Search results for: oxygen extraction fraction; TIA

Authors: Amit Kumar Bhandary, Prithviraj Gupta, Siddhartha Mukherjee, Mahua Ghosh Chaudhuri, Rajib Dey

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Chromite ores are primarily used for extraction of chromium, which is an expensive metal. For low grade chromite ores (containing less than 40% Cr₂O₃), the chromium extraction is not usually economically viable. India possesses huge quantities of low grade chromite reserves. This deposit can be utilized after proper physical beneficiation. Magnetic separation techniques may be useful after reduction for the beneficiation of low grade chromite ore. The sample collected from the sukinda mines is characterized by XRD which shows predominant phases like maghemite, chromite, silica, magnesia and alumina. The raw ore is crushed and ground to below 75 micrometer size. The microstructure of the ore shows that the chromite grains surrounded by a silicate matrix and porosity observed the exposed side of the chromite ore. However, this ore may be utilized in refractory applications. Chromite ores contain Cr₂O₃, FeO, Al₂O₃ and other oxides like Fe-Cr, Mg-Cr have a high tendency to form spinel compounds, which usually show high refractoriness. Initially, the low grade chromite ore (containing 34.8% Cr₂O₃) was reduced at 1200 ⁰C for 80 minutes with 30% coke fines by weight, before being subjected to magnetic separation. The reduction by coke leads to conversion of higher state of iron oxides converted to lower state of iron oxides. The pre-reduced samples are then characterized by XRD. The magnetically inert mass was then reacted with 20% MgO by weight at 1450 ⁰C for 2 hours. The resultant product was then tested for various refractoriness parameters like apparent porosity, slag resistance etc. The results were satisfactory, indicating that the resultant spinel compounds are suitable for refractory applications for elevated temperature processes.

Keywords: apparent porosity, beneficiation, low-grade chromite, refractory, spinel compounds, slag resistance

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Authors: Jung-Ho Moon, Tae Kwon Ha

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The effect of Yttrium addition on the microstructure and mechanical properties of Sn-Zn eutectic alloy, which has been attracting intensive focus as a Pb-free solder material, was investigated in this study. Phase equilibrium has been calculated by using FactSage® to evaluate the composition and fraction of equilibrium intermetallic compounds and construct a phase diagram. In the case of Sn-8.8 Zn eutectic alloy, the as-cast microstructure was typical lamellar. With addition of 0.25 wt. %Y, a large amount of pro-eutectic phases have been observed and various YZnx intermetallic compounds were expected to successively form during cooling. Hardness of Sn-8.8 Zn alloy was not affected by Y-addition and both alloys could be rolled by 90% at room temperature.

Keywords: Sn-Zn eutectic alloy, yttrium, FactSage®, microstructure, mechanical properties

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Authors: Chijioke Okafor, Malik Maaza, Touhami Mokrani

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Proton exchange membrane, PEM was developed and tested for potential application in fuel cell. Nafion was electrospun to nanofiber network with the aid of poly(ethylene oxide), PEO, as a carrier polymer. The matrix polymer was crosslinked with Norland Optical Adhesive 63 under UV after compacting and annealing. The welded nanofiber mat was characterized for morphology, proton conductivity, and methanol permeability, then tested in a single cell test station. The results of the fabricated nanofiber membrane showed a proton conductivity of 0.1 S/cm at 25 oC and higher fiber volume fraction; methanol permeability of 3.6x10^-6 cm2/s and power density of 96.1 and 81.2 mW/cm2 for 5M and 1M methanol concentration respectively.

Keywords: fuel cell, nafion, nanofiber, permeability

Procedia PDF Downloads 477

Authors: Silvia Grassi, Stefano Schiavon, Ernestina Casiraghi, Cristina Alamprese

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Dry-cured ham is an uncooked meat product particularly appreciated for its peculiar sensory traits among which lipid component plays a key role in defining quality and, consequently, consumers’ acceptability. Usually, fat content and distribution are chemically determined by expensive, time-consuming, and destructive analyses. Moreover, different sensory techniques are applied to assess product conformity to desired standards. In this context, visual systems are getting a foothold in the meat market envisioning more reliable and time-saving assessment of food quality traits. The present work aims at developing a simple but systematic and objective visual methodology to assess the fat amount of dry-cured ham slices, in terms of total, intermuscular and intramuscular fractions. To the aim, 160 slices from 80 PDO dry-cured hams were evaluated by digital image analysis and Soxhlet extraction. RGB images were captured by a flatbed scanner, converted in grey-scale images, and segmented based on intensity histograms as well as on a multi-stage algorithm aimed at edge enhancement. The latter was performed applying the Canny algorithm, which consists of image noise reduction, calculation of the intensity gradient for each image, spurious response removal, actual thresholding on corrected images, and confirmation of strong edge boundaries. The approach allowed for the automatic calculation of total, intermuscular and intramuscular fat fractions as percentages of the total slice area. Linear regression models were run to estimate the relationships between the image analysis results and the chemical data, thus allowing for the prediction of the total, intermuscular and intramuscular fat content by the dry-cured ham images. The goodness of fit of the obtained models was confirmed in terms of coefficient of determination (R²), hypothesis testing and pattern of residuals. Good regression models have been found being 0.73, 0.82, and 0.73 the R2 values for the total fat, the sum of intermuscular and intramuscular fat and the intermuscular fraction, respectively. In conclusion, the edge enhancement visual procedure brought to a good fat segmentation making the simple visual approach for the quantification of the different fat fractions in dry-cured ham slices sufficiently simple, accurate and precise. The presented image analysis approach steers towards the development of instruments that can overcome destructive, tedious and time-consuming chemical determinations. As future perspectives, the results of the proposed image analysis methodology will be compared with those of sensory tests in order to develop a fast grading method of dry-cured hams based on fat distribution. Therefore, the system will be able not only to predict the actual fat content but it will also reflect the visual appearance of samples as perceived by consumers.

