Search results for: machine learning techniques

Authors: Ahmed Amin Mousa, M. Abd El-Salam

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This study discusses a simple solution for the problem of shortage in learning resources for kindergarten teachers. Occasionally, kindergarten teachers cannot access proper resources by usual search methods as libraries or search engines. Furthermore, these methods require a long time and efforts for preparing. The study is expected to facilitate accessing learning resources. Moreover, it suggests a potential direction for using QR code inside the classroom. The present work proposes that QR code can be used for digitizing kindergarten curriculums and accessing various learning resources. It investigates using QR code for saving information related to the concepts which kindergarten teachers use in the current educational situation. The researchers have established a guide for kindergarten teachers based on the Egyptian official curriculum. The guide provides different learning resources for each scientific and mathematical concept in the curriculum, and each learning resource is represented as a QR code image that contains its URL. Therefore, kindergarten teachers can use smartphone applications for reading QR codes and displaying the related learning resources for students immediately. The guide has been provided to a group of 108 teachers for using inside their classrooms. The results showed that the teachers approved the guide, and gave a good response.

Keywords: kindergarten, child, learning resources, QR code, smart phone, mobile

Procedia PDF Downloads 289

Authors: Shreyansh Singh, Afroz Ahmed

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Sentiment Analysis intends to naturally reveal the hidden mentality that we hold towards an entity. The total of this assumption over a populace addresses sentiment surveying and has various applications. Current text-based sentiment analysis depends on the development of word embeddings and Machine Learning models that take in conclusion from enormous text corpora. Sentiment Analysis from text is presently generally utilized for consumer loyalty appraisal and brand insight investigation. With the expansion of online media, multimodal assessment investigation is set to carry new freedoms with the appearance of integral information streams for improving and going past text-based feeling examination using the new transforms methods. Since supposition can be distinguished through compelling follows it leaves, like facial and vocal presentations, multimodal opinion investigation offers good roads for examining facial and vocal articulations notwithstanding the record or printed content. These methodologies use the Recurrent Neural Networks (RNNs) with the LSTM modes to increase their performance. In this study, we characterize feeling and the issue of multimodal assessment investigation and audit ongoing advancements in multimodal notion examination in various spaces, including spoken surveys, pictures, video websites, human-machine, and human-human connections. Difficulties and chances of this arising field are additionally examined, promoting our theory that multimodal feeling investigation holds critical undiscovered potential.

Keywords: sentiment analysis, RNN, LSTM, word embeddings

Procedia PDF Downloads 119

Authors: Molakala Mourya Vardhan Reddy, Kandimala Revanth, Koduru Sumanth, Beena B. M.

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Emergency response and recovery operations are severely hampered by natural catastrophes, especially floods. Understanding post-flood scenarios is essential to disaster management because it facilitates quick evaluation and decision-making. To this end, we introduce FloodNet, a brand-new high-resolution aerial picture collection created especially for comprehending post-flood scenes. A varied collection of excellent aerial photos taken during and after flood occurrences make up FloodNet, which offers comprehensive representations of flooded landscapes, damaged infrastructure, and changed topographies. The dataset provides a thorough resource for training and assessing computer vision models designed to handle the complexity of post-flood scenarios, including a variety of environmental conditions and geographic regions. Pixel-level semantic segmentation masks are used to label the pictures in FloodNet, allowing for a more detailed examination of flood-related characteristics, including debris, water bodies, and damaged structures. Furthermore, temporal and positional metadata improve the dataset's usefulness for longitudinal research and spatiotemporal analysis. For activities like flood extent mapping, damage assessment, and infrastructure recovery projection, we provide baseline standards and evaluation metrics to promote research and development in the field of post-flood scene comprehension. By integrating FloodNet into machine learning pipelines, it will be easier to create reliable algorithms that will help politicians, urban planners, and first responders make choices both before and after floods. The goal of the FloodNet dataset is to support advances in computer vision, remote sensing, and disaster response technologies by providing a useful resource for researchers. FloodNet helps to create creative solutions for boosting communities' resilience in the face of natural catastrophes by tackling the particular problems presented by post-flood situations.

Keywords: image classification, segmentation, computer vision, nature disaster, unmanned arial vehicle(UAV), machine learning.

