Search results for: powder fine recycled aggregate

Authors: Bahar Salavati Vie Le Sage, Ismaïl Ben Hariz, Flavien Viguier, Sirine Noura Kahil, Audrey Jacquin, Maxime Convert

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The ballast layer plays a key role in railroad maintenance and the geometry of the track structure. Ballast also holds the track in place as the trains roll over it. Track ballast is packed between the sleepers and on the sides of railway tracks. An imbalance in ballast volume on the tracks can lead to safety issues as well as a quick degradation of the overall quality of the railway segment. If there is a lack of ballast in the track bed during the summer, there is a risk that the rails will expand and buckle slightly due to the high temperatures. Furthermore, the knowledge of the ballast quantities that will be excavated during renewal works is important for efficient ballast management. The volume of excavated ballast per meter of track can be calculated based on excavation depth, excavation width, volume of track skeleton (sleeper and rail) and sleeper spacing. Since 2012, SNCF has been collecting 3D points cloud data covering its entire railway network by using 3D laser scanning technology (LiDAR). This vast amount of data represents a modelization of the entire railway infrastructure, allowing to conduct various simulations for maintenance purposes. This paper aims to present an automated method for ballast volume estimation based on the processing of LiDAR data. The estimation of abnormal volumes in ballast on the tracks is performed by analyzing the cross-section of the track. Further, since the amount of ballast required varies depending on the track configuration, the knowledge of the ballast profile is required. Prior to track rehabilitation, excess ballast is often present in the ballast shoulders. Based on 3D laser scans, a Digital Terrain Model (DTM) was generated and automatic extraction of the ballast profiles from this data is carried out. The surplus in ballast is then estimated by performing a comparison between this ballast profile obtained empirically, and a geometric modelization of the theoretical ballast profile thresholds as dictated by maintenance standards. Ideally, this excess should be removed prior to renewal works and recycled to optimize the output of the ballast renewal machine. Based on these parameters, an application has been developed to allow the automatic measurement of ballast profiles. We evaluated the method on a 108 kilometers segment of railroad LiDAR scans, and the results show that the proposed algorithm detects ballast surplus that amounts to values close to the total quantities of spoil ballast excavated.

Keywords: ballast, railroad, LiDAR , cloud point, track ballast, 3D point

Procedia PDF Downloads 109

Authors: Lukas Ded

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Studying the tissue structure and histogenesis in the natural, 3D context is challenging but highly beneficial process. Contrary to classical approach of the physical tissue sectioning and subsequent imaging, it enables to study the relationships of individual cellular and histological structures in their native context. Recent developments in the tissue clearing approaches and microscopic volume imaging/data processing enable the application of these methods also in the areas of developmental and reproductive biology. Here, using the CLARITY tissue procedure and 3D confocal volume imaging we optimized the protocol for clearing, staining and imaging of the mice seminiferous tubules isolated from the testes without cardiac perfusion procedure. Our approach enables the high magnification and fine resolution axial imaging of the whole diameter of the seminiferous tubules with possible unlimited lateral length imaging. Hence, the large continuous pieces of the seminiferous tubule can be scanned and digitally reconstructed for the study of the single tubule seminiferous stages using nuclear dyes. Furthermore, the application of the antibodies and various molecular dyes can be used for molecular labeling of individual cellular and subcellular structures and resulting 3D images can highly increase our understanding of the spatiotemporal aspects of the seminiferous tubules development and sperm ultrastructure formation. Finally, our newly developed algorithms for 3D data processing enable the massive parallel processing of the large amount of individual cell and tissue fluorescent signatures and building the robust spermatogenic models under physiological and pathological conditions.

Keywords: CLARITY, spermatogenesis, testis, tissue clearing, volume imaging

Procedia PDF Downloads 136

Authors: Pranas Baltrėnas, Dainius Paliulis

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Cyclones are widely used for separating particles from gas in energy production objects. Efficiency of normal centrifugal air cleaning devices ranges from 85 to 90%, but weakness of many cyclones is low collection efficiency of particles less than 10 μm in diameter. Many factors have impact on cyclone efficiency – humidity, temperature, gas (air) composition, airflow velocity and etc. Many scientists evaluated only effect of origin and size of PM on cyclone efficiency. Effect of gas (air) composition and temperature on cyclone efficiency still demands contributions. Complex experimental research on efficiency of cylindrical eight-channel system with adjustable half-rings for removing fine dispersive particles (< 20 μm) was carried out. The impact of gaseous smoke components on removal of wood ashes was analyzed. Gaseous components, present in the smoke mixture, with the dynamic viscosity lower than that of same temperature air, decrease the d50 value, simultaneously increasing the overall particulate matter removal efficiency in the cyclone, i.e. this effect is attributed to CO2 and CO, while O2 and NO have the opposite effect. Air temperature influences the d50 value, an increase in air temperature yields an increase in d50 value, i.e. the overall particulate matter removal efficiency declines, the reason for this being an increasing dynamic air viscosity. At 120 °C temperature the d50 value is approximately 11.8 % higher than at air temperature of 20 °C. With an increase in smoke (gas) temperature from 20 °C to 50 °C, the aerodynamic resistance in a 1-tier eight-channel cylindrical cyclone drops from 1605 to 1380 Pa, from 1660 to 1420 Pa in a 2-tier eight-channel cylindrical cyclone, from 1715 to 1450 Pa in a 3-tier eight-channel cylindrical cyclone. The reason for a decline in aerodynamic resistance is the declining gas density. The aim of the paper is to analyze the impact of gaseous smoke components on the eight–channel cyclone with tangential inlet.

