Search results for: teaching and learning effectiveness

Authors: P. Larpsomboonchai

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Agro-industry is one of major industries that has strong impacts on national economic incomes, growth, stability, and sustainable development. Moreover, this industry also has strong influences on social, cultural and political issues. Furthermore, this industry, as producing primary and secondary products, is facing challenges from such diverse factors such as demand inconsistency, intense international competition, technological advancements and new competitors. In order to maintain and to improve industry’s competitiveness in both domestics and international markets, science and technology are key factors. Besides hard sciences and technologies, modern industrial engineering concepts such as Just in Time (JIT) Total Quality Management (TQM), Quick Response (QR), Supply Chain Management (SCM) and Lean can be very effective to supportant to increase efficiency and effectiveness of these agricultural products on world stage. Onion is one of Thailand’s major export products which brings back national incomes. But, it also facing challenges in many ways. This paper focused its interests in onion packing process and its related activities such as storage and shipment from one of major packing plant and storage in Mae Wang District, Chiang Mai, Thailand, by applying Toyota Production System (TPS) or Lean concepts, to improve process capability throughout the entire packing and distribution process which will be profitable for the whole onion supply chain. And it will be beneficial to other related agricultural products in Thailand and other ASEAN countries.

Keywords: packing process, Toyota Production System (TPS), lean concepts, waste reduction, lean in agro-industries activities

Procedia PDF Downloads 270

Authors: Andy Zhang, Awnik Roy, Trevor B. Chen, Bibik Oleksandar, Subodh Adhikari, Paul S. Hsu

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The durability of a combustor in gas-turbine engines is a strong function of its component temperatures and requires good control of these temperatures. Since the temperature of combustion gases frequently exceeds the melting point of the combustion liner walls, an efficient air-cooling system with optimized flow rates of cooling air is significantly important to elongate the lifetime of liner walls. To determine the effectiveness of the air-cooling system, accurate two-dimensional (2D) surface temperature measurement of combustor liner walls is crucial for advanced engine development. Traditional diagnostic techniques for temperature measurement in this application include the rmocouples, thermal wall paints, pyrometry, and phosphors. They have shown some disadvantages, including being intrusive and affecting local flame/flow dynamics, potential flame quenching, and physical damages to instrumentation due to harsh environments inside the combustor and strong optical interference from strong combustion emission in UV-Mid IR wavelength. To overcome these drawbacks, a compact and small borescope long-wave-infrared (LWIR) sensor is developed to achieve 2D high-spatial resolution, high-fidelity thermal imaging of 2D surface temperature in gas-turbine engines, providing the desired engine component temperature distribution. The compactLWIRborescope sensor makes it feasible to promote the durability of a combustor in gas-turbine engines and, furthermore, to develop more advanced gas-turbine engines.

Keywords: borescope, engine, low-wave-infrared, sensor

Procedia PDF Downloads 121

Authors: Hanna Faron, Wojciech Marcinkowski, Daniel Prusak

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The aim of this article is to familiarize with the activity of AGH Racing scientific circle, pertaining to the international project -Formula Student, giving the opportunity to young engineers from all around the world to validate their talent and knowledge in the real world conditions, under the pressure of time, and the design requirements. Every year, the team begins the process of building a race car from the formation of human resources. In case of the public sector, to which public universities can be included, the scientific circles represent the structure uniting students with the common interests and level of determination. Due to the scientific nature of the project which simulates the market conditions, they have a chance to verify previously acquired knowledge in practice. High level of the innovation and competitiveness of participating in the project Formula Student teams, requires an intelligent organizational system, which is characterized by a high dynamics. It is connected with the necessity of separation of duties, setting priorities, selecting optimal solutions which is often a compromise between the available technology and a limited budget. Proper selection of the adequate guidelines in the design phase allows an efficient transition to the implementation stage, which is process-oriented implementation of the project. Four dynamic and three static competitions are the main verification and evaluation of year-round work and effort put into the process of building a race car. Acquired feedback flowing during the race is a very important part while monitoring the effectiveness of AGH Racing scientific circle, as well as the main criterion while determining long-term goals and all the necessary improvements in the team.

Keywords: SAE, formula student, race car, public sector, automotive industry

Procedia PDF Downloads 343

Authors: Abdullah Abu-Tineh, Hissa Sadiq, Fatma Al-Mutawah, Youmen Chabaan

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The current study examined the experiences of educators in Qatar with the licensure process currently implemented at government schools. Using a survey study design, a total of 1,669 participants expressed their perceptions on the strengths and weaknesses of the licensure system, the professional standards, and the professional portfolio. Findings included participants’ beliefs on the importance of the licensure system in improving their performance, the necessity of using the professional standards as tools for professional growth and development, the importance of refining the professional portfolio for authenticity and reliability, and the inclusion of multiple sources of evidence, such as classroom observations, interviews, student learning outcomes, and surveys. Documenting teachers’ and school leaders’ voices was fundamental in finding ways to successfully drive future developments of the licensure system. The findings may also provide implications for other countries interested in developing or refining their own appraisal systems.

Keywords: licensure system, educator voice, professional standards, professional portfolio

