Search results for: autonomous learning system

Authors: Nick Woodier, Paul Sampson, Iain Moppett

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Background: For years, healthcare across the world has recognised that patients are coming to harm from the very processes meant to help them. In response, healthcare tells itself that it needs to ‘be more like aviation.’ Aviation safety is highly regarded by those in healthcare and is seen as an exemplar. Specifically, healthcare is keen to learn from how aviation uses near misses to make their industry safer. Healthcare is rife with near misses; however, there has been little progress addressing them, with most research having focused on reporting. Addressing the factors that contribute to near misses will potentially help reduce the number of significant, harm patientsafety incidents. While the healthcare literature states the need to learn from aviation’s use of near misses, there is nothing that describes how best to do this. The authors, as part of a larger study of near-miss management in healthcare, sought to learn from aviation to develop principles for how healthcare can identify, report, and learn from near misses to improve patient safety. Methods: A Grounded Theory (GT) methodology, augmented by a scoping review, was used. Data collection included interviews, field notes, and the literature. The review protocol is accessible online. The GT aimed to develop theories about how aviation, amongst other safety-critical industries, manages near misses. Results: Twelve aviation interviews contributed to the GT across passenger airlines, air traffic control, and bodies involved in policy, regulation, and investigation. The scoping review identified 83 articles across a range of safety-critical industries, but only seven focused on aviation. The GT identified that aviation interprets the term ‘near miss’ in different ways, commonly using it to specifically refer to near-miss air collisions, also known as Airproxes. Other types of near misses exist, such as health and safety, but the reporting of these and the safety climate associated with them is not as mature. Safety culture in aviation was regularly discussed, with evidence that culture varies depending on which part of the industry is being considered (e.g., civil vs. business aviation). Near misses are seen as just one part of an extensive safety management system, but processes to support their reporting and their analysis are not consistent. Their value alone is also questionable, with the challenge to long-held beliefs originating from the ‘common cause hypothesis.’ Conclusions: There is learning that healthcare can take from how parts of aviation manage and learn from near misses. For example, healthcare would benefit from a formal safety management system that currently does not exist. However, it may not be as simple as ‘healthcare should learn from aviation’ due to variation in safety maturity across the industry. Healthcare needs to clarify how to incorporate near misses into learning and whether allocating resources to them is of value; it was heard that catastrophes have led to greater improvements in safety in aviation.

Keywords: aviation safety, patient safety, near miss, safety management systems

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Authors: W. S. Barber, S. L. King

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This paper is a qualitative case study analysis of the development of a fully online learning community of graduate students through arts-based community building activities. With increasing numbers and types of online learning spaces, it is incumbent upon educators to continue to push the edge of what best practices look like in digital learning environments. In digital learning spaces, instructors can no longer be seen as purveyors of content knowledge to be examined at the end of a set course by a final test or exam. The rapid and fluid dissemination of information via Web 3.0 demands that we reshape our approach to teaching and learning, from one that is content-focused to one that is process-driven. Rather than having instructors as formal leaders, today’s digital learning environments require us to share expertise, as it is the collective experiences and knowledge of all students together with the instructors that help to create a very different kind of learning community. This paper focuses on innovations pursued in a 36 hour 12 week graduate course in higher education entitled “Critical and Reflective Practice”. The authors chronicle their journey to developing a fully online learning community (FOLC) by emphasizing the elements of social, cognitive, emotional and digital spaces that form a moving interplay through the community. In this way, students embrace anywhere anytime learning and often take the learning, as well as the relationships they build and skills they acquire, beyond the digital class into real world situations. We argue that in order to increase student online engagement, pedagogical approaches need to stem from two primary elements, both creativity and critical reflection, that are essential pillars upon which instructors can co-design learning environments with students. The theoretical framework for the paper is based on the interaction and interdependence of Creativity, Intuition, Critical Reflection, Social Constructivism and FOLCs. By leveraging students’ embedded familiarity with a wide variety of technologies, this case study of a graduate level course on critical reflection in education, examines how relationships, quality of work produced, and student engagement can improve by using creative and imaginative pedagogical strategies. The authors examine their professional pedagogical strategies through the lens that the teacher acts as facilitator, guide and co-designer. In a world where students can easily search for and organize information as self-directed processes, creativity and connection can at times be lost in the digitized course environment. The paper concludes by posing further questions as to how institutions of higher education may be challenged to restructure their credit granting courses into more flexible modules, and how students need to be considered an important part of assessment and evaluation strategies. By introducing creativity and critical reflection as central features of the digital learning spaces, notions of best practices in digital teaching and learning emerge.

