Search results for: evolutionary optimization techniques

Authors: D. H. Tejavathi

Abstract:

Medicinal plants are globally valuable sources of herbal products. Wild populations of many medicinal plants are facing threat of extinction because of their narrow distribution, endemicity, and degradation of specific habitats. Micropropagation is an established in vitro technique by which large number of clones can be obtained from a small bit of explants in a short span of time within a limited space. Mycorrhization can minimize the transient transplantation shock, experienced by the micropropagated plants when they are transferred from lab to land. AM fungal association improves the physiological status of the host plants through better uptake of water and nutrients, particularly phosphorus. Consequently, the growth performance and biosynthesis of active principles are significantly enhanced in AM fungal treated plants. Bacopa monnieri, Andrographis paniculata, Agave vera-curz, Drymaria cordata and Majorana hortensis, important medicinal plants used in various indigenous systems of medicines, are selected for the present study. They form the main constituents of many herbal formulations. Standard in vitro techniques were followed to obtain the micropropagated plants. Shoot tips and nodal segments were used as explants. Explants were cultured on Murashige and Skoog, and Phillips and Collins media supplemented with various combinations of growth regulators. Multiple shoots were obtained on a media containing both auxins and cytokinins at various concentrations and combinations. Multiple shoots were then transferred to rooting media containing auxins for root induction. Thus, obtained in vitro regenerated plants were subjected to brief acclimatization before transferring them to land. One-month-old in vitro plants were treated with AM fungi, and the symbiotic effect on the overall growth parameters was analyzed. It was found that micropropagation coupled with mycorrhization has significant effect on the enhancement of biomass and biosynthesis of active principles in these selected medicinal plants. In vitro techniques coupled with mycorrhization have opened a possibility of obtaining better clones in respect of enhancement of biomass and biosynthesis of active principles. Beneficial effects of AM fungal association with medicinal plants are discussed.

Keywords: cultivation, medicinal plants, micropropagation, mycorrhization

Procedia PDF Downloads 166

Authors: Anudeep Appe, Bhanu Poluparthi, Lakshmi Kasivajjula, Udai Mv, Sobha Bagadi, Punya Modi, Aditya Singh, Hemanth Gunupudi, Spenser Troiano, Jeff Paul, Justin Stovall, Justin Yamamoto

Abstract:

The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data is considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP, to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since its data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for ex. quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP (SHapley Additive exPlanations), a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: competition, DAGs, facility, healthcare, machine learning, market share, random forest, SHAP

Procedia PDF Downloads 85

Authors: Afsheen Masood, Sumaira Rashid, Shama Mazahir

Abstract:

The main aim of this research is to evaluate the efficacy of a culturally adapted management program The Stepping Stones Positive Parenting Program (Tripple P; SSTP) for caregivers of children with autism spectrum disorders and Down syndrome. Positive psychology has catered new dimensions to the traditional perspectives of parenting. The current study was designed to determine the adoptions of positive parenting elements such as parenting styles, parental satisfaction, parental competency, and management of parental stress in alignment with behavioral problems of children with special needs after their parents get trained on Positive Parenting Techniques. This research study was devised in liaison with rehabilitation institute that is extending services for children with Autism Spectrum Disorder and Down syndrome. A Quasi experimental research design was employed with pre-test, post-test control group study in order to evaluate the changes in parenting patterns of parents with children (with Autism and Down syndrome). Caregivers of children diagnosed with Autism and Down syndrome between the age ranges of 25 to 45 years, n=20 from autism group and 20 from Down syndrome group (while their children with special needs in the age ranges of 8 to 14 years) participated in the current research. Parenting scale encompassing areas of parental efficacy, parental satisfaction was used in addition to Parenting Stress Index (SF), indigenously developed Child Behavior Problems Checklist and demographic sheet. Findings revealed statistically significant improvement for caregivers in intervention group from pretest to posttest situation. There was considerable decrease in reported mean behavioral issues of children with Down syndrome when parents in experimental group started practicing Positive Parenting Techniques with their special needs children. This change was somehow not recorded in parents of children with autism. Thus these findings establish the efficacy of culturally adapted parenting program that is evidence based and is established in western empirical research. This carries significant implication for practitioners in special needs domain and for school psychologists in Pakistan.