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Authors: Edu Marcelina, Sule Sheidu A., Nsor Eunice

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As open and distance education is gradually becoming an acceptable means of solving the problem of access in higher education, quality has now become one of the main concerns among institutions and stakeholders of open and distance learning (ODL) and the education sector in general. This study assessed the challenges of academic quality in the open and distance learning (ODL) education in Nigeria using Distance Learning Institute (DLI), University of Lagos and National Open University of Nigeria as a case. In carrying out the study, a descriptive survey research design was employed. A researcher-designed and validated questionnaire was used to elicit responses that translated to the quantitative data for this study. The sample comprised 665 students of the Distance Learning Institute (DLI), and National Open University of Nigeria (NOUN), carefully selected through the method of simple random sampling. Data collected from the study were analyzed using Chi-Square (X2) at 0.05 Level of significance. The results of the analysis revealed that; the use of ICT tools is a factor in ensuring quality in the Open and Distance Learning (ODL) operations; the quality of the materials made available to ODL students will determine the quality of education that will be received by the students; and the time scheduled for students for self-study, online lecturing/interaction and face to face study and the quality of education in Open and Distance Learning Institutions has a lot of impact on the quality of education the students receive. Based on the findings, a number of recommendations were made.

Keywords: open and distance learning, quality, ICT, face-to-face interaction

Procedia PDF Downloads 377

Authors: Abdelaziz Hussien

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This article reports investigations of a study into the effectiveness of a traits cooperative learning (TCL) on teacher candidates’ writing achievement, composition, and attitudes towards traits of writing approach and small group learning. Mixed methodologies were used with the participants in a repeated measures quasi-experimental design. Forty-two class teacher candidates, enrolled in the Bahrain Teachers College, completed the pre and post author-developed measures. The results suggest that TCL has a positive effect on the participants’ writing achievement, composition, and attitudes towards traits of writing approach, but not on the attitudes towards small group learning. Further implications to teacher education are presented.

Keywords: trait-based language education, cooperative learning, writing achievement, writing composition, traits of writing, teacher education

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Authors: Zhikang Rong

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The 4th industrial revolution has introduced technologies like interconnectivity, machine learning, and real-time big data analytics that improve operations and business efficiency. This paper examines how these advancements have led to a concentration of wealth, specifically among the top 1%, and investigates whether this wealth provides value to society. Through analyzing impacts on employment, productivity, supply-demand dynamics, and potential externalities, it is shown that successful businesspeople, by enhancing productivity and creating jobs, contribute positively to long-term economic growth. Additionally, externalities such as environmental degradation are managed by social entrepreneurship and government policies.

Keywords: wealth creation, employment, productivity, social entrepreneurship

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Authors: Chul Lee, Seoae Cho, Erich D. Jarvis, Heebal Kim

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Vocal learning, the ability to imitate vocalizations based on auditory experience, is a homoplastic character state observed in different independent lineages of animals such as songbirds, parrots, hummingbirds and human. It has now become possible to perform genome-wide molecular analyses across vocal learners and vocal non-learners with the recent expansion of avian genome data. It was analyzed the whole genomes of human and 48 avian species including those belonging to the three avian vocal learning lineages, to determine if behavior and neural convergence are associated with molecular convergence in divergent species of vocal learners. Analyses of 8295 orthologous genes across bird species revealed 141 genes with amino acid substitutions specific to vocal learners. Out of these, 25 genes have vocal learner specific genetic homoplasies, and their functions were enriched for learning. Several sites in these genes are estimated under convergent evolution and positive selection. A potential role for a subset of these genes in vocal learning was supported by associations with gene expression profiles in vocal learning brain regions of songbirds and human disease that cause language dysfunctions. The key candidate gene with multiple independent lines of the evidences specific to vocal learners was DRD5. Our findings suggest cAMP-based learning pathway in avian vocal learners, indicating molecular homoplastic changes associated with a complex behavioral trait, vocal learning.

