Search results for: learning delivery modes
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 9737

Search results for: learning delivery modes

5057 Experimental and Numerical Investigation on Deformation Behaviour of Single Crystal Copper

Authors: Suman Paik, P. V. Durgaprasad, Bijan K. Dutta

Abstract:

A study combining experimental and numerical investigation on the deformation behaviour of single crystals of copper is presented in this paper. Cylindrical samples were cut in specific orientations from high purity copper single crystal and subjected to uniaxial compression loading at quasi-static strain rate. The stress-strain curves along two different crystallographic orientations were then extracted. In order to study and compare the deformation responses, a single crystal plasticity model incorporating non-Schmid effects was developed assuming cross-slip plays an important role in orientation of the material. By making use of crystal plasticity finite element method, the model was applied to investigate the orientation dependence of the stress-strain behaviour of two crystallographic orientations. Finally, details of slip activities of deformed crystals were investigated by linking the orientation of slip lines with the theoretical traces of possible crystallographic planes. The experimentally determined active slip modes were matched with those determined by simulations.

Keywords: crystal plasticity, modelling, non-Schmid effects, finite elements, finite strain

Procedia PDF Downloads 210
5056 On the Effectiveness of Play Therapy on Mentally Retarded Elementary School Students’ Educational Progress

Authors: Nassrin Badrkhani

Abstract:

Current paper was designed aiming at finding the impacts of play therapy on the development of mentally retarded students in elementary school. The sample included 191 elementary students from 5 classes. Sixty students were chosen from each class, and based on their learning capabilities, they were further assigned into similar control and treatment groups. Then, five groups received treatments with special types of games, instruments, and methods for two months. The teacher-made instruments in literature, math, and science were adopted after their content validity had been confirmed by experienced teachers. The findings were analyzed in both descriptive, including mean, median, and standard deviation, and interpretive levels, using covariance analysis in SPSS. The results were indicative of the fact that play therapy (individual and group games) was positively effective in mentally retarded students’ educational development. Moreover, regarding P ˂0/001, it was found that group games were more influential than individual ones. It was also clear that the students’ gender played no role in this kind of treatment. Therefore, it is highly recommended to implement play therapy as a part of the educational curriculum for mentally retarded pupils.

Keywords: development, education, learning, play therapy, student, teacher

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5055 Rendering Religious References in English: Naguib Mahfouz in the Arabic as a Foreign Language Classroom

Authors: Shereen Yehia El Ezabi

Abstract:

The transition from the advanced to the superior level of Arabic proficiency is widely known to pose considerable challenges for English speaking students of Arabic as a Foreign Language (AFL). Apart from the increasing complexity of the grammar at this juncture, together with the sprawling vocabulary, to name but two of those challenges, there is also the somewhat less studied hurdle along the way to superior level proficiency, namely, the seeming opacity of many aspects of Arab/ic culture to such learners. This presentation tackles one specific dimension of such issues: religious references in literary texts. It illustrates how carefully constructed translation activities may be used to expand and deepen students’ understanding and use of them. This is shown to be vital for making the leap to the desired competency, given that such elements, as reflected in customs, traditions, institutions, worldviews, and formulaic expressions lie at the very core of Arabic culture and, as such, pervade all modes and levels of Arabic discourse. A short story from the collection “Stories from Our Alley”, by preeminent novelist Naguib Mahfouz is selected for use in this context, being particularly replete with such religious references, of which religious expressions will form the focus of the presentation. As a miniature literary work, it provides an organic whole, so to speak, within which to explore with the class the most precise denotation, as well as the subtlest connotation of each expression in an effort to reach the ‘best’ English rendering. The term ‘best’ refers to approximating the meaning in its full complexity from the source text, in this case Arabic, to the target text, English, according to the concept of equivalence in translation theory. The presentation will show how such a process generates the sort of thorough discussion and close text analysis which allows students to gain valuable insight into this central idiom of Arabic. A variety of translation methods will be highlighted, gleaned from the presenter’s extensive work with advanced/superior students in the Center for Arabic Study Abroad (CASA) program at the American University in Cairo. These begin with the literal rendering of expressions, with the purpose of reinforcing vocabulary learning and practicing the rules of derivational morphology as they form each word, since the larger context remains that of an AFL class, as opposed to a translation skills program. However, departures from the literal approach are subsequently explored by degrees, moving along the spectrum of functional and pragmatic freer translations in order to transmit the ‘real’ meaning in readable English to the target audience- no matter how culture/religion specific the expression- while remaining faithful to the original. Samples from students’ work pre and post discussion will be shared, demonstrating how class consensus is formed as to the final English rendering, proposed as the closest match to the Arabic, and shown to be the result of the above activities. Finally, a few examples of translation work which students have gone on to publish will be shared to corroborate the effectiveness of this teaching practice.