Keywords: cyclone, adjustable half-rings, particulate matter, efficiency, gaseous compounds, smoke

Procedia PDF Downloads 289

Authors: Yuri A. Kalvachev, Totka D. Todorova

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Zeolite mordenite has been investigated as a transition metal support for the preparation of efficient catalysts in the oxidation of volatile organic compounds (VOCs). The highly crystalline mordenite samples were treated with hydrofluoric acid and ammonium fluoride to get hierarchical material with secondary porosity. The obtained supports by this method have a high active surface area, good diffusion properties and prevent the extraction of metal components during catalytic reactions. The active metal phases platinum and copper were loaded by impregnation on both mordenite materials (parent and acid treated counterparts). Monometalic Pt and Cu, and bimetallic Pt/Cu catalysts were obtained. The metal phases were fine dispersed as nanoparticles on the functional porous materials. The catalysts synthesized in this way were investigated in the reaction of complete oxidation of propane and benzene. Platinum, copper and platinum/copper were loaded and there catalytic activity was investigated and compared. All samples are characterized by X-ray diffraction analysis, nitrogen adsorption, scanning electron microscopy (SEM), X-ray photoelectron measurements (XPS) and temperature programed reduction (TPR). The catalytic activity of the samples obtained is investigated in the reaction of complete oxidation of propane and benzene by using of Gas Chromatography (GC). The oxidation of three organic molecules was investigated—methane, propane and benzene. The activity of metal loaded mordenite catalysts for methane oxidation is almost the same for parent and treated mordenite as a support. For bigger molecules as propane and benzene, the activity of catalysts based on treated mordenite is higher than those based on parent zeolite.

Keywords: metal loaded catalysts, mordenite, VOCs oxidation, zeolites

Procedia PDF Downloads 130

Authors: Jackson Simon Lusagalika, Lai Hsin-Chih, Dai Yu-Tung

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Particles with an aerodynamic diameter of 2.5 meters or less are referred to as "fine particulate matter" (PM₂.₅) are easily inhaled and can go deeper into the lungs than other particles in the atmosphere, where it may have detrimental health consequences. In this study, we use a hybrid model that combined CMAQ and AERMOD as well as initial meteorological fields from the Weather Research and Forecasting (WRF) model to study the impact of power plant PM₂.₅ emissions in South Taiwan since it frequently experiences higher PM₂.₅ levels. A specific date of March 3, 2022, was chosen as a result of a power outage that prompted the bulk of power plants to shut down. In some way, it is not conceivable anywhere in the world to turn off the power for the sole purpose of doing research. Therefore, this catastrophe involving a power outage and the shutdown of power plants offers a great occasion to evaluate the impact of air pollution driven by this power sector. As a result, four numerical experiments were conducted in the study using the Continuous Emission Data System (CEMS), assuming that the power plants continued to function normally after the power outage. The hybrid model results revealed that power plants have a minor impact in the study region. However, we examined the accumulation of PM₂.₅ in the study and discovered that once the vortex at 925hPa was established and moved to the north of Taiwan's coast, the study region experienced higher observed PM₂.₅ concentrations influenced by meteorological factors. This study recommends that decision-makers take into account not only control techniques, specifically emission reductions, but also the atmospheric and meteorological implications for future investigations.

Keywords: PM₂.₅ concentration, powerplants, hybrid air quality model, CEMS, Vorticity

Procedia PDF Downloads 76

Authors: Bernard Eze Orji

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The masquerade, which is the most popular indigenous art form in Africa, is obviously identified by its elaborate, weird, and opulent costumes. The costume is the major essential accouterments in the art of the masquerade. From time past, masquerades have performed and enjoyed the freedom associated with its inscrutability and mystification solely because of its costumes. Noninitiates and women watched masquerades from a distance due to the reverence attached to its costumes and performances. In fact, whether in performance or as an item of art, the masquerade costume was seen as an embodiment of a tradition of liveliness, showiness, secrecy, and sacredness. This liveliness and showiness transformed masked characters who are believed to be possessed by spirits of ancestors and animals that inhabited the costumes. However, with the translocation of masquerade in new festivals such as carnival and state-sponsored cultural days, its costumes have been reduced to a mere item of entertainment and aesthetic values. The sacredness and reverence which hitherto elevated masquerade art to the point of wonderment have given way to an aesthetic appreciation of ingenious and individual creativity deployed in these festivals. This is as a result of the realistic and artistic creations that pervade masquerade costumes and masks in these festivals. It is a common sight to see such masquerades of animal and human genera like a lion, elephant, hippopotamus, and antelope; Agbogho Mmuo, Adamma, and Nchiekwa, respectively. This creative flair has emerged to expunge the ritual narratives associated with masquerades in the past. The study utilized performance analysis and aesthetic theory to establish that the creative ingenuity deployed by fine artists and mask designers who combine traditional artifacts to achieve modern masterpieces for the masquerades of the new festivals have reduced the ritual trappings and hype ascribed to masquerades in indigenous societies.

Keywords: costume and mask designs, entertainment, masquerade, ritual

Procedia PDF Downloads 128

Authors: Gong Zhilin, Jing Yang, Jian Yin

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The purpose of this paper is to develop a novel system for credit card fraud detection based on sequential modeling of data using hybrid deep learning models. The projected model encapsulates five major phases are pre-processing, imbalance-data handling, feature extraction, optimal feature selection, and fraud detection with an ensemble classifier. The collected raw data (input) is pre-processed to enhance the quality of the data through alleviation of the missing data, noisy data as well as null values. The pre-processed data are class imbalanced in nature, and therefore they are handled effectively with the K-means clustering-based SMOTE model. From the balanced class data, the most relevant features like improved Principal Component Analysis (PCA), statistical features (mean, median, standard deviation) and higher-order statistical features (skewness and kurtosis). Among the extracted features, the most optimal features are selected with the Self-improved Arithmetic Optimization Algorithm (SI-AOA). This SI-AOA model is the conceptual improvement of the standard Arithmetic Optimization Algorithm. The deep learning models like Long Short-Term Memory (LSTM), Convolutional Neural Network (CNN), and optimized Quantum Deep Neural Network (QDNN). The LSTM and CNN are trained with the extracted optimal features. The outcomes from LSTM and CNN will enter as input to optimized QDNN that provides the final detection outcome. Since the QDNN is the ultimate detector, its weight function is fine-tuned with the Self-improved Arithmetic Optimization Algorithm (SI-AOA).