Procedia PDF Downloads 194

Authors: Priyajeet Kaur Kaleka

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Introduction: A dentist is often the first responder in the battle for a patient’s healthy body and maybe the first health professional to observe signs of child abuse, be it physical, emotional, and/or sexual mistreatment. Therefore, it is an ethical responsibility for the dental clinician to detect and report suspected cases of child abuse and neglect (CAN). The main reasons for not reporting suspected cases of CAN, with special emphasis on the third: 1) Uncertainty of the diagnosis, 2) Lack of knowledge of the reporting procedure, and 3) Child abuse and neglect somewhat remained the subject of ignorance among dental professionals because of a lack of advance clinical training. Given these epidemic proportions, there is a scope of further research about dental school curriculum design. Purpose: This study aimed to assess the knowledge and attitude of dentists in Canada regarding signs and symptoms of child abuse and neglect (CAN), reporting procedures, and whether educational strategies followed by dental schools address this sensitive issue. In pursuit of that aim, this abstract summarizes the evidence related to this question. Materials and Methods: Data was collected through a specially designed questionnaire adapted and modified from the author’s previous cross-sectional study on (CAN), which was conducted in Pune, India, in 2016 and is available on the database of PubMed. Design: A random sample was drawn from the targeted population of registered dentists and dental students in Canada regarding their knowledge, professional responsibilities, and behavior concerning child abuse. Questionnaire data were distributed to 200 members. Out of which, a total number of 157 subjects were in the final sample for statistical analysis, yielding response of 78.5%. Results: Despite having theoretical information on signs and symptoms, 55% of the participants indicated they are not confident to detect child physical abuse cases. 90% of respondents believed that recognition and handling the CAN cases should be a part of undergraduate training. Only 4.5% of the participants have correctly identified all signs of abuse due to inadequate formal training in dental schools and workplaces. Although nearly 96.3% agreed that it is a dentist’s legal responsibility to report CAN, only a small percentage of the participants reported an abuse case in the past. While 72% stated that the most common factor that might prevent a dentist from reporting a case was doubt over the diagnosis. Conclusion: The goal is to motivate dental schools to deal with this critical issue and provide their students with consummate training to strengthen their capability to care for and protect children. The educational institutions should make efforts to spread awareness among dental students regarding the management and tackling of CAN. Clinical Significance: There should be modifications in the dental school curriculum focusing on problem-based learning models to assist graduates to fulfill their legal and professional responsibilities. CAN literacy should be incorporated into the dental curriculum, which will eventually benefit future dentists to break this intergenerational cycle of violence.

Keywords: abuse, child abuse and neglect, dentist knowledge, dental school curriculum, problem-based learning

Procedia PDF Downloads 193

Authors: Sayed M. Soleimani, Nader H. Ghareeb, Nourhan H. Shaker, Muhammad B. Siddiqui

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Honeycomb sandwich panels have been widely used as protective structural elements against blast loading. The main advantages of these panels include their light weight due to the presence of voids, as well as their energy absorption capability. Terrorist activities have imposed new challenges to structural engineers to design protective measures for vital structures. Since blast loading is not usually considered in the load combinations during the design process of a structure, researchers around the world have been motivated to study the behavior of potential elements capable of resisting sudden loads imposed by the detonation of explosive materials. One of the best candidates for this objective is the honeycomb sandwich panel. Studying the effects of explosive materials on the panels requires costly and time-consuming experiments. Moreover, these type of experiments need permission from defense organizations which can become a hurdle. As a result, modeling and simulation using an appropriate tool can be considered as a good alternative. In this research work, the finite element package ABAQUS® is used to study the behavior of hexagonal and squared honeycomb steel sandwich panels under the explosive effects of different amounts of trinitrotoluene (TNT). The results of finite element modeling of a specific honeycomb configuration are initially validated by comparing them with the experimental results from literature. Afterwards, several configurations including different geometrical properties of the honeycomb wall are investigated and the results are compared with the original model. Finally, the effectiveness of the core shape and wall thickness are discussed, and conclusions are made.

Keywords: Abaqus, blast loading, finite element modeling, steel honeycomb sandwich panel

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Authors: An-Jui. Li, Kelvin Lim, Chien-Kuo Chiu, Benson Hsiung

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This paper details the utilization of artificial intelligence (AI) in the field of slope stability whereby quick and convenient solutions can be obtained using the developed tool. The AI tool used in this study is the artificial neural network (ANN), while the slope stability analysis methods are the finite element limit analysis methods. The developed tool allows for the prompt prediction of the safety factors of fill slopes and their corresponding probability of failure (depending on the degree of variation of the soil parameters), which can give the practicing engineer a reasonable basis in their decision making. In fact, the successful use of the Extreme Learning Machine (ELM) algorithm shows that slope stability analysis is no longer confined to the conventional methods of modeling, which at times may be tedious and repetitive during the preliminary design stage where the focus is more on cost saving options rather than detailed design. Therefore, similar ANN-based tools can be further developed to assist engineers in this aspect.

Keywords: landslide, limit analysis, artificial neural network, soil properties

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Authors: A. A. Sadia, A. Emdad, E. Hossain

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The increasing importance of mushrooms as a source of nutrition, health benefits, and even potential cancer treatment has raised awareness of the impact of climate-sensitive variables on their cultivation. Factors like temperature, relative humidity, air quality, and substrate composition play pivotal roles in shaping mushroom growth, especially in Bangladesh. Oyster mushrooms, a commonly cultivated variety in this region, are particularly vulnerable to climate fluctuations. This research explores the climatic dynamics affecting oyster mushroom cultivation and, presents an approach to address these challenges and provides tangible solutions to fortify the agro-economy, ensure food security, and promote the sustainability of this crucial food source. Using climate and production data, this study evaluates the performance of three clustering algorithms -KMeans, OPTICS, and BIRCH- based on various quality metrics. While each algorithm demonstrates specific strengths, the findings provide insights into their effectiveness for this specific dataset. The results yield essential information, pinpointing the optimal temperature range of 13°C-22°C, the unfavorable temperature threshold of 28°C and above, and the ideal relative humidity range of 75-85% with the suitable production regions in three different seasons: Kharif-1, 2, and Robi. Additionally, a user-friendly web application is developed to support mushroom farmers in making well-informed decisions about their cultivation practices. This platform offers valuable insights into the most advantageous periods for oyster mushroom farming, with the overarching goal of enhancing the efficiency and profitability of mushroom farming.