Keywords: superior level proficiency in Arabic as a foreign language, teaching Arabic as a foreign language, teaching idiomatic expressions, translation in foreign language teaching

Procedia PDF Downloads 193
5054 Relative Study of the Effect of the Temperature Gradient on Free Vibrations of Clamped Visco-Elastic Rectangular Plates with Linearly and Exponentially Thickness Variations Respectively in Two Directions

Authors: Harvinder Kaur

Abstract:

Rayleigh–Ritz method is a broadly used classical method for the calculation of the natural vibration frequency of a structure in the second or higher order. Here it is used to construct a mathematical model of relative study of the thermal effect on free transverse vibrations of clamped (c-c-c-c type) visco-elastic rectangular plate with linearly and exponentially thickness variations respectively in two directions. Researchers in the field of Engineering always make an effort for better designs of mechanical structures. In-depth study of the vibration behavior of tapered plates with diverse thickness variation under high temperature would ultimately help to finalize the accurate design of a structure. The perfect tapered structure saves weight and as well as expenses. In the present paper, the comparison has been done for deflection and time period corresponding to the first two modes of vibrations of clamped plate for various values of aspect ratio, thermal constants, and taper constants of both the cases.

Keywords: Rayleigh-Ritz Method, tapered plates, transverse vibration, thermal constant, visco-elasticity

Procedia PDF Downloads 223
5053 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 228
5052 Electronic Government Services Adoption from Multi-Nationalities Perspectives

Authors: Isaac Kofi Mensah, Jianing Mi, Cheng Feng

Abstract:

Electronic government is the application of Information and Communication Technologies (ICTs) by the government to improve public service delivery to citizens and businesses. The purpose of this study is to investigate factors influencing the adoption and use of e-government services from different nationalities perspectives. The Technology Acceptance Model (TAM) will be used as the theoretical framework for the study. A questionnaire would be developed and administered to 500 potential respondents who are students from different nationalities in China. Predictors such as perceived usefulness, perceived ease of use, computer self-efficacy, trust in both the internet and government, social influence and perceived service quality would be examined with regard to their impact on the intention to use e-government services. This research is currently at the design and implementation stage. The completion of this study will provide useful insights into understanding factors impacting the decision to use e-government services from a cross and multi nationalities perspectives.

Keywords: different nationalities, e-government, e-government services, technology acceptance model (TAM)

Procedia PDF Downloads 423
5051 Intercultural Initiatives and Canadian Bilingualism

Authors: Muna Shafiq

Abstract:

Growth in international immigration is a reflection of increased migration patterns in Canada and in other parts of the world. Canada continues to promote itself as a bilingual country, yet the bilingual French and English population numbers do not reflect this platform. Each province’s integration policies focus only on second language learning of either English or French. Moreover, since English Canadians outnumber French Canadians, maintaining, much less increasing, English-French bilingualism appears unrealistic. One solution to increasing Canadian bilingualism requires creating intercultural communication initiatives between youth in Quebec and the rest of Canada. Specifically, the focus is on active, experiential learning, where intercultural competencies develop outside traditional classroom settings. The target groups are Generation Y Millennials and Generation Z Linksters, the next generations in the career and parenthood lines. Today, Canada’s education system, like many others, must continually renegotiate lines between programs it offers its immigrant and native communities. While some purists or right-wing nationalists would disagree, the survival of bilingualism in Canada has little to do with reducing immigration. Children and youth immigrants play a valuable role in increasing Canada’s French and English speaking communities. For instance, a focus on more immersion, over core French education programs for immigrant children and youth would not only increase bilingual rates; it would develop meaningful intercultural attachments between Canadians. Moreover, a vigilant increase of funding in French immersion programs is critical, as are new initiatives that focus on experiential language learning for students in French and English language programs. A favorable argument supports the premise that other than French-speaking students in Québec and elsewhere in Canada, second and third generation immigrant students are excellent ambassadors to promote bilingualism in Canada. Most already speak another language at home and understand the value of speaking more than one language in their adopted communities. Their dialogue and participation in experiential language exchange workshops are necessary. If the proposed exchanges take place inter-provincially, the momentum to increase collective regional voices increases. This regional collectivity can unite Canadians differently than nation-targeted initiatives. The results from an experiential youth exchange organized in 2017 between students at the crossroads of Generation Y and Generation Z in Vancouver and Quebec City respectively offer a promising starting point in assessing the strength of bringing together different regional voices to promote bilingualism. Code-switching between standard, international French Vancouver students, learn in the classroom versus more regional forms of Quebec French spoken locally created regional connectivity between students. The exchange was equally rewarding for both groups. Increasing their appreciation for each other’s regional differences allowed them to contribute actively to their social and emotional development. Within a sociolinguistic frame, this proposed model of experiential learning does not focus on hands-on work experience. However, the benefits of such exchanges are as valuable as work experience initiatives developed in experiential education. Students who actively code switch between French and English in real, not simulated contexts appreciate bilingualism more meaningfully and experience its value in concrete terms.