Keywords: credit card, data mining, fraud detection, money transactions

Procedia PDF Downloads 131

Authors: J. T. Johnson, R. A. Atule, E. Gbodo

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The widespread problem of infant malnutrition in developing countries has stirred efforts in research, development and extension by both local and international organizations. As a result, the formulation and development of nutritious weaning foods from local and readily available raw materials which are cost effective has become imperative in many developing countries. Thus, local and readily available raw materials where used to compound and develop nutritious new infant formulae. The materials used for this study include maize, millet, cowpea, pumpkin, fingerlings, and fish bone. The materials where dried and blended to powder. The powders were weighed in the ratio of 4:4:4:3:1:1 respectively and were then mixed properly. Analysis of nutritive value was conducted on the formulae and compared with NAN-2 standard and results reveals that the formulae had reasonable amount of moisture, lipids, carbohydrate, protein, and fibre. Although NAN-2 was superior in both carbohydrate and protein, the new infant formula was higher in mineral elements, vitamins, fibre, and lipids. All the essentials vitamins and both macro and micro minerals where found in appreciable quantity capable of meeting the biochemical and physiological demand of the body while the anti-nutrients composition were significantly below FAO and WHO safe limits. Finally, the compounded infant formulae was feed to a set of albino Wistar rats while some other set of rats was feed with NAN-2 for the period of twenty seven (27) days and body weight was measure at three days intervals. The results of body weight changes was spectacular as their body weight over shot or almost double that of those animals that were feed with NAN-2 at each point of measurement. The results suggest that the widespread problem of infant malnutrition in the developing world especially among the low income segment of the society can now be reduced if not totally eradicated since nutritive and cost effective weaning formulae can be prepared locally from common readily available materials.

Keywords: formulation, nutritive value, local, materials

Procedia PDF Downloads 378

Authors: Saeedeh Imani Moqadam, Ilya Bobrov, Jérémy Epp, Nils Ellendt, Lutz Mädler

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High entropy alloys (HEAs), having adjustable properties and enhanced stability compared with intermetallic compounds, are solid solution alloys that contain more than five principal elements with almost equal atomic percentage. The concept of producing such alloys pave the way for developing advanced materials with unique properties. However, the synthesis of such alloys may require advanced processes with high cooling rates depending on which alloy elements are used. In this study, the micro spheres of different diameters of HEAs were generated via a drop-on-demand droplet generator and subsequently solidified during free-fall in an argon atmosphere. Such droplet generators can generate individual droplets with high reproducibility regarding droplet diameter, trajectory and cooling while avoiding any interparticle momentum or thermal coupling. Metallography as well as X-ray diffraction investigations for each diameter of the generated metallic droplets where then carried out to obtain information about the microstructural state. To calculate the cooling rate of the droplets, a droplet cooling model was developed and validated using model alloys such as CuSn%6 and AlCu%4.5 for which a correlation of secondary dendrite arm spacing (SDAS) and cooling rate is well-known. Droplets were generated from these alloys and their SDAS was determined using quantitative metallography. The cooling rate was then determined from the SDAS and used to validate the cooling rates obtained from the droplet cooling model. The application of that model on the HEA then leads to the cooling rate dependency and hence to the identification of process windows for the synthesis of these alloys. These process windows were then compared with cooling rates obtained in processes such as powder production, spray forming, selective laser melting and casting to predict if a synthesis is possible with these processes.

Keywords: cooling rate, drop-on-demand, high entropy alloys, microstructure, single droplet generation, X-ray Diffractometry

Procedia PDF Downloads 211

Authors: Tyler Palma, Praveen Damasus, Michael Munther, Mehrdad Mohsenizadeh, Keivan Davami

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The advancement of additive manufacturing, in both research and commercial realms, is highly dependent upon continuing innovations and creativity in materials and designs. Additive manufacturing shows great promise towards revolutionizing various industries, due largely to the fact that design data can be used to create complex products and components, on demand and from the raw materials, for the end user at the point of use. However, it will be critical that the material properties of additively-made parts for engineering purposes be fully understood. As it is a relatively new additive manufacturing method, the response of properties of Multi Jet Fusion (MJF) produced parts to different printing parameters has not been well studied. In this work, testing of mechanical and tribological properties MJF-printed Polyamide 12 parts was performed to determine whether printing orientation in this method results in significantly different part performances. Material properties were studied at macro- and nanoscales. Tensile tests, in combination with tribology tests including steady-state wear, were performed. Results showed a significant difference in resultant part characteristics based on whether they were printed in a vertical or horizontal orientation. Tensile performance of vertically and horizontally printed samples varied, both in ultimate strength and strain. Tribology tests showed that printing orientation has notable effects on the resulting mechanical and wear properties of tested surfaces, due largely to layer orientation and the presence of unfused fused powder grain inclusions. This research advances the understanding of how print orientation affects the mechanical properties of additively manufactured structures, and also how print orientation can be exploited in future engineering design.

Keywords: additive manufacturing, indentation, nano mechanical characterization, print orientation

Procedia PDF Downloads 137

Authors: Mahesh M. Patil, K. A. Anu-Appaiah

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Overweight and obesity is a serious medical problem, increasing in prevalence, and affecting millions worldwide. Investigators have been trying from decades to articulate the burden of obesity and related risk factors. To answer this problem, we suggest a new therapeutic anti-obesity compounds from Garcinia xanthochymus fruit. However, there is little published scientific information on non-hydroxycitric acid Garcinia species. Our findings include biochemical characterization of the fruit; in vivo toxicity and bio-efficacy study of G. xanthochymus in high fat diet wistar rat model. We observed that Garcinia pericarp is a rich source of organic acids, polyphenols, mono- (40.63%) and poly-unsaturated fatty acids (16.45%; omega-3: 10.02%). Toxicological studies have showed that Garcinia is safe and had no observed adverse effect level up to 400 mg/kg/day. Body weight and food intake was significantly (P<0.05) reduced in oral gavage treated rats (sonicated Garcinia powder) in 13 weeks. Subcutaneous fat was significantly (P<0.05) reduced in Garcinia treated rats. Hepatocytes significantly (p<0.05) overexpressed sterol regulatory element binding protein 2, liver X receptor- α, liver X receptor- β, lipoprotein lipase and monoacylglycerol lipase. Fatty acid binding protein 1 and peroxisome proliferator activated receptor- α were down regulated as assessed by real time qPCR. Currently our research is focused on the adipocyte obesity related gene expressions, effect of Garcinia on 3T3-adipocyte cell lines and high fat diet induced mice model. This in vivo pre-clinical data suggests that G. xanthochymus may have clinical utility for the treatment of obesity. However, further studies are required to establish its potency.

