Search results for: reinforcement learning
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7526

Search results for: reinforcement learning

2336 Mechanical Properties of Poly(Propylene)-Based Graphene Nanocomposites

Authors: Luiza Melo De Lima, Tito Trindade, Jose M. Oliveira

Abstract:

The development of thermoplastic-based graphene nanocomposites has been of great interest not only to the scientific community but also to different industrial sectors. Due to the possible improvement of performance and weight reduction, thermoplastic nanocomposites are a great promise as a new class of materials. These nanocomposites are of relevance for the automotive industry, namely because the emission limits of CO2 emissions imposed by the European Commission (EC) regulations can be fulfilled without compromising the car’s performance but by reducing its weight. Thermoplastic polymers have some advantages over thermosetting polymers such as higher productivity, lower density, and recyclability. In the automotive industry, for example, poly(propylene) (PP) is a common thermoplastic polymer, which represents more than half of the polymeric raw material used in automotive parts. Graphene-based materials (GBM) are potential nanofillers that can improve the properties of polymer matrices at very low loading. In comparison to other composites, such as fiber-based composites, weight reduction can positively affect their processing and future applications. However, the properties and performance of GBM/polymer nanocomposites depend on the type of GBM and polymer matrix, the degree of dispersion, and especially the type of interactions between the fillers and the polymer matrix. In order to take advantage of the superior mechanical strength of GBM, strong interfacial strength between GBM and the polymer matrix is required for efficient stress transfer from GBM to the polymer. Thus, chemical compatibilizers and physicochemical modifications have been reported as important tools during the processing of these nanocomposites. In this study, PP-based nanocomposites were obtained by a simple melt blending technique, using a Brabender type mixer machine. Graphene nanoplatelets (GnPs) were applied as structural reinforcement. Two compatibilizers were used to improve the interaction between PP matrix and GnPs: PP graft maleic anhydride (PPgMA) and PPgMA modified with tertiary amine alcohol (PPgDM). The samples for tensile and Charpy impact tests were obtained by injection molding. The results suggested the GnPs presence can increase the mechanical strength of the polymer. However, it was verified that the GnPs presence can promote a decrease of impact resistance, turning the nanocomposites more fragile than neat PP. The compatibilizers’ incorporation increases the impact resistance, suggesting that the compatibilizers can enhance the adhesion between PP and GnPs. Compared to neat PP, Young’s modulus of non-compatibilized nanocomposite increase demonstrated that GnPs incorporation can promote a stiffness improvement of the polymer. This trend can be related to the several physical crosslinking points between the PP matrix and the GnPs. Furthermore, the decrease of strain at a yield of PP/GnPs, together with the enhancement of Young’s modulus, confirms that the GnPs incorporation led to an increase in stiffness but to a decrease in toughness. Moreover, the results demonstrated that incorporation of compatibilizers did not affect Young’s modulus and strain at yield results compared to non-compatibilized nanocomposite. The incorporation of these compatibilizers showed an improvement of nanocomposites’ mechanical properties compared both to those the non-compatibilized nanocomposite and to a PP sample used as reference.

Keywords: graphene nanoplatelets, mechanical properties, melt blending processing, poly(propylene)-based nanocomposites

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2335 Evaluating the Performance of Offensive Lineman in the National Football League

Authors: Nikhil Byanna, Abdolghani Ebrahimi, Diego Klabjan

Abstract:

How does one objectively measure the performance of an individual offensive lineman in the NFL? The existing literature proposes various measures that rely on subjective assessments of game film, but has yet to develop an objective methodology to evaluate performance. Using a variety of statistics related to an offensive lineman’s performance, we develop a framework to objectively analyze the overall performance of an individual offensive lineman and determine specific linemen who are overvalued or undervalued relative to their salary. We identify eight players across the 2013-2014 and 2014-2015 NFL seasons that are considered to be overvalued or undervalued and corroborate the results with existing metrics that are based on subjective evaluation. To the best of our knowledge, the techniques set forth in this work have not been utilized in previous works to evaluate the performance of NFL players at any position, including offensive linemen.

Keywords: offensive lineman, player performance, NFL, machine learning

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2334 A Phenomenological Exploration of Alcohol Consumption Patterns and Problems Among Male Students at the University of Kwazulu-Natal

Authors: Isaiah Phillip Smith

Abstract:

It is reported that alcohol consumption accounts for 3 million annual deaths globally, thus, it is a significant public health challenge internationally. The excessive consumption of alcohol is argued in literature to be related to problematic behaviors like crime, accident, fighting, violence, and unprotected sex, among others. Alcohol consumption among university students in South Africa particularly is considered endemic – with a prevalence rate of 25.27%, 32.34%, and 23.34% across universities, colleges, and high schools. Adopting the tenets of social learning and ecological theories, the culture of drinking amongst male university students is critically explored. This study found that age, gender, early exposure to alcohol, and peer pressure are significant factors contributing to alcohol consumption amongst university students. While participants acknowledged that moderate and responsible consumption of alcohol is necessary, they agree that it does not translate to responsible drinking behaviours.