Keywords: experiential learning, intercultural communication, social and emotional learning, sociolinguistic code-switching

Procedia PDF Downloads 133
5050 Effects of Artificial Intelligence and Machine Learning on Social Media for Health Organizations

Authors: Ricky Leung

Abstract:

Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

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5049 Air-Coupled Ultrasonic Testing for Non-Destructive Evaluation of Various Aerospace Composite Materials by Laser Vibrometry

Authors: J. Vyas, R. Kazys, J. Sestoke

Abstract:

Air-coupled ultrasonic is the contactless ultrasonic measurement approach which has become widespread for material characterization in Aerospace industry. It is always essential for the requirement of lightest weight, without compromising the durability. To archive the requirements, composite materials are widely used. This paper yields analysis of the air-coupled ultrasonics for composite materials such as CFRP (Carbon Fibre Reinforced Polymer) and GLARE (Glass Fiber Metal Laminate) and honeycombs for the design of modern aircrafts. Laser vibrometry could be the key source of characterization for the aerospace components. The air-coupled ultrasonics fundamentals, including principles, working modes and transducer arrangements used for this purpose is also recounted in brief. The emphasis of this paper is to approach the developed NDT techniques based on the ultrasonic guided waves applications and the possibilities of use of laser vibrometry in different materials with non-contact measurement of guided waves. 3D assessment technique which employs the single point laser head using, automatic scanning relocation of the material to assess the mechanical displacement including pros and cons of the composite materials for aerospace applications with defects and delaminations.

Keywords: air-coupled ultrasonics, contactless measurement, laser interferometry, NDT, ultrasonic guided waves

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5048 Synthesis and Characterization of Mass Catalysts Based on Cobalt and Molybdenum

Authors: Nassira Ouslimani

Abstract:

The electronic structure of transition metals gives them many catalytic possibilities in many types of reactions, particularly cobalt and molybdenum. It is in this context that this study is part of the synthesis and characterization of mass catalysts based on cobalt and molybdenum Co1₋xMoO4 (X=0 and X=0.5 and X=1). The two catalysts were prepared by Co-precipitation using ammonia as a precipitating agent and one by precipitation. The samples obtained were analyzed by numerous physic-chemical analysis techniques: ATG-ATD-DSC, DRX-HT, SEM-EDX, and the elemental composition of the catalysts was verified by SAA as well as the FTIR. The ATG-DSC shows a mass loss for all the catalysts of approximately 8%, corresponding to the loss of water and the decomposition of nitrates. The DRX-HT analysis allows the detection of the two CoMoO4 phases with diffraction peaks which increase with the increase in temperature. The results of the FTIR analysis made it possible to highlight the vibration modes of the bonds of the structure of the prepared catalysts. The SEM images of the solids show very different textures with almost homogeneous surfaces with a more regular particle size distribution and a more defined grain shape. The EDX analysis showed the presence of the elements Co, Mo, and O in proportions very close to the nominal proportions. Finally, the actual composition, evaluated by SAA, is close to the theoretical composition fixed during the preparation. This testifies to the good conditions for the preparation of the catalysts by the co-precipitation method.

Keywords: catalytic, molybdenum, coprecipitation, cobalt, ammonia

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5047 Developing a Machine Learning-based Cost Prediction Model for Construction Projects using Particle Swarm Optimization

Authors: Soheila Sadeghi

Abstract:

Accurate cost prediction is essential for effective project management and decision-making in the construction industry. This study aims to develop a cost prediction model for construction projects using Machine Learning techniques and Particle Swarm Optimization (PSO). The research utilizes a comprehensive dataset containing project cost estimates, actual costs, resource details, and project performance metrics from a road reconstruction project. The methodology involves data preprocessing, feature selection, and the development of an Artificial Neural Network (ANN) model optimized using PSO. The study investigates the impact of various input features, including cost estimates, resource allocation, and project progress, on the accuracy of cost predictions. The performance of the optimized ANN model is evaluated using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and R-squared. The results demonstrate the effectiveness of the proposed approach in predicting project costs, outperforming traditional benchmark models. The feature selection process identifies the most influential variables contributing to cost variations, providing valuable insights for project managers. However, this study has several limitations. Firstly, the model's performance may be influenced by the quality and quantity of the dataset used. A larger and more diverse dataset covering different types of construction projects would enhance the model's generalizability. Secondly, the study focuses on a specific optimization technique (PSO) and a single Machine Learning algorithm (ANN). Exploring other optimization methods and comparing the performance of various ML algorithms could provide a more comprehensive understanding of the cost prediction problem. Future research should focus on several key areas. Firstly, expanding the dataset to include a wider range of construction projects, such as residential buildings, commercial complexes, and infrastructure projects, would improve the model's applicability. Secondly, investigating the integration of additional data sources, such as economic indicators, weather data, and supplier information, could enhance the predictive power of the model. Thirdly, exploring the potential of ensemble learning techniques, which combine multiple ML algorithms, may further improve cost prediction accuracy. Additionally, developing user-friendly interfaces and tools to facilitate the adoption of the proposed cost prediction model in real-world construction projects would be a valuable contribution to the industry. The findings of this study have significant implications for construction project management, enabling proactive cost estimation, resource allocation, budget planning, and risk assessment, ultimately leading to improved project performance and cost control. This research contributes to the advancement of cost prediction techniques in the construction industry and highlights the potential of Machine Learning and PSO in addressing this critical challenge. However, further research is needed to address the limitations and explore the identified future research directions to fully realize the potential of ML-based cost prediction models in the construction domain.