Keywords: Autism and Parenting, Downsyndrome and Parenting , Positive Parenting, Stepping Stone Positive Parenting Program, Mangement of Behavioral Problems with positive parenting

Procedia PDF Downloads 246

Authors: Erwin Chan, Aravind Subramaniyan, Siti Abdullah Fatehah, Steve Lian Kuling

Abstract:

Foam assisted lift technology is proven across the industry to provide efficient deliquification in gas wells. Such deliquification is typically achieved by delivering the foamer chemical downhole via capillary strings. In highly liquid loaded wells where capillary strings are not readily available, foamer can be delivered via batch injection or bull-heading. The latter techniques differ from the former in that cap strings allow for liquid to be unloaded continuously, whereas foamer batches require that periodic batching be conducted for the liquid to be unloaded. Although batch injection allows for liquid to be unloaded in wells with suitable water to gas (WGR) ratio and condensate to gas (CGR) ratio without well intervention for capillary string installation, this technique comes with its own set of challenges - for foamer to de-liquify liquids, the chemical needs to reach perforation locations where gas bubbling is observed. In highly scaled perforation zones in certain wells, foamer delivered in batches is unable to reach the gas bubbling zone, thus achieving poor lift efficiency. This paper aims to discuss the techniques and challenges for unloading liquid via batch injection in scaled perforation wells X and Y, whose WGR is 6bbl/MMscf, whose scale build-up is observed at the bottom of perforation interval, whose water column is 400 feet, and whose ‘bubbling zone’ is less than 100 feet. Variables such as foamer Z dosage, batching technique, and well flow control valve opening times are manipulated during the duration of the trial to achieve maximum liquid unloading and gas rates. During the field trial, the team has found optimal values between the three aforementioned parameters for best unloading results, in which each cycle’s gas and liquid rates are compared with baselines with similar flowing tubing head pressures (FTHP). It is discovered that amongst other factors, a good agitation technique is a primary determinant for efficient liquid unloading. An average increment of 2MMscf/d against an average production of 4MMscf/d at stable FTHP is recorded during the trial.

Keywords: foam, foamer, gas lift, liquid unloading, scale, batch injection

Procedia PDF Downloads 174

Authors: Zhou BingHai, Fradet Victor

Abstract:

Lean philosophy follows the simple principle of “creating more value with fewer resources”. In accordance with this policy, material handling can be managed by the mean of Kanban which by triggering every feeding tour only when needed regulates the flow of material in one of the most efficient way. This paper focuses on Kanban Supermarket’s parameters and their optimization on a purely cost-based point of view. Number and size of forklifts, as well as size of the containers they carry, will be variables of the cost function which includes handling costs, inventory costs but also shortage costs. With an innovative computational approach encoded into industrial engineering software Tecnomatix and reproducing real-life conditions, a fictive assembly line is established and produces a random list of orders. Multi-scenarios are then run to study the impact of each change of parameter and the variation of costs it implies. Lastly, best-case scenarios financially speaking are selected.

Keywords: Kanban, supermarket, parts-feeding policies, multi-scenario simulation, assembly line

Procedia PDF Downloads 191

Authors: Mustofa Ahda, Fiqri Rozi, Gina Noor Habibah, Mas Ulfah Lestari, Tomy Hardianto, Yuni Andriani

Abstract:

The development of natural antioxidants in the Centella asiatica and Majapahit is a great potential. This research has been optimizing the composition of ethanol extract of Centella asiatica and leaves Majapahit as an antioxidants source using measure the free radical scavenging activity of DPPH. The results of the research showed that both the ethanol extract of Centella asiatica and leaves Majapahit has a total content of phenol. It is shown with the ability to reduce reagent Folin Ciocalteu become blue colour. The composition optimization of extract Centella asiatica leaves Majapahit = 30:70 has free radical scavenging activity of DPPH most well compared ethanol extract of Centella asiatica and leaves Majapahit. IC50 values for the composition of ethanol extract of Centella asiatica : leaves Majapahit = 30:70 is 0,103 mg/mL.

Keywords: antioxidant activity, Centella asiatica, Cresentia cujete, composition extract

Procedia PDF Downloads 325

Authors: Diego Luján Villarreal

Abstract:

Visual prostheses are designed to repair some eyesight in patients blinded by photoreceptor diseases, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD). Electrode-to-cell proximity has drawn attention due to its implications on secure single-localized stimulation. Yet, few techniques are available for understanding the relationship between the number of cells activated and the current injection. We propose an answering technique by solving the governing equation for time-dependent electrical currents using finite element discretization to obtain the volume of stimulation.

Keywords: visual prosthetic devices, volume for stimulation, FEM discretization, 3D simulation

Procedia PDF Downloads 65

Authors: Joanna Estkowska

Abstract:

Sensory integration methods are very useful and improve daily functioning autistic and mentally disabled children. Autism is a neurobiological disorder that impairs one's ability to communicate with and relate to others as well as their sensory system. Children with autism, even highly functioning kids, can find it difficult to process language with surrounding noise or smells. They are hypersensitive to things we can ignore such as sight, sounds and touch. Adolescents with highly functioning autism or Asperger Syndrome can study Science and Math but the social aspect is difficult for them. Nature science is an area of study that attracts many of these kids. It is a systematic field in which the children can focus on a small aspect. If you follow these rules you can come up with an expected result. Sensory integration program and systematic classroom observation are quantitative methods of measuring classroom functioning and behaviors from direct observations. These methods specify both the events and behaviors that are to be observed and how they are to be recorded. Our students with and without autism attended the lessons in the classroom of nature science in the school and in the laboratory of University of Science and Technology in Bydgoszcz. The aim of this study is investigation the effects of sensory integration methods in teaching to students with autism. They were observed during experimental lessons in the classroom and in the laboratory. Their physical characteristics, sensory dysfunction, and behavior in class were taken into consideration by comparing their similarities and differences. In the chemistry classroom, every autistic student is paired with a mentor from their school. In the laboratory, the children are expected to wear goggles, gloves and a lab coat. The chemistry classes in the laboratory were held for four hours with a lunch break, and according to the assistants, the children were engaged the whole time. In classroom of nature science, the students are encouraged to use the interactive exhibition of chemical, physical and mathematical models constructed by the author of this paper. Our students with and without autism attended the lessons in those laboratories. The teacher's goals are: to assist the child in inhibiting and modulating sensory information and support the child in processing a response to sensory stimulation.

Keywords: autism spectrum disorder, science education, sensory integration techniques, student with special educational needs

Procedia PDF Downloads 187

Authors: Natalia Sáez, Dina Shulfman

Abstract:

There is an important research gap regarding accessible pedagogical techniques for teaching foreign languages to adults with visual impairments. English as a foreign language (EFL), in particular, is needed in many countries to expand occupational opportunities and improve living standards. Within EFL research, teaching and learning prepositions have only recently gained momentum, considering that they constitute one of the most difficult structures to learn in a foreign language and are fundamental for communicating about spatial relations in the world, both on the physical and imaginary levels. Learning to use prepositions would not only facilitate communication when referring to the surrounding tangible environment but also when conveying ideas about abstract topics (e.g., justice, love, society), for which students’ sociocultural knowledge about space could play an important role. By potentiating visually impaired students’ ability to construe mental spatial imagery, this study made efforts to explore pedagogical techniques that cater to their strengths, helping them create new worlds by welcoming and expanding their sociocultural funds of knowledge as they learn to use English prepositions. Fifteen visually impaired adults living in Chile participated in the study. Their first language was Spanish, and they were learning English at the intermediate level of proficiency in an EFL workshop at La Biblioteca Central para Ciegos (The Central Library for the Blind). Within this workshop, a series of activities and interviews were designed and implemented with the intention of uncovering students’ spatial funds of knowledge when learning literal/physical uses of three English prepositions, namely “in,” “at,” and “on”. The activities and interviews also explored whether students used their original spatial funds of knowledge when learning metaphorical uses of these prepositions and if their use of spatial imagery changed throughout the learning activities. Over the course of approximately half a year, it soon became clear that the students construed mental images of space when learning both literal/physical and metaphorical uses of these prepositions. This research could inform a new approach to inclusive language education using pedagogical methods that are relevant and accessible to students with visual impairments.

Keywords: EFL, funds of knowledge, prepositions, spatial cognition, visually impaired students

Procedia PDF Downloads 74

Authors: Pilar Rey del Castillo

Abstract:

This document describes the building of an average indicator of the general sentiments about the future exposed in the newspapers in Spain. The raw data are collected through the scraping of the Digital Periodical and Newspaper Library website. Basic tools of natural language processing are later applied to the collected information to evaluate the sentiment strength of each word in the texts using a polarized dictionary. The last step consists of summarizing these sentiments to produce daily indices. The results are a first insight into the applicability of these techniques to produce periodic sentiment indicators.

Keywords: natural language processing, periodic indicator, sentiment analysis, web scraping

Procedia PDF Downloads 123

Authors: Polina Prokopovich

Abstract:

Despite the well-established dependence of cartilage mechanical properties on the frequency of the applied load, most research in the field is carried out in either load-free or constant load conditions because of the complexity of the equipment required for the determination of time-dependent properties. These simpler analyses provide a limited representation of cartilage properties thus greatly reducing the impact of the information gathered hindering the understanding of the mechanisms involved in this tissue replacement, development and pathology. More complex techniques could represent better investigative methods, but their uptake in cartilage research is limited by the highly specialised training required and cost of the equipment. There is, therefore, a clear need for alternative experimental approaches to cartilage testing to be deployed in research and clinical settings using more user-friendly and financial accessible devices. Frequency dependent material properties can be determined through rheometry that is an easy to use requiring a relatively inexpensive device; we present how a commercial rheometer can be adapted to determine the viscoelastic properties of articular cartilage. Frequency-sweep tests were run at various applied normal loads on immature, mature and trypsinased (as model of osteoarthritis) cartilage samples to determine the dynamic shear moduli (G*, G′ G″) of the tissues. Moduli increased with increasing frequency and applied load; mature cartilage had generally the highest moduli and GAG depleted samples the lowest. Hydraulic permeability (KH) was estimated from the rheological data and decreased with applied load; GAG depleted cartilage exhibited higher hydraulic permeability than either immature or mature tissues. The rheometer-based methodology developed was validated by the close comparison of the rheometer-obtained cartilage characteristics (G*, G′, G″, KH) with results obtained with more complex testing techniques available in literature. Rheometry is relatively simpler and does not require highly capital intensive machinery and staff training is more accessible; thus the use of a rheometer would represent a cost-effective approach for the determination of frequency-dependent properties of cartilage for more comprehensive and impactful results for both healthcare professional and R&D.