Keywords: alcohol, drinking, university, students

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2333 On the Market Prospects of Long-Term Electricity Storages

Authors: Reinhard Haas, Amela Ajanovic

Abstract:

In recent years especially electricity generation from intermittent sources like wind and solar has increased remarkably. To balance electricity supply over time calls for storages has been launched. Because intermittency also exists over longer periods – months, years, especially the need for long-term electricity storages is discussed. The major conclusions of our analysis are: (i) Despite many calls for a prophylactic construction of new storage capacities with respect to all centralized long-term storage technologies the future perspectives will be much less promising than currently indicated in several papers and discussions; (ii) new long term hydro storages will not become economically attractive in general in the next decades; however, daily storages will remain the cheapest option and the most likely to be competitive; (iii) For PtG-technologies it will also become very hard to compete in the electricity markets despite a high technological learning potential. Yet, for hydrogen and methane there are prospects for use in the transport sector.

Keywords: storages, electricity markets, power-to-gas, hydro pump storages, economics

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2332 Amazon and Its AI Features

Authors: Leen Sulaimani, Maryam Hafiz, Naba Ali, Roba Alsharif

Abstract:

One of Amazon’s most crucial online systems is artificial intelligence. Amazon would not have a worldwide successful online store, an easy and secure way of payment, and other services if it weren’t for artificial intelligence and machine learning. Amazon uses AI to expand its operations and enhance them by upgrading the website daily; having a strong base of artificial intelligence in a worldwide successful business can improve marketing, decision-making, feedback, and more qualities. Aiming to have a rational AI system in one’s business should be the start of any process; that is why Amazon is fortunate that they keep taking care of the base of their business by using modern artificial intelligence, making sure that it is stable, reaching their organizational goals, and will continue to thrive more each and every day. Artificial intelligence is used daily in our current world and is still being amplified more each day to reach consumer satisfaction and company short and long-term goals.

Keywords: artificial intelligence, Amazon, business, customer, decision making

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2331 An Examination of Thai Tourists' Motivation Behavior and Perception of Cultural Heritage in Chiang Mai Province

Authors: Sujui Yang, Peeraya Somsak, Markus Blut

Abstract:

This research examines the international tourists in Chiang Mai, Thailand. It aims to study non-Thai tourists’ of this region to better understand their behavior and motives influencing the choice of cultural heritage tourists in Chiang Mai, Thailand. The data includes questionnaires of 250 tourists in the study area. The most important motives influencing decisions choices are several concerning customers’ perspectives on tourist destinations in cultural heritage in Chiang Mai province. Thai tourists in Chiang Mai are single, 72.5 percent are in the age of 21-40 years old and 50% of sample group are from central and northern of Thailand. Tourists’ motives capture the factor loading as well as the corresponding show 5 components: relaxation motives, place/ physical motives, learning motives, image motives, and achievement motives.

Keywords: tourists motives, cultural heritage, Chiang Mai, customers’ perspectives

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2330 Assessing Readiness Model for Business Intelligence Implementation in Organization

Authors: Abdul Razak Rahmat, Azizah Ahmad, Azman Ta’aa

Abstract:

The deployment of Business Intelligence (BI) for organization at the beginning phase is very crucial. Results from the previous studies found that more than half of the BI project fails to meet the objective even though a lot money are spent. Based on that problem, the readiness level of BI for the organization is important to identify in order to reduce the risk before the actual BI project is implemented. In this paper, rigorous literature review on the aspect success factors such as Critical Success Factors (CSFs), Readiness Factors (RFs), Success Factors (SFs), are discussed by different authors. The paper also adopted a few models from previous study as a guide for the assessment of BI readiness. The expected finding from this research is the Business Intelligent Readiness Model (BiRM) as a guild before implement the BI system.

Keywords: business intelligence readiness model, business intelligence for higher learning, BI readiness factors, BI critical success factors(CSF)

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2329 A Step Towards Automating the Synthesis of a Scene Script

Authors: Americo Pereira, Ricardo Carvalho, Pedro Carvalho, Luis Corte-Real

Abstract:

Generating 3D content is a task mostly done by hand. It requires specific knowledge not only on how to use the tools for the task but also on the fundamentals of a 3D environment. In this work, we show that automatic generation of content can be achieved, from a scene script, by leveraging existing tools so that non-experts can easily engage in a 3D content generation without requiring vast amounts of time in exploring and learning how to use specific tools. This proposal carries several benefits, including flexible scene synthesis with different levels of detail. Our preliminary results show that the automatically generated content is comparable to the content generated by users with low experience in 3D modeling while vastly reducing the amount of time required for the generation and adds support to implement flexible scenarios for visual scene visualization.