Keywords: online, pedagogy, learning, communities

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Authors: J. B. G. Ibarra, J. M. A. Gagui, E. J. T. Jonson, J. A. V. Lim

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This paper focused on studying the performance of the solar panels that were equipped with water-spray cooling system, solar tracking system, and combination of both systems. The efficiencies were compared with the solar panels without any efficiency improvement technique. The efficiency of each setup was computed on an hourly basis every day for a month. The study compared the efficiencies and combined systems that significantly improved at a specific time of the day. The data showed that the solar tracking system had the highest efficiency during 6:00 AM to 7:45 AM. Then after 7:45 AM, the combination of both solar tracking and water-spray cooling system was the most efficient to use up to 12:00 NN. Meanwhile, from 12:00 NN to 12:45 PM, the water-spray cooling system had the significant contribution on efficiency. From 12:45 PM up to 4:30 PM, the combination of both systems was the most efficient, and lastly, from 4:30 PM to 6:00 PM, the solar tracking system was the best to use. The study intended to use solar tracking or water-spray cooling system or combined systems alternately to improve the solar panel efficiency on a specific time of the day.

Keywords: solar panel efficiency, solar panel efficiency technique, solar tracking system, water-spray cooling system

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Authors: Prabir Mukhopadhyay, Atul Kohale

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Going to school for Indian kids is a panic situation. Many of them are unable to adjust themselves to the confinement of the school building and this problem is compounded by other factors like unknown people in the vicinity, absence of either parents etc. This project aims at addressing these issues by exposing the kids at home to the learning environment. The purpose is to design a physical model with interfaces at each surface. The model would be like a cube with interactive surfaces where the child would be able to draw, paint, complete a picture and do such fun activities.

Keywords: interface, kids, play, computer systems engineering

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Authors: Gizem Eser Erdek

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This study is research on predicting the remaining life of industrial cutting tools used in the industrial production process with deep learning methods. When the life of cutting tools decreases, they cause destruction to the raw material they are processing. This study it is aimed to predict the remaining life of the cutting tool based on the damage caused by the cutting tools to the raw material. For this, hole photos were collected from the hole-drilling machine for 8 months. Photos were labeled in 5 classes according to hole quality. In this way, the problem was transformed into a classification problem. Using the prepared data set, a model was created with convolutional neural networks, which is a deep learning method. In addition, VGGNet and ResNet architectures, which have been successful in the literature, have been tested on the data set. A hybrid model using convolutional neural networks and support vector machines is also used for comparison. When all models are compared, it has been determined that the model in which convolutional neural networks are used gives successful results of a %74 accuracy rate. In the preliminary studies, the data set was arranged to include only the best and worst classes, and the study gave ~93% accuracy when the binary classification model was applied. The results of this study showed that the remaining life of the cutting tools could be predicted by deep learning methods based on the damage to the raw material. Experiments have proven that deep learning methods can be used as an alternative for cutting tool life estimation.

Keywords: classification, convolutional neural network, deep learning, remaining life of industrial cutting tools, ResNet, support vector machine, VggNet

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Authors: Akash Amalan, Rui Wang, Yanqi Qiao, Emmanouil Panaousis, Kaitai Liang

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Federated learning is an emerging concept in the domain of distributed machine learning. This concept has enabled General Adversarial Networks (GANs) to benefit from the rich distributed training data while preserving privacy. However, in a non-IID setting, current federated GAN architectures are unstable, struggling to learn the distinct features, and vulnerable to mode collapse. In this paper, we propose an architecture MULTI-FLGAN to solve the problem of low-quality images, mode collapse, and instability for non-IID datasets. Our results show that MULTI-FLGAN is four times as stable and performant (i.e., high inception score) on average over 20 clients compared to baseline FLGAN.