Keywords: amino acid substitutions, convergent evolution, positive selection, vocal learning

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Authors: Sabo Elizabeth

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Electronic learning is increasingly popular learning approach in higher educational institutions due to vast growth of internet technology. This approach is important in human capital development. An investigation of open distance and e-learning facilities and information need by open and distance learning students was carried out in Jalingo, Nigeria. Structured questionnaires were administered to 70 registered ODL students of the NOUN. Information sourced from the respondents covered demographic, economic and institutional variables. Data collected for demographic variables were computed as frequency count and percentages. Assessment of the effectiveness of ODL facilities and information need among open and distance learning students was computed on a three or four point Likert Rating Scale. Findings indicated that there are more men compared to women. A large proportion of the respondents are married and there are more matured students in ODL compared to the youth. A high proportion of the ODL students obtained qualifications higher than the secondary school certificate. The proportion of computer literate ODL students was high, and large number of the students does not own a laptop computer. Inadequate e -books and reference materials, internet gadgets and inadequate books (hard copies) and reference material are factors that limit utilization of e-learning facilities in the study areas. Inadequate computer facilities and power back up caused inconveniences and delay in administering and use of e learning facilities. To a high extent, open and distance learning students needed information on university time table and schedule of activities, availability and access to books (hard and e-books) and reference materials. The respondents emphasized that contact with course coordinators via internet will provide a better learning and academic performance.

Keywords: open and distance learning, information required, electronic books, internet gadgets, Likert scale test

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Authors: Yahia A. M. AlKhoudary

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This Study presents the outcome of an investigation to evaluate the importance of autonomous learning as a means of motivation. However, very little research done in this field. Thus, the aims of this study are to ascertain the needs of the learners and to investigate their attitudes and motivation towards the mode of learning. Various suggestions made on how to improve learners’ participation in the learning process. A survey conducted on a sample group of 60 Omani College students. Self-report questionnaires and retrospective interviews conducted to find out their material-type preferences in a self-access learning context. Achieving autonomous learning system, which learners is one of the Ministry of Education goals in the Sultanate of Oman. As a result, this study presents the outcome of an investigation to evaluate the students’ performance in English as a Foreign Language (EFL). It focuses on the effect of autonomous learning that encourages students to learn English, a research conducted at Buraimi city, the Sultanate of Oman. The procedure of this investigation based on four dimensions: (1) sixty students are selected and divided into two groups, (2) pre and posttest projects are given to them, and (3) questionnaires are administered to both students who are involved in the experiment and 50 teachers (25 males and 25 females) to collect accurate data, (4) an interview with students and teachers to find out their attitude towards autonomous learning. Analysis of participants’ responses indicated that autonomous learning motivates students to learn English independently and increase the intrinsic rather than extrinsic motivation to improve their English language as a long-life active learning. The findings of this study show that autonomous learning approach is the best remedy to empower the students’ skills and overcome all relevant difficulties. They also show that secondary school teachers can fully rely on this learning approach that encourages language learners to monitor their progress, increase both learners and teachers’ motivation and ameliorate students’ behavior in the classroom. This approach is also an ongoing process, which takes time, patience and support to be lifelong learning.

Keywords: Omani, autonomous learning system, English as a Foreign Language (EFL), learning approach

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Authors: Z. Tasir, S. N. Kew, D. West, Z. Abdullah, D. Toohey

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Research on Learning Analytics is progressively developing in the higher education field by concentrating on the process of students' learning. Therefore, a research project between Malaysian and Australian Universities was initiated in 2015 to look at the use of Learning Analytics to support the development of teaching practice. The focal point of this article is to discuss and share the experiences of Malaysian and Australian universities in the process of developing the collaborative research on Learning Analytics. Three aspects of this will be discussed: 1) Establishing an international research project and team members, 2) cross-cultural understandings, and 3) ways of working in relation to the practicalities of the project. This article is intended to benefit other researchers by highlighting the challenges as well as the strategies used in this project to ensure such collaborative research succeeds.

