Search results for: teaching report writing for innovative learning

Authors: Maria Isabel Garcia-Planas, Maria Victoria Garcia-Camba

Abstract:

Recent advances in cognitive neuroscience have allowed a step forward in perceiving the processes involved in learning from the point of view of the acquisition of new information or the modification of existing mental content. The evoked potentials technique reveals how basic brain processes interact to achieve adequate and flexible behaviours. The objective of this work, using evoked potentials, is to study if it is possible to distinguish if a patient suffers a specific type of learning disorder to decide the possible therapies to follow. The methodology used, is the analysis of the dynamics of different areas of the brain during a cognitive activity to find the relationships between the different areas analyzed in order to better understand the functioning of neural networks. Also, the latest advances in neuroscience have revealed the existence of different brain activity in the learning process that can be highlighted through the use of non-invasive, innocuous, low-cost and easy-access techniques such as, among others, the evoked potentials that can help to detect early possible neuro-developmental difficulties for their subsequent assessment and cure. From the study of the amplitudes and latencies of the evoked potentials, it is possible to detect brain alterations in the learning process specifically in dyscalculia, to achieve specific corrective measures for the application of personalized psycho pedagogical plans that allow obtaining an optimal integral development of the affected people.

Keywords: dyscalculia, neurodevelopment, evoked potentials, Learning disabilities, neural networks

Procedia PDF Downloads 122

Authors: Asim Majeed, Rehan Bhana, Mak Sharma, Rebecca Goode, Nizam Bolia, Mike Lloyd-Williams

Abstract:

This study aims to investigate and explore the underlying causes of security concerns of customers emerged when WHSmith transformed its physical system to virtualized business model through NetSuite. NetSuite is essentially fully integrated software which helps transforming the physical system to virtualized business model. Modern organisations are moving away from traditional business models to cloud based models and consequently it is expected to have a better, secure and innovative environment for customers. The vital issue of the modern age race is the security when transforming virtualized through cloud based models and designers of interactive systems often misunderstand privacy and even often ignore it, thus causing concerns for users. The content analysis approach is being used to collect the qualitative data from 120 online bloggers including TRUSTPILOT. The results and finding provide useful new insights into the nature and form of security concerns of online users after they have used the WHSmith services offered online through their website. Findings have theoretical as well as practical implications for the successful adoption of cloud computing Business-to-Business model and similar systems.

Keywords: innovation, virtualization, cloud computing, organizational flexibility

Procedia PDF Downloads 371

Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

Abstract:

Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

Procedia PDF Downloads 227

Authors: Deborah Idowu

Abstract:

This research delves into the effectiveness of explicitly teaching productive non-cognate French suffixes to English beginner learners of the French language. It is widely accepted that cognates, especially orthographic ones, can be inferred by learners from their first language (in this case, English). The same is the case for derived French words with cognate suffixes, provided the learner is familiar with the lemma, which can either be cognate or non-cognate. However, the same cannot be said for derived French words with non-cognate suffixes. These suffixes often pose challenges to learners, even when the base word is familiar to them. The primary goal of this research is to enhance the vocabulary comprehension and expansion of English-speaking beginners in French by focusing on the recognition of derived French words that may not align with their L1 knowledge. The methodology employed in this study of derivational morphology involves an experimental group receiving explicit instruction on productive non-cognate suffixes, while a control group does not. By utilizing confidence ratings and other analytical tools, the analysis aims to measure the impact of this targeted instruction on the learners' ability to understand and incorporate non-cognate suffixes into their French vocabulary. Through this experimental approach, the research seeks to provide valuable insights into how explicit instruction on non-cognate suffixes can benefit beginner French learners, ultimately aiding them in navigating the intricacies of French derivational morphology. The objectives of this research are as follows: i. to investigate the impact of explicitly teaching productive non-cognate suffixes on the vocabulary comprehension and expansion of beginner learners of the French language; ii. to assess the effectiveness of targeted instruction on non-cognate suffixes in aiding English-speaking learners in recognizing and understanding derived French words that may not align with their native language knowledge, iii. to compare the vocabulary acquisition and retention of beginner French learners who receive explicit instruction on non-cognate suffixes with those who do not to determine the effectiveness of this instructional approach, iv. to analyze the confidence ratings and other analytical methods to gauge the learners' ability to integrate non-cognate suffixes into their French vocabulary and comprehend the meaning of derived words more effectively, v. to contribute insights into how explicit instruction on non-cognate suffixes can enhance the overall language learning experience for beginner learners of French, particularly in the area of French derivational morphology.