Keywords: federated learning, generative adversarial network, inference attack, non-IID data distribution

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Authors: Aicha Akrout, Amira Echtioui, Mohamed Ghorbel

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Pneumonia remains a significant global health concern, posing a substantial threat to human lives due to its contagious nature and potentially fatal respiratory complications caused by bacteria, fungi, or viruses. The reliance on chest X-rays for diagnosis, although common, often necessitates expert interpretation, leading to delays and potential inaccuracies in treatment. This study addresses these challenges by employing transfer learning techniques to automate the detection of lung diseases, with a focus on pneumonia. Leveraging three pre-trained models, VGG-16, ResNet50V2, and MobileNetV2, we conducted comprehensive experiments to evaluate their performance. Our findings reveal that the proposed model based on VGG-16 demonstrates superior accuracy, precision, recall, and F1 score, achieving impressive results with an accuracy of 93.75%, precision of 94.50%, recall of 94.00%, and an F1 score of 93.50%. This research underscores the potential of transfer learning in enhancing pneumonia diagnosis and treatment outcomes, offering a promising avenue for improving healthcare delivery and reducing mortality rates associated with this debilitating respiratory condition.

Keywords: chest x-ray, lung diseases, transfer learning, pneumonia detection

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Authors: M. Shadmand

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The curing process of insulation system for electrical machines plays a determinative role for its durability and reliability. Polar structure of insulating resin molecules and used filler of insulation system can be taken as an occasion to leverage it to enhance overall characteristics of insulation system, mechanically and electrically. The curing process regime for insulating system plays an important role for its mechanical and electrical characteristics by arranging the polymerization of chain structure for resin. In this research, the effect of electrical field application on in-curing insulating system for Global Vacuum Pressurized Impregnation (GVPI) system for traction motor was considered by performing the dissipation factor, polarization and de-polarization current (PDC) and voltage endurance (aging) measurements on sample test objects. Outcome results depicted obvious improvement in mechanical strength of the insulation system as well as higher electrical characteristics with routing and long-time (aging) electrical tests. Coming together, polarization of insulation system during curing process would enhance the machine life time. 

Keywords: insulation system, GVPI, PDC, aging

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Authors: John Acire, Wilfred Lajul, Ogwang Tom

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Using a qualitative research technique, this study investigates the influence of Early Childhood Education (ECE) on learning outcomes in lower primary schools in Gulu City, Uganda. The study, which is based on Vygotsky's sociocultural theory of human learning, fills gaps in the current literature on the influence of ECE on learning outcomes. The aims of the study include analyzing the state of learning outcomes, investigating ECE practices, and determining the influence of these practices on learning outcomes in lower primary schools. The findings highlight the critical significance of ECE in promoting children's overall development. Nursery education helps children improve their handwriting, reading abilities, and general cognitive development. Children who have received nursery education have improved their abilities to handle pencils, form letters, and engage in social interactions, highlighting the significance of fine motor skills and socializing. Despite the good elements, difficulties in implementing ECE practices were found, such as differences in teaching styles, financial limits, and potential weariness due to prolonged school hours. The study suggests focused interventions to improve the effectiveness of ECE practices, ensure their connection with educational goals and maximize their influence on children's development. The study's findings show that respondents agree on the importance of nursery education in supporting holistic development, socialization, language competency, and conceptual comprehension. Challenges in nursery education, such as differences in teaching techniques and insufficient resources, highlight the need for comprehensive measures to address these challenges. Furthermore, parental engagement in home learning activities was revealed as an important factor affecting early education outcomes. Children who were engaged at home performed better in lower primary, emphasizing the value of a supportive family environment. Finally, the report suggests measures to enhance parental participation, changes in teaching methods through retraining, and age-appropriate enrolment. Future studies might concentrate on the involvement of parents, ECE policy practice, and the influence of ECE teachers on lower primary school learning results. These ideas are intended to help create a more favorable learning environment by encouraging holistic development and preparing children for success in succeeding academic levels.