Keywords: 3D virtualization, multimedia, scene script, synthesis

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2328 Increasing Adherence to Preventative Care Bundles for Healthcare-Associated Infections: The Impact of Nurse Education

Authors: Lauren G. Coggins

Abstract:

Catheter-associated urinary tract infections (CAUTI) and central line-associated bloodstream infections (CLABSI) are among the most common healthcare-associated infections (HAI), contributing to prolonged lengths of stay, greater costs of patient care, and increased patient mortality. Evidence-based preventative care bundles exist to establish consistent, safe patient-care practices throughout an entire organization, helping to ensure the collective application of care strategies that aim to improve patient outcomes and minimize complications. The cardiac intensive care unit at a nationally ranked teaching and research hospital in the United States exceeded its annual CAUTI and CLABSI targets in the fiscal year 2019, prompting examination into the unit’s infection prevention efforts that included preventative care bundles for both HAIs. Adherence to the CAUTI and CLABSI preventative care bundles was evaluated through frequent audits conducted over three months, using standards and resources from The Joint Commission, a globally recognized leader in quality improvement in healthcare and patient care safety. The bundle elements with the lowest scores were identified as the most commonly missed elements. Three elements from both bundles, six elements in total, served as key content areas for the educational interventions targeted to bedside nurses. The CAUTI elements included appropriate urinary catheter order, appropriate continuation criteria, and urinary catheter care. The CLABSI elements included primary tubing compliance, needleless connector compliance, and dressing change compliance. An integrated, multi-platform education campaign featured content on each CAUTI and CLABSI preventative care bundle in its entirety, with additional reinforcement focused on the lowest scoring elements. One-on-one educational materials included an informational pamphlet, badge buddy, a presentation to reinforce nursing care standards, and real-time application through case studies and electronic health record demonstrations. A digital hub was developed on the hospital’s Intranet for quick access to unit resources, and a bulletin board helped track the number of days since the last CAUTI and CLABSI incident. Audits continued to be conducted throughout the education campaign, and staff were given real-time feedback to address any gaps in adherence. Nearly every nurse in the cardiac intensive care unit received all educational materials, and adherence to all six key bundle elements increased after the implementation of educational interventions. Recommendations from this implementation include providing consistent, comprehensive education across multiple teaching tools and regular audits to track adherence. The multi-platform education campaign brought focus to the evidence-based CAUTI and CLABSI bundles, which in turn will help to reduce CAUTI and CLABSI rates in clinical practice.

Keywords: education, healthcare-associated infections, infection, nursing, prevention

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2327 Types of Motivation at a Rural University

Authors: Sandra Valdez-Hernández

Abstract:

Motivation is one of the most important factors when teaching language. Most institutions at least in Mexico, pay low attention to the types of motivation students have when they are studying English; however, considering the motivation they have, may lead to better understanding about their needs and purposes for learning English and the professors may understand and focus on their interests for making them persist in action through the course. This topic has been widely investigated in different countries, but more research needs to be done in Mexico to shed light on this area of potential impact. The aim of this research is to focus on the types of motivation, intrinsic and extrinsic, instrumental and integrative and the attitudes students have about English language to identify aspects that are alike to other contexts and research areas based on the theory of Dörnyei (2013) and Gardner (2001). It was carried out at a Mexican University in a small village in Quintana Roo. The potential implications, the findings as well as the limitations are presented.

Keywords: attides of motivation, factors of motivation, extrinsic and intrinsic motivation, instrumental and integrative motivation

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2326 Alternative Sources of Funding Tertiary Institution in Nigeria

Authors: Mark Omu

Abstract:

Education has remained the greatest fulcrum on which the developmental aspirations of societies and the world over is Anchored. This has been the case from the antiquity. As a result of recognition of this fact, education occupies a crucial and centripetal position at different epochs of societal formation and transformation. This paper recognized the all-embracing role of education to society and it utilized the literary research and review of literature to espouse on the role of alternative sources of financing education. This position was borne out of the dwindling resources available to education. Especially to finance teaching, learning, research and retraining of staffers. This paper found among other things that alternative funding of education is possible and it can be achieved through selling of its research products like entrepreneurial skills, collaborative ventures in public private partnership, philanthropic of endowments, etc. These are capable of bridging the financial gap currently bedevilling the educational sectors.