Keywords: suffixes, derivational morphology, non-cognates, vocabulary acquisition, French language learners

Procedia PDF Downloads 14

Authors: Sally A. Brown

Abstract:

Over the last 30 years, researchers have developed models or frameworks to provide a more structured understanding of the reading comprehension process. Cognitive information processing models and social cognitive theories both provide frameworks to inform reading comprehension instruction. The purpose of this paper is to (a) provide an overview of the historical development of reading comprehension theory, (b) review the literature framed by cognitive information processing, social cognitive, and integrated reading comprehension theories, and (c) demonstrate how these frameworks inform instruction. As integrated models of reading can guide the interpretation of various factors related to student learning, an integrated framework designed by the researcher will be presented. Results indicated that features of cognitive processing and social cognitivism theory—represented in the integrated framework—highlight the importance of the role of the teacher. This model can aid teachers in not only improving reading comprehension instruction but in identifying areas of challenge for students.

Keywords: explicit instruction, integrated models of reading comprehension, reading comprehension, teacher’s role

Procedia PDF Downloads 81

Authors: Y. Kim, H. Lee, M. Park, B. Lee

Abstract:

Planning is understood as the determination of what has to be performed, how, in which sequence, when, what resources are needed, and their cost within the organization before execution. In most construction project, it is evident that the inherent nature of planning is dynamic, and initial planning is subject to be changed due to various uncertain conditions of construction project. Planners take a continuous revision process during the course of a project and until the very end of project. However, current practice lacks reliable, systematic tool for setting variance thresholds to determine when and what corrective actions to be taken. Rather it is heavily dependent on the level of experience and knowledge of the planner. Thus, this paper introduces a machine learning approach to evaluate project control threshold reliability incorporating project-specific data and presents a method to automate the process. The results have shown that the model improves the efficiency and accuracy of the monitoring process as an early warning.

Keywords: machine learning, project control, project progress monitoring, schedule

Procedia PDF Downloads 233

Authors: Eu Tteum Ha, Seyoung Kim, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

The smart home environment backed up by IoT (internet of things) technologies enables intelligent services based on the awareness of the situation a user is currently in. One of the convenient sensors for recognizing the situations within a home is the smart meter that can monitor the status of each electrical appliance in real time. This paper aims at learning a Bayesian network that models the causal relationship between the user situations and the status of the electrical appliances. Using such a network, we can infer the current situation based on the observed status of the appliances. However, learning the conditional probability tables (CPTs) of the network requires many training examples that cannot be obtained unless the user situations are closely monitored by any means. This paper proposes a method for learning the CPT entries of the network relying only on the user feedbacks generated occasionally. In our case study with a robot vacuum cleaner, the feedback comes in whenever the user gives an order to the robot adversely from its preprogrammed setting. Given a network with randomly initialized CPT entries, our proposed method uses this feedback information to adjust relevant CPT entries in the direction of increasing the probability of recognizing the desired situations. Simulation experiments show that our method can rapidly improve the recognition performance of the Bayesian network using a relatively small number of feedbacks.

Keywords: Bayesian network, IoT, learning, situation -awareness, smart home

Procedia PDF Downloads 509

Authors: Katherine O'Grady-Bray

Abstract:

For some deaf children, reading books can be a challenge. Frank Barnes School (FBS) provides guided reading time with Teachers of the Deaf, in which they read books with deaf children using a bilingual approach. The vocabulary and context of the story is explained to deaf children in BSL so they develop skills bridging English and BSL languages. However, the success of this practice is only achieved if the person is fluent in both languages. FBS piloted a scheme to convert an Oxford Reading Tree (ORT) book into an e-book that can be read using tablets. Deaf readers at FBS have access to both languages (BSL and English) during lessons and outside the classroom. The pupils receive guided reading sessions with a Teacher of the Deaf every morning, these one to one sessions give pupils the opportunity to learn how to bridge both languages e.g. how to translate English to BSL and vice versa. Generally, due to our pupils’ lack of access to incidental learning, gaining new information about the world around them is limited. This highlights the importance of quality time to scaffold their language development. In some cases, there is a shortfall of parental support at home due to poor communication skills or an unawareness of how to interact with deaf children. Some families have a limited knowledge of sign language or simply don’t have the required learning environment and strategies needed for language development with deaf children. As the majority of our pupils’ preferred language is BSL we use that to teach reading and writing English. If this is not mirrored at home, there is limited opportunity for joint reading sessions. Development of the e-Book required planning and technical development. The overall production took time as video footage needed to be shot and then edited individually for each page. There were various technical considerations such as having an appropriate background colour so not to draw attention away from the signer. Appointing a signer with the required high level of BSL was essential. The language and pace of the sign language was an important consideration as it was required to match the age and reading level of the book. When translating English text to BSL, careful consideration was given to the nonlinear nature of BSL and the differences in language structure and syntax. The e-book was produced using Apple’s ‘iBook Author’ software which allowed video footage of the signer to be embedded on pages opposite the text and illustration. This enabled BSL translation of the content of the text and inferences of the story. An interpreter was used to directly ‘voice over’ the signer rather than the actual text. The aim behind the structure and layout of the e-book is to allow parents to ‘read’ with their deaf child which helps to develop both languages. From observations, the use of e-books has given pupils confidence and motivation with their reading, developing skills bridging both BSL and English languages and more effective reading time with parents.