Keywords: academic research project, collaborative research, cross-cultural understanding, international research project

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Authors: Juvanie C. Lapesigue

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Worldwide school closures result from a significant public health crisis that has affected the nation and the entire world. It has affected students, educators, educational organizations globally, and many other aspects of society. Academic institutions worldwide teach students using diverse approaches of various learning delivery modes. This paper investigates the competence and performance of physical education teachers using various learning delivery modes, including Distance learning, Blended Learning, and Homeschooling during online distance education. To identify the Gap between their age generation using various learning delivery that affects teachers' preparation for distance learning and evaluates how these modalities impact teachers’ competence and performance in the case of a pandemic. The respondents were the Senior High School teachers of the Department of Education who taught in Davao City before and during the pandemic. Purposive sampling was utilized on 61 Senior High School Teachers in Davao City Philippines. The result indicated that teaching performance based on pedagogy and assessment has significantly affected teaching performance in teaching physical education, particularly those Non-PE teachers teaching physical education subjects. It should be supplied with enhancement training workshops to help them be more successful in preparation in terms of teaching pedagogy and assessment in the following norm. Hence, a proposed unique training design for non-P.E. Teachers has been created to improve the teachers’ performance in terms of pedagogy and assessment in teaching P.E subjects in various learning delivery modes in the next normal.

Keywords: distance learning, learning delivery modes, P.E teachers, senior high school, teaching competence, teaching performance

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Authors: Ameema Mahroof, Muhammad Saeed

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Purpose: The paper aimed to explore the problems faced by the faculty in a distant and online learning environment. It proposes the remedies of the problems faced by the teachers. In distant and online learning mode, the methods of student assessment are different than traditional learning mode. In this paper, the assessment strategies of these learning modes are identified, and the challenges faced by the teachers regarding these assessment methods are explored. Design/Methodology/Approach: The study is qualitative and opted for an exploratory study, including eight interviews with faculty of distant and online universities. The data for this small scale study was gathered using semi-structured interviews. Findings: Findings of the study revealed that assignment and tests are the most effective way of assessment in these modes. It further showed that less student-teacher interaction, plagiarized assignments, passive students, less time for marking are the main challenges faced by the teachers in these modes. Research Limitations: Because of the chosen research approach, the study might not be able to provide generalizable results. That’s why it is recommended to do further studies on this topic. Practical Implications: The paper includes implications for the better assessment system in online and distant learning mode. Originality/Value: This paper fulfills an identified need to study the challenges and problems faced by the teachers regarding student assessment.

Keywords: online learning, distant learning, student assessment, assignments

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Authors: Sneha Leslie

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The current situation in the cyber world is that crimes performed by Botnets are increasing and the masterminds (botmaster) are not detectable easily. The botmaster in the botnet compromises the legitimate host machines in the network and make them bots or zombies to initiate the cyber-attacks. This paper will focus on the live detection of the botmaster in the network by using the strong framework 'metasploit', when distributed denial of service (DDOS) attack is performed by the botnet. The affected victim machine will be continuously monitoring its incoming packets. Once the victim machine gets to know about the excessive count of packets from any IP, that particular IP is noted and details of the noted systems are gathered. Using the vulnerabilities present in the zombie machines (already compromised by botmaster), the victim machine will compromise them. By gaining access to the compromised systems, applications are run remotely. By analyzing the incoming packets of the zombies, the victim comes to know the address of the botmaster. This is an effective and a simple system where no specific features of communication protocol are considered.

Keywords: bonet, DDoS attack, network security, detection system, metasploit framework

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Authors: Ravi Vishwanath, Saumya Kumaar, S. N. Omkar

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Brain-computer interfacing (BCI) is a technology that is almost four decades old, and it was developed solely for the purpose of developing and enhancing the impact of neuroprosthetics. However, in the recent times, with the commercialization of non-invasive electroencephalogram (EEG) headsets, the technology has seen a wide variety of applications like home automation, wheelchair control, vehicle steering, etc. One of the latest developed applications is the mind-controlled quadrotor unmanned aerial vehicle. These applications, however, do not require a very high-speed response and give satisfactory results when standard classification methods like Support Vector Machine (SVM) and Multi-Layer Perceptron (MLPC). Issues are faced when there is a requirement for high-speed control in the case of fixed-wing unmanned aerial vehicles where such methods are rendered unreliable due to the low speed of classification. Such an application requires the system to classify data at high speeds in order to retain the controllability of the vehicle. This paper proposes a novel method of classification which uses a combination of Common Spatial Paradigm and Linear Discriminant Analysis that provides an improved classification accuracy in real time. A non-linear SVM based classification technique has also been discussed. Further, this paper discusses the implementation of the proposed method on a fixed-wing and VTOL unmanned aerial vehicles.