Keywords: alternative sources, funding, tertiary, education, society, partnership, Nigeria

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2325 Reciprocal Interferences in Bilingual English-Igbo Speaking Society: The Implications in Language Pedagogy

Authors: Ugwu Elias Ikechukwu

Abstract:

Discussions on bilingualism have always dwelt on how the mother tongue interferes with the target language. This interference is considered a serious problem in second language learning. Usually, the interference has been phonological. But the objective of this research is to explore how the target language interferes with the mother tongue. In the case of the Igbo language, it interferes with English mostly at the phonological level while English interferes with Igbo at the realm of vocabulary. The result is a new language \"Engligbo\" which is a hybrid of English and Igbo. The Igbo language spoken by about 25 million people is one of the three most prominent languages in Nigeria. This paper discusses the phenomenal Engligbo, and other implications for Igbo learners of English. The method of analysis is descriptive. A number of recommendations were made that would help teachers handle problems arising from such mutual interferences.

Keywords: reciprocal interferences, bilingualism, implications, language pedagogy

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2324 Using WebQuest for Developing English Reading Comprehension Skills for Preparatory Experimental School Students: Proposed Design

Authors: Sarah Hamdy Abd-Al Hamid Seyam

Abstract:

The research aimed investigating the effect of using web quest on developing English reading comprehension skills for preparatory experimental school students. The descriptive design was adopted in the study. The tools of the study are represented in: a checklist for the English reading comprehension skills and a test of the English reading comprehension skills for the first year preparatory experimental school students. Results of the study were discussed in relation to various factors that affect the learning process. Finally the research presented applicable contributions according to using web quest in teaching English as a foreign language generally and improving reading comprehension in particular.

Keywords: English as a second language, preparatory experimental schools, reading comprehension, WebQuest

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2323 Learning to Recommend with Negative Ratings Based on Factorization Machine

Authors: Caihong Sun, Xizi Zhang

Abstract:

Rating prediction is an important problem for recommender systems. The task is to predict the rating for an item that a user would give. Most of the existing algorithms for the task ignore the effect of negative ratings rated by users on items, but the negative ratings have a significant impact on users’ purchasing decisions in practice. In this paper, we present a rating prediction algorithm based on factorization machines that consider the effect of negative ratings inspired by Loss Aversion theory. The aim of this paper is to develop a concave and a convex negative disgust function to evaluate the negative ratings respectively. Experiments are conducted on MovieLens dataset. The experimental results demonstrate the effectiveness of the proposed methods by comparing with other four the state-of-the-art approaches. The negative ratings showed much importance in the accuracy of ratings predictions.

Keywords: factorization machines, feature engineering, negative ratings, recommendation systems

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2322 Hegemonic Salaryman Masculinity: Case Study of Transitional Male Gender Roles in Today's Japan

Authors: D. Norton

Abstract:

This qualitative study focuses on the lived experience and displacement of young white-collar masculinities in Japan. In recent years, the salaryman lifestyle has undergone significant disruption - increased competition for regular employment, rise in non-regular structurings of labour across public/private sectors, and shifting role expectations within the home. Despite this, related scholarship hints at a continued reinforcement of the traditional male gender role - that the salaryman remains a key benchmark of Japanese masculine identity. For those in structural proximity to these more ‘normative’ performativities, interest lies their engagement with such narratives - how they make sense of their masculinity in response to stated changes. In light of the historical emphasis on labour and breadwinning logics, notions of respective security or precarity generated as a result remain unclear. Similarly, concern extends to developments within the private sphere - by what means young white-collar men construct ideas of singlehood and companionship according to traditional gender ideologies or more contemporary, flexible readings. The influence of these still-emergent status distinctions on the logics of the social group in question is yet to be explored in depth by gender scholars. This project, therefore, focuses on a salaryman archetype as hegemonic - its transformation amidst these changes and socialising mechanisms that continue to legitimate unequal gender hierarchies. For data collection, a series of ethnographic interviews were held over a period of 12 months with university-educated, white-collar male employees from both Osaka and the Greater Tokyo Area. Findings suggest a modern salaryman ideal reflecting both continuities and shifts within white-collar employment. Whilst receptive to more contemporary workplace practices, the narratives of those interviewed remain imbued with logics supporting patterns of internal hegemony. Regular/non-regular distinction emerged as the foremost variable for both material and discursive patterns of white-collar stratification, with variants of displacement for each social group. Despite the heightened valorisation of stable employment, regular workers articulated various concerns over a model of corporate masculinity seen to be incompatible with recent socioeconomic developments. Likewise, non-regular employees face detachment owing to a still-inflexible perception of their working masculinity as marginalized amidst economic precarity. In seeking to negotiate respective challenges, those interviewed demonstrated an engagement with various concurrent social changes that would often either accommodate, reinforce, or expand upon traditional role behaviours. Few of these narratives offered any notable transgression of said ideal, however, suggesting that within the spectre of white-collar employment in Japan for the near future, any substantive transformation of corporate masculinity remains dependant upon economic developments, less so the agency of those involved.