Keywords: bilingual book, e-book, BSL and English, bilingual e-book

Procedia PDF Downloads 157

Authors: Kien Tsong Chau, Zarina Samsudin, Wan Ahmad Jaafar Wan Yahaya

Abstract:

The paper examined the capability of a prototype of a tangible multimedia system that was augmented with tangible objects in motivating young preschoolers in learning. Preschoolers’ learning behaviour is highly captivated and motivated by external physical stimuli. Hence, conventional multimedia which solely dependent on digital visual and auditory formats for knowledge delivery could potentially place them in inappropriate state of circumstances that are frustrating, boring, or worse, impede overall learning motivations. This paper begins by discussion with the objectives of the research, followed by research questions, hypotheses, ARCS model of motivation adopted in the process of macro-design, and the research instrumentation, Persuasive Multimedia Motivational Scale was deployed for measuring the level of motivation of subjects towards the experimental tangible multimedia. At the close, a succinct description of the findings of a relevant research is provided. In the research, a total of 248 preschoolers recruited from seven Malaysian kindergartens were examined. Analyses revealed that the tangible multimedia system improved preschoolers’ learning motivation significantly more than conventional multimedia. Overall, the findings led to the conclusion that the tangible multimedia system is a motivation conducive multimedia for preschoolers.

Keywords: tangible multimedia, preschoolers, multimedia, tangible objects

Procedia PDF Downloads 595

Authors: Donald Wright

Abstract:

The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

Procedia PDF Downloads 131

Authors: Abdul Rahman Chamseddine

Abstract:

Tawfiq al-Hakim remains one of the most prominent playwrights in his native in Egypt, and in the broader Arab world. His works, at the time of their release, drew international attention and acclaim. His first 1933 masterpiece Ahl al-Kahf (The People of the Cave) especially, garnered fame and recognition in both Europe and the Arab world. Borrowing its title from the Qur’anic Sura, al-Hakim’s play relays the untold story of the life of those 'three saints' after they wake up from their prolonged sleep. The playwright’s selection of topics upon which to base his works displays a deep appreciation of Arabic and Islamic heritage. Al-Hakim was clearly influenced by Islam, to such a degree that he wrote the biography of the Prophet Muhammad in 1936 very early in his career. Knowing that Al-Hakim was preceded by many poets and creative writers in writing the Prophet Muhammad’s biography. Notably like Al-Barudi, Ahmad Shawqi, Haykal, Al-‘Aqqad, and Taha Husayn who have had their own ways in expressing their views of the Prophet Muhammad. The attempt to understand the concern of all those renaissance men and others in the person of the Prophet would be indispensable in this study. This project will examine the reasons behind al-Hakim’s choice to draw upon these particular texts, embedded as they are in the context of Arabic and Islamic heritage, and how the use of traditional texts serves his contemporary goals. The project will also analyze the image of Islam in al-Hakim’s imagination. Elsewhere, he envisions letters or conversations between God and himself, which offers a window into understanding the powerful impact of the Divine on Tawfiq al-Hakim, one that informs his literature and merits further scholarly attention. His works occupying a major rank in Arabic literature, does not reveal Al-Hakim solely but the unquestioned assumptions operative in the life of his community, its mental make-up and its attitudes. Furthermore, studying the reception of works that touch on sensitive issues, like writing a letter to God, in Al-Hakim’s historical context would be of a great significance in the process of comprehending the mentality of the Muslim community at that time.