Keywords: climate variability, mushroom cultivation, clustering techniques, food security, sustainability, web-application

Procedia PDF Downloads 57

Authors: Muhammad Saeed, Nazeer Ahmed, Mukhtar Alam, Fazli Subhan, Muhammad Adnan, Fazli Wahid, Hidayat Ullah, Rafiullah

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The present experiment evaluated different synthetic insecticides against Jassid (Amrasca devastations) on pea crop at Agriculture Research Institute Tarnab, Peshawar Khyber Pakhtunkhwa. The field was prepared to cultivate okra crop in Randomized Complete Block (RCB) Design having six treatments with four replications. Plant to plant and row to row distance was kept at 15 cm and 30 cm, respectively. Pre and post spray data were recorded randomly from the top, middle and bottom leaves of five selected plants. Five synthetic insecticides, namely Confidor (Proponil), a neonicotinoid insecticide, Chlorpyrifos (chlorinated organophosphate (OP) insecticide), Lazer (dinitroaniline) (Pendimethaline), Imidacloprid (neonicotinoids insecticide) and Thiodan (Endosulfan, organochlorine insecticide), were used against infestation of aphids, pea pod borer, stem fly, leaf minor and pea weevil. Each synthetic insecticide showed significantly more effectiveness than control (untreated plots) but was non-significant among each other. The lowest population density was recorded in the plot treated with synthetic insecticide i.e. Confidor (0.6175 liter.ha-1) (4.24 aphids plant⁻¹) which is followed by Imidacloprid (0.6175 liter.ha⁻¹) (4.64 pea pod borer plant⁻¹), Thiodan (1.729 liter.ha⁻¹) (4.78 leaf minor plant⁻¹), Lazer (2.47 liter.ha-1) (4.91 pea weevil plant⁻¹), Chlorpyrifos (1.86 liter.ha⁻¹) (5.11 stem fly plant⁻¹), respectively while the highest population was recorded from the control plot. It is concluded from the data that the residual effect decreases with time after the application of spray, which may be less dangerous to the environment and human beings and can effectively manage this dread.

Keywords: okra crop, jassids, Confidor, imidacloprid, chlorpyrifos, laser, Thiodan

Procedia PDF Downloads 76

Authors: Namirimu Beatrice Doreen

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In recent years, there has been growing recognition of the importance of diversity, equity, and inclusion (DEI) in advertising, driven in part by the increasing diversity of society and the expanding reach of new media platforms. As marketers grapple with the challenge of creating campaigns that resonate with a wide range of audiences, the role of new media adoption emerges as a critical, independent variable shaping the landscape of DEI in advertising. This paper delves into the evolving dynamics of DEI in advertising, examining the multifaceted challenges and opportunities encountered by brands in their pursuit of more inclusive marketing strategies. Drawing on theoretical frameworks from marketing, sociology, and communication studies, this paper explores the intricate interplay between DEI initiatives and their impact on consumer perceptions, brand reputation, and market performance. The analysis considers how new media adoption influences the effectiveness and reach of DEI initiatives as brands leverage digital platforms to engage with diverse audiences in innovative ways. Through insightful case studies, this paper illustrates best practices and identifies areas for improvement in the realm of inclusive advertising, shedding light on the practical implications of DEI principles for marketers. By synthesizing insights from academia and industry, this paper offers actionable recommendations for marketers seeking to navigate the complexities of DEI in their advertising strategies. By embracing DEI principles and harnessing the power of new media platforms, brands can foster a more equitable and inclusive advertising landscape, ultimately enhancing their connections with diverse audiences and driving positive social change.

Keywords: diversity, equity, inclusion, new media, contemporary marketing communication

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Authors: Hadjer Didouh, Mohamed Hadj Meliani, Izzeddine Sameut Bouhaik

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As global demand for natural gas intensifies, Algeria is increasing its production to meet this rising need, placing significant strain on the nation's extensive pipeline infrastructure. Sonatrach, Algeria's national oil and gas company, faces persistent challenges from metal corrosion, particularly microbiologically influenced corrosion (MIC), leading to substantial economic losses. This study investigates the corrosion-inhibiting properties of Calotropis procera extracts, known as karanka, as a sustainable alternative to conventional inhibitors, which often pose environmental risks. The Calotropis procera extracts were evaluated for their efficacy on carbon steel API 5L X52 through electrochemical techniques, including potentiodynamic polarization and electrochemical impedance spectroscopy (EIS), under simulated operational conditions at varying concentrations, particularly at 10%, and elevated temperatures up to 60°C. The results demonstrated remarkable inhibition efficiency, achieving 96.73% at 60°C, attributed to the formation of a stable protective film on the metal surface that suppressed anodic and cathodic corrosion reactions. Scanning electron microscopy (SEM) confirmed the stability and adherence of these protective films, while EIS analysis indicated a significant increase in charge transfer resistance, highlighting the extract's effectiveness in enhancing corrosion resistance. The abundant availability of Calotropis procera in Algeria and its low-cost extraction processes present a promising opportunity for sustainable biocorrosion management strategies in the oil and gas industry, reinforcing the potential of plant-based extracts as viable alternatives to synthetic inhibitors for environmentally friendly corrosion control.

Keywords: corrosion inhibition, calotropis procera, microbiologically influenced corrosion, eco-friendly inhibitor

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Authors: F. Al-Sheikh, C. Moralejo, M. Pritzker, W. A. Anderson, A. Elkamel

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Ammonia in mining wastewater is a significant problem, and treatment can be especially difficult in cold climates where biological treatment is not feasible. An adsorption process is one of the alternative processes that can be used to reduce ammonia concentrations to acceptable limits, and therefore a LEWATIT resin strongly acidic H+ form ion exchange resin and a Bowie Chabazite Na form AZLB-Na zeolite were tested to assess their effectiveness. For these adsorption tests, two packed bed columns (a mini-column constructed from a 32-cm long x 1-cm diameter piece of glass tubing, and a 60-cm long x 2.5-cm diameter Ace Glass chromatography column) were used containing varying quantities of the adsorbents. A mining wastewater with ammonia concentrations of 22.7 mg/L was fed through the columns at controlled flowrates. In the experimental work, maximum capacities of the LEWATIT ion exchange resin were 0.438, 0.448, and 1.472 mg/g for 3, 6, and 9 g respectively in a mini column and 1.739 mg/g for 141.5 g in a larger Ace column while the capacities for the AZLB-Na zeolite were 0.424, and 0.784 mg/g for 3, and 6 g respectively in the mini column and 1.1636 mg/g for 38.5 g in the Ace column. In the theoretical work, Thomas, Adams-Bohart, and Yoon-Nelson models were constructed to describe a breakthrough curve of the adsorption process and find the constants of the above-mentioned models. In the regeneration tests, 5% hydrochloric acid, HCl (v/v) and 10% sodium hydroxide, NaOH (w/v) were used to regenerate the LEWATIT resin and AZLB-Na zeolite with 44 and 63.8% recovery, respectively. In conclusion, continuous flow adsorption using a LEWATIT ion exchange resin and an AZLB-Na zeolite is efficient when using a co-flow technique for removal of the ammonia from wastewater. Thomas, Adams-Bohart, and Yoon-Nelson models satisfactorily fit the data with R² closer to 1 in all cases.