Keywords: gender ideologies, hegemonic masculinity, Japan, white-collar employment

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2321 Using Historical Data for Stock Prediction

Authors: Sofia Stoica

Abstract:

In this paper, we use historical data to predict the stock price of a tech company. To this end, we use a dataset consisting of the stock prices in the past five years of ten major tech companies – Adobe, Amazon, Apple, Facebook, Google, Microsoft, Netflix, Oracle, Salesforce, and Tesla. We experimented with a variety of models– a linear regressor model, K nearest Neighbors (KNN), a sequential neural network – and algorithms - Multiplicative Weight Update, and AdaBoost. We found that the sequential neural network performed the best, with a testing error of 0.18%. Interestingly, the linear model performed the second best with a testing error of 0.73%. These results show that using historical data is enough to obtain high accuracies, and a simple algorithm like linear regression has a performance similar to more sophisticated models while taking less time and resources to implement.

Keywords: finance, machine learning, opening price, stock market

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2320 “The Unbearable Lightness of Being” Book as an Interdisciplinary Study Basis for Students’ Learning Process about Love and Politics at Old Communist Czechoslovakia

Authors: Clarissa Valença Travassos da Silva

Abstract:

In this article, it is intended to study the book “The unbearable Lightness of Being” by the Czech Republican writer Milan Kundera. The main objective is to be an interdisciplinary study basis for students in the world about love and politics at old communist Czechoslovakia. Love is presented by discussing the relationship between Tomas and Tereza and the discovery of true love. Furthermore, it is debated the Russian invasion in Czechoslovakia and the outcomes of it for the personages, all this related to the contradiction of lightness and heaviness in life. For the production of this didactic material, the researcher based her work on the original book, “The Unbearable Lightness of Being” by Kundera, Milan Kundera’s interviews, Friedrich Nietzche, Zygmunt Bauman and George Orwell, among Brazilian and international articles on the issue.

Keywords: lightness, heaviness, Russia, Czechoslovakia, love

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2319 Location3: A Location Scouting Platform for the Support of Film and Multimedia Industries

Authors: Dimitrios Tzilopoulos, Panagiotis Symeonidis, Michael Loufakis, Dimosthenis Ioannidis, Dimitrios Tzovaras

Abstract:

The domestic film industry in Greece has traditionally relied heavily on state support. While film productions are crucial for the country's economy, it has not fully capitalized on attracting and promoting foreign productions. The lack of motivation, organized state support for attraction and licensing, and the absence of location scouting have hindered its potential. Although recent legislative changes have addressed the first two of these issues, the development of a comprehensive location database and a search engine that would effectively support location scouting at the pre-production location scouting is still in its early stages. In addition to the expected benefits of the film, television, marketing, and multimedia industries, a location-scouting service platform has the potential to yield significant financial gains locally and nationally. By promoting featured places like cultural and archaeological sites, natural monuments, and attraction points for visitors, it plays a vital role in both cultural promotion and facilitating tourism development. This study introduces LOCATION3, an internet platform revolutionizing film production location management. It interconnects location providers, film crews, and multimedia stakeholders, offering a comprehensive environment for seamless collaboration. The platform's central geodatabase (PostgreSQL) stores each location’s attributes, while web technologies like HTML, JavaScript, CSS, React.js, and Redux power the user-friendly interface. Advanced functionalities, utilizing deep learning models, developed in Python, are integrated via Node.js. Visual data presentation is achieved using the JS Leaflet library, delivering an interactive map experience. LOCATION3 sets a new standard, offering a range of essential features to enhance the management of film production locations. Firstly, it empowers users to effortlessly upload audiovisual material enriched with geospatial and temporal data, such as location coordinates, photographs, videos, 360-degree panoramas, and 3D location models. With the help of cutting-edge deep learning algorithms, the application automatically tags these materials, while users can also manually tag them. Moreover, the application allows users to record locations directly through its user-friendly mobile application. Users can then embark on seamless location searches, employing spatial or descriptive criteria. This intelligent search functionality considers a combination of relevant tags, dominant colors, architectural characteristics, emotional associations, and unique location traits. One of the application's standout features is the ability to explore locations by their visual similarity to other materials, facilitated by a reverse image search. Also, the interactive map serves as both a dynamic display for locations and a versatile filter, adapting to the user's preferences and effortlessly enhancing location searches. To further streamline the process, the application facilitates the creation of location lightboxes, enabling users to efficiently organize and share their content via email. Going above and beyond location management, the platform also provides invaluable liaison, matchmaking, and online marketplace services. This powerful functionality bridges the gap between visual and three-dimensional geospatial material providers, local agencies, film companies, production companies, etc. so that those interested in a specific location can access additional material beyond what is stored on the platform, as well as access production services supporting the functioning and completion of productions in a location (equipment provision, transportation, catering, accommodation, etc.).