Keywords: brain-computer interface, classification, machine learning, unmanned aerial vehicles

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Authors: Vine Petzer, Mirna Nel

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An explanatory mixed method design was used to investigate accounting classroom conditions in the Further Education and Training (FET) Phase in South Africa. A descriptive survey research study with a heterogeneous group of learners and teachers was conducted in the first phase. In the qualitative phase, semi-structured individual interviews with learners and teachers, as well as observations in the accounting classroom, were employed to gain more in depth understanding of the learning conditions in the accounting classroom. The findings of the empirical research informed the development of a model for teachers in accounting, supporting them to use more effective teaching methods and create positive learning conditions for all learners to experience successful learning. A model towards creating positive Accounting classroom conditions that support successful learning was developed and recommended for education policy and decision-makers for use as a classroom intervention capacity building tool. The model identifies and delineates classroom practices that exert significant effect on learner attainment of quality education.

Keywords: accounting classroom conditions, positive education, successful learning, teaching accounting

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Authors: Majid Zargar, Frank Bullen, Ron Ayers

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One of the important factors in the design of asphalt concrete mixes is the accurate measurement of air voids and their variable distribution. Both can have significant impact on long and short term fatigue and creep behaviour under traffic. While some simple methods exist for overall evaluation of air voids, measuring air void distribution in asphalt concrete is very complex, involving expensive techniques such as X-ray methodologies. The research reported in the paper investigated the use of non-destructive ultrasonic techniques as an alternative to estimate the amount of air voids and their distribution within asphalt samples. Seventy-four Standard AC–14 asphalt samples made with three types of bitumen; Multigrade, PMB and C320 were analysed using ultrasonic techniques. The results have illustrated that ultrasonic testing has the potential of being a rapid, accurate and cost-effective method of estimating air void distribution in asphalt.

Keywords: asphalt concrete, air voids, ultrasonic, mechanical behaviour

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Authors: Giovanni Gonzalez Araujo, Michael Kyrilov, Angelo Kyrilov

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STEAMplug is a web-based innovative educational platform which makes teaching easier and learning more effective. It requires no setup, eliminating the barriers to entry, allowing students to focus on their learning throughreal-world development environments. The student-centric tools enable easy collaboration between peers and teachers. Analyzing user interactions with the system enables us to predict student performance and identify at-risk students, allowing early instructor intervention.

Keywords: plagiarism detection, identifying at-Risk Students, education technology, e-learning system, collaborative development, learning and teaching with technology

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Authors: S. Dey, T. Mukhopadhyay, S. Adhikari

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This paper presents an exhaustive comparative investigation on sampling techniques of polynomial regression model based stochastic natural frequency of composite plates. Both individual and combined variations of input parameters are considered to map the computational time and accuracy of each modelling techniques. The finite element formulation of composites is capable to deal with both correlated and uncorrelated random input variables such as fibre parameters and material properties. The results obtained by Polynomial regression (PR) using different sampling techniques are compared. Depending on the suitability of sampling techniques such as 2k Factorial designs, Central composite design, A-Optimal design, I-Optimal, D-Optimal, Taguchi’s orthogonal array design, Box-Behnken design, Latin hypercube sampling, sobol sequence are illustrated. Statistical analysis of the first three natural frequencies is presented to compare the results and its performance.

Keywords: composite plate, natural frequency, polynomial regression model, sampling technique, uncertainty quantification

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Authors: Ibrahim Garba

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This research involved the use of word distributions and morphological knowledge by speakers of Arabic learning English connected different allomorphs in order to realize how the morphology and syntax of English gives meaning through using interactive crossword puzzles (ICP). Fifteen chapters covered with a class of nine learners over an academic year of an intensive English program were reviewed using the ICP. Learners were questioned about how the use of this gaming element enhanced and motivated their learning of English. The findings were positive indicating a successful implementation of ICP both at creational and user levels. This indicated a positive role technology had when learning and teaching English through adopting an interactive gaming element for learning English.