Keywords: tissue, rheometer, biomaterial, cartilage

Procedia PDF Downloads 69

Authors: Deniz Peksen

Abstract:

This thesis aims to predict trend movement of closing price of stock and to maximize portfolio by utilizing the predictions. In this context, the study aims to define a stock portfolio strategy from models created by using Logistic Regression, Gradient Boosting and Random Forest. Recently, predicting the trend of stock price has gained a significance role in making buy and sell decisions and generating returns with investment strategies formed by machine learning basis decisions. There are plenty of studies in the literature on the prediction of stock prices in capital markets using machine learning methods but most of them focus on closing prices instead of the direction of price trend. Our study differs from literature in terms of target definition. Ours is a classification problem which is focusing on the market trend in next 20 trading days. To predict trend direction, fourteen years of data were used for training. Following three years were used for validation. Finally, last three years were used for testing. Training data are between 2002-06-18 and 2016-12-30 Validation data are between 2017-01-02 and 2019-12-31 Testing data are between 2020-01-02 and 2022-03-17 We determine Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate as benchmarks which we should outperform. We compared our machine learning basis portfolio return on test data with return of Hold Stock Portfolio, Best Stock Portfolio and USD-TRY Exchange rate. We assessed our model performance with the help of roc-auc score and lift charts. We use logistic regression, Gradient Boosting and Random Forest with grid search approach to fine-tune hyper-parameters. As a result of the empirical study, the existence of uptrend and downtrend of five stocks could not be predicted by the models. When we use these predictions to define buy and sell decisions in order to generate model-based-portfolio, model-based-portfolio fails in test dataset. It was found that Model-based buy and sell decisions generated a stock portfolio strategy whose returns can not outperform non-model portfolio strategies on test dataset. We found that any effort for predicting the trend which is formulated on stock price is a challenge. We found same results as Random Walk Theory claims which says that stock price or price changes are unpredictable. Our model iterations failed on test dataset. Although, we built up several good models on validation dataset, we failed on test dataset. We implemented Random Forest, Gradient Boosting and Logistic Regression. We discovered that complex models did not provide advantage or additional performance while comparing them with Logistic Regression. More complexity did not lead us to reach better performance. Using a complex model is not an answer to figure out the stock-related prediction problem. Our approach was to predict the trend instead of the price. This approach converted our problem into classification. However, this label approach does not lead us to solve the stock prediction problem and deny or refute the accuracy of the Random Walk Theory for the stock price.

Keywords: stock prediction, portfolio optimization, data science, machine learning

Procedia PDF Downloads 75

Authors: Gopi Ram, Durbadal Mandal, Rajib Kar, Sakti Prasad Ghoshal

Abstract:

A design problem of non-uniform circular antenna arrays for maximum reduction of both the side lobe level (SLL) and first null beam width (FNBW) is dealt with. This problem is modeled as a simple optimization problem. The method of Firefly algorithm (FFA) is used to determine an optimal set of current excitation weights and antenna inter-element separations that provide radiation pattern with maximum SLL reduction and much improvement on FNBW as well. Circular array antenna laid on x-y plane is assumed. FFA is applied on circular arrays of 8-, 10-, and 12- elements. Various simulation results are presented and hence performances of side lobe and FNBW are analyzed. Experimental results show considerable reductions of both the SLL and FNBW with respect to those of the uniform case and some standard algorithms GA, PSO, and SA applied to the same problem.

Keywords: circular arrays, first null beam width, side lobe level, FFA

Procedia PDF Downloads 249

Authors: Fatemeh Yazdanmehr, Iulian Nistor

Abstract:

The scope of the current study is the prediction of water separation in a two-stage industrial crude oil desalting plant. This research study was focused on developing a desalting operation in an existing production unit of one Iranian heavy oil field with 75 MBPD capacity. Because of some operational issues, such as oil dehydration at high temperatures, the optimization of the desalter operational parameters was essential. The mathematical desalting is modeled based on the population balance method. The existing operational data is used for tuning and validation of the accuracy of the modeling. The inlet oil temperature to desalter used was decreased from 110°C to 80°C, and the desalted electrical field was increased from 0.75 kv to 2.5 kv. The proposed condition for the desalter also meets the water oil specification. Based on these conditions of desalter, the oil recovery is increased by 574 BBL/D, and the gas flaring decrease by 2.8 MMSCF/D. Depending on the oil price, the additional production of oil can increase the annual income by about $15 MM and reduces greenhouse gas production caused by gas flaring.