Keywords: AZLB-Na zeolite, continuous adsorption, Lewatit resin, models, regeneration

Procedia PDF Downloads 379

Authors: Sara atibi, Azzeddine Atibi, Salim Ahmed, Khadija El Kababi

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The emergence of an entrepreneurial culture within academic institutions is increasingly seen as essential for preparing students for contemporary economic challenges. This study examines the effectiveness of educational programs and interventions aimed at promoting entrepreneurial spirit at Al Akhawayn University. The central issue explores the types of programs most efficient in instilling the necessary entrepreneurial skills and attitudes in students. The primary question about the ‘types of educational programs and interventions that are most effective in cultivating and reinforcing the entrepreneurial spirit among students at Al Akhawayn University' is broken down into sub-questions detailing the characteristics of current programs, factors influencing their success, the evolution of students' entrepreneurial skills, the role of teachers and mentors, best practices from other institutions, and the long-term impacts on graduates' entrepreneurial careers. To address this question, a mixed-methods approach, combining quantitative and qualitative methods, was adopted. Quantitative data collection includes questionnaires and surveys designed to evaluate students' attitudes, skills, and perceptions before and after participating in entrepreneurship programs. Simultaneously, semi-structured interviews, focus groups, and participant observations provide in-depth qualitative data on the experiences of students, teachers, and administrators. Quantitative data analysis employs descriptive and inferential statistical techniques, while qualitative analysis uses a thematic approach to identify key perceptions and experiences. This triangulation of data ensures robust and comprehensive results.

Keywords: student entrepreneurship, pedagogical interventions, Al Akhawayn university, entrepreneurial culture, entrepreneurial skills

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Authors: Ayaka A. Matsuo, Gweyneth Victoria I. Maranan, Shawn Mikel Hobayan

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In this study, we delve into the application of mahogany fruits as biochar for soil amendment, aiming to evaluate their effectiveness in improving soil quality and influencing the growth parameters of okra plants through a comprehensive analysis employing various multivariate tests. In a more straightforward approach, our results show that biochar derived from isn't just a minor player but emerges as a key contributor to our study. This finding holds profound implications, as it highlights the material significance of biochar derived from Mahogany (Swietenia macrophylla) fruits, leaves, and branches in shaping the outcomes. The importance of this discovery lies in its contribution to an enhanced comprehension of the overall effects of biochar on the variables explored in our investigation. Notably, the positive changes observed in height, number of leaves, and width of leaves in okra plants further support the premise that the incorporation of biochar improves soil quality. These findings provide valuable insights for agricultural practices, suggesting that biochar derived from Mahogany (Swietenia macrophylla) fruits, leaves, and branches holds promise as a sustainable soil amendment with positive implications for plant growth. The statistical results from multivariate tests serve to solidify the conclusion that biochar plays a pivotal role in driving the observed outcomes in our study. In essence, this research not only sheds light on the potential of mahogany fruit-derived biochar but also emphasizes its significance in fostering healthier soil conditions and, consequently, enhanced plant growth.

Keywords: soil amendment, biochar, mahogany, soil health

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Authors: Yuanjin Liu

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Retirement withdrawal strategies are very important to minimize the probability of ruin in retirement. The ruin probability is modeled as a function of initial withdrawal age, gender, asset allocation, inflation rate, and initial withdrawal rate. The ruin probability is obtained based on the 2019 period life table for the Social Security, IRS Required Minimum Distribution (RMD) Worksheets, US historical bond and equity returns, and inflation rates using simulation. Several popular machine learning algorithms of the generalized additive model, random forest, support vector machine, extreme gradient boosting, and artificial neural network are built. The model validation and selection are based on the test errors using hyperparameter tuning and train-test split. The optimal model is recommended for retirees to monitor the ruin probability. The optimal withdrawal strategy can be obtained based on the optimal predictive model.

Keywords: ruin probability, retirement withdrawal strategies, predictive models, optimal model

Procedia PDF Downloads 71

Authors: M. Testa, L. Peotta, S. Giusiano, B. Lazzolino, U. Manera, A. Canosa, M. Grassano, F. Palumbo, A. Bombaci, S. Cabras, F. Di Pede, L. Solero, E. Matteoni, C. Moglia, A. Calvo, A. Chio

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Amyotrophic Lateral Sclerosis (ALS) is a neurodegenerative disease of adulthood, which primarily affects the central nervous system and is characterized by progressive bilateral degeneration of motor neurons. The degeneration processes in ALS extend far beyond the neurons of the motor system, and affects cognition, behaviour and language. To outline the prevalence of language deficits in an ALS cohort and explore their profile along with demographic and neuropsychological data. A full neuropsychological battery and language assessment was administered to 56 ALS patients. Neuropsychological assessment included tests of executive functioning, verbal fluency, social cognition and memory. Language was assessed using tests for verbal comprehension, production and pragmatics. Patients were cognitively classified following the Revised Consensus Criteria and divided in three groups showing different levels of language deficits: group 1 - no language deficit; group 2 - one language deficit; group 3 - two or more language deficits. Chi-square for independence and non-parametric measures to compare groups were applied. Nearly half of ALS-CN patients (48%) reported one language test under the clinical cut-off, and only 13% of patents classified as ALS-CI showed no language deficits, while the rest 87% of ALS-CI reported two or more language deficits. ALS-BI and ALS-CBI cases all reported two or more language deficits. Deficits in production and in comprehension appeared more frequent in ALS-CI patients (p=0.011, p=0.003 respectively), with a higher percentage of comprehension deficits (83%). Nearly all ALS-CI reported at least one deficit in pragmatic abilities (96%) and all ALS-BI and ALS-CBI patients showed pragmatic deficits. Males showed higher percentage of pragmatic deficits (97%, p=0.007). No significant differences in language deficits have been found between bulbar and spinal onset. Months from onset and level of impairment at testing (ALS-FRS total score) were not significantly different between levels and type of language impairment. Age and education were significantly higher for cases showing no deficits in comprehension and pragmatics and in the group showing no language deficits. Comparing performances at neuropsychological tests among the three levels of language deficits, no significant differences in neuropsychological performances were found between group 1 and 2; compared to group 1, group 3 appeared to decay specifically on executive testing, verbal/visuospatial learning, and social cognition. Compared to group 2, group 3 showed worse performances specifically in tests of working memory and attention. Language deficits have found to be spread in our sample, encompassing verbal comprehension, production and pragmatics. Our study reveals that also cognitive intact patients (ALS-CN) showed at least one language deficit in 48% of cases. Pragmatic domain is the most compromised (84% of the total sample), present in nearly all ALS-CI (96%), likely due to the influence of executive impairment. Lower age and higher education seem to preserve comprehension, pragmatics and presence of language deficits. Finally, executive functions, verbal/visuospatial learning and social cognition differentiate the group with no language deficits from the group with a clinical language impairment (group 3), while attention and working memory differentiate the group with one language deficit from the clinical impaired group.