Keywords: distribution, gaming, interactive-crossword-puzzle, morphology

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Authors: Haodong Huang, Zida Zhao, Shilong Sun, Chiyao Li, Wenfu Xu

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The control methods for legged robots based on deep reinforcement learning have seen widespread application; however, the inherent black-box nature of neural networks presents challenges in understanding the decision-making motives of the robots. To address this issue, we propose a fully interpretable deep reinforcement learning training method to elucidate the underlying principles of legged robot motion. We incorporate the dynamics of legged robots into the policy, where observations serve as inputs and actions as outputs of the dynamics model. By embedding the dynamics equations within the multi-layer perceptron (MLP) computation process and making the parameters trainable, we enhance interpretability. Additionally, Bayesian optimization is introduced to train these parameters. We validate the proposed fully interpretable motion control algorithm on a legged robot, opening new research avenues for motion control and learning algorithms for legged robots within the deep learning framework.

Keywords: deep reinforcement learning, interpretation, motion control, legged robots

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Authors: Hadi Manjiri, Mahdyeh Bakhshi, Ali Jafari, Maryam Salati

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This study investigates the influence of e-learning on teacher-student instructional interactions through the mediating role of computer literacy among elementary school teachers in Tehran. The research method is a survey that was conducted among elementary school students in Tehran. A sample size of 338 was determined based on Morgan's table. A stratified random sampling method was used to select 228 women and 110 men for the study. Bagherpour et al.'s computer literacy questionnaire, Elahi et al.'s e-learning questionnaire, and Lourdusamy and Khine's questionnaire on teacher-student instructional interactions were used to measure the variables. The data were analyzed using SPSS and LISREL software. It was found that e-learning affects teacher-student instructional interactions, mediated by teachers' computer literacy. In addition, the results suggest that e-learning predicts a 0.66 change in teacher-student instructional interactions, while computer literacy predicts a 0.56 change in instructional interactions between teachers and students.

Keywords: e-learning, instructional interactions, computer literacy, students

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Authors: Kashi Raj Pandey

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Transformative learning is a form of learning rooted in learners' life experiences and their inherent love for learning. It emphasizes the importance of incorporating students' everyday work through the use of learning diaries and reflective journals. It encourages learners to take a proactive role in their own improvement, fostering creativity and promoting informed discussions about the learning process. Reflecting on the personal experience with English language learning in a rural village in Nepal where rote memorization was the prevailing teaching method, this traditional approach hindered a deeper understanding of the language, prompting the author to recognize the need for more effective pedagogy. In this study, the author delved into the cultural contextualization of English language learning, taking into account learners' backgrounds. The study’s findings highlighted the importance of equity, inclusion, mutuality, and social justice in the classroom, emphasizing the significance of integrating students' lived experiences into the pedagogical approach. This, in turn, can encourage students to engage in profound and collaborative learning practices within the realm of English language education. Upon successfully implementing the research findings, including the eight key conditions of transformative learning, in multiple classrooms, the author collaborated with international educationists and government stakeholders in Nepal. The purpose was to disseminate the research findings, conduct teacher training workshops, and systematically enhance Nepali students’ English language learning. These methods have already demonstrated a significant improvement in student engagement within the same school where the author once learned English as a child. This study aims to explore teachers’ decision-making process regarding the transition from traditional teaching methods to interactive ones, which have gained national recognition within the ESL/EFL teaching community in Nepal. By sharing these experiences, it is expected that other teachers will also contemplate adopting transformative learning pedagogy in their own classrooms.

Keywords: reflection, student engagement, pedagogy, transformative learning

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Authors: Amna Khan, Zareena Kausar, Saad Malik

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Bio Mechatronics has extended applications in the field of rehabilitation. It has been contributing since World War II in improving the applicability of prosthesis and assistive devices in real life scenarios. In this paper, classification accuracies have been compared for two classifiers against five positions of elbow. Electromyography (EMG) signals analysis have been acquired directly from skeletal muscles of human forearm for each of the three defined positions and at modified extreme positions of elbow flexion and extension using 8 electrode Myo armband sensor. Features were extracted from filtered EMG signals for each position. Performance of two classifiers, support vector machine (SVM) and linear discriminant analysis (LDA) has been compared by analyzing the classification accuracies. SVM illustrated classification accuracies between 90-96%, in contrast to 84-87% depicted by LDA for five defined positions of elbow keeping the number of samples and selected feature the same for both SVM and LDA.

