density less than 10%. This process would rather be economical as well as eco-friendly process for future optimization of the recovery of metal values from spent catalyst.

Keywords: Bioleaching, spent catalyst, leaching yield, thermophile.

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285 Precise Measurement of Displacement using Pixels

Authors: Razif Mahadi, John Billingsley

Abstract:

Manufacturing processes demand tight dimensional tolerances. The paper concerns a transducer for precise measurement of displacement, based on a camera containing a linescan chip. When tests were conducted using a track of black and white stripes with a 2mm pitch, errors in measuring on individual cycle amounted to 1.75%, suggesting that a precision of 35 microns is achievable.

Keywords: Linescan, microcontroller, pixels.

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284 Optimization by Means of Genetic Algorithm of the Equivalent Electrical Circuit Model of Different Order for Li-ion Battery Pack

Authors: V. Pizarro-Carmona, S. Castano-Solis, M. Cortés-Carmona, J. Fraile-Ardanuy, D. Jimenez-Bermejo

Abstract:

The purpose of this article is to optimize the Equivalent Electric Circuit Model (EECM) of different orders to obtain greater precision in the modeling of Li-ion battery packs. Optimization includes considering circuits based on 1RC, 2RC and 3RC networks, with a dependent voltage source and a series resistor. The parameters are obtained experimentally using tests in the time domain and in the frequency domain. Due to the high non-linearity of the behavior of the battery pack, Genetic Algorithm (GA) was used to solve and optimize the parameters of each EECM considered (1RC, 2RC and 3RC). The objective of the estimation is to minimize the mean square error between the measured impedance in the real battery pack and those generated by the simulation of different proposed circuit models. The results have been verified by comparing the Nyquist graphs of the estimation of the complex impedance of the pack. As a result of the optimization, the 2RC and 3RC circuit alternatives are considered as viable to represent the battery behavior. These battery pack models are experimentally validated using a hardware-in-the-loop (HIL) simulation platform that reproduces the well-known New York City cycle (NYCC) and Federal Test Procedure (FTP) driving cycles for electric vehicles. The results show that using GA optimization allows obtaining EECs with 2RC or 3RC networks, with high precision to represent the dynamic behavior of a battery pack in vehicular applications.

Keywords: Li-ion battery packs modeling optimized, EECM, GA, electric vehicle applications.

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283 Comparative Evaluation of Accuracy of Selected Machine Learning Classification Techniques for Diagnosis of Cancer: A Data Mining Approach

Authors: Rajvir Kaur, Jeewani Anupama Ginige

Abstract:

With recent trends in Big Data and advancements in Information and Communication Technologies, the healthcare industry is at the stage of its transition from clinician oriented to technology oriented. Many people around the world die of cancer because the diagnosis of disease was not done at an early stage. Nowadays, the computational methods in the form of Machine Learning (ML) are used to develop automated decision support systems that can diagnose cancer with high confidence in a timely manner. This paper aims to carry out the comparative evaluation of a selected set of ML classifiers on two existing datasets: breast cancer and cervical cancer. The ML classifiers compared in this study are Decision Tree (DT), Support Vector Machine (SVM), k-Nearest Neighbor (k-NN), Logistic Regression, Ensemble (Bagged Tree) and Artificial Neural Networks (ANN). The evaluation is carried out based on standard evaluation metrics Precision (P), Recall (R), F1-score and Accuracy. The experimental results based on the evaluation metrics show that ANN showed the highest-level accuracy (99.4%) when tested with breast cancer dataset. On the other hand, when these ML classifiers are tested with the cervical cancer dataset, Ensemble (Bagged Tree) technique gave better accuracy (93.1%) in comparison to other classifiers.

Keywords: Artificial neural networks, breast cancer, cancer dataset, classifiers, cervical cancer, F-score, logistic regression, machine learning, precision, recall, support vector machine.

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282 Opponent Color and Curvelet Transform Based Image Retrieval System Using Genetic Algorithm

Authors: Yesubai Rubavathi Charles, Ravi Ramraj

Abstract:

In order to retrieve images efficiently from a large database, a unique method integrating color and texture features using genetic programming has been proposed. Opponent color histogram which gives shadow, shade, and light intensity invariant property is employed in the proposed framework for extracting color features. For texture feature extraction, fast discrete curvelet transform which captures more orientation information at different scales is incorporated to represent curved like edges. The recent scenario in the issues of image retrieval is to reduce the semantic gap between user’s preference and low level features. To address this concern, genetic algorithm combined with relevance feedback is embedded to reduce semantic gap and retrieve user’s preference images. Extensive and comparative experiments have been conducted to evaluate proposed framework for content based image retrieval on two databases, i.e., COIL-100 and Corel-1000. Experimental results clearly show that the proposed system surpassed other existing systems in terms of precision and recall. The proposed work achieves highest performance with average precision of 88.2% on COIL-100 and 76.3% on Corel, the average recall of 69.9% on COIL and 76.3% on Corel. Thus, the experimental results confirm that the proposed content based image retrieval system architecture attains better solution for image retrieval.