Keywords: amyotrophic lateral sclerosis, language assessment, neuropsychological assessment, language deficit

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Authors: Sobhani U. Pilapitiya, Tharanga Peiris

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Software Engineering curriculums generally consist of industry-based practices such as project-based learning (PBL) which mainly focuses on efficient and innovative product development. These approaches can be tailored and used in project-based modules in software engineering curriculums. However, there are very limited attempts in the area especially related to the Sri Lankan context. This paper describes a tailored pedagogical approach and its results of using design sprint which can be used for project-based modules in SE curriculums. A controlled group of second-year software engineering students was selected for the study. The study results indicate that 100% of students agreed that the Design Sprint approach is effective in group-based projects and 83% of students stated that it minimized the re-work compared to traditional project approaches. The tailored process was effective, easy to implement and produced desired results at the end of the session while providing students an enjoyable experience.

Keywords: design sprint, PBL, software engineering, curriculum

Procedia PDF Downloads 195

Authors: Mojtaba Fayaz, Richard Hallal

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This study examines the various types of dangers that our virtual environment is vulnerable to, including how it can be attacked and how to avoid/secure our data. The terrain of cyberspace is never completely safe, and Covid- 19 has added to the confusion, necessitating daily periodic checks and evaluations. Cybercriminals have been able to enact with greater skill and undertake more conspicuous and sophisticated attacks while keeping a higher level of finesse by operating from home. Different types of cyberattacks, such as operation-based attacks, authentication-based attacks, and software-based attacks, are constantly evolving, but research suggests that software-based threats, such as Ransomware, are becoming more popular, with attacks expected to increase by 93 percent by 2020. The effectiveness of cyber frameworks has shifted dramatically as the pandemic has forced work and private life to become intertwined, destabilising security overall and creating a new front of cyber protection for security analysis and personal. The high-rise formats in which cybercrimes are carried out, as well as the types of cybercrimes that exist, such as phishing, identity theft, malware, and DDoS attacks, have created a new front of cyber protection for security analysis and personal safety. The overall strategy for 2022 will be the introduction of frameworks that address many of the issues associated with offsite working, as well as education that provides better information about commercialised software that does not provide the highest level of security for home users, allowing businesses to plan better security around their systems.

Keywords: cyber security, authentication, software, hardware, malware, COVID-19, threat actors, awareness, home users, confidentiality, integrity, availability, attacks

Procedia PDF Downloads 110

Authors: Li Kewen, Su Zhaoxin, Wang Xingmou, Zhu Jian Bing

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Conventional reservoir prediction methods ar not sufficient to explore the implicit relation between seismic attributes, and thus data utilization is low. In order to improve the predictive classification accuracy of reservoir lithology, this paper proposes a deep learning lithology prediction method based on ResNet (Residual Neural Network) and SENet (Squeeze-and-Excitation Neural Network). The neural network model is built and trained by using seismic attribute data and lithology data of Shengli oilfield, and the nonlinear mapping relationship between seismic attribute and lithology marker is established. The experimental results show that this method can significantly improve the classification effect of reservoir lithology, and the classification accuracy is close to 70%. This study can effectively predict the lithology of undrilled area and provide support for exploration and development.

Keywords: convolutional neural network, lithology, prediction of reservoir, seismic attributes

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Authors: B. Gechbaia, K. Goletiani, G. Gabedava, N. Mikeltadze

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At this stage, Georgia is a country which is actively involved in the European integration process, for which the primary priority is effective integration in the European education system. The modern Georgian higher education system is the process of establishing a new sociocultural reality, whose main priorities are determined by the Quality System as a continuous cycle of planning, implementation, checking and acting. Obviously, in this situation, the issue of management of education institutions comes out in the foreground, since the proper planning and implementation of personnel management processes is one of the main determinants of the company's performance. At the same time, one of the most important factors is the psychological comfort of the personnel, ensuring their protection and efficiency of stress management policy. The purpose of this research is to determine how intensely the relationship is between the psychological comfort of the personnel and the efficiency of the quality system in the institution as the quality assurance mechanisms of educational institutions affect the stability of personnel, prevention and management of the stressful situation. The research was carried out within the framework of the Internal Grant Project «The Role of Organizational Culture in the Process of Settlement of Management of Stress and Conflict, Georgian Reality and European Experience » of the Batumi Navigation Teaching University, based on the analysis of the survey results of target groups. The small-scale research conducted by us has revealed that the introduction of quality assurance system and its active implementation increased the quality of management of Georgian educational institutions, increased the level of universal engagement in internal and external processes and as a result, it has improved the quality of education as well as social and psychological comfort indicators of the society.