Keywords: dry-cured ham, edge detection algorithm, fat content, image analysis

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Authors: M. Feliciano, F. Maia, A. Gonçalves

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Olive oil production sector plays an important role in Portuguese economy. It had a major growth over the last decade, increasing its weight in the overall national exports. International market penetration for Mediterranean traditional products is increasingly more demanding, especially in the Northern European markets, where consumers are looking for more sustainable products. Trying to support this growing demand this study addresses olive oil production under the environmental and eco-efficiency perspectives. The analysis considers two consecutive product life cycle stages: olive trees farming; and olive oil extraction in mills. Addressing olive farming, data collection covered two different organizations: a middle-size farm (~12ha) (F1) and a large-size farm (~100ha) (F2). Results from both farms show that olive collection activities are responsible for the largest amounts of Green House Gases (GHG) emissions. In this activities, estimate for the Carbon Footprint per olive was higher in F2 (188g CO2e/kgolive) than in F1 (148g CO2e/kgolive). Considering olive oil extraction, two different mills were considered: one using a two-phase system (2P) and other with a three-phase system (3P). Results from the study of two mills show that there is a much higher use of water in 3P. Energy intensity (EI) is similar in both mills. When evaluating the GHG generated, two conditions are evaluated: a biomass neutral condition resulting on a carbon footprint higher in 3P (184g CO2e/Lolive oil) than in 2P (92g CO2e/Lolive oil); and a non-neutral biomass condition in which 2P increase its carbon footprint to 273g CO2e/Lolive oil. When addressing the carbon footprint of possible combinations among studied subsystems, results suggest that olive harvesting is the major source for GHG.

Keywords: carbon footprint, environmental indicators, farming subsystem, industrial subsystem, olive oil

Procedia PDF Downloads 282

Authors: Caroline M. B. De Araujo, Helenise A. Do Nascimento, Claudia J. Da S. Cavalcanti, Mauricio A. Da Motta Sobrinho, Maria F. Pimentel

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Oil production is often followed by the joint production of water and gas. During the journey up to the surface, due to severe conditions of temperature and pressure, the mixing between these three components normally occurs. Thus, the three phases separation process must be one of the first steps to be performed after crude oil extraction, where the water-oil separation is the most complex and important step, since the presence of water into the process line can increase corrosion and hydrates formation. A wide range of methods can be applied in order to proceed with oil-water separation, being more commonly used: flotation, hydrocyclones, as well as the three phase separator vessels. Facing what has been presented so far, it is the aim of this paper to study a system consisting of a three-phase separator, evaluating the influence of three variables: temperature, working pressure and separator type, for two types of oil (light and heavy), by performing two factorial design plans 23, in order to find the best operating condition. In this case, the purpose is to obtain the greatest oil flow rate in the product stream (m3/h) as well as the lowest percentage of water in the oil stream. The simulation of the three-phase separator was performed using Aspen Hysys®2006 simulation software in stationary mode, and the evaluation of the factorial experimental designs was performed using the software Statistica®. From the general analysis of the four normal probability plots of effects obtained, it was observed that interaction effects of two and three factors did not show statistical significance at 95% confidence, since all the values were very close to zero. Similarly, the main effect "separator type" did not show significant statistical influence in any situation. As in this case, it has been assumed that the volumetric flow of water, oil and gas were equal in the inlet stream, the effect separator type, in fact, may not be significant for the proposed system. Nevertheless, the main effect “temperature” was significant for both responses (oil flow rate and mass fraction of water in the oil stream), considering both light and heavy oil, so that the best operation condition occurs with the temperature at its lowest level (30oC), since the higher the temperature, the liquid oil components pass into the vapor phase, going to the gas stream. Furthermore, the higher the temperature, the higher the formation water vapor, so that ends up going into the lighter stream (oil stream), making the separation process more difficult. Regarding the “working pressure”, this effect showed to be significant only for the oil flow rate, so that the best operation condition occurs with the pressure at its highest level (9bar), since a higher operating pressure, in this case, indicated a lower pressure drop inside the vessel, generating lower level of turbulence inside the separator. In conclusion, the best-operating condition obtained for the proposed system, at the studied range, occurs for temperature is at its lowest level and the working pressure is at its highest level.

Keywords: factorial experimental design, oil production, simulation, three-phase separator

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Authors: Kleche Myriam, Ziane Nadia, Berrebbah Houria, Djebar Mohammed Reda

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The Phytoremediation has now become a necessity. Thus, in our work, we are interested in the biological wastewater treatment of Oued Meboudja. The physicochemical analysis of water after treatment showed a significant reduction of suspended matter, COD and BOD5 and rate of metals in roots for example iron and zinc. We also highlighted some significant changes in biometric and physiological parameters such as increasing the number of roots and increased respiratory metabolism through the oxygen consumption in isolated roots of Phragmites australis, placed in a polluted environment.

Keywords: phragmites australis, roots, phytoremediation, iron, zinc

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Authors: Marija Milašinović-Šeremešić, Valentina Semenčenko, Milica Radosavljević, Dušanka Terzić, Ljiljana Mojović, Ljubica Dokić

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Maize (Zea mays L.) is one of the most important cereal crops, and as such, one of the most significant naturally renewable carbohydrate raw materials for the production of energy and multitude of different products. The main goal of the present study was to investigate a suitability of selected maize hybrids of different genetic background produced in Maize Research Institute ‘Zemun Polje’, Belgrade, Serbia, for starch, bioethanol and animal feed production. All the hybrids are commercial and their detailed characterization is important for the expansion of their different uses. The starches were isolated by using a 100-g laboratory maize wet-milling procedure. Hydrolysis experiments were done in two steps (liquefaction with Termamyl SC, and saccharification with SAN Extra L). Starch hydrolysates obtained by the two-step hydrolysis of the corn flour starch were subjected to fermentation by S. cerevisiae var. ellipsoideus under semi-anaerobic conditions. The digestibility based on enzymatic solubility was performed by the Aufréré method. All investigated ZP maize hybrids had very different physical characteristics and chemical composition which could allow various possibilities of their use. The amount of hard (vitreous) and soft (floury) endosperm in kernel is considered one of the most important parameters that can influence the starch and bioethanol yields. Hybrids with a lower test weight and density and a greater proportion of soft endosperm fraction had a higher yield, recovery and purity of starch. Among the chemical composition parameters only starch content significantly affected the starch yield. Starch yields of studied maize hybrids ranged from 58.8% in ZP 633 to 69.0% in ZP 808. The lowest bioethanol yield of 7.25% w/w was obtained for hybrid ZP 611k and the highest by hybrid ZP 434 (8.96% w/w). A very significant correlation was determined between kernel starch content and the bioethanol yield, as well as volumetric productivity (48h) (r=0.66). Obtained results showed that the NDF, ADF and ADL contents in the whole maize plant of the observed ZP maize hybrids varied from 40.0% to 60.1%, 18.6% to 32.1%, and 1.4% to 3.1%, respectively. The difference in the digestibility of the dry matter of the whole plant among hybrids (ZP 735 and ZP 560) amounted to 18.1%. Moreover, the differences in the contents of the lignocelluloses fraction affected the differences in dry matter digestibility. From the results it can be concluded that genetic background of the selected maize hybrids plays an important part in estimation of the technological value of maize hybrids for various purposes. Obtained results are of an exceptional importance for the breeding programs and selection of potentially most suitable maize hybrids for starch, bioethanol and animal feed production.