Keywords: desalter, demulsification, modelling, water-oil separation, crude oil emulsion

Procedia PDF Downloads 68

Authors: Allan F. F. Alves, Fernando A. Bacchim Neto, Guilherme Giacomini, Marcela de Oliveira, Ana L. M. Pavan, Maria E. D. Rosa, Diana R. Pina

Abstract:

Stroke is a worldwide concern, only in Brazil it accounts for 10% of all registered deaths. There are 2 stroke types, ischemic (87%) and hemorrhagic (13%). Early diagnosis is essential to avoid irreversible cerebral damage. Non-enhanced computed tomography (NECT) is one of the main diagnostic techniques used due to its wide availability and rapid diagnosis. Detection depends on the size and severity of lesions and the time spent between the first symptoms and examination. The Alberta Stroke Program Early CT Score (ASPECTS) is a subjective method that increases the detection rate. The aim of this work was to implement an image segmentation system to enhance ischemic stroke and to quantify the area of ischemic and hemorrhagic stroke lesions in CT scans. We evaluated 10 patients with NECT examinations diagnosed with ischemic stroke. Analyzes were performed in two axial slices, one at the level of the thalamus and basal ganglion and one adjacent to the top edge of the ganglionic structures with window width between 80 and 100 Hounsfield Units. We used different image processing techniques such as morphological filters, discrete wavelet transform and Fuzzy C-means clustering. Subjective analyzes were performed by a neuroradiologist according to the ASPECTS scale to quantify ischemic areas in the middle cerebral artery region. These subjective analysis results were compared with objective analyzes performed by the computational algorithm. Preliminary results indicate that the morphological filters actually improve the ischemic areas for subjective evaluations. The comparison in area of the ischemic region contoured by the neuroradiologist and the defined area by computational algorithm showed no deviations greater than 12% in any of the 10 examination tests. Although there is a tendency that the areas contoured by the neuroradiologist are smaller than those obtained by the algorithm. These results show the importance of a computer aided diagnosis software to assist neuroradiology decisions, especially in critical situations as the choice of treatment for ischemic stroke.

Keywords: ischemic stroke, image processing, CT scans, Fuzzy C-means

Procedia PDF Downloads 363

Authors: Prakash Kumar Nayak, Avinash Kumar, Uma Dash, Kalpana Rayaguru

Abstract:

Soybean oil is one of the most widely consumed cooking oils, worldwide. Deep-fat frying of foods at higher temperatures adds unique flavour, golden brown colour and crispy texture to foods. But it brings in various changes like hydrolysis, oxidation, hydrogenation and thermal alteration to oil. The presence of Peroxide value (PV) is one of the most important factors affecting the quality of the deep-fat fried oil. Using bentonite as an adsorbent, the PV can be reduced, thereby improving the quality of the soybean oil. In this study, operating parameters like heating time of oil (10, 15, 20, 25 & 30 h), contact time ( 5, 10, 15, 20, 25 h) and concentration of adsorbent (0.25, 0.5, 0.75, 1.0 and 1.25 g/ 100 ml of oil) have been optimized by response surface methodology (RSM) considering percentage reduction of PV as a response. Adsorption data were analysed by fitting with Langmuir and Freundlich isotherm model. The results show that the Langmuir model shows the best fit compared to the Freundlich model. The adsorption process was also found to follow a pseudo-second-order kinetic model.

Keywords: bentonite, Langmuir isotherm, peroxide value, RSM, soybean oil

Procedia PDF Downloads 369

Authors: A. Armin, R. Fotouhi, W. Szyszkowski

Abstract:

In this paper a 3-D finite element (FE) investigation of soil-blade interaction is described. The effects of blade’s shape and rake angle are examined both numerically and experimentally. The soil is considered as an elastic-plastic granular material with non-associated Drucker-Prager material model. Contact elements with different properties are used to mimic soil-blade sliding and soil-soil cutting phenomena. A separation criterion is presented and a procedure to evaluate the forces acting on the blade is given and discussed in detail. Experimental results were derived from tests using soil bin facility and instruments at the University of Saskatchewan. During motion of the blade, load cells collect data and send them to a computer. The measured forces using load cells had noisy signals which are needed to be filtered. The FE results are compared with experimental results for verification. This technique can be used in blade shape optimization and design of more complicated blade’s shape.