Keywords: Garcinia xanthochymus, anti-obesity, high fat diet, real time qPCR

Procedia PDF Downloads 251

Authors: Muhammad Waheed Mushtaq, Shahid bashir, Atta Ur Rehman

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In the past decade, the growing demand for capital and the increased utilization of supercapacitors reflect advancements in energy-producing systems and energy storage devices. Metal oxides and ferrites have emerged as promising candidates for supercapacitors and batteries. In our current study, we synthesized Lithium manganese nanoferrite, denoted as LixMnxFe₂O₄, using the hydrothermal technique. Subsequently, we treated it with sodium dodecyl benzene sulphonate (SDBS) surfactant to create nanocomposites of Lithium manganese nano ferrite (LMFe) with poly pyrrole (LixMnxFe₂O₄-PPY). We employed Powder X-ray diffraction (XRD) to confirm the crystalline nature and spinel phase structure of LMFe nanoparticles, which exhibited a single-phase crystal structure, indicating sample purity. To assess the surface topography, morphology, and grain size of both synthesized LixMnxFe₂O₄ and LixMnxFe₂O₄-PPY, we used atomic force microscopy and scanning electron microscopy (SEM). The average particle size of pure ferrite was found to be 54 nm, while that of its nanocomposite was 71 nm. Energy dispersive X-ray (EDX) analysis confirmed the presence of all required elements, including Li, Mn, Fe, and O, in the appropriate proportions. Saturation magnetization (32.69 emu), remanence (Mr), and coercive force (Hc) were measured using a Vibrating Sample Magnetometer (VSM). To assess the electrochemical performance of the material, we conducted Cyclic Voltammetry (CV) measurements for both pure LMFe and LMFe-PPY. The CV results for LMFe-PPY demonstrated that specific capacitance decreased with increasing scan rate while the area of the current-voltage loop increased. These findings are promising for the development of supercapacitors and lithium-ion batteries (LIBs).

Keywords: lithium manganese ferrite, poly pyrrole, nanocomposites, cyclic voltammetry, cathode

Procedia PDF Downloads 71

Authors: P. N. Okeke, J. N. Chikwendu

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The study evaluated the effects of varying fermentation periods on the nutrients and anti-nutrients composition of African yam bean (Sphenostylis stenocarpa) and acha (Digitaria exilis) flour blends and sensory properties of their products. The African yam bean seeds and acha grains were fermented for 24 hrs, 48 and 72 hrs, dried (sun drying) and milled into fine flour. The fermented flours were used in a ratio of 70:30 (Protein basis) to formulate composite flour for meat pie and biscuits production. Both the fermented and unfermented flours and products were analyzed for chemical composition using the standard method. The data were statistically analyzed using SPSS version 15 to determine the mean and standard deviation. The 24, 48, and 72 hrs fermentation periods increased protein (22.81, 26.15 and 24.00% respectively). The carbohydrate, ash and moisture contents of the flours were also increased as a result of fermentation (68.01-76.83, 2.26-4.88, and 8.36-13.00% respectively). The 48 hrs fermented flour blends had the highest increase in ash relative to the control (4.88%). Fermentation increased zinc, iron, magnesium and phosphorus content of the flours. Treatment drastically reduced the anti-nutrient (oxalate, saponin, tannin, phytate, and hemagglutinin) levels of the flours. Both meat pie and biscuits had increased protein relative to the control (27.36-34.28% and 23.66-25.09%). However, the protein content of the meat pie increased more than that of the biscuits. Zinc, Iron, Magnesium and phosphorus levels increased in both meat pie and biscuits. Organoleptic attributes of the products (meat pie and biscuits) were slightly lower than the control except those of the 72 hrs fermented flours.

Keywords: fermentation, African yam bean, acha, biscuits, meat-pie

Procedia PDF Downloads 277

Authors: Lu Song Ma Li Zhi

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With the rapid advancement of artificial intelligence technology, large language models (LLMs) have become a milestone in the field of natural language processing, demonstrating remarkable capabilities in semantic understanding, intelligent question answering, and text generation. These models are gradually penetrating various industries, particularly showcasing significant application potential in the data analysis domain. However, retraining or fine-tuning these models requires substantial computational resources and ample downstream task datasets, which poses a significant challenge for many enterprises and research institutions. Without modifying the internal parameters of the large models, prompt engineering techniques can rapidly adapt these models to new domains. This paper proposes a prompt design strategy aimed at leveraging the capabilities of large language models to automate the generation of data analysis code. By carefully designing prompts, data analysis requirements can be described in natural language, which the large language model can then understand and convert into executable data analysis code, thereby greatly enhancing the efficiency and convenience of data analysis. This strategy not only lowers the threshold for using large models but also significantly improves the accuracy and efficiency of data analysis. Our approach includes requirements for the precision of natural language descriptions, coverage of diverse data analysis needs, and mechanisms for immediate feedback and adjustment. Experimental results show that with this prompt design strategy, large language models perform exceptionally well in multiple data analysis tasks, generating high-quality code and significantly shortening the data analysis cycle. This method provides an efficient and convenient tool for the data analysis field and demonstrates the enormous potential of large language models in practical applications.