Keywords: bioethanol, biomass quality, maize, starch

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Authors: Sang-Keun Moon, Hong-Rok Lim, Jin-O Kim

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This paper presents a Power Quality (PQ) modeling and filtering processes for the distribution system disturbances using recognition learning methods. Typical PQ waveforms with mathematical applications and gathered field data are applied to the proposed models. The objective of this paper is analyzing PQ data with respect to monitoring, discriminating, and evaluating the waveform of power disturbances to ensure the system preventative system failure protections and complex system problem estimations. Examined signal filtering techniques are used for the field waveform noises and feature extractions. Using extraction and learning classification techniques, the efficiency was verified for the recognition of the PQ disturbances with focusing on interactive modeling methods in this paper. The waveform of selected 8 disturbances is modeled with randomized parameters of IEEE 1159 PQ ranges. The range, parameters, and weights are updated regarding field waveform obtained. Along with voltages, currents have same process to obtain the waveform features as the voltage apart from some of ratings and filters. Changing loads are causing the distortion in the voltage waveform due to the drawing of the different patterns of current variation. In the conclusion, PQ disturbances in the voltage and current waveforms indicate different types of patterns of variations and disturbance, and a modified technique based on the symmetrical components in time domain was proposed in this paper for the PQ disturbances detection and then classification. Our method is based on the fact that obtained waveforms from suggested trigger conditions contain potential information for abnormality detections. The extracted features are sequentially applied to estimation and recognition learning modules for further studies.

Keywords: power quality recognition, PQ modeling, waveform feature extraction, disturbance trigger condition, PQ signal filtering

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Authors: Lee Derk Huan, Nur Irmawati

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This paper aims to investigate the heat transfer and fluid flow characteristics of nanofluids used in spray cooling systems. The effect of spray height, type of nanofluids and concentration of nanofluids are numerically investigated. Five different nanofluids such as AgH2O, Al2O3, CuO, SiO2 and TiO2 with volume fraction range of 0.5% to 2.5% are used. The results revealed that the heat transfer performance decreases as spray height increases. It is found that TiO2 has the highest transfer coefficient among other nanofluids. In dilute spray conditions, low concentration of nanofluids is observed to be more effective in heat removal in a spray cooling system.

Keywords: numerical investigation, spray cooling, heat transfer, nanofluids

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Authors: Kai-Shiang Chang, Shiao-Shing Chen, Saikat Sinha Ray, Hung-Te Hsu

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In recent years, membrane bioreactors (MBR) have been widely utilized as it can effectively replace conventional activated sludge process (CAS). Membrane bioreactor (MBR) is found to be more effective technology compared to other conventional activated sludge process and advanced membrane separation technique. Additionally, as far as the MBR is concerned, it is having excellent control of sludge retention time (SRT) and hydraulic retention time (HRT) and conducive to the retention of high concentration of sludge biomass. The membrane bioreactor (MBR) can effectively reduce footprint in terms of area and omit the secondary processing procedures in the conventional activated sludge process (CAS). Currently, as per the membrane technology, the ceramic membrane is found to have highly strong anti-acid-base properties, and it is more suitable than polymeric membrane while using for backwash and chemical cleaning. This study is based upon the treatment of Cutting Fluid wastewater, as the Cutting Fluid is widely used in the cutting equipment. However, the Cutting Fluid wastewater is very difficult to treat. In this study, the ceramic membrane was used and combine with of MBR system to treat the Cutting Fluid wastewater. In this present study, different kind of chemical coagulants have been utilized for pretreatment purpose in order to get the supernatant and simultaneously this wastewater (supernatant) was treated by MBR process. Nevertheless, ceramic membrane has three advantages such as high mechanical strength, drug resistance and reuse. During the experiment, the backwash technique was used for every interval of 10 minutes in order to avoid fouling of the membrane. In this study, during pretreatment the Chemical Oxygen Demand (COD) removal efficiency was found to be 71-86% and oil removal efficiency was analyzed to be 83-92%. This pretreatment study suggests that it is quiet effective methodology to reduce COD and oil concentration. Finally, In the MBR system when the HRT is more than 7.5 hour, the COD removal efficiency was found to be 87-93% and could achieve 100% oil removal efficiency. Coagulation test series were seen in Refs coagulants for the treatment of wastewater containing cutting oil with better oil and COD removal efficiency. The results also showed that the oil removal efficiency in the MBR system could reduce the oil content to less than 1 mg / L when the oil quality was 126 mg / L. Therefore, in this paper, the performance of membrane bioreactor by utilizing ceramic membrane has been demonstrated for treatment of Cutting Fluid wastewater.

Keywords: membrane bioreactor, cutting fluid, oil, chemical oxygen demand

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Authors: Ji Chan Kim, Seok Hong Min, Tae Kwon Ha

Abstract:

The effect of Yttrium addition on the microstructure and mechanical properties of Sn-Zn eutectic alloy, which has been attracting intensive focus as a Pb-free solder material, was investigated in this study. Phase equilibrium has been calculated by using FactSage® to evaluate the composition and fraction of equilibrium intermetallic compounds and construct a phase diagram. In the case of Sn-8.8 Zn eutectic alloy, the as-cast microstructure was typical lamellar. With addition of 0.25 wt. %Y, a large amount of pro-eutectic phases have been observed and various YZnx intermetallic compounds were expected to successively form during cooling. Hardness of Sn-8.8 Zn alloy was not affected by Y-addition and both alloys could be rolled by 90% at room temperature.