Keywords: early childhood education, learning outcomes in lower primary schools, early childhood education practices, how ECE practices influence learning outcomes in lower primary schools

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Authors: M. Mansouri, P. Jaklitsch, E. Teiniker

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SQL injection on web applications is a very popular kind of attack. There are mechanisms such as intrusion detection systems in order to detect this attack. These strategies often rely on techniques implemented at high layers of the application but do not consider the low level of system calls. The problem of only considering the high level perspective is that an attacker can circumvent the detection tools using certain techniques such as URL encoding. One technique currently used for detecting low-level attacks on privileged processes is the tracing of system calls. System calls act as a single gate to the Operating System (OS) kernel; they allow catching the critical data at an appropriate level of detail. Our basic assumption is that any type of application, be it a system service, utility program or Web application, “speaks” the language of system calls when having a conversation with the OS kernel. At this level we can see the actual attack while it is happening. We conduct an experiment in order to demonstrate the suitability of system call analysis for detecting SQL injection. We are able to detect the attack. Therefore we conclude that system calls are not only powerful in detecting low-level attacks but that they also enable us to detect high-level attacks such as SQL injection.

Keywords: Linux system calls, web attack detection, interception, SQL

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Authors: Halima Musa Kamilu

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This paper discusses the effective strategies for teaching English language to learners in primary schools in Nigeria. English language development is the systematic use of instructional strategies designed to promote the acquisition of English by pupils in primary schools whose primary language is not English. Learning a second language is through total immersion. These strategies support this learning method, allowing pupils to have the knowledge of English language in a pattern similar to the way they learned their native language through regular interaction with others who already know the language. The focus is on fluency and learning to speak English in a social context with native speakers. The strategies allow for effective acquisition. The paper also looked into the following areas: visuals that reinforce spoken or written words, employ gestures for added emphasis, adjusting of speech, stressing of high-frequency vocabulary words, use of fewer idioms and clarifying the meaning of words or phrases in context, stressing of participatory learning and maintaining a low anxiety level and boosting of enthusiasm. It recommended that the teacher include vocabulary words that will make the content more comprehensible to the learner.

Keywords: effective, strategies, teaching, beginners and primary schools

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Authors: Blanco T. F., Fernández-López A.

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Nowadays, education, motivated by the new demands of the 21st century, acquires a dimension that converts the skills that new generations may need into a huge and uncertain set of knowledge too broad to be entirety covered. Within this set, and as tools to reach them, we find Learning and Knowledge Technologies (LKT). Thus, in order to prepare students for an everchanging society in which the technological boom involves everything, it is essential to develop digital competence. Nevertheless LKT seems not to have found their place in the educational system. This work is aimed to go a step further in the research of the most appropriate procedures and resources for technological integration in the classroom. The main objective of this exploratory study is to analyze the didactic suitability (epistemic, cognitive, affective, interactional, mediational and ecological) for teaching and learning processes of mathematics with robotics and 3D printing. The analysis carried out is drawn from a STEAM (Science, Technology, Engineering, Art and Mathematics) project that has the Pilgrimage way to Santiago de Compostela as a common thread. The sample is made up of 25 Primary Education students (10 and 11 years old). A qualitative design research methodology has been followed, the sessions have been distributed according to the type of technology applied. Robotics has been focused towards learning two-dimensional mathematical notions while 3D design and printing have been oriented towards three-dimensional concepts. The data collection instruments used are evaluation rubrics, recordings, field notebooks and participant observation. Indicators of didactic suitability proposed by Godino (2013) have been used for the analysis of the data. In general, the results show a medium-high level of didactic suitability. Above these, a high mediational and cognitive suitability stands out, which led to a better understanding of the positions and relationships of three-dimensional bodies in space and the concept of angle. With regard to the other indicators of the didactic suitability, it should be noted that the interactional suitability would require more attention and the affective suitability a deeper study. In conclusion, the research has revealed great expectations around the combination of teaching-learning processes of mathematics and LKT. Although there is still a long way to go in terms of the provision of means and teacher training.