Keywords: large language models, prompt design, data analysis, code generation

Procedia PDF Downloads 39

Authors: Shazia Anwer

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This paper has discussed the unusual form of resistance in theatre against censorship board in Pakistan. The atypical approach of dramaturgy created massive space for performers and audiences to integrate and communicate. The social and religious absolutes creates suffocation in Pakistani society, strict control over all Fine and Performing Art has made art political, contemporary dramatics has started an amalgamated theatre to avoid censorship. Contemporary Punjabi theatre techniques are directly dependent on human cognition. The idea of indirect thought processing is not unique but dependent on spectators. The paper has provided an account of these techniques and their specific use for conveying specific messages across the audiences. For the Dramaturge of today, theatre space is an expression representing a linguistic formulation that includes qualities of experimental and non-traditional use of classical theatrical space in the context of fulfilling the concept of open theatre. Paper has explained the transformation of the theatrical experience into an event where the actor and the audience are co-existing and co-experiencing the dramatical experience. The denial of the existence of the 4th -Wall made two-way communication possible. This paper has elaborated that the previously marginalized genres such as naach, jugat, miras, are extensively included to counter the censorship board. Figurativeness, visual elements, allegory, scenic imagery are basic support system for contemporary Punjabi theatre. The body of the actor is used as a source for non-verbal communication, and for an escape from traditional theatrical space which by every means has every element that could be controlled and reprimanded by the controlling authority.

Keywords: communication, Punjabi theatre, figurativeness, censorship

Procedia PDF Downloads 134

Authors: Ernest Nweke

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This paper examines the changing trend in ownership of Mongolian companies and how this trend has influenced corporate governance mechanisms in Mongolian companies. A study of this magnitude is essential as it x-rays the systematic transformation of Mongolia’s corporate world from the public to private ownership and the tremendous impact it has had on firm governance mechanisms. Owing to Mongolia’s Soviet past, much of the companies in Mongolia were state-owned, state-directed and state-controlled resulting in serious inefficiencies in these companies. This scenario is antithetical to the economic growth and development of any nation as it is grossly at variance with the fundamental principles of good corporate governance that drive prosperity. Consequently, the Mongolian government has in the past decades fine-tuned government policy to prioritize private ownership, establishing various frameworks that will strengthen corporate governance structures in Mongolia. These efforts have paid off and gone a long way in changing the trend in the ownership of companies in Mongolia reversing the old order. The expectation locally and internationally is that companies in post-socialist Mongolia will be more closely aligned to generally accepted corporate governance mechanisms, generally improving company performance and ultimately returns to shareholders. To achieve the research objectives, the survey research method was employed utilizing a sample of seventy randomly selected listed companies representing 22% of Mongolian Stock Exchange listings. Research hypotheses formulated to guide the conduct of the study were tested using Chi-Square analysis, and results show that ownership trend has drastically changed in the post-socialist Mongolia leading to better corporate governance practices in Mongolian companies. This result has important policy implications.

Keywords: corporate disclosure, free market, private ownership, Mongolia

Procedia PDF Downloads 143

Authors: Daniela Rivera-Tobar Mario Perez-Won, Roberto Lemus-Mondaca, Gipsy Tabilo-Munizaga

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Different dietary trends worldwide seek to consume foods with anti-inflammatory properties, rich in antioxidants, proteins, and unsaturated fatty acids that lead to better metabolic, intestinal, mental, and cardiac health. In this sense, food matrices with high protein content based on macro and microalgae are an excellent alternative to meet the new needs of consumers. An emerging and environmentally friendly technology for producing protein matrices is ultrasonic agglomeration. It consists of the formation of permanent bonds between particles, improving the agglomeration of the matrix compared to conventionally agglomerated products (compression). Among the advantages of this process are the reduction of nutrient loss and the avoidance of binding agents. The objective of this research was to optimize the ultrasonic agglomeration process in matrices composed of Spirulina (Arthrospira platensis) powder and Cochayuyo (Durvillae Antartica) flour, by means of the response variable (Young's modulus) and the independent variables were the process conditions (percentage of ultrasonic amplitude: 70, 80 and 90; ultrasonic agglomeration times and cycles: 20, 25 and 30 seconds, and 3, 4 and 5). It was evaluated using a central composite design and analyzed using response surface methodology. In addition, the effects of agglomeration on thermophysical and microstructural properties were evaluated. It was determined that ultrasonic compression with 80 and 90% amplitude caused conformational changes according to Fourier infrared spectroscopy (FTIR) analysis, the best condition with respect to observed microstructure images (SEM) and differential scanning calorimetry (DSC) analysis, was the condition of 90% amplitude 25 and 30 seconds with 3 and 4 cycles of ultrasound. In conclusion, the agglomerated matrices present good macro and microstructural properties which would allow the design of food systems with better nutritional and functional properties.

Keywords: ultrasonic agglomeration, physical properties of food, protein matrices, macro and microalgae

Procedia PDF Downloads 61

Authors: Yatimah Alias, Tilagam Marimuthu, M. R. Mahmoudian, Sharifah Mohamad

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The rapid growth of science and technology in energy and environmental fields has enlightened the substantial importance of the conducting polymer and metal composite materials engineered at nano-scale. In this study, polypyrrole-cobalt composites (PPy-Co Cs) and polypyrrole-nickel oxide composites (PPy-NiO Cs) were prepared by a simple and facile chemical polymerization method with an aqueous solution of pyrrole monomer in the presence of metal salt. These composites then fabricated into non-enzymatic hydrogen peroxide (H2O2) and glucose sensor. The morphology and composition of the composites are characterized by the Field Emission Scanning Electron Microscope, Fourier Transform Infrared Spectrum and X-ray Powder Diffraction. The obtained results were compared with the pure PPy and metal oxide particles. The structural and morphology properties of synthesized composites are different from those of pure PPy and metal oxide particles, which were attributed to the strong interaction between the PPy and the metal particles. Besides, a favorable micro-environment for the electrochemical oxidation of H2O2 and glucose was achieved on the modified glassy carbon electrode (GCE) coated with PPy-Co Cs and PPy-NiO Cs respectively, resulting in an enhanced amperometric response. Both PPy-Co/GCE and PPy-NiO/GCE give high response towards target analyte at optimum condition of 500 μl pyrrole monomer content. Furthermore, the presence of pyrrole monomer greatly increases the sensitivity of the respective modified electrode. The PPy-Co/GCE could detect H2O2 in a linear range of 20 μM to 80 mM with two linear segments (low and high concentration of H2O2) and the detection limit for both ranges is 2.05 μM and 19.64 μM, respectively. Besides, PPy-NiO/GCE exhibited good electrocatalytic behavior towards glucose oxidation in alkaline medium and could detect glucose in linear ranges of 0.01 mM to 0.50 mM and 1 mM to 20 mM with detection limit of 0.33 and 5.77 μM, respectively. The ease of modifying and the long-term stability of this sensor have made it superior to enzymatic sensors, which must kept in a critical environment.