Keywords: lead-free solder, zn-al-sn alloy, phase equilibrium, rolling, microstructure, hardness

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Authors: Nima Samie, Batoul Sadat Haerian, Sekaran Muniandy, M. S. Kanthimathi

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Colon and breast cancers are categorized as the most prevalent types of cancer worldwide. Recently, the broad clinical application of metal complex compounds has led to the discovery of potential therapeutic drugs. The aim of this study was to evaluate the cytotoxic action of a selected nickel complex compound (NCC) against human colon and breast cancer cells. In this context, we determined the potency of the compound in the induction of apoptosis, cell cycle arrest, and cytoskeleton rearrangement. HT-29, WiDr, CCD-18Co, MCF-7 and Hs 190.T cell lines were used to determine the IC50 of the compound using the MTT assay. Analysis of apoptosis was carried out using immunofluorescence, acridine orange/ propidium iodide double staining, Annexin-V-FITC assay, evaluation of the translocation of NF-kB, oxygen radical antioxidant capacity, quenching of reactive oxygen species content , measurement of LDH release, caspase-3/-7, -8 and -9 assays and western blotting. The cell cycle arrest was examined using flowcytometry and gene expression was assessed using qPCR array. Results showed that our nickel complex compound displayed a potent suppressive effect on HT-29, WiDr, MCF-7 and Hs 190.T after 24 h of treatment with IC50 value of 2.02±0.54, 2.13±0.65, 3.76±015 and 3.14±0.45 µM respectively. This cytotoxic effect on normal cells was insignificant. Dipping in the mitochondrial membrane potential and increased release of cytochrome c from the mitochondria indicated induction of the intrinsic apoptosis pathway by the nickel complex compound. Activation of this pathway was further evidenced by significant activation of caspase 9 and 3/7.The nickel complex compound (NCC) was also shown activate the extrinsic pathways of apoptosis by activation of caspase-8 which is linked to the suppression of NF-kB translocation to the nucleus. Cell cycle arrest in the G1 phase and up-regulation of glutathione reductase, based on excessive ROS production were also observed. The results of this study suggest that the nickel complex compound is a potent anti-cancer agent inducing both intrinsic and extrinsic pathways as well as cell cycle arrest in colon and breast cancer cells.

Keywords: nickel complex, apoptosis, cytoskeletal rearrangement, colon cancer, breast cancer

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Authors: Chahrazed Zouaoui

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In recent years, the volume of geospatial information is increasing due to the evolution of communication technologies and information, this information is presented often by geographic information systems (GIS) and stored on of spatial databases (BDS). The classical data mining revealed a weakness in knowledge extraction at these enormous amounts of data due to the particularity of these spatial entities, which are characterized by the interdependence between them (1st law of geography). This gave rise to spatial data mining. Spatial data mining is a process of analyzing geographic data, which allows the extraction of knowledge and spatial relationships from geospatial data, including methods of this process we distinguish the monothematic and thematic, geo- Clustering is one of the main tasks of spatial data mining, which is registered in the part of the monothematic method. It includes geo-spatial entities similar in the same class and it affects more dissimilar to the different classes. In other words, maximize intra-class similarity and minimize inter similarity classes. Taking account of the particularity of geo-spatial data. Two approaches to geo-clustering exist, the dynamic processing of data involves applying algorithms designed for the direct treatment of spatial data, and the approach based on the spatial data pre-processing, which consists of applying clustering algorithms classic pre-processed data (by integration of spatial relationships). This approach (based on pre-treatment) is quite complex in different cases, so the search for approximate solutions involves the use of approximation algorithms, including the algorithms we are interested in dedicated approaches (clustering methods for partitioning and methods for density) and approaching bees (biomimetic approach), our study is proposed to design very significant to this problem, using different algorithms for automatically detecting geo-spatial neighborhood in order to implement the method of geo- clustering by pre-treatment, and the application of the bees algorithm to this problem for the first time in the field of geo-spatial.

Keywords: mining, GIS, geo-clustering, neighborhood

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Authors: Ruth Diego, Luis M. Romeo, Antonio Morán

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In the present work, a study of the coupling of a Bioelectrochemical System together with an oxy-combustion boiler is carried out; specifically, it proposes to connect the combustion gas outlet of a boiler with a microbial electrolysis cell (MEC) where the CO2 from the gases are transformed into methane in the cathode chamber, and the oxygen produced in the anode chamber is recirculated to the oxy-combustion boiler. The MEC mainly consists of two electrodes (anode and cathode) immersed in an aqueous electrolyte; these electrodes are separated by a proton exchange membrane (PEM). In this case, the anode is abiotic (where oxygen is produced), and it is at the cathode that an electroactive biofilm is formed with microorganisms that catalyze the CO2 reduction reactions. Real data from an oxy-combustion process in a boiler of around 20 thermal MW have been used for this study and are combined with data obtained on a smaller scale (laboratory-pilot scale) to determine the yields that could be obtained considering the system as environmentally sustainable energy storage. In this way, an attempt is made to integrate a relatively conventional energy production system (oxy-combustion) with a biological system (microbial electrolysis cell), which is a challenge to be addressed in this type of new hybrid scheme. In this way, a novel concept is presented with the basic dimensioning of the necessary equipment and the efficiency of the global process. In this work, it has been calculated that the efficiency of this power-to-gas system based on MEC cells when coupled to industrial processes is of the same order of magnitude as the most promising equivalent routes. The proposed process has two main limitations, the overpotentials in the electrodes that penalize the overall efficiency and the need for storage tanks for the process gases. The results of the calculations carried out in this work show that certain real potentials achieve an acceptable performance. Regarding the tanks, with adequate dimensioning, it is possible to achieve complete autonomy. The proposed system called OxyMES provides energy storage without energetically penalizing the process when compared to an oxy-combustion plant with conventional CO2 capture. According to the results obtained, this system can be applied as a measure to decarbonize an industry, changing the original fuel of the oxy-combustion boiler to the biogas generated in the MEC cell. It could also be used to neutralize CO2 emissions from industry by converting it to methane and then injecting it into the natural gas grid.