Keywords: deep learning models, film industry, geospatial data management, location scouting

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2318 Reflections on the Role of Cultural Identity in a Bilingual Education Program

Authors: Lina Tenjo, Ilba Rodríguez

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The role of cultural identity in bilingual programs has been barely discussed in regards to SLA. This research focuses on providing relevant information that helps in having more knowledge about the experiences that an elementary student has during the second language learning process in a bilingual program within a multicultural context. This study explores the experience of 18 students in a dual language program, in a public elementary school in Northern Virginia, USA. It examines their dual language experience and the different ways this experience contributes to the formation of their cultural identity. The findings were studied with the purpose of determining the relationship between participants and certain aspects of cultural identity in a multicultural context. The reflections that originate from the voices of children are the key source that helps us to better understand the particular needs that young learners have during their participation in a DLP.

Keywords: acculturation, bilingual education, culture, dual language program, identity, second language acquisition

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2317 Prediction of the Tunnel Fire Flame Length by Hybrid Model of Neural Network and Genetic Algorithms

Authors: Behzad Niknam, Kourosh Shahriar, Hassan Madani

Abstract:

This paper demonstrates the applicability of Hybrid Neural Networks that combine with back propagation networks (BPN) and Genetic Algorithms (GAs) for predicting the flame length of tunnel fire A hybrid neural network model has been developed to predict the flame length of tunnel fire based parameters such as Fire Heat Release rate, air velocity, tunnel width, height and cross section area. The network has been trained with experimental data obtained from experimental work. The hybrid neural network model learned the relationship for predicting the flame length in just 3000 training epochs. After successful learning, the model predicted the flame length.

Keywords: tunnel fire, flame length, ANN, genetic algorithm

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2316 Results of Twenty Years of Laparoscopic Hernia Repair Surgeries

Authors: Arun Prasad

Abstract:

Introduction: Laparoscopic surgery of hernia started in early 1990 and has had a mixed acceptance across the world, unlike laparoscopic cholecystectomy that has become a gold standard. Laparoscopic hernia repair claims to have less pain, less recurrence, and less wound infection compared to open hernia repair leading to early recovery and return to work. Materials and Methods: Laparoscopic hernia repair has been done in 2100 patients from 1995 till now with a follow-up data of 1350 patients. Data was analysed for results and satisfaction. Results: There is a recurrence rate of 0.1%. Early complications include bleeding, trocar injury and nerve pain. Late complications were rare. Conclusion: Laparoscopic inguinal hernia repair has a steep learning curve but after that the results and patient satisfaction are very good. It should be the procedure of choice in all bilateral and recurrent hernias.

Keywords: laparoscopy, hernia, mesh, surgery

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2315 Performance Analysis of Artificial Neural Network with Decision Tree in Prediction of Diabetes Mellitus

Authors: J. K. Alhassan, B. Attah, S. Misra

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Human beings have the ability to make logical decisions. Although human decision - making is often optimal, it is insufficient when huge amount of data is to be classified. medical dataset is a vital ingredient used in predicting patients health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance of Artificial Neural Network (ANN) and Decision Tree Algorithms (DTA) as regards to some performance metrics using diabetes data. The evaluations was done using weka software and found out that DTA performed better than ANN. Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were the two algorithms used for ANN, while RegTree and LADTree algorithms were the DTA models used. The Root Mean Squared Error (RMSE) of MLP is 0.3913,that of RBF is 0.3625, that of RepTree is 0.3174 and that of LADTree is 0.3206 respectively.

Keywords: artificial neural network, classification, decision tree algorithms, diabetes mellitus

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2314 Characterization of Group Dynamics for Fostering Mathematical Modeling Competencies

Authors: Ayse Ozturk

Abstract:

The study extends the prior research on modeling competencies by positioning students’ cognitive and language resources as the fundamentals for pursuing their own inquiry and expression lines through mathematical modeling. This strategy aims to answer the question that guides this study, “How do students’ group approaches to modeling tasks affect their modeling competencies over a unit of instruction?” Six bilingual tenth-grade students worked on open-ended modeling problems along with the content focused on quantities over six weeks. Each group was found to have a unique cognitive approach for solving these problems. Three different problem-solving strategies affected how the groups’ modeling competencies changed. The results provide evidence that the discussion around groups’ solutions, coupled with their reflections, advances group interpreting and validating competencies in the mathematical modeling process

Keywords: cognition, collective learning, mathematical modeling competencies, problem-solving

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2313 Improving Teaching in English-Medium Instruction Classes at Japanese Universities through Needs-Based Professional Development Workshops