Keywords: cost prediction, construction projects, machine learning, artificial neural networks, particle swarm optimization, project management, feature selection, road reconstruction

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5046 Organizational Innovations of the 20th Century as High Tech of the 21st: Evidence from Patent Data

Authors: Valery Yakubovich, Shuping wu

Abstract:

Organization theorists have long claimed that organizational innovations are nontechnological, in part because they are unpatentable. The claim rests on the assumption that organizational innovations are abstract ideas embodied in persons and contexts rather than in context-free practical tools. However, over the last three decades, organizational knowledge has been increasingly embodied in digital tools which, in principle, can be patented. To provide the first empirical evidence regarding the patentability of organizational innovations, we trained two machine learning algorithms to identify a population of 205,434 patent applications for organizational technologies (OrgTech) and, among them, 141,285 applications that use organizational innovations accumulated over the 20th century. Our event history analysis of the probability of patenting an OrgTech invention shows that ideas from organizational innovations decrease the probability of patent allowance unless they describe a practical tool. We conclude that the present-day digital transformation places organizational innovations in the realm of high tech and turns the debate about organizational technologies into the challenge of designing practical organizational tools that embody big ideas about organizing. We outline an agenda for patent-based research on OrgTech as an emerging phenomenon.

Keywords: organizational innovation, organizational technology, high tech, patents, machine learning

Procedia PDF Downloads 117
5045 Logistics Hub Location and Scheduling Model for Urban Last-Mile Deliveries

Authors: Anastasios Charisis, Evangelos Kaisar, Steven Spana, Lili Du

Abstract:

Logistics play a vital role in the prosperity of today’s cities, but current urban logistics practices are proving problematic, causing negative effects such as traffic congestion and environmental impacts. This paper proposes an alternative urban logistics system, leasing hubs inside cities for designated time intervals, and using handcarts for last-mile deliveries. A mathematical model for selecting the locations of hubs and allocating customers, while also scheduling the optimal times during the day for leasing hubs is developed. The proposed model is compared to current delivery methods requiring door-to-door truck deliveries. It is shown that truck traveled distances decrease by more than 60%. In addition, analysis shows that in certain conditions the approach can be economically competitive and successfully applied to address real problems.

Keywords: hub location, last-mile, logistics, optimization

Procedia PDF Downloads 188
5044 Dialogic Approaches to Writing Pedagogy

Authors: Yael Leibovitch

Abstract:

Teaching academic writing is a source of concern for secondary schools. Many students struggle to meet the basic standards of literacy while teacher confidence in this arena remains low. These issues are compounded by the conventionally prescriptive character of writing instruction, which fails to engage student writers. At the same time, a growing body of research on dialogic teaching has highlighted the powerful role of talk in student learning. With the intent of enhancing pedagogical capability, this paper shares finding from a co-inquiry case study that investigated how teachers think about and negotiate classroom discourse to position students as effective academic writers and thinkers. Using a range of qualitative methods, this project closely documents the iterative collaboration of educators as they sought to create more opportunities for dialogic engagement. More specifically, it triangulates both teacher and student data regarding the efficacy of interdependent thinking and collaborative reasoning as organizing principals for literacy learning. Findings indicate that a dialogic teaching repertoire helps to develop the cognitive and metacognitive skills of adolescent writers. In addition, they underscore the importance of sustained professional collaboration to the uptake of new writing pedagogies.

Keywords: dialogic teaching, writing, teacher professional development, student literacy

Procedia PDF Downloads 210
5043 Technology Blending as an Innovative Construction Mechanism in the Global South

Authors: Janet Kaningen, Richard N. Kaningen, Jonas Kaningen

Abstract:

This paper aims to discover the best ways to improve production efficiency, cost efficiency, community cohesion, and long-term sustainability in Ghana's housing delivery. Advanced Construction Technologies (ACTs) are set to become the sustainable mainstay of the construction industry due to the demand for innovative housing solutions. Advances in material science, building component production, and assembly technologies are leading to the development of next-generation materials such as polymeric-fiber-based products, light-metal alloys, and eco-materials. Modular housing construction has become more efficient and cost-effective than traditional building methods and is becoming increasingly popular for commercial, industrial, and residential projects. Effective project management and logistics will be imperative in the future speed and cost of modular construction housing.