Keywords: microbial electrolysis cells, oxy-combustion, co2, power-to-gas

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Authors: Tsitsi Nyukurayi Muparari, Walter Timo De Vries, Jaap Zevenbergen

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The nature of Land administration accommodates diversity in terms of both spatial data handling activities and the expertise involved, which supposedly aims to satisfy the unpredictable demands of land data and the diverse demands of the customers arising from the land. However, it is known that strategic decisions of restructuring are in most cases repelled in favour of complex structures that strive to accommodate professional diversity and diverse roles in the field of Land administration. Yet despite of this widely accepted knowledge, there is scanty theoretical knowledge concerning the psychological methodologies that can extract the deeper perceptions from the diverse spatial expertise in order to explain the invisible control arm of the polarised reception of the ideas of change. This paper evaluates Q methodology in the context of a cadastre and land registry merger (under one agency) using the Swedish cadastral system as a case study. Precisely, the aim of this paper is to evaluate the effectiveness of Q methodology towards modelling the diverse psychological perceptions of spatial professionals who are in a widely contested decision of merging the cadastre and land registry components of Land administration using the Swedish cadastral system as a case study. An empirical approach that is prescribed by Q methodology starts with the concourse development, followed by the design of statements and q sort instrument, selection of the participants, the q-sorting exercise, factor extraction by PQMethod and finally narrative development by logic of abduction. The paper uses 36 statements developed from a dominant competing value theory that stands out on its reliability and validity, purposively selects 19 participants to do the Qsorting exercise, proceeds with factor extraction from the diversity using varimax rotation and judgemental rotation provided by PQMethod and effect the narrative construction using the logic abduction. The findings from the diverse perceptions from cadastral professionals in the merger decision of land registry and cadastre components in Sweden’s mapping agency (Lantmäteriet) shows that focus is rather inclined on the perfection of the relationship between the legal expertise and technical spatial expertise. There is much emphasis on tradition, loyalty and communication attributes which concern the organisation’s internal environment rather than innovation and market attributes that reveals customer behavior and needs arising from the changing humankind-land needs. It can be concluded that Q methodology offers effective tools that pursues a psychological approach for the evaluation and gradations of the decisions of strategic change through extracting the local perceptions of spatial expertise.

Keywords: cadastre, factor extraction, land administration merger, land registry, q-methodology, rotation

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Authors: Rayenne Djemil

Abstract:

The mechanism of oxidation reaction of linoleic acid C18: 2 (9 cis12) by singlet oxygen 1O2 were theoretically investigated via using quantum chemical methods. We explored the four reaction pathways at PM3, Hartree-Fock HF and, B3LYP functional associated with the base 6-31G (d) level. The results are in favor of the first and the last reaction ways. The transition states were found by QST3 method. Thus the pathways between the transition state structures and their corresponding minima have been identified by the IRC calculations. The thermodynamic study showed that the four ways of oxidation of linoleic acid are spontaneous, exothermic and, the enthalpy values confirm that conjugate hydroperoxydes are the most favorable products.

Keywords: echanism, quantum mechanics, oxidation, linoleic acid H

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Authors: M. Tarik Boyraz, M. Bilge Imer

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Conventionally cast nickel-based super alloys, such as commercial alloy IN 738 LC, are widely used in manufacturing of industrial gas turbine blades. With carefully designed microstructure and the existence of alloying elements, the blades show improved mechanical properties at high operating temperatures and corrosive environment. The aim of this work is to model and estimate these mechanical properties of IN 738 LC alloy solely based on simulations for projected heat treatment conditions or service conditions. The microstructure (size, fraction and frequency of gamma prime- γ′ and carbide phases in gamma- γ matrix, and grain size) of IN 738 LC needs to be optimized to improve the high temperature mechanical properties by heat treatment process. This process can be performed at different soaking temperature, time and cooling rates. In this work, micro-structural evolution studies were performed experimentally at various heat treatment process conditions, and these findings were used as input for further simulation studies. The operation time, soaking temperature and cooling rate provided by experimental heat treatment procedures were used as micro-structural simulation input. The results of this simulation were compared with the size, fraction and frequency of γ′ and carbide phases, and grain size provided by SEM (EDS module and mapping), EPMA (WDS module) and optical microscope for before and after heat treatment. After iterative comparison of experimental findings and simulations, an offset was determined to fit the real time and theoretical findings. Thereby, it was possible to estimate the final micro-structure without any necessity to carry out the heat treatment experiment. The output of this microstructure simulation based on heat treatment was used as input to estimate yield stress and creep properties. Yield stress was calculated mainly as a function of precipitation, solid solution and grain boundary strengthening contributors in microstructure. Creep rate was calculated as a function of stress, temperature and microstructural factors such as dislocation density, precipitate size, inter-particle spacing of precipitates. The estimated yield stress values were compared with the corresponding experimental hardness and tensile test values. The ability to determine best heat treatment conditions that achieve the desired microstructural and mechanical properties were developed for IN 738 LC based completely on simulations.

Keywords: heat treatment, IN738LC, simulations, super-alloys

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Authors: Aminu Mohammed, Shahidul Islam

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Aframomum melegueta K.Schum commonly known as Grains of Paradise has been a popularly used spice in most of the African food preparation. Available data have shown that ethyl acetate fraction from crude ethanolic extract exhibited α-amylase and α-glucosidase inhibitory actions, improved pancreatic β-cell damage and ameliorated insulin resistance in diabetic rats. Additionally, 6-gingerol, 6-shogaol, 6-paradol and oleanolic acid are shown to be the compounds responsible for the antidiabetic action of A. melegueta. However, detail antioxidant potential of this spice in a diabetic animal model has not yet been reported. Thus, the present study investigates the effect of oral consumption of A. melegueta fruit on the in vivo antioxidant status of type 2 diabetes (T2D) model of rats. T2D was induced in rats by feeding a 10% fructose solution ad libitum for two weeks followed by a single intraperitoneal injection of streptozotocin (40 mg/kg body weight (bw)). The animals were orally administered with 150 (DAML) or 300 mg/kg bw (DAMH) of the fraction once daily for four weeks. Data were analyzed by using a statistical software package (SPSS for Windows, version 22, IBM Corporation, NY, USA) using Tukey’s-HSD multiple range post-hoc test. Values were considered significantly different at p < 0.05. According to the data, after four weeks of intervention, diabetic untreated animals showed significantly (p < 0.05) elevation of blood glucose levels. The levels of thiobarbituric acid reactive substances (TBARS) were observed to increase with concomitant reduction of reduced glutathione (GSH) levels in the serum and organs (liver, kidney, heart and pancreas) of diabetic untreated animals. The activities of endogenous antioxidant enzymes (superoxide dismutase, catalase, glutathione peroxidase, and reductase) were greatly reduced in the serum and organs of diabetic untreated animals compared to the normal animals. These alterations were reverted to near-normal after the treatment of A. melegueta fruit in the treated groups (DAML & DAMH) within the study period, especially at the dose of 300 mg/kg bw. This potent antioxidant action may partly be attributed to the presence of the 6-Gingerol, 6-shogaol and 6-paradol are known to possess antioxidant action. The results of our study showed that A. melegueta intake improved the antioxidant status of T2D rats and therefore could be used to ameliorate the diabetes-induced oxidative damage.