Keywords: classification accuracies, electromyography, linear discriminant analysis (LDA), Myo armband sensor, support vector machine (SVM)

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Authors: Agada N. Ihuoma, Nagata Yasunori

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Artificial intelligence (AI) techniques play a crucial role in predicting the expected energy outcome and its performance, analysis, modeling, and control of renewable energy. Renewable energy is becoming more popular for economic and environmental reasons. In the face of global energy consumption and increased depletion of most fossil fuels, the world is faced with the challenges of meeting the ever-increasing energy demands. Therefore, incorporating artificial intelligence to predict solar radiation outcomes from the intermittent sunlight is crucial to enable a balance between supply and demand of energy on loads, predict the performance and outcome of solar energy, enhance production planning and energy management, and ensure proper sizing of parameters when generating clean energy. However, one of the major problems of forecasting is the algorithms used to control, model, and predict performances of the energy systems, which are complicated and involves large computer power, differential equations, and time series. Also, having unreliable data (poor quality) for solar radiation over a geographical location as well as insufficient long series can be a bottleneck to actualization. To overcome these problems, this study employs the anaconda Navigator (Jupyter Notebook) for machine learning which can combine larger amounts of data with fast, iterative processing and intelligent algorithms allowing the software to learn automatically from patterns or features to predict the performance and outcome of Solar Energy which in turns enables the balance of supply and demand on loads as well as enhance production planning and energy management.

Keywords: artificial Intelligence, backward elimination, linear regression, solar energy

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Authors: Kailin K. Zhang, Anne W. Thompson

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Electronic learning for continuing professional education (CPE) and interprofessional education (IPE) in healthcare have been shown to improve learners’ satisfaction, attitudes, and performance. Yet, their impact on behavior change in healthcare professionals through continuing interprofessional education (CIPE) is less known. A scoping review of 32 articles from 2010 to 2020 was conducted using the Arksey and O’Malley framework across all healthcare settings. It focused on evaluating the effectiveness of CIPE on behavior change of healthcare professionals, as well as identifying course features of electronic CIPE programs facilitating behavior change. Eight different types of electronic learning methods, including online programs, tele-education, and social media, were identified as interventions. More than 35,542 healthcare professionals participated in the interventions. Electronic learning for CIPE led to positive behavior outcomes in 30 out of 32 studies, especially through a change in patient care practices. The most successful programs provided interactive and authentic learning experiences tailored to learners’ needs while promoting the direct application of what was learned in their clinical settings. Future research should include monitoring of sustained behavior changes and their resultant patient outcomes.

Keywords: behavior change, continuing interprofessional education, distance learning, electronic learning

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Authors: Sirimanee Banjong

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This study aimed to 1) develop pre-service teachers’ leadership skills through camp-based learning, and 2) develop pre-service teachers’ teamwork skills through camp-based learning. An applied research methodology was used. The target group was derived from a purposive selection. It involved 32 fourth-year students in Early Childhood Education Program enrolling in a course entitled Seminar in Early Childhood Education provided during the second semester of the academic year 2013. The treatment was camp-based learning activities which applied a PDCA process including four stages: 1) plan, 2) do, 3) check, and 4) act. Research instruments were a learning camp program, a camp-based learning management plan, a 5-level assessment form for leadership skills and a 5-level assessment form for assessing teamwork skills. Data were analyzed using descriptive statistics. Results were: 1) pre-service teachers’ leadership skills yielded the before treatment average score at ¯("x" )=3.4, S.D.= 0.62 and the after-treatment average score at ¯("x" ) 4.29, S.D.=0.66 pre-service teachers’ teamwork skills yielded the before-treatment average score at ¯("x" )=3.31, S.D.= 0.60 and the after-treatment average score at ¯("x" )=4.42, S.D.= 0.66. Both differences were statistically significant at the .05 level. Thus, the pre-service teachers’ leadership and teamwork skills were significantly improved through the camp-based learning approach.