Keywords: quality assurance, effective management, stability of personnel, psychological comfort, stress management

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Authors: Fatai Olaitan Alao, Thimoty Abiodun Adebayo, Oladele Abiodun Olaniran

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This experiment was conducted at Ladoke Akintola University of Technology, Ogbomoso, Teaching and Research farm during the major and minor planting season , 2017 to determine the effects of Annona squamosa (Linn.) and Moringa oleifera (Lam) extracts on insect pests of watermelon and their effects on nutritional contents of watermelon fruits. Synthetic insecticide and untreated plots were included in the treatments for comparison. Selected plants were prepared with cold water and each plant extracts was applied at three different concentrations (5,10 and 20% v/v). Data were collected on population density of insect pests, number of aborted fruits, number of defoliated flowers , the yield was calculated in t/ha, nutritional and fatty acid contents were determine using gas chromatography. The results show that the two major insects were observed - Diabrotica undicimpunctata and Dacus cucurbitea. The tested plant extracts had about 65% control of the observed insect pests when compared with the control and the two plant extracts had the same insecticidal efficacy. However, the applied plant extracts at 20% v/v had higher insecticidal effects than the other tested concentrations. Significant higher yield was observed on the plant extracts treated plants compared with untreated plants which had the least yield() but none of the plant extracts performed effectively as Lambdachyalothrin in the control of insect pests and yield. Meanwhile, the tested plant extracts significantly improved the proximate and fatty acid contents of watermelon fruits while Lambdachyalothrin contributed negatively to the nutritional contents of watermelon fruits. Therefore, A. squpmosa and M. oleifera can be used in the management of insect pests and to improve the nutritional contents of the watermelon especially in the organic farming system.

Keywords: Annona squamosa, Dacus cucubitea, Diabrotical undicimpunctata, Moringa oleifera, watermelon

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Authors: Niracha Chompurach, Dararat Khampusaen

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EFL students have to be able to synthesize the texts they are reading critically to compose and connect the information. This study focuses on the effects of the application of Infographics as a supplementary tool to improve Thai EFL students’ Academic reading skills. Infographics are graphic visual representations of information, data, and knowledge offering students to work on gathering multiple types of information, such as pictures, texts, graphs, mapping, and charts. The study aims to investigate if the Infographics as a supplementary tool in academic reading lessons can make a difference in students’ reading skills, and the students’ opinions toward the application of infographics as a reading tool. The participants of this study were 3rd year Thai EFL Khon Kaen University students who took English Academic Reading course. This study employed Infographics assignments, Infographics rubric, and Gucus group interview. This study would advantage for both EFL teachers and students as a means to engage the students to handle the larger load of and represents the complex information in visible and comprehensible way.

Keywords: EFL, e-learning, infographics, language education

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Authors: Douglas Arthur, Oluwayemisi Ekor, Ernest Obese, Andrew Kissi Agyei, Elvis Ofori Ameyaw

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bjective: Pain negatively impacts every aspect of health, and patients with pain disorders create enormous demands on healthcare systems globally, costing economies up to $635 billion annually. The study was therefore conducted at the Cape Coast Teaching Hospital (CCTH), the only Tertiary Hospital in the Central Region of Ghana and was designed to assess pain disorders in patients between 18 and 90 years attending Urology Clinic. Methods: The study employed a descriptive cross-sectional design, and 149 subjects (16-24, 25-34, 35-44, 45-54, 55-64, 65-90 years) were conveniently selected. The McGill Pain Questionnaire (MPQ), a multidimensional instrument that assesses several aspects of pain by the use of words (descriptors) that the patient chooses to express his/her pain, was used as the primary instrument for data collection. A patient profile form (PPF) was also designed to document the demographics and history of patients. Results: The prevalence of pain disorders was higher among females compared to males. The univariate and multivariate analysis showed that females were more likely to experience pain while being married correlated with a lower likelihood of pain. Again, the 45-54 age group exhibited the highest prevalence of pain disorders. Results from the MPQ showed that half of the patients experienced pain on a daily basis, 15.91% had experienced pain for 3-6 months and 37% experienced pain for more than one year. Pain intensity was described by 25% of the subjects as excruciating for their worst pain experience, followed by 21% for the distressing experience. The most frequently reported area of pain was the abdominal region (22.72%). The co-administration of NSAIDs and opioid compounds was provided for 17.46% of the patients with chronic pain. Conclusion: The treatment interventions improved the pain and associated symptoms such as nausea, improved daily activities and ability to sleep. However, attention and resources should be devoted to 45-54 age group.

Keywords: pain, opioids, distressing, excruciating

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Authors: Ligia Nascimento, Manuela Faia Correia

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Nowadays, Information and Communication Technologies (ICT) are embedded in most professions. Technostress - or stress induced by the use of ICTs, has been studied in various sectors of activity and in different geographical areas, mainly from the perspective of its harmful impacts. In the context of work, the technological contexts capable of causing stress have been examined in-depth, as well as the type of individuals most likely to experience its negative effects. However, new lines of the research argue that the stress generated by the use of ICTs may not necessarily be detrimental (technodistress), admitting that, in contrast, and in addition, it may actually be beneficial to organizations and their employees (technoeustress). Any measures that succeed in reducing technodistress do not necessarily lead to the creation of technoeustress, justifying the study of this phenomenon in a focused and independent manner. Adopting the transactional model of stress as the basic theoretical framework, an ongoing research project aims to study technoeustress independently. Given the role played in the qualification and progress of society and the economy, it becomes particularly critical to care for the well-being of the higher education teacher. Particularly in recent times, when teleworking is prevalent, these professionals have made a huge, compulsive effort to adapt to a new teaching reality. Rather than limiting itself to mitigating adverse effects of ICT use, which featured earlier approaches, the present study seeks to understand how to activate the positive side of technostress in higher education teachers in order to obtain favorable personal and organizational outcomes from ICT use at work. The research model seeks to understand, upstream, the ICT characteristics that increase the perception of technoeustress among higher education teachers, studying the direct and moderating effects of individual and organizational variables and, downstream, the impacts that technoeustress has on job satisfaction and performance. This research contributes both to expanding the knowledge of the technostress phenomenon and to identify possible recommendations for management.