Keywords: technology blending, sustainability, housing, Ghana

Procedia PDF Downloads 80
5042 Support Services in Open and Distance Education: An Integrated Model of Open Universities

Authors: Evrim Genc Kumtepe, Elif Toprak, Aylin Ozturk, Gamze Tuna, Hakan Kilinc, Irem Aydin Menderis

Abstract:

Support services are very significant elements for all educational institutions in general; however, for distance learners, these services are more essential than traditional (face-to-face) counterparts. One of the most important reasons for this is that learners and instructors do not share the same physical environment and that distance learning settings generally require intrapersonal interactions rather than interpersonal ones. Some learners in distance learning programs feel isolated. Furthermore, some fail to feel a sense of belonging to the institution because of lack of self-management skills, lack of motivation levels, and the need of being socialized, so that they are more likely to fail or drop out of an online class. In order to overcome all these problems, support services have emerged as a critical element for an effective and sustainable distance education system. Within the context of distance education support services, it is natural to include technology-based and web-based services and also the related materials. Moreover, institutions in education sector are expected to use information and communication technologies effectively in order to be successful in educational activities and programs. In terms of the sustainability of the system, an institution should provide distance education services through ICT enabled processes to support all stakeholders in the system, particularly distance learners. In this study, it is envisaged to develop a model based on the current support services literature in the field of open and distance learning and the applications of the distance higher education institutions. Specifically, content analysis technique is used to evaluate the existing literature in the distance education support services, the information published on websites, and applications of distance higher education institutions across the world. A total of 60 institutions met the inclusion criteria which are language option (English) and availability of materials in the websites. The six field experts contributed to brainstorming process to develop and extract codes for the coding scheme. During the coding process, these preset and emergent codes are used to conduct analyses. Two coders independently reviewed and coded each assigned website to ensure that all coders are interpreting the data the same way and to establish inter-coder reliability. Once each web page is included in descriptive and relational analysis, a model of support services is developed by examining the generated codes and themes. It is believed that such a model would serve as a quality guide for future institutions, as well as the current ones.

Keywords: support services, open education, distance learning, support model

Procedia PDF Downloads 193
5041 Ensemble of Deep CNN Architecture for Classifying the Source and Quality of Teff Cereal

Authors: Belayneh Matebie, Michael Melese

Abstract:

The study focuses on addressing the challenges in classifying and ensuring the quality of Eragrostis Teff, a small and round grain that is the smallest cereal grain. Employing a traditional classification method is challenging because of its small size and the similarity of its environmental characteristics. To overcome this, this study employs a machine learning approach to develop a source and quality classification system for Teff cereal. Data is collected from various production areas in the Amhara regions, considering two types of cereal (high and low quality) across eight classes. A total of 5,920 images are collected, with 740 images for each class. Image enhancement techniques, including scaling, data augmentation, histogram equalization, and noise removal, are applied to preprocess the data. Convolutional Neural Network (CNN) is then used to extract relevant features and reduce dimensionality. The dataset is split into 80% for training and 20% for testing. Different classifiers, including FVGG16, FINCV3, QSCTC, EMQSCTC, SVM, and RF, are employed for classification, achieving accuracy rates ranging from 86.91% to 97.72%. The ensemble of FVGG16, FINCV3, and QSCTC using the Max-Voting approach outperforms individual algorithms.

Keywords: Teff, ensemble learning, max-voting, CNN, SVM, RF

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5040 Use of Computer and Machine Learning in Facial Recognition

Authors: Neha Singh, Ananya Arora

Abstract:

Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

Procedia PDF Downloads 102
5039 Artificial Intelligence in Global Healthcare: Need for Robust Governance Frameworks

Authors: Sandeep Reddy, Sonia Allan, Simon Coghlan, Paul Cooper

Abstract:

Artificial Intelligence (AI) and its application in medicine has generated ample interest amongst policymakers and clinicians. Successes with AI in medical imaging interpretation and clinical decision support are paving the way for its incorporation into routine healthcare delivery. While there has been a focus on the development of ethical principles to guide its application in healthcare, challenges of this application go beyond what ethics principles can address thus requiring robust governance frameworks. Also, while ethical challenges of medical artificial intelligence are being discussed, the ethics of deploying AI in lower-income countries receive less attention than in other developed economies. This creates an imperative not only for sound ethical guidelines but also for robust governance frameworks to regulate AI in medicine around the world. In this article, we discuss what components need to be considered in developing these governance frameworks and who should lead this worldwide effort.

Keywords: artificial intelligence, global health, governance, ethics

Procedia PDF Downloads 145
5038 Omni: Data Science Platform for Evaluate Performance of a LoRaWAN Network

Authors: Emanuele A. Solagna, Ricardo S, Tozetto, Roberto dos S. Rabello

Abstract:

Nowadays, physical processes are becoming digitized by the evolution of communication, sensing and storage technologies which promote the development of smart cities. The evolution of this technology has generated multiple challenges related to the generation of big data and the active participation of electronic devices in society. Thus, devices can send information that is captured and processed over large areas, but there is no guarantee that all the obtained data amount will be effectively stored and correctly persisted. Because, depending on the technology which is used, there are parameters that has huge influence on the full delivery of information. This article aims to characterize the project, currently under development, of a platform that based on data science will perform a performance and effectiveness evaluation of an industrial network that implements LoRaWAN technology considering its main parameters configuration relating these parameters to the information loss.