Keywords: metal oxide, composite, non-enzymatic sensor, polypyrrole

Procedia PDF Downloads 266

Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The educational system faces a significant concern with regards to Dyslexia and Dysgraphia, which are learning disabilities impacting reading and writing abilities. This is particularly challenging for children who speak the Sinhala language due to its complexity and uniqueness. Commonly used methods to detect the risk of Dyslexia and Dysgraphia rely on subjective assessments, leading to limited coverage and time-consuming processes. Consequently, delays in diagnoses and missed opportunities for early intervention can occur. To address this issue, the project developed a hybrid model that incorporates various deep learning techniques to detect the risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16, and YOLOv8 models were integrated to identify handwriting issues. The outputs of these models were then combined with other input data and fed into an MLP model. Hyperparameters of the MLP model were fine-tuned using Grid Search CV, enabling the identification of optimal values for the model. This approach proved to be highly effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention. The Resnet50 model exhibited a training accuracy of 0.9804 and a validation accuracy of 0.9653. The VGG16 model achieved a training accuracy of 0.9991 and a validation accuracy of 0.9891. The MLP model demonstrated impressive results with a training accuracy of 0.99918, a testing accuracy of 0.99223, and a loss of 0.01371. These outcomes showcase the high accuracy achieved by the proposed hybrid model in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, dyslexia, dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 64

Authors: Satyananda Behera, Ritwik Sarkar

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In iron and steel industries, MgO–C refractories are widely used in basic oxygen furnaces, electric arc furnaces and steel ladles due to their excellent corrosion resistance, thermal shock resistance, and other excellent hot properties. Conventionally magnesia carbon refractories contain about 8-20 wt% of carbon but the use of carbon is also associate with disadvantages like oxidation, low fracture strength, high heat loss and higher carbon pick up in steel. So, MgO-C refractory having low carbon content without compromising the beneficial properties is the challenge. Nano carbon, having finer particles, can mix and distribute within the entire matrix uniformly and can result in improved mechanical, thermo-mechanical, corrosion and other refractory properties. Previous experiences with the use of nano carbon in low carbon MgO-C refractory have indicated an optimum range of use of nano carbon around 1 wt%. This optimum nano carbon content was used in MgO-C compositions with flaky graphite followed by aluminum and silicon metal powder as an anti-oxidant. These low carbon MgO-C refractory compositions were prepared by conventional manufacturing techniques. At the same time 16 wt. % flaky graphite containing conventional MgO-C refractory was also prepared parallel under similar conditions. The developed products were characterized for various refractory related properties. Nano carbon containing compositions showed better mechanical, thermo-mechanical properties, and oxidation resistance compared to that of conventional composition. Improvement in the properties is associated with the formation of in-situ ceramic phase-like aluminum carbide, silicon carbide, and magnesium aluminum spinel. Higher surface area and higher reactivity of N220 nano carbon black resulted in greater formation in-situ ceramic phases, even at a much lower amount. Nano carbon containing compositions were found to have improved properties in MgO-C refractories compared to that of the conventional ones at much lower total carbon content.

Keywords: N220nano carbon black, refractory properties, conventionally manufacturing techniques, conventional magnesia carbon refractories

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Authors: Jonas Hamann, Siavash Saki, Tobias Hagen

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Discretization of urban areas is a crucial aspect in many spatial analyses. The process of discretization of space into subspaces without overlaps and gaps is called tessellation. It helps understanding spatial space and provides a framework for analyzing geospatial data. Tessellation methods can be divided into two groups: regular tessellations and irregular tessellations. While regular tessellation methods, like squares-grids or hexagons-grids, are suitable for addressing pure geometry problems, they cannot take the unique characteristics of different subareas into account. However, irregular tessellation methods allow the border between the subareas to be defined more realistically based on urban features like a road network or Points of Interest (POI). Even though Python is one of the most used programming languages when it comes to spatial analysis, there is currently no library that combines different tessellation methods to enable users and researchers to compare different techniques. To close this gap, we are proposing TessPy, an open-source Python package, which combines all above-mentioned tessellation methods and makes them easily accessible to everyone. The core functions of TessPy represent the five different tessellation methods: squares, hexagons, adaptive squares, Voronoi polygons, and city blocks. By using regular methods, users can set the resolution of the tessellation which defines the finesse of the discretization and the desired number of tiles. Irregular tessellation methods allow users to define which spatial data to consider (e.g., amenity, building, office) and how fine the tessellation should be. The spatial data used is open-source and provided by OpenStreetMap. This data can be easily extracted and used for further analyses. Besides the methodology of the different techniques, the state-of-the-art, including examples and future work, will be discussed. All dependencies can be installed using conda or pip; however, the former is more recommended.

Keywords: geospatial data science, geospatial data analysis, tessellations, urban studies

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Authors: Samaneh Rahsepar, Mehrzad Moghadasi

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To evaluate the effect of Test Pump supplement on the physiological and functional performance of futsal women, twenty female futsal subjects were divided into two groups: placebo (n = 10) and supplement (n = 10) and were given buccal tablets for 7 days and 12 g daily supplement each day. The placebo group used starch powder during this period. Speed, agility with ball, agility without ball and dribbling time were measured before and after supplementation. In addition, the rate of heart rate and blood pressure changes were measured before and after the YOYO test. The results showed that the test pump had no significant effect on improving speed, agility with ball, agility without ball, dribbling time and heart rate changes and diastolic blood pressure, and only affect the maximum oxygen consumption and systolic blood pressure (P <0.05). In general, the use of the test-pump supplement does not have a significant effect on the physiological and functional performance of futsal women. The results of this study showed that the use of supplementary pump tests on women's futsal heart rate changes after loading period had a significant difference between the two groups in resting heart rate with heart rate after exercise and 5 minutes after exercise. However, it did not have a significant effect on the increase in heart rate. Supplementation significantly increased systolic blood pressure after exercise compared to resting blood pressure, as well as a significant increase in systolic blood pressure after exercise compared to resting systolic blood pressure and 5 minutes after exercise in both groups from the loading period. On the other hand, there was a significant difference in systolic blood pressure in both placebo and supplemented groups.