Keywords: higher education teachers, ICT, stress, technoeustress

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Authors: Adriana Salgado, Sandra Castaneda, Ivan Perez

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Learning to read and write is a complex process involving several cognitive skills, contextual, and cultural environments. The basis of this development is linguistic skills, such as the ability to name and understand vocabulary, retell a story, phonological awareness, letter knowledge, among others. In children with autism spectrum disorder (ASD), one of the main concerns is related to language disorders. Nevertheless, most of the children with ASD are able to decode written information but have difficulties in reading comprehension. The research of these processes in the Spanish-speaking population is limited. However, the increasing prevalence of this diagnosis (1 in 115 children) in Mexico has implications at different levels. Educational research is an important area of interest in ASD children, such as emergent literacy. Reading and writing expand the possibilities of academic, cultural, and social information access. Taking this information into account, the objective of this research was to identify the relationship between language skills, alphabet knowledge, phonological awareness, and early reading and writing in ASD Spanish-speaking children. The method used for this research was based on tasks that were selected, adapted and in some cases designed to measure initial reading and writing, as well as language skills (naming, receptive vocabulary, and narrative skills), phonological awareness (similar phonological word pairs, beginning sound awareness and spelling) and letter knowledge, in a sample of 45 children (38 boys and 7 girls) with prior diagnosis of ASD. Descriptive analyses, as well as bivariate correlations, cluster analysis, and canonical correspondence, were obtained for the data results. Results showed that variability was large; however, it was possible to characterize the sample in low, medium, and high score groups regarding children performance. The low score group (46.7% of the sample), had a null or deficient performance in language skills and phonological awareness, some could identify up to five letters of the alphabet, showed no early reading skills but they could scribble. The middle score group was characterized by a highly variable performance in different tasks, with better language skills in receptive and naming vocabulary, some narrative, letter knowledge, and phonological awareness (beginning sound awareness) skills. The high score group, (24.4% of the sample) had the best performance in language skills in relation to the sample data, as well as in the rest of the measured skills. Finally, scores were canonically correlated between naming, receptive vocabulary, narrative, phonological awareness, letter knowledge and initial learning of reading and writing skills for the high score group and letter knowledge, naming and receptive vocabulary for the lower score group, which is consistent with previous research in typical and ASD children. In conclusion, the obtained data is consistent with previous studies. Despite large variability, it was possible to identify performance profiles and relations based on linguistic, phonological awareness, and letter knowledge skills. These skills were predictor variables of the initial development of reading and writing. The above has implications for a future program and strategies development that may benefit the acquisition of reading and writing in ASD children.

Keywords: autism, autism spectrum disorders, early literacy, emergent literacy

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Authors: Nwadioha Samuel Iheanacho, Abah Paul, Odimayo Simidele Michael

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Background: The World Health Assembly through the Global Health Sector Strategy on viral hepatitis calls for the elimination of viral hepatitis as a public health threat by 2030. All hands are on deck to actualize this goal through an effective and active vaccination and monitoring tool. Aim: To combine the Epidemiologic with Laboratory Hepatitis B Virus vaccination monitoring tools. Method: Laboratory results analysis of subjects recruited during the World Hepatitis week from July 2020 to July 2021 was done after obtaining their epidemiologic data on Hepatitis B virus risk factors, in the Medical Microbiology Laboratory of Benue State University Teaching Hospital, Nigeria. Result: A total of 500 subjects comprising males 60.0%(n=300/500) and females 40.0%(n=200/500) were recruited. A fifty-three percent majority was of the age range of 26 to 36 years. Serologic profiles were as follows, 15.0%(n=75/500) HBsAg; 7.0% (n=35/500) HBeAg; 8.0% (n=40/500) Anti-Hbe; 20.0% (n=100/500) Anti-HBc and 38.0% (n=190/500) Anti-HBs. Immune responses to vaccination were as follows, 47.0%(n=235/500) Immune naïve {no serologic marker + normal ALT}; 33%(n=165/500) Immunity by vaccination {Anti-HBs + normal ALT}; 5%(n=25/500) Immunity to previous infection {Anti-HBs, Anti-HBc, +/- Anti-HBe + normal ALT}; 8%(n=40/500) Carriers {HBsAg, Anti-HBc, Anti-HBe +normal ALT} and 7% (35/500) Anti-HBe serum- negative infections {HBsAg, HBeAg, Anti-HBc +elevated ALT}. Conclusion: The present 33.0% immunity by vaccination coverage in Central Nigeria was much lower than the 41.0% national peak in 2013, and a far cry from the global expectation of attainment of a Global Health Sector Strategy on the elimination of viral hepatitis as a public health threat by 2030. Therefore, more creative ideas and collective effort are needed to attain this goal of the World Health Assembly.

Keywords: Hepatitis B, vaccination status, laboratory tools, resource-limited settings

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Authors: Usha Lokala, Srinivas Nowduri, Prabhakar K. Sharma

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Useful information has been extracted from the road accident data in United Kingdom (UK), using data analytics method, for avoiding possible accidents in rural and urban areas. This analysis make use of several methodologies such as data integration, support vector machines (SVM), correlation machines and multinomial goodness. The entire datasets have been imported from the traffic department of UK with due permission. The information extracted from these huge datasets forms a basis for several predictions, which in turn avoid unnecessary memory lapses. Since data is expected to grow continuously over a period of time, this work primarily proposes a new framework model which can be trained and adapt itself to new data and make accurate predictions. This work also throws some light on use of SVM’s methodology for text classifiers from the obtained traffic data. Finally, it emphasizes the uniqueness and adaptability of SVMs methodology appropriate for this kind of research work.