Authors: Todd Enslen

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In order to attract more international students to study for undergraduate degrees in Japan, many universities have been developing English-Medium Instruction degree programs. This means that many faculty members must now teach their courses in English, which raises a number of concerns. A common misconception of English-Medium Instruction (EMI) is that teaching in English is simply a matter of translating materials. Since much of the teaching in Japan still relies on a more traditional, teachercentered, approach, continuing with this style in an EMI environment that targets international students can cause a clash between what is happening and what students expect in the classroom, not to mention what the Scholarship of Teaching and Learning (SoTL) has shown is effective teaching. A variety of considerations need to be taken into account in EMI classrooms such as varying English abilities of the students, modifying input material, and assuring comprehension through interactional checks. This paper analyzes the effectiveness of the English-Medium Instruction (EMI) undergraduate degree programs in engineering, agriculture, and science at a large research university in Japan by presenting the results from student surveys regarding the areas where perceived improvements need to be made. The students were the most dissatisfied with communication with their teachers in English, communication with Japanese students in English, adherence to only English being used in the classes, and the quality of the education they received. In addition, the results of a needs analysis survey of Japanese teachers having to teach in English showed that they believed they were most in need of English vocabulary and expressions to use in the classroom and teaching methods for teaching in English. The result from the student survey and the faculty survey show similar concerns between the two groups. By helping the teachers to understand student-centered teaching and the benefits for learning that it provides, teachers may begin to incorporate more student-centered approaches that in turn help to alleviate the dissatisfaction students are currently experiencing. Through analyzing the current environment in Japanese higher education against established best practices in teaching and EMI, three areas that need to be addressed in professional development workshops were identified. These were “culture” as it relates to the English language, “classroom management techniques” and ways to incorporate them into classes, and “language” issues. Materials used to help faculty better understand best practices as they relate to these specific areas will be provided to help practitioners begin the process of helping EMI faculty build awareness of better teaching practices. Finally, the results from faculty development workshops participants’ surveys will show the impact that these workshops can have. Almost all of the participants indicated that they learned something new and would like to incorporate the ideas from the workshop into their teaching. In addition, the vast majority of the participants felt the workshop provided them with new information, and they would like more workshops like these.

Keywords: English-medium instruction, materials development, professional development, teaching effectiveness

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2312 Phytoplankton Structure and Invasive Cyanobacterial Species of Polish Temperate Lakes: Their Associations with Environmental Parameters and Findings About Their Toxic Properties

Authors: Tumer Orhun Aykut, Robin Michael Crucitti-Thoo, Agnieszka Rudak, Iwona Jasser

Abstract:

Due to eutrophication connected to the growing human population, intensive agriculture, industrialization, and reinforcement of global warming, freshwater resources are changing negatively in every region of the World. This change also concerns the replacement of native species by invasive ones that can spread in many ways. Biological invasions are a developing problem to ecosystem continuity and their presence is mostly common in freshwater bodies. The occurrence and potential invasion of the species depends on associations between abiotic and biotic variables. Due to climate change, many species can extend their range from low to high latitudes and differ in their geographic ranges. In addition, the hydrological issues strongly influence the physicochemical parameters and biological processes, especially the growth rates of species and bloom formation of Cyanobacteria. Among tropical invasive species noted in temperate Europe, Raphidiopsis raciborskii, Chrysosporum bergii, and Sphaerospermopsis aphanizomenoides are considered a serious threat. R. raciborskii being the most important one as it is already known as a highly invasive species in almost all around the World, is a freshwater, planktonic, filamentous, potentially toxic, and nitrogen-fixing Cyanobacteria. This study aimed to investigate the presence of invasive cyanobacterial species in temperate lakes in Northeastern Poland, reveal the composition of phytoplankton communities, determine the effect of environmental variables, and identify the toxic properties of invasive Cyanobacteria and other phytoplankton groups. Our study was conducted in twenty-five lakes in August 2023. The lakes represent a geographical gradient from central Poland to the Northeast and have different depths, sizes, and trophic statuses. According to performed analyses, the presence of R. raciborskii was recorded in five lakes: Szczęśliwickie (Warsaw), Mikołajskie, Rekąty, Sztynorckie (Masurian Lakeland), and further East, in Pobondzie (Suwałki Lakeland). On the other hand, C. bergii was found in three lakes: Rekąty (Masurian Lakeland), Żabinki, and Pobondzie (Suwałki Lakeland), while S. aphanizomenoides only in Pobondzie (Suwałki Lakeland). Maximum phytoplankton diversity was found in Lake Rekąty, a small and shallow lake mentioned above. The highest phytoplankton biomass was detected in highly eutrophic Lake Suskie, followed by Lake Sztynorckie. In this last lake, which is also strongly eutrophic, the highest biomass of R. raciborskii was found. Cyanophyceae had the highest biovolume and was followed by Chlorophyceae in the entire study. Numerous environmental parameters, including nutrients, were studied, and their relationships with the invasive species and the whole phytoplankton community will be presented. In addition, toxic properties of environmental DNA results from each lake will also be shown. In conclusion, investigated invasive cyanobacterial species were found in a few Northeastern Polish temperate lakes, but the number of individuals was quite low, so the biomass was quite low. It has been observed that the structure of phytoplankton changed based on lakes and environmental parameters.