Keywords: test pump supplement, women, speed, dribble, agility, maximum oxygen consumption, cardiovascular

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Authors: Jonathan Rodriguez, Dominga Guerrero, Surupa Shaw

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Automobiles are modeled in various forms, and they interact with air when in motion. Aerodynamics is the study of such interactions where solid bodies affect the way air moves around them. The shape of solid bodies can impact the ease at which they move against the flow of air; due to which any additional freightage, or loads, impact its aerodynamics. It is important to transport people and cargo safely. Despite the various safety measures, there are a large number of vehicle-related accidents. This study precisely explores the effects an automobile experiences, with added cargo and covers. The addition of these items changes the original vehicle shape and the approved design for safe driving. This paper showcases the effects of the changed vehicle shape and design via experimental testing conducted on a physical 1:27 scale and CAD model of an F-150 pickup truck, the most common pickup truck in the United States, with differently shaped loads and weight traveling at a constant speed. The additional freightage produces unwanted drag or lift resulting in lower fuel efficiencies and unsafe driving conditions. This study employs an adjustable external shell on the F-150 pickup truck to create a controlled aerodynamic geometry to combat the detrimental effects of additional freightage. The results utilize colored powder [ which acts as a visual medium for the interaction of air with the vehicle], to highlight the impact of the additional freight on the automobile’s external shell. This will be done along with simulation models using Altair CFD software of twelve cases regarding the effects of an added load onto an F-150 pickup truck. This paper is an attempt toward standardizing the geometric design of the external shell, given the uniqueness of every load and its placement on the vehicle; while providing real-time data to be compared to simulation results from the existing literature.

Keywords: aerodynamics, CFD, freightage, pickup cover

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Authors: Rumaisa Shahid, Saad Aziz Durrani, Shameel Pervez, Ibatsam Khokhar

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Food waste is a prevalent issue in Pakistan, with over 40 percent of food discarded annually. Despite their decay, rotting fruits retain residual nutritional value consumed by microorganisms, notably fungi and bacteria. Fungi, preferred for their extracellular enzyme release, are gaining prominence, particularly for pectinase production. This enzyme offers several advantages, including clarifying juices by breaking down pectic compounds. In this study, three Aspergillus flavus isolates derived from decomposed fruits and manure were selected for pectinase production. The primary aim was to isolate fungi from diverse waste sources, identify the isolates and assess their capacity for pectinase production. The identification was done through morphological characteristics with the help of Light microscopy and Scanning Electron Microscopy (SEM). Pectinolytic potential was screened using pectin minimal salt agar (PMSA) medium, comparing clear zone diameters among isolates. Identification relied on morphological characteristics. Optimizing substrate (lemon and orange peel powder) concentrations, pH, temperature, and incubation period aimed to enhance pectinase yield. Spectrophotometry enabled quantitative analysis. The temperature was set at room temperature (28 ºC). The optimal conditions for Aspergillus flavus strain AF1(isolated from mango) included a pH of 5, an incubation period of 120 hours, and substrate concentrations of 3.3% for orange peels and 6.6% for lemon peels. For AF2 and AF3 (both isolated from soil), the ideal pH and incubation period were the same as AF1 i.e. pH 5 and 120 hours. However, their optimized substrate concentrations varied, with AF2 showing maximum activity at 3.3% for orange peels and 6.6% for lemon peels, while AF3 exhibited its peak activity at 6.6% for orange peels and 8.3% for lemon peels. Among the isolates, AF1 demonstrated superior performance under these conditions, comparatively.

Keywords: pectinase, lemon peel, orange peel, aspergillus flavus

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Authors: Rajat Jain, Himanshu Pandey, Somesh Mehta, Pravin P. Patil

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Formula SAE cars are the student designed and fabricated formula prototype cars, designed according to SAE INTERNATIONAL design rules which compete in the various national and international events. This paper shows a FEM based comparative study of free vibration analysis of different mode shapes of a formula prototype car chassis frame. Tubing sections of different diameters as per the design rules are designed in such a manner that the desired strength can be achieved. Natural frequency of first five mode was determined using finite element analysis method. SOLIDWORKS is used for designing the frame structure and SOLIDWORKS SIMULATION and ANSYS WORKBENCH 16.2 are used for the modal analysis. Mode shape results of ANSYS and SOLIDWORKS were compared. Fixed –fixed boundary conditions are used for fixing the A-arm wishbones. The simulation results were compared for the validation of the study. First five modes were compared and results were found within the permissible limits. The AISI4130 (CROMOLY- chromium molybdenum steel) material is used and the chassis frame is discretized with fine quality QUAD mesh followed by Fixed-fixed boundary conditions. The natural frequency of the chassis frame is 53.92-125.5 Hz as per the results of ANSYS which is found within the permissible limits. The study is concluded with the light weight and compact chassis frame without compensation with strength. This design allows to fabricate an extremely safe driver ergonomics, compact, dynamically stable, simple and light weight tubular chassis frame with higher strength.