Keywords: support vector mechanism (SVM), machine learning (ML), support vector machines (SVM), department of transportation (DFT)

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Authors: Jovana M. Ćirković, Aleksandar M. Radojković, Sanja Z. Perać, Jelena N. Jovanović, Zorica M. Branković, Slobodan D. Milanović, Ivan Lj. Milenković, Jovan N. Dobrosavljević, Nemanja V. Simović, Vanja M. Tadić, Ana R. Žugić, Goran O. Branković

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The protection of forests is a national interest and of strategic importance in every country. The spongy moth (Lymantria dispar) is a damaging invasive pest that can weaken and destroy trees by defoliating them. Chemical pesticides commonly used to protect forests against spongy moths not only have a negative impact on terrestrial and aquatic organisms/ecosystems but also often fail to provide significant protection. Therefore, many eco-friendly alternatives have been considered. Within this research, a new biopesticide was developed based on the method of nanoencapsulation of plant extracts in a biopolymer matrix, which provides a slow release of the active components during a substantial time period. The antifeedant activity of plant extracts of common (Fraxinus excelsior L.), manna (F. ornus L.) ash tree, and the tree of heaven Ailanthus altissima (Mill.) was tested on the spongy moth (Lymantria dispar L, 1758) larvae. To test the antifeedant activity of these compounds, the choice and non-choice tests in laboratory conditions for different plant extract concentrations (0.01, 0.1, 0.5, and 1 % v/v) were carried out. In both cases, the best results showed formulations based on the tree of heaven and common ash for the concentration of 1%, with deterioration indices of 163 and 132, respectively. The main benefit of these formulations is their versatility, effectiveness, prolonged effect, and because they are completely environmentally acceptable. Therefore, they can be considered for suppression of the spongy moth in forest ecosystems.

Keywords: Ailanthus altissima (Mill.), Fraxinus excelsior L., encapsulation, Lymantria dispar

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Authors: Pau Rodriguez, Jordi Gonzalez, Josep M. Gonfaus, Xavier Roca

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Image sharing in social networks has increased exponentially in the past years. Officially, there are 600 million Instagrammers uploading around 100 million photos and videos per day. Consequently, there is a need for developing new tools to understand the content expressed in shared images, which will greatly benefit social media communication and will enable broad and promising applications in education, advertisement, entertainment, and also psychology. Following these trends, our work aims to take advantage of the existing relationship between text and personality, already demonstrated by multiple researchers, so that we can prove that there exists a relationship between images and personality as well. To achieve this goal, we consider that images posted on social networks are typically conditioned on specific words, or hashtags, therefore any relationship between text and personality can also be observed with those posted images. Our proposal makes use of the most recent image understanding models based on neural networks to process the vast amount of data generated by social users to determine those images most correlated with personality traits. The final aim is to train a weakly-supervised image-based model for personality assessment that can be used even when textual data is not available, which is an increasing trend. The procedure is described next: we explore the images directly publicly shared by users based on those accompanying texts or hashtags most strongly related to personality traits as described by the OCEAN model. These images will be used for personality prediction since they have the potential to convey more complex ideas, concepts, and emotions. As a result, the use of images in personality questionnaires will provide a deeper understanding of respondents than through words alone. In other words, from the images posted with specific tags, we train a deep learning model based on neural networks, that learns to extract a personality representation from a picture and use it to automatically find the personality that best explains such a picture. Subsequently, a deep neural network model is learned from thousands of images associated with hashtags correlated to OCEAN traits. We then analyze the network activations to identify those pictures that maximally activate the neurons: the most characteristic visual features per personality trait will thus emerge since the filters of the convolutional layers of the neural model are learned to be optimally activated depending on each personality trait. For example, among the pictures that maximally activate the high Openness trait, we can see pictures of books, the moon, and the sky. For high Conscientiousness, most of the images are photographs of food, especially healthy food. The high Extraversion output is mostly activated by pictures of a lot of people. In high Agreeableness images, we mostly see flower pictures. Lastly, in the Neuroticism trait, we observe that the high score is maximally activated by animal pets like cats or dogs. In summary, despite the huge intra-class and inter-class variabilities of the images associated to each OCEAN traits, we found that there are consistencies between visual patterns of those images whose hashtags are most correlated to each trait.

Keywords: emotions and effects of mood, social impact theory in social psychology, social influence, social structure and social networks

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Authors: Jana Abu Ahmada, Zaineb Mohamed, Ilyasse Aksikas

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The linear quadratic control system of hyperbolic first order partial differential equations (PDEs) are presented. The aim of this research is to control chemical reactions. This is achieved by converting the PDEs system to ordinary differential equations (ODEs) using the method of characteristics to reduce the system to control it by using the integral reinforcement learning. The designed controller is applied to a catalytic cracking reactor. Background—Transport-Reaction systems cover a large chemical and bio-chemical processes. They are best described by nonlinear PDEs derived from mass and energy balances. As a main application to be considered in this work is the catalytic cracking reactor. Indeed, the cracking reactor is widely used to convert high-boiling, high-molecular weight hydrocarbon fractions of petroleum crude oils into more valuable gasoline, olefinic gases, and others. On the other hand, control of PDEs systems is an important and rich area of research. One of the main control techniques is feedback control. This type of control utilizes information coming from the system to correct its trajectories and drive it to a desired state. Moreover, feedback control rejects disturbances and reduces the variation effects on the plant parameters. Linear-quadratic control is a feedback control since the developed optimal input is expressed as feedback on the system state to exponentially stabilize and drive a linear plant to the steady-state while minimizing a cost criterion. The integral reinforcement learning policy iteration technique is a strong method that solves the linear quadratic regulator problem for continuous-time systems online in real time, using only partial information about the system dynamics (i.e. the drift dynamics A of the system need not be known), and without requiring measurements of the state derivative. This is, in effect, a direct (i.e. no system identification procedure is employed) adaptive control scheme for partially unknown linear systems that converges to the optimal control solution. Contribution—The goal of this research is to Develop a characteristics-based optimal controller for a class of hyperbolic PDEs and apply the developed controller to a catalytic cracking reactor model. In the first part, developing an algorithm to control a class of hyperbolic PDEs system will be investigated. The method of characteristics will be employed to convert the PDEs system into a system of ODEs. Then, the control problem will be solved along the characteristic curves. The reinforcement technique is implemented to find the state-feedback matrix. In the other half, applying the developed algorithm to the important application of a catalytic cracking reactor. The main objective is to use the inlet fraction of gas oil as a manipulated variable to drive the process state towards desired trajectories. The outcome of this challenging research would yield the potential to provide a significant technological innovation for the gas industries since the catalytic cracking reactor is one of the most important conversion processes in petroleum refineries.

Keywords: PDEs, reinforcement iteration, method of characteristics, riccati equation, cracking reactor

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