Keywords: learning camp, leadership skills, teamwork skills, pre-service teachers

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Authors: Okewu E. Jonathan

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There are several techniques of production in the field of ceramics. These different techniques overtime have been categorised under three methods of production which includes; casting, throwing and hand building. Hand building method of production is further broken down into other techniques and they include coiling, slabbing and pinching. Ceramic artists find the different hand building techniques to be very interesting, practicable and rewarding. This has encouraged ceramic artist in their various studios at different levels to experiment for further hand building techniques that could be unique and unusual. The art of “Clay Palm Press” is a development from studio experiment in a quest for uniqueness in conceptual ceramic practise. Clay palm press is a technique that requires no formal tutelage but at the same time, it is not easily comprehensible when viewed. It is a practice of putting semi-solid clay in the palm and inserting a closed fist pressure so as to take the imprint of the human palm. This clay production from the palm when dried, fired and explored into an art, work reveals an absolute awesomeness of what the palm imprint could result in.

Keywords: ceramics, clay palm press, conceptual forms, hand building, technique

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Authors: Khadija Bouzaachane, El Mahdi El Guarmah

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The classification of low-resolution satellite images has been a worthwhile and fertile field that attracts plenty of researchers due to its importance in monitoring geographical areas. It could be used for several purposes such as disaster management, military surveillance, agricultural monitoring. The main objective of this work is to classify efficiently and accurately low-resolution satellite images by using novel technics of deep learning and reinforcement learning. The images include roads, residential areas, industrial areas, rivers, sea lakes, and vegetation. To achieve that goal, we carried out experiments on the sentinel-2 images considering both high accuracy and efficiency classification. Our proposed model achieved a 91% accuracy on the testing dataset besides a good classification for land cover. Focus on the parameter precision; we have obtained 93% for the river, 92% for residential, 97% for residential, 96% for the forest, 87% for annual crop, 84% for herbaceous vegetation, 85% for pasture, 78% highway and 100% for Sea Lake.

Keywords: classification, deep learning, reinforcement learning, satellite imagery

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Authors: Una Carthy

Abstract:

A recent study of third level institutions in Ireland reveals that both age and aptitude can be overcome by teaching methodologies to motivate second language learners. This PhD investigation gathered quantitative and qualitative data from 14 Institutes of Technology over a three years period from 2011 to 2014. The fundamental research question was to establish the impact of institutional language policy on attitudes towards language learning. However, other related issues around second language acquisition arose in the course of the investigation. Data were collected from both lectures and students, allowing interesting points of comparison to emerge from both datasets. Negative perceptions among lecturers regarding language provision were often associated with the view that language learning belongs to primary and secondary level and has no place in third level education. This perception was offset by substantial data showing positive attitudes towards adult language learning. Lenneberg’s Critical Age Theory postulated that the optimum age for learning a second language is before puberty. More recently, scholars have challenged this theory in their studies, revealing that mature learners can and do succeed at learning languages. With regard to aptitude, a preoccupation among lecturers regarding poor literacy skills among students emerged and was often associated with resistance to second language acquisition. This was offset by a preponderance of qualitative data from students highlighting the crucial role which teaching approaches play in the learning process. Interestingly, the data collected regarding learning disabilities reveals that, given the appropriate learning environments, individuals can be motivated to acquire second languages, and indeed succeed at learning them. These findings are in keeping with other recent studies regarding attitudes towards second language learning among students with learning disabilities. Both sets of findings reinforce the case for language policies in the Institute of Technology (IoTs). Supportive and positive learning environments can be created in third level institutions to motivate adult learners, thereby overcoming perceived obstacles relating to age and aptitude.

Keywords: age, aptitude, second language acquisition, teaching methodologies

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Authors: Reema Alghamdi, Rasees Aleisa, Layan Sukkar

Abstract:

The primary objective of this research is to conduct an examination of the Flo menstrual cycle application. We do that by evaluating the user experience and their satisfaction with integrated AI features. The study seeks to gather data from primary resources, primarily through surveys, to gather different insights about the application, like its usability functionality in addition to the overall user satisfaction. The focus of our project will be particularly directed towards the impact and user perspectives regarding the integration of artificial intelligence features within the application, contributing to an understanding of the holistic user experience.

Keywords: period, women health, machine learning, AI features, menstrual cycle

Procedia PDF Downloads 76