Keywords: FEM, modal analysis, formula SAE cars, chassis frame, Ansys

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Authors: Daniela Panico

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Framed by language socialization and family language policy theories, the present study explores the ways the language choice patterns of bilingual siblings contribute to the shaping of the language environment and the language practices of Italian/English families residing in Sydney. The main source of data is video recordings of naturally occurring parent-children and child-to-child interactions during everyday routines (i.e., family mealtimes and siblings playtime) in the home environment. Recurrent interactional practices are analyzed in detail through a conversational analytical approach. This presentation focuses on the interactional trajectories developing during the negotiation of language choices between all family members and between siblings in face-to-face interactions. Fine-grained analysis is performed on language negotiation sequences of multiparty bilingual conversations in order to uncover the sequential patterns through which a) the children respond to the parental strategies aiming to minority language maintenance, and b) the siblings influence each other’s language use and choice (e.g., older siblings positioning themselves as language teachers and language brokers, younger siblings accepting the role of apprentices). The findings show that, along with the parents, children are active socializing agents in the family and, with their linguistic behavior, they contribute to the establishment of a bilingual or a monolingual context in the home. Moreover, by orienting themselves towards the use of one or the other language in family talk, bilingual siblings are a major internal micro force in the language ecology of a bilingual family and can strongly support language maintenance or language shift processes in such domain. Overall, the study provides insights into the dynamic ways in which family language policy is interactionally negotiated and instantiated in bilingual homes as well as the challenges of intergenerational language transmission.

Keywords: bilingual siblings, family interactions, family language policy, language maintenance

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Authors: Golam Saklayen, Sheikh Rashel al Ahmed, Ferdous Rahman, Ismail Abu Bakar

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Investigation on Lanthanum Fluoride LaF3 layer embedding Silicon Nanocrystals (Si-NCs) fabricated using a novel one-step chemical method has been reported in this presentation. Application of this material has been tested for low-voltage operating non-volatile memory and Schottkey-junction solar cell. Colloidal solution of Si-NCs in hydrofluoric acid (HF) was prepared from meso-porous silicon by ultrasonic vibration (sonication). This solution prevents the Si-NCs to be oxidized. On a silicon (Si) substrate, LaCl3 solution in HCl is allowed to react with the colloidal solution of prepared Si-NCs. Since this solution contains HF, LaCl3 reacts with HF and produces LaF3 crystals that deposits on the silicon substrate as a layer embedding Si-NCs. This a novel single step chemical way of depositing LaF3 insulating layer embedding Si-NCs. The X-Ray diffraction of the deposited layer shows a polycrystalline LaF3 deposition on silicon. A non-stoichiometric LaF3 layer embedding Si-NCs was found by EDX analysis. The presence of Si-NCs was confirmed by SEM. FTIR spectroscopy of the deposited LaF3 powder also confirmed the presence of Si-NCs. The size of Si-NCs was found to be inversely proportional to the ultrasonic power. After depositing proper contacts on the back of Si and LaF3, the devices have been tested as a non-volatile memory and solar cell. A memory window of 525 mV was obtained at a programming and erasing bias of 2V. The LaF3 films with Si NCs showed strong absorption and was also found to decrease optical transmittance than pure LaF3 film of same thickness. The I-V characteristics of the films showed a dependency on the incident light intensity where current changed under various light illumination. Experimental results show a lot of promise for Si-NCs-embedded LaF3 layer to be used as an insulating layer in MIS devices as well as an photoactive material in Schottkey junction solar cells.

Keywords: silicon nanocrystals (Si NCs), LaF3, colloidal solution, Schottky junction solar cell

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Elsayed Amer, Tarek Essam, Abdullah Hella, Mohammed Al-Ajmi

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Hydrocarbon production decline in mature gas fields is inevitable, and mitigating these circumstances is essential to ensure a longer production period. Production decline is not only influenced by reservoir pressure and wellbore integrity; however, associated liquids in the reservoir rock have a considerable impact on the production process. The associated liquid may result in liquid loading, near wellbore damage, condensate banking, fine sand migration, and wellhead pressure depletion. Consequently, the producing well will suffocate, and the liquid column will seize the well from flowing. A common solution in such circumstances is reducing the surface pressure by opening the well to the atmospheric pressure and flaring the produced liquids. This practice may not be applicable to many cases since the atmospheric pressure is not low enough to create a sufficient driving force to flow the well. In addition, flaring the produced hydrocarbon is solving the issue on account of the environment, which is against the world's efforts to mitigate the impact of climate change. This paper presents a novel approach and a case study that utilizes a multi-phase mobile wellhead gas compression unit (MMWGC) to reduce surface pressure to the sub-atmospheric level and transfer the produced hydrocarbons to the sales line. As a result, the liquid column will unload in a zero-flaring manner, and the life of the producing well will extend considerably. The MMWGC unit was able to successfully kick off a dead well to produce up to 10 MMSCFD after reducing the surface pressure for 3 hours. Applying such novelty on a broader scale will not only extend the life of the producing wells yet will also provide a zero-flaring, economically and environmentally preferred solution.

Keywords: petroleum engineering, zero-flaring, liquid loading, well revival

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Authors: Budhvin T. Withana, Sulochana Rupasinghe

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The problem of Dyslexia and Dysgraphia, two learning disabilities that affect reading and writing abilities, respectively, is a major concern for the educational system. Due to the complexity and uniqueness of the Sinhala language, these conditions are especially difficult for children who speak it. The traditional risk detection methods for Dyslexia and Dysgraphia frequently rely on subjective assessments, making it difficult to cover a wide range of risk detection and time-consuming. As a result, diagnoses may be delayed and opportunities for early intervention may be lost. The project was approached by developing a hybrid model that utilized various deep learning techniques for detecting risk of Dyslexia and Dysgraphia. Specifically, Resnet50, VGG16 and YOLOv8 were integrated to detect the handwriting issues, and their outputs were fed into an MLP model along with several other input data. The hyperparameters of the MLP model were fine-tuned using Grid Search CV, which allowed for the optimal values to be identified for the model. This approach proved to be effective in accurately predicting the risk of Dyslexia and Dysgraphia, providing a valuable tool for early detection and intervention of these conditions. The Resnet50 model achieved an accuracy of 0.9804 on the training data and 0.9653 on the validation data. The VGG16 model achieved an accuracy of 0.9991 on the training data and 0.9891 on the validation data. The MLP model achieved an impressive training accuracy of 0.99918 and a testing accuracy of 0.99223, with a loss of 0.01371. These results demonstrate that the proposed hybrid model achieved a high level of accuracy in predicting the risk of Dyslexia and Dysgraphia.

Keywords: neural networks, risk detection system, Dyslexia, Dysgraphia, deep learning, learning disabilities, data science

Procedia PDF Downloads 114