Keywords: biological invasion, cyanobacteria, cyanotoxins, phytoplankton ecology, sanger sequencing

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2311 Art Beyond Borders: Virtual School Field Trips

Authors: Audrey Hudson

Abstract:

In 2020, educational field trips went virtual for all students. At the Art Gallery of Ontario (AGO) in Canada, our solution was to create a virtual school program that addressed three pillars of access—economic, geographic and cultural—with art at the center. Now, at the close of three years, we have reached 1.6 million students! Exponentially more than we have ever welcomed for onsite school visits. In 2022, we partnered with the Museum of Modern Art (MoMA), the Hong Kong University Museum and the National Gallery of Singapore, which has pushed the boundaries of art education into the expanse of the global community. Looking forward to our fourth year of the program, we are using the platform of technology to expand our program of art, access and learning to a global platform. In 2023/24, we intend to connect across more borders to expand the pedagogical benefits of art education for a global community. We invite you to listen to how you can join this journey.

Keywords: technology, museums, art education, pedagogy

Procedia PDF Downloads 48
2310 Fitness Action Recognition Based on MediaPipe

Authors: Zixuan Xu, Yichun Lou, Yang Song, Zihuai Lin

Abstract:

MediaPipe is an open-source machine learning computer vision framework that can be ported into a multi-platform environment, which makes it easier to use it to recognize the human activity. Based on this framework, many human recognition systems have been created, but the fundamental issue is the recognition of human behavior and posture. In this paper, two methods are proposed to recognize human gestures based on MediaPipe, the first one uses the Adaptive Boosting algorithm to recognize a series of fitness gestures, and the second one uses the Fast Dynamic Time Warping algorithm to recognize 413 continuous fitness actions. These two methods are also applicable to any human posture movement recognition.

Keywords: computer vision, MediaPipe, adaptive boosting, fast dynamic time warping

Procedia PDF Downloads 94
2309 Pre-Service EFL Teachers' Perceptions of Written Corrective Feedback in a Wiki-Based Environment

Authors: Mabel Ortiz, Claudio Díaz

Abstract:

This paper explores Chilean pre-service teachers' perceptions about the provision of corrective feedback in a wiki environment during the collaborative writing of an argumentative essay. After conducting a semi-structured interview on 22 participants, the data were processed through the content analysis technique. The results show that students have positive perceptions about corrective feedback, provided through a wiki virtual environment, which in turn facilitates feedback provision and impacts language learning effectively. Some of the positive perceptions about virtual feedback refer to permanent access, efficiency, simultaneous revision and immediacy. It would then be advisable to integrate wiki-based feedback as a methodology for the language classroom and collaborative writing tasks.

Keywords: argumentative essay, focused corrective feedback, perception, wiki environment

Procedia PDF Downloads 273
2308 Speaker Recognition Using LIRA Neural Networks

Authors: Nestor A. Garcia Fragoso, Tetyana Baydyk, Ernst Kussul

Abstract:

This article contains information from our investigation in the field of voice recognition. For this purpose, we created a voice database that contains different phrases in two languages, English and Spanish, for men and women. As a classifier, the LIRA (Limited Receptive Area) grayscale neural classifier was selected. The LIRA grayscale neural classifier was developed for image recognition tasks and demonstrated good results. Therefore, we decided to develop a recognition system using this classifier for voice recognition. From a specific set of speakers, we can recognize the speaker’s voice. For this purpose, the system uses spectrograms of the voice signals as input to the system, extracts the characteristics and identifies the speaker. The results are described and analyzed in this article. The classifier can be used for speaker identification in security system or smart buildings for different types of intelligent devices.

Keywords: extreme learning, LIRA neural classifier, speaker identification, voice recognition

Procedia PDF Downloads 158
2307 Nonlinear Adaptive PID Control for a Semi-Batch Reactor Based on an RBF Network

Authors: Magdi. M. Nabi, Ding-Li Yu

Abstract:

Control of a semi-batch polymerization reactor using an adaptive radial basis function (RBF) neural network method is investigated in this paper. A neural network inverse model is used to estimate the valve position of the reactor; this method can identify the controlled system with the RBF neural network identifier. The weights of the adaptive PID controller are timely adjusted based on the identification of the plant and self-learning capability of RBFNN. A PID controller is used in the feedback control to regulate the actual temperature by compensating the neural network inverse model output. Simulation results show that the proposed control has strong adaptability, robustness and satisfactory control performance and the nonlinear system is achieved.

Keywords: Chylla-Haase polymerization reactor, RBF neural networks, feed-forward, feedback control

Procedia PDF Downloads 684