Keywords: Internet of Things, LoRa, LoRaWAN, smart cities

Procedia PDF Downloads 142
5037 Understanding English Language in Career Development of Academics in Non-English Speaking HEIs: A Systematic Literature Review

Authors: Ricardo Pinto Mario Covele, Patricio V. Langa, Patrick Swanzy

Abstract:

The English language has been recognized as a universal medium of instruction in academia, especially in Higher Education Institutions (HEIs) hence exerting enormous influence within the context of research and publication. By extension, the English Language has been embraced by scholars from non-English speaking countries. The purpose of this review was to synthesize the discussions using four databases. Discussion in the English language in the career development of academics, particularly in non-English speaking universities, is largely less visible. This paper seeks to fill this gap and to improve the visibility of the English language in the career development of academics focusing on non-English language speaking universities by undertaking a systematic literature review. More specifically, the paper addresses the language policy, English language learning model as a second language, sociolinguistic field and career development, methods, as well as its main findings. This review analyzed 75 relevant resources sourced from Western Cape’s Library, Scopus, Google scholar, and web of science databases from November 2020 to July 2021 using the PQRS framework as an analytical lens. The paper’s findings demonstrate that, while higher education continues to be under-challenges of English language usage, literature targeting non-English speaking universities remains less discussed than it is often described. The findings also demonstrate the dominance of English language policy, both for knowledge production and dissemination of literature challenging emerging scholars from non-English speaking HEIs. Hence, the paper argues for the need to reconsider the context of non-English language speakers in the English language in the career development of academics’ research, both as empirical fields and as emerging knowledge producers. More importantly, the study reveals two bodies of literature: (1) the instrumentalist approach to English Language learning and (2) Intercultural approach to the English Language for career opportunities, classified as the appropriate to explain the English language learning process and how is it perceived towards scholars’ academic careers in HEIs.

Keywords: English language, public and private universities, language policy, career development, non-English speaking countries

Procedia PDF Downloads 147
5036 A Smart Contract Project: Peer-to-Peer Energy Trading with Price Forecasting in Microgrid

Authors: Şakir Bingöl, Abdullah Emre Aydemir, Abdullah Saado, Ahmet Akıl, Elif Canbaz, Feyza Nur Bulgurcu, Gizem Uzun, Günsu Bilge Dal, Muhammedcan Pirinççi

Abstract:

Smart contracts, which can be applied in many different areas, from financial applications to the internet of things, come to the fore with their security, low cost, and self-executing features. In this paper, it is focused on peer-to-peer (P2P) energy trading and the implementation of the smart contract on the Ethereum blockchain. It is assumed a microgrid consists of consumers and prosumers that can produce solar and wind energy. The proposed architecture is a system where the prosumer makes the purchase or sale request in the smart contract and the maximum price obtained through the distribution system operator (DSO) by forecasting. It is aimed to forecast the hourly maximum unit price of energy by using deep learning instead of a fixed pricing. In this way, it will make the system more reliable as there will be more dynamic and accurate pricing. For this purpose, Istanbul's energy generation, energy consumption and market clearing price data were used. The consistency of the available data and forecasting results is observed and discussed with graphs.

Keywords: energy trading smart contract, deep learning, microgrid, forecasting, Ethereum, peer to peer

Procedia PDF Downloads 129
5035 Functionalized Nanoparticles for Biomedical Applications

Authors: Temesgen Geremew

Abstract:

Functionalized nanoparticles have emerged as a revolutionary class of materials with immense potential in various biomedical applications. These engineered nanoparticles possess unique properties tailored to interact with biological systems, offering unprecedented opportunities in drug delivery, imaging, diagnostics, and therapy. This research delves into the design, synthesis, and characterization of functionalized nanoparticles for targeted biomedical applications. The primary focus lies on developing nanoparticles with precisely controlled size, surface chemistry, and biocompatibility for specific medical purposes. The research will also explore the crucial interaction of these nanoparticles with biological systems, encompassing cellular uptake, biodistribution, and potential toxicity evaluation. The successful development of functionalized nanoparticles holds the promise to revolutionize various aspects of healthcare. This research aspires to contribute significantly to this advancement by providing valuable insights into the design and application of these versatile materials within the ever-evolving field of biomedicine.

Keywords: nanoparticles, biomedicals, cancer, biocompatibility

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5034 A Model for Solid Transportation Problem with Three Hierarchical Objectives under Uncertain Environment

Authors: Wajahat Ali, Shakeel Javaid

Abstract:

In this study, we have developed a mathematical programming model for a solid transportation problem with three objective functions arranged in hierarchical order. The mathematical programming models with more than one objective function to be solved in hierarchical order is termed as a multi-level programming model. Our study explores a Multi-Level Solid Transportation Problem with Uncertain Parameters (MLSTPWU). The proposed MLSTPWU model consists of three objective functions, viz. minimization of transportation cost, minimization of total transportation time, and minimization of deterioration during transportation. These three objective functions are supposed to be solved by decision-makers at three consecutive levels. Three constraint functions are added to the model, restricting the total availability, total demand, and capacity of modes of transportation. All the parameters involved in the model are assumed to be uncertain in nature. A solution method based on fuzzy logic is also discussed to obtain the compromise solution for the proposed model. Further, a simulated numerical example is discussed to establish the efficiency and applicability of the proposed model.