Keywords: Arabic language, Arabic literature, Arabic theology, modern Arabic literature

Procedia PDF Downloads 338

Authors: Chen Guo, Heng Tang, Ben Niu

Abstract:

Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

Procedia PDF Downloads 123

Authors: Mohammed A. Alfayyadh, Halla A. AlAbdulhadi, Mahdi H. Almubarak

Abstract:

Purpose: Eales’ disease is an idiopathic vasculitis that affects the peripheral retina. It is characterized by recurrent vitreous hemorrhage as a complication of retinal neovascularization. It is more prevalent in India and affects young males. Here we present a patient with neovascular glaucoma as a rare first presentation of Eales’ disease. Observations: This is a 24-year-old Indian gentleman, who complained of a sudden decrease in vision in the left eye over less than 24 hours, along with frontal headache and eye pain for the last three weeks. Ocular examination revealed peripheral retinal ischemia in the right eye, very high intraocular pressure, rubeosis iridis, vitreous hemorrhage and extensive retinal ischemia in the left eye, vascular sheathing and neovascularization in both eyes. Purified protein derivative skin test was positive. The patient was managed with anti-glaucoma, intravitreal anti-vascular endothelial growth factor and laser photocoagulation. Systemic steroids and anti-tuberculous therapy were also initiated. Conclusions: Neovascular glaucoma is an infrequent complication of Eales’ disease. However, the lack of early detection of the disease in the early stages might lead to such serious complication.

Keywords: case report, Eales’ disease, mycobacterium tuberculosis, neovascular glaucoma

Procedia PDF Downloads 113

Authors: Soumaya Gharssallah Falhi, Houda Kohli Kallel

Abstract:

This article explores the emergence of prehistoric art within the Homo Sapiens species, highlighting their innovative and pioneering characteristics. It investigates the cultural, artistic, and technological advancements that define this era, aiming to understand the importance of prehistoric art in illuminating the nature of early Homo Sapiens as cultural pioneers. The study employs a qualitative approach, analyzing the connection between prehistoric art and tribal cultures to gain insights into ancient societies. By examining various theories and perspectives on art creation during this period, the research underscores the transformative impact of artistic expression on societal development. Findings reveal that prehistoric art played a significant role in portraying Homo Sapiens as innovative beings, showcasing advancements in cultural, artistic, and technological domains. It emphasizes the enduring legacy of ancient art forms in shaping modern societal norms and values. Through data gathered from archaeological findings, literary sources, and expert opinions, the study contributes to the theoretical understanding of prehistoric art as a reflection of early human societies' mindset and way of life. Overall, this research highlights the pivotal role of prehistoric art in cultural evolution and emphasizes its relevance in contemporary understandings of human creativity and progress.

Keywords: Homo sapiens, prehistoric art, cave art, the old stone age (paleolithic era)

Procedia PDF Downloads 28

Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile

Abstract:

Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.

Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection

Procedia PDF Downloads 155

Authors: Jinan Fiaidhi, Sabah Mohammed

Abstract:

Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

Procedia PDF Downloads 95

Authors: Ghada Esheba, Bayan Hafiz, Ashwaq Al-Qarni, Abdulelah AlMalki, Esraa Kaheel

Abstract:

Hydatid disease is caused by genus Echinococcus, it is transmitted to human through sheep and cattle. People who lived in an endemic area should be suspected to have the disease. Pulmonary hydatid disease can be presented by respiratory manifestations as in our case. We report a case of child, 13 years old, who was presented by shortness of breath and non-productive cough 2 months ago. The patient had an attack of hemoptysis 3 months ago but there is no history of fever, other constitutional symptoms or any medical illness. The patient has had a close contact with a horse. On examination, the patient was oriented and vitally stable. Both side of chest were moving equally with decrease air entry on the left side of the chest. Cervical lymph node enlargement was also detected. The case was provisionally diagnosed as tuberculosis. The x-ray was normal, while CT scan showed two cysts in the left side. The patient was treated surgically with resection of both cysts without lobectomy. Broncho-alveolar lavage was done and together with plural effusion and both cysts were sent for histopathology. The patient received the following medication: albendazole 200MG/BID/Orally for 30 days and Cefuroxime 250MG/Q12H/Orally for 10 days.

Keywords: Echinococcus granulosus, hydatid disease, pediatrics, pulmonary hydatid cyst

Procedia PDF Downloads 260

Authors: N. Mesatywa

Abstract:

The aim of the article is to emphasize and motivate for the role of integrating cultures in institutions of learning. The article has used a literature review methodology. Findings indicate that cultures espouse immense social capital that can: facilitate and strengthen moral education that will help learners in mitigating moral decadence and HIV/AIDS; embrace and strengthen the tenets of peace and tranquility among learners from different backgrounds; can form education against xenophobia; can facilitate the process of cultural paradigm shift that will slow down cultural attrition and decadence; can bring back cultural strength, cultural revival, cultural reawakening and cultural emancipation, etc. The article recommends governments to finance cultural activities in institutions of learning; to allow cultural practitioners to be part and parcel of cultural education; and challenge people to pride in the social capital of their indigenous cultures.