Keywords: finite element analysis, experimental results, blade force, soil-blade contact modeling

Procedia PDF Downloads 315

Authors: Nurul Na'imy Wan, Mohamad Sazali Said, Jaharah Ab. Ghani, Rusli Othman

Abstract:

This paper presents the surface roughness of the aluminium silicon alloy (AlSi) matrix composite which has been reinforced with aluminium nitride (AlN). Experiments were conducted at various cutting speeds, feed rates, and depths of cut, according to a standard orthogonal array L27 of Taguchi method using TiN coating tool of insert. The signal-to-noise (S/N) ratio and analysis of variance are applied to study the characteristic performance of cutting speeds, feed rates and depths of cut in measuring the surface roughness during the milling operation. The surface roughness was observed using Mitutoyo Formtracer CS-500 and analyzed using the Taguchi method. From the Taguchi analysis, it was found that cutting speed of 230 m/min, feed rate of 0.4 mm/tooth, depth of cut of 0.3 mm were the optimum machining parameters using TiN coating insert.

Keywords: AlSi/AlN metal matrix composite (MMC), surface roughness, Taguchi method, machining parameters

Procedia PDF Downloads 425

Authors: Arun Prasad Jaganathan

Abstract:

In today's dynamic industrial world, traditional task allocation methods often fall short in adapting to evolving operational conditions. This paper introduces an AI-enabled task assistance and management system designed to overcome the limitations of conventional approaches. By using artificial intelligence (AI) and machine learning (ML), the system intelligently interprets user instructions, analyzes tasks, and allocates resources based on real-time data and environmental factors. Additionally, geolocation tracking enables proactive identification of potential delays, ensuring timely interventions. With its transparent reporting mechanisms, the system provides stakeholders with clear insights into task progress, fostering accountability and informed decision-making. The paper presents a comprehensive overview of the system architecture, algorithm, and implementation, highlighting its potential to revolutionize task management across diverse industries.

Keywords: artificial intelligence, machine learning, task allocation, operational efficiency, resource optimization

Procedia PDF Downloads 47

Authors: Boutheina Ben Abdelmoumen Mardassi, Salim Chibani, Safa Boujemaa, Amaury Vaysse, Julien Guglielmini, Elhem Yacoub

Abstract:

Background and aim: Mycoplasma hominis (MH) is a pathogenic bacterium belonging to the Mollicutes class. It causes a wide range of gynecological infections and infertility among adults. Recently, we have explored for the first time the phylodistribution of Tunisian M. hominis clinical strains using an expanded MLST. We have demonstrated their distinction into two pure lineages, which each corresponding to a specific pathotype: genital infections and infertility. The aim of this project is to gain further insight into the evolutionary dynamics and the specific genetic factors that distinguish MH pathotypes Methods: Whole genome sequencing of Mycoplasma hominis clinical strains was performed using illumina Miseq. Denovo assembly was performed using a publicly available in-house pipeline. We used prokka to annotate the genomes, panaroo to generate the gene presence matrix and Jolytree to establish the phylogenetic tree. We used treeWAS to identify genetic loci associated with the pathothype of interest from the presence matrix and phylogenetic tree. Results: Our results revealed a clear categorization of the 62 MH clinical strains into two distinct genetic lineages, with each corresponding to a specific pathotype.; gynecological infections and infertility[AV1] . Genome annotation showed that GC content is ranging between 26 and 27%, which is a known characteristic of Mycoplasma genome. Housekeeping genes belonging to the core genome are highly conserved among our strains. TreeWas identified 4 virulence genes associated with the pathotype gynecological infection. encoding for asparagine--tRNA ligase, restriction endonuclease subunit S, Eco47II restriction endonuclease, and transcription regulator XRE (involved in tolerance to oxidative stress). Five genes have been identified that have a statistical association with infertility, tow lipoprotein, one hypothetical protein, a glycosyl transferase involved in capsule synthesis, and pyruvate kinase involved in biofilm formation. All strains harbored an efflux pomp that belongs to the family of multidrug resistance ABC transporter, which confers resistance to a wide range of antibiotics. Indeed many adhesion factors and lipoproteins (p120, p120', p60, p80, Vaa) have been checked and confirmed in our strains with a relatively 99 % to 96 % conserved domain and hypervariable domain that represent 1 to 4 % of the reference sequence extracted from gene bank. Conclusion: In summary, this study led to the identification of specific genetic loci associated with distinct pathotypes in M hominis.

Keywords: mycoplasma hominis, infertility, gynecological infections, virulence genes, antibiotic resistance

Procedia PDF Downloads 85

Authors: Nikhil Yadav, Shubham Verma

Abstract:

Gas lift is a common technique used to optimize oil production in wells. Prosper software is a powerful tool for modeling and optimizing gas lift systems in oil wells. This review paper examines the effectiveness of Prosper software in optimizing gas lift systems in oil-producing wells. The literature review identified several studies that demonstrated the use of Prosper software to adjust injection rate, depth, and valve characteristics to optimize gas lift system performance. The results showed that Prosper software can significantly improve production rates and reduce operating costs in oil-producing wells. However, the accuracy of the model depends on the accuracy of the input data, and the cost of Prosper software can be high. Therefore, further research is needed to improve the accuracy of the model and evaluate the cost-effectiveness of using Prosper software in gas lift system optimization