Keywords: solid transportation problem, multi-level programming, uncertain variable, uncertain environment

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5033 Comparison of Different k-NN Models for Speed Prediction in an Urban Traffic Network

Authors: Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

A database that records average traffic speeds measured at five-minute intervals for all the links in the traffic network of a metropolitan city. While learning from this data the models that can predict future traffic speed would be beneficial for the applications such as the car navigation system, building predictive models for every link becomes a nontrivial job if the number of links in a given network is huge. An advantage of adopting k-nearest neighbor (k-NN) as predictive models is that it does not require any explicit model building. Instead, k-NN takes a long time to make a prediction because it needs to search for the k-nearest neighbors in the database at prediction time. In this paper, we investigate how much we can speed up k-NN in making traffic speed predictions by reducing the amount of data to be searched for without a significant sacrifice of prediction accuracy. The rationale behind this is that we had a better look at only the recent data because the traffic patterns not only repeat daily or weekly but also change over time. In our experiments, we build several different k-NN models employing different sets of features which are the current and past traffic speeds of the target link and the neighbor links in its up/down-stream. The performances of these models are compared by measuring the average prediction accuracy and the average time taken to make a prediction using various amounts of data.

Keywords: big data, k-NN, machine learning, traffic speed prediction

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5032 Implant Guided Surgery and Immediate Loading

Authors: Omid Tavakol, Mahnaz Gholami

Abstract:

Introduction : In this oral presentation the main goal is discussing immediate loading in dental implants , from treatment planning and surgical guide designing to delivery , follow up and occlusal consideration . Methods and materials : first of all systematic reviews about immediate loading will be considered . besides , a comparison will be made between immediate loading and conventional loading in terms of success rate and complications . After that different methods , prosthetic options and materials best used in immediate loading will be explained. Particularly multi unit abutments and their mechanism of function will be explained .Digital impressions and designing the temporaries is the next topic we are to explicate .Next issue is the differences between single unit , multiple unit and full arch implantation in immediate loading .Following we are going to describe methods for tissue engineering and papilla formation after extraction . Last slides are about a full mouth rehabilitation via immediate loading technique from surgical designing to follow up .At the end we would talk about potential complications , how to prevent from occurrence and what to do if we face up with .

Keywords: guided surgery, digital implantology, immediate loading, digital dentistry

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5031 Learning the Most Common Causes of Major Industrial Accidents and Apply Best Practices to Prevent Such Accidents

Authors: Rajender Dahiya

Abstract:

Investigation outcomes of major process incidents have been consistent for decades and validate that the causes and consequences are often identical. The debate remains as we continue to experience similar process incidents even with enormous development of new tools, technologies, industry standards, codes, regulations, and learning processes? The objective of this paper is to investigate the most common causes of major industrial incidents and reveal industry challenges and best practices to prevent such incidents. The author, in his current role, performs audits and inspections of a variety of high-hazard industries in North America, including petroleum refineries, chemicals, petrochemicals, manufacturing, etc. In this paper, he shares real life scenarios, examples, and case studies from high hazards operating facilities including key challenges and best practices. This case study will provide a clear understanding of the importance of near miss incident investigation. The incident was a Safe operating limit excursion. The case describes the deficiencies in management programs, the competency of employees, and the culture of the corporation that includes hazard identification and risk assessment, maintaining the integrity of safety-critical equipment, operating discipline, learning from process safety near misses, process safety competency, process safety culture, audits, and performance measurement. Failure to identify the hazards and manage the risks of highly hazardous materials and processes is one of the primary root-causes of an incident, and failure to learn from past incidents is the leading cause of the recurrence of incidents. Several investigations of major incidents discovered that each showed several warning signs before occurring, and most importantly, all were preventable. The author will discuss why preventable incidents were not prevented and review the mutual causes of learning failures from past major incidents. The leading causes of past incidents are summarized below. Management failure to identify the hazard and/or mitigate the risk of hazardous processes or materials. This process starts early in the project stage and continues throughout the life cycle of the facility. For example, a poorly done hazard study such as HAZID, PHA, or LOPA is one of the leading causes of the failure. If this step is performed correctly, then the next potential cause is. Management failure to maintain the integrity of safety critical systems and equipment. In most of the incidents, mechanical integrity of the critical equipment was not maintained, safety barriers were either bypassed, disabled, or not maintained. The third major cause is Management failure to learn and/or apply learning from the past incidents. There were several precursors before those incidents. These precursors were either ignored altogether or not taken seriously. This paper will conclude by sharing how a well-implemented operating management system, good process safety culture, and competent leaders and staff contributed to managing the risks to prevent major incidents.