Keywords: cultures, cultural practitioners, integration, traditional healers

Procedia PDF Downloads 444

Authors: Renukswamy Chikkamath, Vishvapalsinhji Ramsinh Parmar, Christoph Hewel, Markus Endres

Abstract:

Given a patent document, identifying distinct semantic annotations is an interesting research aspect. Text annotation helps the patent practitioners such as examiners and patent attorneys to quickly identify the key arguments of any invention, successively providing a timely marking of a patent text. In the process of manual patent analysis, to attain better readability, recognising the semantic information by marking paragraphs is in practice. This semantic annotation process is laborious and time-consuming. To alleviate such a problem, we proposed a dataset to train machine learning algorithms to automate the highlighting process. The contributions of this work are: i) we developed a multi-class dataset of size 150k samples by traversing USPTO patents over a decade, ii) articulated statistics and distributions of data using imperative exploratory data analysis, iii) baseline Machine Learning models are developed to utilize the dataset to address patent paragraph highlighting task, and iv) future path to extend this work using Deep Learning and domain-specific pre-trained language models to develop a tool to highlight is provided. This work assists patent practitioners in highlighting semantic information automatically and aids in creating a sustainable and efficient patent analysis using the aptitude of machine learning.

Keywords: machine learning, patents, patent sentiment analysis, patent information retrieval

Procedia PDF Downloads 75

Authors: Christopher Celozzi, Sarah Kochav

Abstract:

Our research investigates the numerous challenges faced by Chinese ESL university students enrolled in the medical and related healthcare professional fields. The over-arching research question is how gender influences classroom participation and learning. The second research question addressed is 'what instructional strategies may be utilized to promote student participation and language acquisition?'. Participants’ language ability has been assessed and evaluated in order to facilitate the establishment of a statistical baseline for the subsequent intervention. This research delves deeper into each individual’s personal and academic circumstances, in an effort to reveal any held intrinsic gender beliefs and social identities that may influence learning. Also considered is the impact on learning for a homogenized student population within a uniform, highly structured learning environment. Specially, what is the influence of China’s ‘one-child policy’ on individual learning habits? The impact of their millennial identity and reliance on social media is also examined. A qualitative methodology with a case study approach is employed, with interviews conducted among the participants. Student response to the intervention and selected remediation strategies are documented, analyzed and discussed. The findings of the study may serve to inform educator instructional practice, while advancing the student learner in their pursuit of English competency in highly competitive professions.

Keywords: Chinese students, gender, English, language acquisition

Procedia PDF Downloads 192

Authors: Natalia Kartushina

Abstract:

Foreign (second) language (L2) learning is highly promoted in modern society. Students are encouraged to study abroad (SA) to achieve the most effective learning outcomes. However, L2 learning has side effects for native language (L1) production, as L1 sounds might show a drift from the L1 norms towards those of the L2, and this, even after a short period of L2 learning. L1 assimilatory drift has been attributed to a strong perceptual association between similar L1 and L2 sounds in the mind of L2 leaners; thus, a change in the production of an L2 target leads to the change in the production of the related L1 sound. However, nowadays, it is quite common that speakers acquire two languages from birth, as, for example, it is the case for many bilingual communities (e.g., Basque and Spanish in the Basque Country). Yet, it remains to be established how FL learning affects native production in individuals who have two native languages, i.e., in simultaneous or very early bilinguals. Does FL learning (here a third language, L3) affect bilinguals’ both languages or only one? What factors determine which of the bilinguals’ languages is more susceptible to change? The current study examines the effects of L3 (English) learning on the production of vowels in the two native languages of simultaneous Spanish-Basque bilingual adolescents enrolled into the Erasmus SA English program. Ten bilingual speakers read five Spanish and Basque consonant-vowel-consonant-vowel words two months before their SA and the next day after their arrival back to Spain. Each word contained the target vowel in the stressed syllable and was repeated five times. Acoustic analyses measuring vowel openness (F1) and backness (F2) were performed. Two possible outcomes were considered. First, we predicted that L3 learning would affect the production of only one language and this would be the language that would be used the most in contact with English during the SA period. This prediction stems from the results of recent studies showing that early bilinguals have separate phonological systems for each of their languages; and that late FL learner (as it is the case of our participants), who tend to use their L1 in language-mixing contexts, have more L2-accented L1 speech. The second possibility stated that L3 learning would affect both of the bilinguals’ languages in line with the studies showing that bilinguals’ L1 and L2 phonologies interact and constantly co-influence each other. The results revealed that speakers who used both languages equally often (balanced users) showed an F1 drift in both languages toward the F1 of the English vowel space. Unbalanced speakers, however, showed a drift only in the less used language. The results are discussed in light of recent studies suggesting that the amount of language use is a strong predictor of the authenticity in speech production with less language use leading to more foreign-accented speech and, eventually, to language attrition.