Keywords: gas lift, prosper software, injection rate, operating costs, oil-producing wells

Procedia PDF Downloads 75

Authors: T. Wejrzanowski, M. Grybczuk, E. Tymicki, K. J. Kurzydlowski

Abstract:

In the present study, numerical simulations of heat and mass transfer in Physical Vapor Transport reactor during silicon carbide single crystal growth are addressed. Silicon carbide is a wide bandgap material with unique properties making it highly applicable for high power electronics applications. Because of high manufacturing costs improvements of SiC production process are required. In this study, numerical simulations were used as a tool of process optimization. Computer modeling allows for cost and time effective analysis of processes occurring during SiC single crystal growth and provides essential information needed for improvement of the process. Quantitative relationship between process conditions, such as temperature or pressure, and crystal growth rate and shape of crystallization front have been studied and verified using experimental data. Basing on modeling results, several process improvements were proposed and implemented.

Keywords: Finite Volume Method, semiconductors, Physica Vapor Transport, silicon carbide

Procedia PDF Downloads 495

Authors: Ines Gasmi, Salima Smiti, Makram Soui, Khaled Ghedira

Abstract:

Credit risk is considered as one of the important issues for financial institutions. It provokes great losses for banks. To this objective, numerous methods for credit risk evaluation have been proposed. Many evaluation methods are black box models that cannot adequately reveal information hidden in the data. However, several works have focused on building transparent rules-based models. For credit risk assessment, generated rules must be not only highly accurate, but also highly interpretable. In this paper, we aim to build both, an accurate and transparent credit risk evaluation model which proposes a set of classification rules. In fact, we consider the credit risk evaluation as an optimization problem which uses a genetic programming (GP) algorithm, where the goal is to maximize the accuracy of generated rules. We evaluate our proposed approach on the base of German and Australian credit datasets. We compared our finding with some existing works; the result shows that the proposed GP outperforms the other models.

Keywords: credit risk assessment, rule generation, genetic programming, feature selection

Procedia PDF Downloads 344

Authors: Marwa Ben Abdessalem, Amin Zribi, Ammar Bouallègue

Abstract:

In this paper, a Joint Source Channel coding scheme based on LDPC codes is investigated. We consider two concatenated LDPC codes, one allows to compress a correlated source and the second to protect it against channel degradations. The original information can be reconstructed at the receiver by a joint decoder, where the source decoder and the channel decoder run in parallel by transferring extrinsic information. We investigate the performance of the JSC LDPC code in terms of Bit-Error Rate (BER) in the case of transmission over an Additive White Gaussian Noise (AWGN) channel, and for different source and channel rate parameters. We emphasize how JSC LDPC presents a performance tradeoff depending on the channel state and on the source correlation. We show that, the JSC LDPC is an efficient solution for a relatively low Signal-to-Noise Ratio (SNR) channel, especially with highly correlated sources. Finally, a source-channel rate optimization has to be applied to guarantee the best JSC LDPC system performance for a given channel.

Keywords: AWGN channel, belief propagation, joint source channel coding, LDPC codes

Procedia PDF Downloads 354

Authors: Ratthiwa Deewan, Visanu Tanboonchuy

Abstract:

The optimal conditions for green synthesis of zero-valent (G-NZVI) synthesis are investigated in this study using a Box Behnken design. The factors that were used in the study consisted of 3 factors as follows: the iron solution to mango peel extract ratio (1:1-1:3), feeding rate of mango peel extracts (1-5 mL/min), and agitation speed (300-30 rpm). The results showed that the optimization of conditions using the regression model was appropriate. The optimal conditions of the synthesis of G-NZVI for arsenate removal are the iron solution to mango peel extract ratio of 1:1, the feeding rate of mango peel extract 5 mL/min, and the agitation speed rate of 300 rpm which was able to arsenate removal 100%.

Keywords: Box Behnken design, arsenate removal, green nano zero valent iron, arsenic

Procedia PDF Downloads 12

Authors: Almahd Alshereef, Ahmed Alkilany, Hammad Said, Azuraliza Abu Bakar

Abstract:

From time to time, electrical power grid is directed by the National Electricity Operator to conduct load shedding, which involves hours' power outages on the area of this study, Southern Electrical Grid of Libya (SEGL). Load shedding is conducted in order to alleviate pressure on the National Electricity Grid at times of peak demand. This approach has chosen a set of categories to study load-shedding problem considering the effect of the demand priorities on the operation of the power system during emergencies. Classification of category region for load shedding problem is solved by a new algorithm (the harmony algorithm) based on the "random generation list of category region", which is a possible solution with a proximity degree to the optimum. The obtained results prove additional enhancements compared to other heuristic approaches. The case studies are carried out on SEGL.