Keywords: incident investigation, risk management, loss prevention, process safety, accident prevention

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5030 The Scattering in Flexible Reactive Silencer Containing Rigid Partitioning

Authors: Muhammad Afzal, Junaid Uzair Satti

Abstract:

The noise emanating from the ducting of heating, ventilation, and air-conditioning (HVAC) system is often attenuated by using the dissipative silencers. Such devices work well for the high-frequency noise but are less operative in the low-frequency noise range. The present study analyzes a reactive silencer comprising expansion chamber of the elastic membranes partitioned symmetrically by a rigid plate. The Mode-Matching scheme has been developed to solve the governing boundary value problem. The orthogonal and non-orthogonal duct modes of acoustic pressures and normal velocities are matched at interfaces. It enables to recast the differential system into the infinite system of linear algebraic of equations, which is, then truncated and inverted for the solution. The truncated solution is validated through the conservation of energy and reconstruction of matching conditions. The results for scattering energy flux and transmission loss are shown against frequency and the dimensions of the chamber. It is seen that the stop-band of the silencer can be shifted to the broadband by changing the dimensions of the chamber and the properties of the elastic membranes. The modeled reactive silencer is more efficient in low frequency regime where the passive devices are least effective.

Keywords: acoustic scattering, elastic membranes mode-matching, reactive silencer

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5029 Promoting Students' Worldview Through Integrative Education in the Process of Teaching Biology in Grades 11 and 12 of High School

Authors: Saule Shazhanbayeva, Denise van der Merwe

Abstract:

Study hypothesis: Nazarbayev Intellectual School of Kyzylorda’s Biology teachers can use STEM-integrated learning to improve students' problem-solving ability and responsibility as global citizens. The significance of this study is to indicate how the use of STEM integrative learning during Biology lessons could contribute to forming globally-minded students who are responsible community members. For the purposes of this study, worldview is defined as a view that is broader than the country of Kazakhstan, allowing students to see the significance of their scientific contributions to the world as global citizens. The context of worldview specifically indicates that most students have never traveled outside of their city or region within Kazakhstan. In order to broaden student understanding, it is imperative that students are exposed to different world views and contrasting ideas within the educational setting of Biology as the science being used for the research. This exposure promulgates students understanding of the significance they have as global citizens alongside the obligations which would rest on them as scientifically minded global citizens. Integrative learning should be Biological Science - with Technology and engineering in the form of problem-solving, and Mathematics to allow improved problem-solving skills to develop within the students of Nazarbayev Intellectual School (NIS) of Kyzylorda. The school's vision is to allow students to realise their role as global citizens and become responsible community members. STEM allows integrations by combining four subject skills to solve topical problems designed by educators. The methods used are based on qualitative analysis: for students’ performance during a problem-solution scenario; and Biology teacher interviews to ascertain their understanding of STEM implementation and willingness to integrate it into current lessons. The research indicated that NIS is ready for a shift into STEM lessons to promote globally responsible students. The only additional need is for proper STEM integrative lesson method training for teachers.

Keywords: global citizen, STEM, Biology, high-school

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5028 Prominence of Biopsychosocial Formulation in Health Care Delivery for Aging Population: Empowering Caregiving through Natural Socio-Environmental Approaches

Authors: Kristine Demilou D. Santiago

Abstract:

An access to a high-quality health care system is what sets apart industrialized nations, such as the United States from other developing countries, which in this case is specifically pertaining to their older population. But what was the underrated factor in the sphere of quality healthcare rendered to elderly people in the Western context? Will this salient factor could push conviction to prorogue the existing gaps between self-denial patient-client and cheek by jowl medications? Are the natural socio-environmental approaches of caregiving the protracted remedy to healthcare disparities for aging population considering their day to day living? The conceptual framework of this model is primarily associated with addressing health and illness of human beings considering the biological, psychological and socio-environmental factors around them. The relevance of biopsychosocial formulation advancing each of the characteristics in the Biopsychosocial (BPS) model in a balance contemplation is the tumult of this study in an attempt to respond to prevailing disparities in caregiving services for old-aged patients on a day to day living. Caregiving services have been the medium path connecting between the patient and its prescribed medications. Moreover, caregivers serve as positive reinforcers in a patient’s environment. Therefore, caregivers play an important role in healthcare delivery to patients. They are considered significant people whom their acts will give an impact to a patient’s view in life. This research study intends to present the supreme importance of biopsychosocial assessment to old-aged patients with mental health illness and conditions. Biopsychosocial assessment will secure the quality of full medication to an old-aged adult suffering from a mental illness. This is because it offers a recognizably wholesome approach to medical healing of old-aged adult patients. The principle of biopsychosocial supersedes the biomedicine being offered to old-aged adults having mental illness, but it does not take away the high relevance of scientific biomedicine in healing patients. The framework presented an overlapping participation of each of its factors in its BPS model that affects in general a person’s health. The correlation between the biological (physiological), psychological (mental) and social (environment) in a person’s health condition requires equal attention according to BPS, and it always coexist with each other. Indisputably said, bio-medicine has been and is being in its unceasing endeavor to provide scientifically proven health care medications for every individual seeking medical treatments. As we grow older and eventually reach the other side of the median population, not only our physiological aspects change, our psychological and socio-environmental changes happen too. Caregiving is a salient responsibility taking place on these inevitable changes.

Keywords: biopsychosocial formulation, caregiving through natural approaches, US health care, BPS in caregiving, caregiving for aging population

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