Keywords: language-contact, multilingualism, phonetic drift, bilinguals' production

Procedia PDF Downloads 96

Authors: Calassandra Nwokoro

Abstract:

Introduction: The nursing profession requires a lot of commitment, effort, and time to efficiently manage patients and provide them quality healthcare services, this work load may eventually cause the nurses to become burned out and experience psychological distress. This study assessed the prevalence of burnout, risk factors, and the coping strategies among nurses working in Lagos University Teaching Hospital (LUTH), Lagos state, Nigeria. Methodology: A descriptive cross-sectional study design was conducted among 308 nurses working in LUTH. Simple random sampling was used in selection of study respondents. The questionnaire comprised three parts; the sociodemographic characteristics of the respondents, the extent of burnout syndrome using the Maslach Burnout Inventory, and the coping strategies used among the respondents using the BRIEF-COPE Inventory. Results: This study revealed relatively high levels of burnout among the nurses in LUTH with a prevalence of 16.9%, 31.2% and 20.1% for high emotional exhaustion, high depersonalization and reduced professional accomplishment respectively. It also showed that burnout was significantly associated with long working hours. Religion was found to be the most commonly used coping strategy overall, while emotional support was the most frequently used coping strategy among nurses who had burnout. Conclusion: This study has revealed a relatively high prevalence of burnout among the nurses in Lagos University Teaching Hospital. In order to minimize the negative health impacts of burnout, the government should collaborate with psychologists and psychiatrists to implement regular stress management and stress inoculation programs for nurses and other health professionals in the country.

Keywords: burnout, nurses, coping strategies, healthcare

Procedia PDF Downloads 61

Authors: Jay-R M. Mendoza

Abstract:

In almost all mathematics classrooms, students demonstrated discrepancies in their knowledge, skills, and understanding. OECD reports predicted that this continued to aggravate as not all teachers were sufficiently trained to handle this concentration. In response, the paper explored the potential of reSolve’s professional learning module 3 (PLM3) as an affordable and accessible professional development (PD) resource. Participants’ hands-on experience and exposure to PLM3 were audio recorded. After it was transcribed and examined and their work samples were analysed, there were four issues emerged: (1) criticality of conducting preliminary data collections and increasing the validity of inferences about what students can and cannot do by addressing the probabilistic nature of their performance; (2) criticality of the conclusion: a > b and/or (a-b) ∈ Z⁺ among students’ algebraic reasoning; (3) enabling and extending prompts provided by reSolve were found useful; and (4) dynamic adaptation of reSolve PLM3 through developing transferable skills and collaboration among teachers. PLM3 provided valuable insights on assessment, teaching, and planning to include all students in mathematics experiences.

Keywords: algebraic reasoning, building teacher capacity, including all students in mathematics experiences, professional development

Procedia PDF Downloads 108

Authors: Mohammed Zahid Akter

Abstract:

In the studies of language change, mental factors including analogy, reanalysis, and frequency have received considerable attention as possible catalysts for language change. In comparison, relatively little is known regarding which functional domains or construction types are more amenable to these mental factors than others. In this regard, this paper will show with data from South Central (Kuki-Chin) Tibeto-Burman languages how language change interacts with certain functional domains or construction types. These construction types include transitivity, person marking, and polarity distinctions. Thus, it will be shown that transitive clauses are more prone to change than intransitive and ditransitive clauses, clauses with 1st person argument marking are more prone to change than clauses with 2nd and 3rd person argument marking, non-copular clauses are more prone to change than copular clauses, affirmative clauses are more prone to change than negative clauses, and standard negatives are more prone to change than negative imperatives. The following schematic structure can summarize these findings: transitive>intransitive, ditransitive; 1st person>2nd person, 3rd person; non-copular>copular; and affirmative>negative; and standard negative>negative imperatives. In the interest of space, here only one of these findings is illustrated: affirmative>negative. In Hyow (South Central, Bangladesh), the innovative and preverbal 1st person subject k(V)- occurs in an affirmative construction, and the archaic and postverbal 1st person subject -ŋ occurs in a negative construction. Similarly, in Purum (South Central, Northeast India), the innovative and preverbal 1st person subject k(V)- occurs in an affirmative construction, and the archaic and postverbal 1st person subject *-ŋ occurs in a negative construction. Like 1st person subject, we also see that in Anal (South Central, Northeast India), the innovative and preverbal 2nd person subject V- occurs in an affirmative construction, and the archaic and postverbal 2nd person subject -t(V) in a negative construction. To conclude, data from South Central Tibeto-Burman languages suggest that language change interacts with functional domains as some construction types are more susceptible to change than others.