Keywords: optimization, harmony algorithm, load shedding, classification

Procedia PDF Downloads 386

Authors: Michel Wakim, Rodrigo Rivera Tinoco

Abstract:

Supersonic ejector is an economical device that use high pressure vapor to compress a low pressure vapor without any rotating parts or external power sources. Entrainment ratio is a major characteristic of the ejector performance, so the ejector performance is highly dependent on its geometry. The aim of this paper is to design ejector geometry, based on pre-specified operating conditions, and to study the flow behavior inside the ejector by using computational fluid dynamics ‘CFD’ by using ‘ANSYS FLUENT 15.0’ software. In the first section; 1-D mathematical model is carried out to predict the ejector geometry. The second part describes the flow behavior inside the designed model. CFD is the most reliable tool to reveal the mixing process at different parts of the supersonic turbulent flow and to study the effect of the geometry on the effective ejector area. Finally, the results show the effect of the geometry on the entrainment ratio.

Keywords: computational fluids dynamics, ejector, entrainment ratio, geometry optimization, performance

Procedia PDF Downloads 269

Authors: Mahsa Mousavi, Hamid Reza Pourshaghaghi, Mohammad Tahghighi, Henk Corporaal

Abstract:

Recently, Statistic Random-Access Memory-based (SRAM-based) Field-Programmable Gate Arrays (FPGAs) are widely used in aeronautics and space systems where high dependability is demanded and considered as a mandatory requirement. Since design’s circuit is stored in configuration memory in SRAM-based FPGAs; they are very sensitive to Single Event Upsets (SEUs). In addition, the adverse effects of SEUs on the electronics used in space are much higher than in the Earth. Thus, developing fault tolerant techniques play crucial roles for the use of SRAM-based FPGAs in space. However, fault tolerance techniques introduce additional penalties in system parameters, e.g., area, power, performance and design time. In this paper, an accurate estimation of configuration memory vulnerability to SEUs is proposed for approximate-tolerant applications. This vulnerability estimation is highly required for compromising between the overhead introduced by fault tolerance techniques and system robustness. In this paper, we study applications in which the exact final output value is not necessarily always a concern meaning that some of the SEU-induced changes in output values are negligible. We therefore define and propose Approximate-based Configuration Memory Vulnerability Factor (ACMVF) estimation to avoid overestimating configuration memory vulnerability to SEUs. In this paper, we assess the vulnerability of configuration memory by injecting SEUs in configuration memory bits and comparing the output values of a given circuit in presence of SEUs with expected correct output. In spite of conventional vulnerability factor calculation methods, which accounts any deviations from the expected value as failures, in our proposed method a threshold margin is considered depending on user-case applications. Given the proposed threshold margin in our model, a failure occurs only when the difference between the erroneous output value and the expected output value is more than this margin. The ACMVF is subsequently calculated by acquiring the ratio of failures with respect to the total number of SEU injections. In our paper, a test-bench for emulating SEUs and calculating ACMVF is implemented on Zynq-7000 FPGA platform. This system makes use of the Single Event Mitigation (SEM) IP core to inject SEUs into configuration memory bits of the target design implemented in Zynq-7000 FPGA. Experimental results for 32-bit adder show that, when 1% to 10% deviation from correct output is considered, the counted failures number is reduced 41% to 59% compared with the failures number counted by conventional vulnerability factor calculation. It means that estimation accuracy of the configuration memory vulnerability to SEUs is improved up to 58% in the case that 10% deviation is acceptable in output results. Note that less than 10% deviation in addition result is reasonably tolerable for many applications in approximate computing domain such as Convolutional Neural Network (CNN).

Keywords: fault tolerance, FPGA, single event upset, approximate computing

Procedia PDF Downloads 192

Authors: Jihene Jebeniani

Abstract:

We proposed an approach combining both the techniques of experimental economy and the flexibility of discrete choice models in order to test the loss aversion. Our main objective was to test the loss aversion of the Cumulative Prospect Theory (CPT). We developed an experimental laboratory in the context of the financial investments that aimed to analyze the attitude towards the risk of the investors. The study uses the lotteries and is basing on econometric modeling. The estimated model was the ordered probit.

Keywords: risk aversion, behavioral finance, experimental economic, lotteries, cumulative prospect theory

Procedia PDF Downloads 463

Authors: Pinn Tsin Isabel Yee

Abstract:

Students are increasingly turning towards online learning materials to supplement their education. One such approach would be the gamified student engagement platforms (GSEPs) to instill a new learning culture. Data was collected from closed-ended questions via content analysis techniques. About 81.8% of college students from the Monash University Foundation Year agreed that GSEPs (Quizizz) was an effective tool for learning. Approximately 85.5% of students disagreed that games were a waste of time. GSEPs were highly effective among students to facilitate the learning process.

Keywords: engagement, gamified, Quizizz, technology

Procedia PDF Downloads 101