Keywords: Content based image retrieval, Curvelet transform, Genetic algorithm, Opponent color histogram, Relevance feedback.

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281 Effect of Segregation on the Reaction Rate of Sewage Sludge Pyrolysis in a Bubbling Fluidized Bed

Authors: A. Soria-Verdugo, A. Morato-Godino, L. M. García-Gutiérrez, N. García-Hernando

Abstract:

The evolution of the pyrolysis of sewage sludge in a fixed and a fluidized bed was analyzed using a novel measuring technique. This original measuring technique consists of installing the whole reactor over a precision scale, capable of measuring the mass of the complete reactor with enough precision to detect the mass released by the sewage sludge sample during its pyrolysis. The inert conditions required for the pyrolysis process were obtained supplying the bed with a nitrogen flowrate, and the bed temperature was adjusted to either 500 ºC or 600 ºC using a group of three electric resistors. The sewage sludge sample was supplied through the top of the bed in a batch of 10 g. The measurement of the mass released by the sewage sludge sample was employed to determine the evolution of the reaction rate during the pyrolysis, the total amount of volatile matter released, and the pyrolysis time. The pyrolysis tests of sewage sludge in the fluidized bed were conducted using two different bed materials of the same size but different densities: silica sand and sepiolite particles. The higher density of silica sand particles induces a flotsam behavior for the sewage sludge particles which move close to the bed surface. In contrast, the lower density of sepiolite produces a neutrally-buoyant behavior for the sewage sludge particles, which shows a proper circulation throughout the whole bed in this case. The analysis of the evolution of the pyrolysis process in both fluidized beds show that the pyrolysis is faster when buoyancy effects are negligible, i.e. in the bed conformed by sepiolite particles. Moreover, sepiolite was found to show an absorbent capability for the volatile matter released during the pyrolysis of sewage sludge.

Keywords: Bubbling fluidized bed, pyrolysis time, segregation effects, sewage sludge.

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280 COVID_ICU_BERT: A Fine-tuned Language Model for COVID-19 Intensive Care Unit Clinical Notes

Authors: Shahad Nagoor, Lucy Hederman, Kevin Koidl, Annalina Caputo

Abstract:

Doctors’ notes reflect their impressions, attitudes, clinical sense, and opinions about patients’ conditions and progress, and other information that is essential for doctors’ daily clinical decisions. Despite their value, clinical notes are insufficiently researched within the language processing community. Automatically extracting information from unstructured text data is known to be a difficult task as opposed to dealing with structured information such as physiological vital signs, images and laboratory results. The aim of this research is to investigate how Natural Language Processing (NLP) techniques and machine learning techniques applied to clinician notes can assist in doctors’ decision making in Intensive Care Unit (ICU) for coronavirus disease 2019 (COVID-19) patients. The hypothesis is that clinical outcomes like survival or mortality can be useful to influence the judgement of clinical sentiment in ICU clinical notes. This paper presents two contributions: first, we introduce COVID_ICU_BERT, a fine-tuned version of a clinical transformer model that can reliably predict clinical sentiment for notes of COVID patients in ICU. We train the model on clinical notes for COVID-19 patients, ones not previously seen by Bio_ClinicalBERT or Bio_Discharge_Summary_BERT. The model which was based on Bio_ClinicalBERT achieves higher predictive accuracy than the one based on Bio_Discharge_Summary_BERT (Acc 93.33%, AUC 0.98, and Precision 0.96). Second, we perform data augmentation using clinical contextual word embedding that is based on a pre-trained clinical model to balance the samples in each class in the data (survived vs. deceased patients). Data augmentation improves the accuracy of prediction slightly (Acc 96.67%, AUC 0.98, and Precision 0.92).

Keywords: BERT fine-tuning, clinical sentiment, COVID-19, data augmentation.

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279 Effect of Fly Ash Fineness on Sorption Properties of Geopolymers Based On Liquid Glass

Authors: M. Zelinkova, M. Ondova

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Fly ash (FA) thanks to the significant presence of SiO2 and Al2O3 as the main components is a potential raw material for geopolymers production. Mechanical activation is a method for improving FA reactivity and also the porosity of final mixture; those parameters can be analysed through sorption properties. They have direct impact on the durability of fly ash based geopolymer mortars. In the paper, effect of FA fineness on sorption properties of geopolymers based on sodium silicate, as well as relationship between fly ash fineness and apparent density, compressive and flexural strength of geopolymers are presented. The best results in the evaluated area reached the sample H1, which contents the highest portion of particle under 20μm (100% of GFA). The interdependence of individual tested properties was confirmed for geopolymer mixtures corresponding to those in the cement based mixtures: higher is portion of fine particles < 20μm, higher is strength, density and lower are sorption properties. The compressive strength as well as sorption parameters of the geopolymer can be reasonably controlled by grinding process and also ensured by the higher share of fine particle (to 20μm) in total mass of the material.