Keywords: functional domains, Kuki-Chin, language change, south-central, Tibeto-Burman

Procedia PDF Downloads 54

Authors: Shuai Zhao, Shalendra D. Sharma, Jin Xu

Abstract:

This research uses advanced machine learning models to learn a number of hypotheses regarding political executives. Specifically, it analyses the impact these powerful leaders have on economic growth by using leaders’ data from the Archigos database from 1835 to the end of 2015. The data is processed by the AutoGluon, which was developed by Amazon. Automated Machine Learning (AutoML) and AutoGluon can automatically extract features from the data and then use multiple classifiers to train the data. Use a linear regression model and classification model to establish the relationship between leaders and economic growth (GDP per capita growth), and to clarify the relationship between their characteristics and economic growth from a machine learning perspective. Our work may show as a model or signal for collaboration between the fields of statistics and artificial intelligence (AI) that can light up the way for political researchers and economists.

Keywords: comparative politics, political executives, leaders’ characteristics, artificial intelligence

Procedia PDF Downloads 72

Authors: Afsha Shaikh, Mohammed Azizur Rahman, Ibrahim Hassan, Mayur Pal

Abstract:

Student engagement in learning is instantly affected by the sources of learning methods available for them, such as videos showing the applications of the concept or showing a practical demonstration. Specific to the engineering discipline, there exist enormous challenging concepts that can be simplified when they are connected to real-world scenarios. For this study, the concept of heat exchangers was used as it is a part of multidisciplinary engineering fields. To make the learning experience enjoyable and impactful, 3-D printed heat exchanger models were created for students to use while working on in-class activities and assignments. Students were encouraged to use the 3-D printed heat exchanger models to enhance their understanding of theoretical concepts associated with its applications. To assess the effectiveness of the method, feedback was received by students pursuing undergraduate engineering via an anonymous electronic survey. To make the feedback more realistic, unbiased, and genuine, students spent nearly two to three weeks using the models in their in-class assignments. The impact of these tools on their learning was assessed through their performance in their ungraded assignments as well as their interactive discussions with peers. ‘Having to apply the theory learned in class whilst discussing with peers on a class assignment creates a relaxed and stress-free learning environment in classrooms’; this feedback was received by more than half the students who took the survey and found 3-D models of heat exchanger very easy to use. Amongst many ways to enhance learning and make students more engaged through interactive models, this study sheds light on the importance of physical tools that help create a lasting mental representation in the minds of students. Moreover, in this technologically enhanced era, the concept of augmented reality was considered in this research. E-drawings application was recommended to enhance the vision of engineering students so they can see multiple views of the detailed 3-D models and cut through its different sides and angles to visualize it properly. E-drawings could be the next tool to implement in classrooms to enhance students’ understanding of engineering concepts.

Keywords: student engagement, life-long-learning, visual demonstration, 3-D printed models, engineering education

Procedia PDF Downloads 100

Authors: Hasan Coruk, Recep Cakir

Abstract:

This study aimed at investigating the effect of multimedia containing ‘the structure and properties of matter’ unit on students’ academic achievement level and self-efficacy relating to science and technology course. The study used an experimental design with pre-test and post-test groups. The data collection tools were ‘Science and Technology Course Achievement Test’ and ‘Science and Technology Self-Efficacy Scale’. The sample of the study consisted of 8th grade students at a primary school in Tokat Province. The study was carried out with 42 students from two classes, 21 (8 males, 13 females) from experimental group and 21 (13 males and 8 females) from control group. The data were analyzed in SPSS.18 software. The findings of the study indicated that the use of multimedia increased the students’ academic achievement in science and technology course in comparison with traditional teaching methods. It was also determined that there was not a significant difference in students’ course-oriented self-efficacy levels regarding the two methods. Necessary and feasible suggestions were put forward for whom it concerns.