Keywords: Aframomum melegueta, antioxidant, ethyl acetate extract, type 2 diabetes

Procedia PDF Downloads 293

Authors: N. Szczepanska, B. Kudlak, G. Yotova, S. Tsakovski, J. Namiesnik

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In the scientific literature related to the widely understood issue of packaging materials designed to have contact with food (food contact materials), there is much information on raw materials used for their production, as well as their physiochemical properties, types, and parameters. However, not much attention is given to the issues concerning migration of toxic substances from packaging and its actual influence on the health of the final consumer, even though health protection and food safety are the priority tasks. The goal of this study was to estimate the impact of particular foodstuff packaging type, food production, and storage conditions on the degree of leaching of potentially toxic compounds and endocrine disruptors to foodstuffs using the acute toxicity test Microtox and XenoScreen YES YAS assay. The selected foodstuff packaging materials were metal cans used for fish storage and tetrapak. Five stimulants respectful to specific kinds of food were chosen in order to assess global migration: distilled water for aqueous foods with a pH above 4.5; acetic acid at 3% in distilled water for acidic aqueous food with pH below 4.5; ethanol at 5% for any food that may contain alcohol; dimethyl sulfoxide (DMSO) and artificial saliva were used in regard to the possibility of using it as an simulation medium. For each packaging three independent variables (temperature and contact time) factorial design simulant was performed. Xenobiotics migration from epoxy resins was studied at three different temperatures (25°C, 65°C, and 121°C) and extraction time of 12h, 48h and 2 weeks. Such experimental design leads to 9 experiments for each food simulant as conditions for each experiment are obtained by combination of temperature and contact time levels. Each experiment was run in triplicate for acute toxicity and in duplicate for estrogen disruption potential determination. Multi-factor analysis of variation (MANOVA) was used to evaluate the effects of the three main factors solvent, temperature (temperature regime for cup), contact time and their interactions on the respected dependent variable (acute toxicity or estrogen disruption potential). From all stimulants studied the most toxic were can and tetrapak lining acetic acid extracts that are indication for significant migration of toxic compounds. This migration increased with increase of contact time and temperature and justified the hypothesis that food products with low pH values cause significant damage internal resin filling. Can lining extracts of all simulation medias excluding distilled water and artificial saliva proved to contain androgen agonists even at 25°C and extraction time of 12h. For tetrapak extracts significant endocrine potential for acetic acid, DMSO and saliva were detected.

Keywords: food packaging, extraction, migration, toxicity, biotest

Procedia PDF Downloads 174

Authors: Krishmali N. Ekanayake, Brendan J. Holland, Colin J. Barrow, Rick Wood

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Globally, more than one-third of all food produced is lost or wasted, equating to 1.3 billion tonnes per year. Around 31.2 million tonnes of food waste are generated across the production, supply, and consumption chain in Australia. Generally, the food waste management processes adopt environmental-friendly and more sustainable approaches such as composting, anerobic digestion and energy implemented technologies. However, unavoidable, and non-recyclable food waste ends up as landfilling and incineration that involve many undesirable impacts and challenges on the environment. A biorefinery approach contributes to a waste-minimising circular economy by converting food and other organic biomass waste into valuable outputs, including feeds, nutrition, fertilisers, and biomaterials. As a solution, Green Eco Technologies has developed a food waste treatment process using WasteMaster system. The system uses charged oxygen and moderate temperatures to convert food waste, without bacteria, additives, or water, into a virtually odour-free, much reduced quantity of reusable residual material. In the context of a biorefinery, the WasteMaster dries and mills food waste into a form suitable for storage or downstream extraction/separation/concentration to create products. The focus of the study is to determine the nutritional composition of WasteMaster processed residue to potential develop aquafeed ingredients. The global aquafeed industry is projected to reach a high value market in future, which has shown high demand for the aquafeed products. Therefore, food waste can be utilized for aquaculture feed development by reducing landfill. This framework will lessen the requirement of raw crops cultivation for aquafeed development and reduce the aquaculture footprint. In the present study, the nutritional elements of processed residue are consistent with the input food waste type, which has shown that the WasteMaster is not affecting the expected nutritional distribution. The macronutrient retention values of protein, lipid, and nitrogen free extract (NFE) are detected >85%, >80%, and >95% respectively. The sensitive food components including omega 3 and omega 6 fatty acids, amino acids, and phenolic compounds have been found intact in each residue material. Preliminary analysis suggests a price comparability with current aquafeed ingredient cost making the economic feasibility. The results suggest high potentiality of aquafeed development as 5 to 10% of the ingredients to replace/partially substitute other less sustainable ingredients across biorefinery setting. Our aim is to improve the sustainability of aquaculture and reduce the environmental impacts of food waste.

Keywords: biorefinery, ffood waste residue, input, wasteMaster

Procedia PDF Downloads 61

Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

Procedia PDF Downloads 148

Authors: Sangita Pokhrel, Nalinda Somasiri, Rebecca Jeyavadhanam, Swathi Ganesan

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Tourism is a booming industry with huge future potential for global wealth and employment. There are countless data generated over social media sites every day, creating numerous opportunities to bring more insights to decision-makers. The integration of Big Data Technology into the tourism industry will allow companies to conclude where their customers have been and what they like. This information can then be used by businesses, such as those in charge of managing visitor centers or hotels, etc., and the tourist can get a clear idea of places before visiting. The technical perspective of natural language is processed by analysing the sentiment features of online reviews from tourists, and we then supply an enhanced long short-term memory (LSTM) framework for sentiment feature extraction of travel reviews. We have constructed a web review database using a crawler and web scraping technique for experimental validation to evaluate the effectiveness of our methodology. The text form of sentences was first classified through Vader and Roberta model to get the polarity of the reviews. In this paper, we have conducted study methods for feature extraction, such as Count Vectorization and TFIDF Vectorization, and implemented Convolutional Neural Network (CNN) classifier algorithm for the sentiment analysis to decide the tourist’s attitude towards the destinations is positive, negative, or simply neutral based on the review text that they posted online. The results demonstrated that from the CNN algorithm, after pre-processing and cleaning the dataset, we received an accuracy of 96.12% for the positive and negative sentiment analysis.