Keywords: Alkali activation, geopolymers, fly ash, particle fineness.

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278 Navigation and Guidance System Architectures for Small Unmanned Aircraft Applications

Authors: Roberto Sabatini, Celia Bartel, Anish Kaharkar, Tesheen Shaid, Subramanian Ramasamy

Abstract:

Two multisensor system architectures for navigation and guidance of small Unmanned Aircraft (UA) are presented and compared. The main objective of our research is to design a compact, light and relatively inexpensive system capable of providing the required navigation performance in all phases of flight of small UA, with a special focus on precision approach and landing, where Vision Based Navigation (VBN) techniques can be fully exploited in a multisensor integrated architecture. Various existing techniques for VBN are compared and the Appearance-Based Navigation (ABN) approach is selected for implementation. Feature extraction and optical flow techniques are employed to estimate flight parameters such as roll angle, pitch angle, deviation from the runway centreline and body rates. Additionally, we address the possible synergies of VBN, Global Navigation Satellite System (GNSS) and MEMS-IMU (Micro-Electromechanical System Inertial Measurement Unit) sensors, and the use of Aircraft Dynamics Model (ADM) to provide additional information suitable to compensate for the shortcomings of VBN and MEMS-IMU sensors in high-dynamics attitude determination tasks. An Extended Kalman Filter (EKF) is developed to fuse the information provided by the different sensors and to provide estimates of position, velocity and attitude of the UA platform in real-time. The key mathematical models describing the two architectures i.e., VBN-IMU-GNSS (VIG) system and VIGADM (VIGA) system are introduced. The first architecture uses VBN and GNSS to augment the MEMS-IMU. The second mode also includes the ADM to provide augmentation of the attitude channel. Simulation of these two modes is carried out and the performances of the two schemes are compared in a small UA integration scheme (i.e., AEROSONDE UA platform) exploring a representative cross-section of this UA operational flight envelope, including high dynamics manoeuvres and CAT-I to CAT-III precision approach tasks. Simulation of the first system architecture (i.e., VIG system) shows that the integrated system can reach position, velocity and attitude accuracies compatible with the Required Navigation Performance (RNP) requirements. Simulation of the VIGA system also shows promising results since the achieved attitude accuracy is higher using the VBN-IMU-ADM than using VBN-IMU only. A comparison of VIG and VIGA system is also performed and it shows that the position and attitude accuracy of the proposed VIG and VIGA systems are both compatible with the RNP specified in the various UA flight phases, including precision approach down to CAT-II.

Keywords: Global Navigation Satellite System (GNSS), Lowcost Navigation Sensors, MEMS Inertial Measurement Unit (IMU), Unmanned Aerial Vehicle, Vision Based Navigation.

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277 Characterization of Cement Mortar Based on Fine Quartz

Authors: K. Arroudj, M. Lanez, M. N. Oudjit

Abstract:

The introduction of siliceous mineral additions in cement production allows, in addition to the ecological and economic gain, improvement of concrete performance. This improvement is mainly due to the fixing of Portlandite, released during the hydration of cement, by fine siliceous, forming denser calcium silicate hydrates and therefore a more compact cementitious matrix. This research is part of the valuation of the Dune Sand (DS) in the cement industry in Algeria. The high silica content of DS motivated us to study its effect, at ground state, on the properties of mortars in fresh and hardened state. For this purpose, cement pastes and mortars based on ground dune sand (fine quartz) has been analyzed with a replacement to cement of 15%, 20% and 25%. This substitution has reduced the amount of heat of hydration and avoids any risk of initial cracking. In addition, the grinding of the dune sand provides amorphous thin populations adsorbed at the surface of the crystal particles of quartz. Which gives to ground quartz pozzolanic character. This character results an improvement of mechanical strength of mortar (66 MPa in the presence of 25% of ground quartz).

Keywords: Mineralogical structure, Pozzolanic reactivity, quartz, mechanical strength.

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276 Universal Metadata Definition

Authors: Mohib ur Rehman, Mohammad Haseeb Anwer, Nadeem Iftikhar

Abstract:

The need to have standards has always been a priority of all the disciplines in the world. Today, standards such as XML and USB are trying to create a universal interface for their respective areas. The information regarding every family in the discipline addressed, must have a lot in common, known as Metadata. A lot of work has been done in specific domains such as IEEE LOM and MPEG-7 but they do not appeal to the universality of creating Metadata for all entities, where we take an entity (object) as, not restricted to Software Terms. This paper tries to address this problem of universal Metadata Definition which may lead to increase in precision of search.

Keywords: Metadata, Standard, Universal, XML.

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