Keywords: multimedia learning, science and technology, the structure-properties of matter, self-efficacy, academic achievement

Procedia PDF Downloads 439

Authors: Patrick Ebong Ebewo

Abstract:

The trend of high unemployment levels globally is a growing concern, which suggests that university students especially those studying the creative industries are most likely to face unemployment upon completion of their studies. Therefore the effort of university in fostering entrepreneurial knowledge is equally important to the development of student’s soft skill. The purpose of this paper is to assess the significance of perceived university environment and perceived educational support that influencing University students’ intention in starting their own business in the future. Thus, attempting to answer the question 'How does perceived university environment affect students’ attitude towards entrepreneurship as a career option, perceived entrepreneurial abilities, subjective norm and entrepreneurial intentions?' The study is based on the Theory of Planned Behaviour model adapted from previous studies and empirically tested on graduates at the Tshwane University of Technology. A sample of 150 graduates from the Arts and Design graduates took part in the study and data collected were analysed using structural equation modelling (SEM). Our findings seem to suggest the indirect impact of perceived university environment on entrepreneurial intention through perceived environment support and perceived entrepreneurial abilities. Thus, any increase in perceived university environment might influence students to become entrepreneurs. Based on these results, it is recommended that: (a) Tshwane University of Technology and other universities of technology should establish an ‘Entrepreneurship Internship Programme’ as a tool for stimulated work integrated learning. Post-graduation intervention could be implemented by the development of a ‘Graduate Entrepreneurship Program’ which should be embedded in the Bachelor of Technology (B-Tech now Advance Diploma) and Postgraduate courses; (b) Policymakers should consider the development of a coherent national policy framework that addresses entrepreneurship for the Arts/creative industries sector. This would create the enabling environment for the evolution of Higher Education Institutions from merely Teaching, Learning & Research to becoming drivers for creative entrepreneurship.

Keywords: business venture, entrepreneurship education, entrepreneurial intent, university environment

Procedia PDF Downloads 320

Authors: Zahid Ullah, Atlas Khan

Abstract:

The rapid growth of data in diverse domains has created an urgent need for effective utilization of mathematical and statistical sciences in data analytics. This abstract explores the journey from theory to practice, emphasizing the importance of harnessing mathematical and statistical innovations to unlock the full potential of data analytics. Drawing on a comprehensive review of existing literature and research, this study investigates the fundamental theories and principles underpinning mathematical and statistical sciences in the context of data analytics. It delves into key mathematical concepts such as optimization, probability theory, statistical modeling, and machine learning algorithms, highlighting their significance in analyzing and extracting insights from complex datasets. Moreover, this abstract sheds light on the practical applications of mathematical and statistical sciences in real-world data analytics scenarios. Through case studies and examples, it showcases how mathematical and statistical innovations are being applied to tackle challenges in various fields such as finance, healthcare, marketing, and social sciences. These applications demonstrate the transformative power of mathematical and statistical sciences in data-driven decision-making. The abstract also emphasizes the importance of interdisciplinary collaboration, as it recognizes the synergy between mathematical and statistical sciences and other domains such as computer science, information technology, and domain-specific knowledge. Collaborative efforts enable the development of innovative methodologies and tools that bridge the gap between theory and practice, ultimately enhancing the effectiveness of data analytics. Furthermore, ethical considerations surrounding data analytics, including privacy, bias, and fairness, are addressed within the abstract. It underscores the need for responsible and transparent practices in data analytics, and highlights the role of mathematical and statistical sciences in ensuring ethical data handling and analysis. In conclusion, this abstract highlights the journey from theory to practice in harnessing mathematical and statistical sciences in data analytics. It showcases the practical applications of these sciences, the importance of interdisciplinary collaboration, and the need for ethical considerations. By bridging the gap between theory and practice, mathematical and statistical sciences contribute to unlocking the full potential of data analytics, empowering organizations and decision-makers with valuable insights for informed decision-making.

Keywords: data analytics, mathematical sciences, optimization, machine learning, interdisciplinary collaboration, practical applications

Procedia PDF Downloads 75

Authors: Sadixa Sanjel, Ahmed Sadek, Naseef Mansoor, Zelalem Denekew

Abstract:

Collegiate ice hockey (NCAA) sports analytics is different from the national level hockey (NHL). We apply and compare multiple machine learning models such as Linear Regression, Random Forest, and Neural Networks to predict the win ratio for a team based on their statistics. Data exploration helps determine which statistics are most useful in increasing the win ratio, which would be beneficial to coaches and team managers. We ran experiments to select the best model and chose Random Forest as the best performing. We conclude with how to bridge the gap between the college and national levels of sports analytics and the use of machine learning to enhance team performance despite not having a lot of metrics or budget for automatic tracking.

Keywords: NCAA, NHL, sports analytics, random forest, regression, neural networks, game predictions

Procedia PDF Downloads 102