Keywords: counter vectorization, convolutional neural network, crawler, data technology, long short-term memory, web scraping, sentiment analysis

Procedia PDF Downloads 81

Authors: Agnieszka Antończyk, MałGorzata Ochota, Wojciech Niżański, ZdzisłAw Kiełbowicz

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The goal of the cesarean section (CS) is the delivery of healthy, vigorous pups with the provision of surgical plane anesthesia, appropriate analgesia, and rapid recovery of the dam. In human medicine, spinal or epidural anesthesia is preferred for a cesarean section as associated with a lower risk of neonatal asphyxia and the need for resuscitation. Nevertheless, the specificity of veterinary patients makes the application of regional anesthesia as a sole technique impractical, thus to obtain patient compliance the general anesthesia is required. This study aimed to compare the influence of balanced (inhalant with epidural) and inhalant anesthesia on neonatal umbilical cord blood gas (UCBG) parameters and vitality (modified Apgar scoring). The bitches (31) undergoing elective CS were enrolled in this study. All females received a single dose of 0.2 mg/kg s.c. Meloxicam. Females were randomly assigned into two groups: Gr I (Isoflurane, n=16) and Gr IE (Isoflurane plus Epidural, n=15). Anesthesia was induced with propofol at 4-6 mg/kg to effect, and maintained with isoflurane in oxygen; in IE group epidural anesthesia was also done using lidocaine (3-4 mg/kg) into the lumbosacral space. CSs were performed using a standard mid-line approach. Directly after the puppy extraction, the umbilical cord was double clamped before the placenta detachment. The vessels were gently stretched between forceps to allow blood sampling. At least 100 mcl of mixed umbilical cord blood was collected into a heparinized syringe for further analysis. The modified Apgar scoring system (AS) was used to objectively score neonatal health and vitality immediately after birth (before first aid or neonatal care was instituted), at 5 and 20 min after birth. The neonates were scored as normal (AS 7-10), weak (AS 4-6), or critical (AS 0-3). During surgery, the IE group required a lower isoflurane concentration compared to the females in group I (MAC 1.05±0.2 and 1.4±0.13, respectively, p<0.01). All investigated UCBG parameters were not statistically different between groups. All pups had mild acidosis (pH 7.21±0.08 and 7.21±0.09 in Gr I and IE, respectively) with moderately elevated pCO2 (Gr I 57.18±11.48, Gr IE 58.74±15.07), HCO3- on the lower border (Gr I 22.58±3.24, Gr IE 22.83±3.6), lowered BE (Gr I -6.1±3.57, Gr IE -5.6±4.19) and mildly elevated level of lactates (Gr I 2.58±1.48, Gr IE2.53±1.03). The glucose levels were above the reference limits in both groups of puppies (74.50±25.32 in Gr I, 79.50±29.73 in Gr IE). The initial Apgar score results were similar in I and IE groups. However, the subsequent measurements of AS revealed significant differences between both groups. Puppies from the IE group received better AS scores at 5 and 20 min compared to the I group (6.86±2.23 and 8.06±2.06 vs 5.11±2.40 and 7.83±2.05, respectively). The obtained results demonstrated that administration of epidural anesthesia reduced the requirement for isoflurane in dams undergoing cesarean section and did not affect the neonatal umbilical blood gas results. Moreover, newborns from the epidural anesthesia group were scored significantly higher in AS at 5 and 20 min, indicating their better vitality and quicker improvement post-surgery.

Keywords: apgar scoring, balanced anesthesia, cesarean section, umbilical blood gas

Procedia PDF Downloads 172

Authors: Prashanth Pillai, Purnaprajna Mangsuli

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Oil exploration and production companies invest considerable time and efforts to extract essential well attributes (like well status, surface, and target coordinates, wellbore depths, event timelines, etc.) from unstructured data sources like technical reports, which are often non-standardized, multimodal, and highly domain-specific by nature. It is also important to consider the context when extracting attribute values from reports that contain information on multiple wells/wellbores. Moreover, semantically similar information may often be depicted in different data syntax representations across multiple pages and document sources. We propose a hierarchical multi-source fact extraction workflow based on a deep learning framework to extract essential well attributes at scale. An information retrieval module based on the transformer architecture was used to rank relevant pages in a document source utilizing the page image embeddings and semantic text embeddings. A question answering framework utilizingLayoutLM transformer was used to extract attribute-value pairs incorporating the text semantics and layout information from top relevant pages in a document. To better handle context while dealing with multi-well reports, we incorporate a dynamic query generation module to resolve ambiguities. The extracted attribute information from various pages and documents are standardized to a common representation using a parser module to facilitate information comparison and aggregation. Finally, we use a probabilistic approach to fuse information extracted from multiple sources into a coherent well record. The applicability of the proposed approach and related performance was studied on several real-life well technical reports.

Keywords: natural language processing, deep learning, transformers, information retrieval

Procedia PDF Downloads 189

Authors: Xiang Zheng, Zhaoping Zhong

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In this study, Aspen Plus was used to simulate the whole process of biomass conversion to liquid fuel in different ways, and the main results of material and energy flow were obtained. The process optimization and evaluation were carried out on the four routes of cellulosic biomass pyrolysis gasification low-carbon olefin synthesis olefin oligomerization, biomass water pyrolysis and polymerization to jet fuel, biomass fermentation to ethanol, and biomass pyrolysis to liquid fuel. The environmental impacts of three biomass species (poplar wood, corn stover, and rice husk) were compared by the gasification synthesis pathway. The global warming potential, acidification potential, and eutrophication potential of the three biomasses were the same as those of rice husk > poplar wood > corn stover. In terms of human health hazard potential and solid waste potential, the results were poplar > rice husk > corn stover. In the popular pathway, 100 kg of poplar biomass was input to obtain 11.9 kg of aviation coal fraction and 6.3 kg of gasoline fraction. The energy conversion rate of the system was 31.6% when the output product energy included only the aviation coal product. In the basic process of hydrothermal depolymerization process, 14.41 kg aviation kerosene was produced per 100 kg biomass. The energy conversion rate of the basic process was 33.09%, which can be increased to 38.47% after the optimal utilization of lignin gasification and steam reforming for hydrogen production. The total exergy efficiency of the system increased from 30.48% to 34.43% after optimization, and the exergy loss mainly came from the concentration of precursor dilute solution. Global warming potential in environmental impact is mostly affected by the production process. Poplar wood was used as raw material in the process of ethanol production from cellulosic biomass. The simulation results showed that 827.4 kg of pretreatment mixture, 450.6 kg of fermentation broth, and 24.8 kg of ethanol were produced per 100 kg of biomass. The power output of boiler combustion reached 94.1 MJ, the unit power consumption in the process was 174.9 MJ, and the energy conversion rate was 33.5%. The environmental impact was mainly concentrated in the production process and agricultural processes. On the basis of the original biomass pyrolysis to liquid fuel, the enzymatic hydrolysis lignin residue produced by cellulose fermentation to produce ethanol was used as the pyrolysis raw material, and the fermentation and pyrolysis processes were coupled. In the coupled process, 24.8 kg ethanol and 4.78 kg upgraded liquid fuel were produced per 100 kg biomass with an energy conversion rate of 35.13%.

Keywords: biomass conversion, biofuel, process optimization, life cycle assessment

Procedia PDF Downloads 67

Authors: P. Karthick, K. Mahesh

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Video has become an increasingly significant component of our digital everyday contact. With the advancement of greater contents and shows of the resolution, its significant volume poses serious obstacles to the objective of receiving, distributing, compressing, and revealing video content of high quality. In this paper, we propose the primary beginning to complete a deep video compression model that jointly upgrades all video compression components. The video compression method involves splitting the video into frames, comparing the images using convolutional neural networks (CNN) to remove duplicates, repeating the single image instead of the duplicate images by recognizing and detecting minute changes using generative adversarial network (GAN) and recorded with long short-term memory (LSTM). Instead of the complete image, the small changes generated using GAN are substituted, which helps in frame level compression. Pixel wise comparison is performed using K-nearest neighbours (KNN) over the frame, clustered with K-means, and singular value decomposition (SVD) is applied for each and every frame in the video for all three color channels [Red, Green, Blue] to decrease the dimension of the utility matrix [R, G, B] by extracting its latent factors. Video frames are packed with parameters with the aid of a codec and converted to video format, and the results are compared with the original video. Repeated experiments on several videos with different sizes, duration, frames per second (FPS), and quality results demonstrate a significant resampling rate. On average, the result produced had approximately a 10% deviation in quality and more than 50% in size when compared with the original video.

Keywords: video compression, K-means clustering, convolutional neural network, generative adversarial network, singular value decomposition, pixel visualization, stochastic gradient descent, frame per second extraction, RGB channel extraction, self-detection and deciding system

Procedia PDF Downloads 179

Authors: A. Azizi, M. Toubane, L. Chetibi

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Differential scanning calorimetry (DSC) is a widely used technique for the study of phase transformations, particularly in the study of precipitation. The kinetic of the precipitation and dissolution is always related to the concept of activation energy Ea. The determination of the activation energy gives important information about the kinetic of the precipitation reaction. In this work, we were interested in the study of the isothermal and non-isothermal treatments on the decomposition of the supersaturated solid solution in the alloy AZ91 (Mg-9 Al-Zn 1-0.2 Mn. mass fraction %), using Differential Calorimetric method. Through this method, the samples were heat treated up to 425° C, using different rates. To calculate the apparent activation energies associated with the formation of precipitated phases, we used different isoconversional methods. This study was supported by other analysis: X-ray diffraction and microhardness measurements.

Keywords: calorimetric, activation energy, AZ91 alloys, microstructural evolution

Procedia PDF Downloads 436

Authors: Nur Azlina Mohamed Mokmin, Mona Masood

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Guided by the theory of learning style, this study is based on the development of a multimedia learning application for students with mastery learning style. The learning material was developed by applying a graduated difficulty learning strategy. Algebraic fraction was chosen as the learning topic for this application. The effectiveness of this application in helping students learn is measured by giving a pre- and post-test. The result shows that students who learn using the learning material that matches their preferred learning style performs better than the students with a non-personalized learning material.

Keywords: algebraic fractions, graduated difficulty, mastery learning style, multimedia

Procedia PDF Downloads 506

Authors: Hozaifa Zaki, Ghada Soliman

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In this paper, we introduced an approach for Automated Dotted Arabic Expiration Date Extraction using Optimized Convolutional Autoencoder (ARABEX) with bidirectional LSTM. This approach is used for translating the Arabic dot-matrix expiration dates into their corresponding filled-in dates. A custom lightweight Convolutional Recurrent Neural Network (CRNN) model is then employed to extract the expiration dates. Due to the lack of available dataset images for the Arabic dot-matrix expiration date, we generated synthetic images by creating an Arabic dot-matrix True Type Font (TTF) matrix to address this limitation. Our model was trained on a realistic synthetic dataset of 3287 images, covering the period from 2019 to 2027, represented in the format of yyyy/mm/dd. We then trained our custom CRNN model using the generated synthetic images to assess the performance of our model (ARABEX) by extracting expiration dates from the translated images. Our proposed approach achieved an accuracy of 99.4% on the test dataset of 658 images, while also achieving a Structural Similarity Index (SSIM) of 0.46 for image translation on our dataset. The ARABEX approach demonstrates its ability to be applied to various downstream learning tasks, including image translation and reconstruction. Moreover, this pipeline (ARABEX+CRNN) can be seamlessly integrated into automated sorting systems to extract expiry dates and sort products accordingly during the manufacturing stage. By eliminating the need for manual entry of expiration dates, which can be time-consuming and inefficient for merchants, our approach offers significant results in terms of efficiency and accuracy for Arabic dot-matrix expiration date recognition.

Keywords: computer vision, deep learning, image processing, character recognition

Procedia PDF Downloads 78