Keywords: 3D printing, didactic suitability, educational design, robotics

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Authors: Yasser Aldali

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The scope of this paper is to evaluate and compare the potential of LS-PV (Large Scale Photovoltaic Power Plant) power generation systems in the southern region of Libya at Al-Kufra for both stationary and tracking systems. A Microsoft Excel-VBA program has been developed to compute slope radiation, dew-point, sky temperature, and then cell temperature, maximum power output and module efficiency of the system for stationary system and for tracking system. The results for energy production show that the total energy output is 114GWh/year for stationary system and 148 GWh/year for tracking system. The average module efficiency for the stationary system is 16.6% and 16.2% for the tracking system. The values of electricity generation capacity factor (CF) and solar capacity factor (SCF) for stationary system were found to be 26% and 62.5% respectively and 34% and 82% for tracking system. The GCR (Ground Cover Ratio) for a stationary system is 0.7, which corresponds to a tilt angle of 24°. The GCR for tracking system was found to be 0.12. The estimated ground area needed to build a 50MW PV plant amounts to approx. 0.55 km2 for a stationary PV field constituted by HIT PV arrays and approx. 91 MW/km2. In case of a tracker PV field, the required ground area amounts approx. 2.4k m2 and approx. 20.5 MW/km2.

Keywords: large scale photovoltaic power plant, two-axis tracking system, stationary system, landscape impact

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Authors: M. Reni Sagayaraj, S. Anand Gnana Selvam, R. Reynald Susainathan

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This study analyzed a queueing system with blocking and no waiting line. The customers arrive according to a Poisson process and the service times follow exponential distribution. There are two non-identical servers in the system. The queue discipline is FCFS, and the customers select the servers on fastest server first (FSF) basis. The service times are exponentially distributed with parameters μ1 and μ2 at servers I and II, respectively. Besides, the catastrophes occur in a Poisson manner with rate γ in the system. When server I is busy or blocked, the customer who arrives in the system leaves the system without being served. Such customers are called lost customers. The probability of losing a customer was computed for the system. The explicit time dependent probabilities of system size are obtained and a numerical example is presented in order to show the managerial insights of the model. Finally, the probability that arriving customer finds system busy and average number of server busy in steady state are obtained numerically.

Keywords: queueing system, blocking, poisson process, heterogeneous servers, queue discipline FCFS, busy period

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Authors: Xue Wu

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Since the 1980s, a series of policies and practices have been implemented in China in response to the unprecedented rate of ageing population. The paper provides a detailed narrative of what later-life learning policy discourses have been advocated and gives a description on relevant practical issues during the past three decades. The research process based on the discourse approach with a systematic review of the government-issued documents. It finds that the main practices taken by central government at various levels were making University of the Aged (UA) available in all urban and rural regions to consolidate the newly student enrollments; focusing social-recreational, leisure and cultural activities on 55-75 age group; and utilizing various methods including voluntary works and tourism to improve older adults’ physical and mental wellness. Although there were greater achievements with 30 years of development, many problems still exist. Finding reveals that the curriculum should be modified to meet the needs of the local development, to promote older adults’ contact and contribution to the community, and to enhance technical competences of those in rural areas involving in agricultural production. Central government should also integrate resources from all sectors of the society for further developing later-life learning in China. The result of this paper highlights the value to promote community-based later-life learning for building a society for active ageing and ageing in place.

Keywords: ageing population, China, later-life learning, policy, University of the Aged

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Authors: Fatemeh Miraki

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The use of authentic materials in English Language Teaching (ELT) has become increasingly prominent as educators recognize the value of exposing learners to real-world language use and cultural contexts. The integration of authentic materials in ELT aligns with the understanding that language learning is most effective when situated within authentic contexts (Richards & Rodgers, 2001). Tomlinson (1998) highlights the significance of authentic materials in ELT by research indicating that they offer learners exposure to genuine language use and cultural contexts. Tomlinson's work emphasizes the importance of creating meaningful learning experiences through the use of authentic materials. Research by Dörnyei (2001) underscores the potential of authentic materials to enhance students' intrinsic motivation through their relevance to real-life language use. The goal of this review paper is to explore the use of authentic materials in English Language Teaching (ELT) and its impact on language learning. It also discusses best practices for selecting and integrating such authentic materials into ELT curriculum, highlighting the benefits and challenges of using authentic materials to enhance student engagement, motivation, and language proficiency. Drawing on current research and practical examples, this paper provides insights into how teachers can effectively navigate the world of authentic materials to create dynamic and meaningful learning experiences for 21st century ELT learners. The findings of this study advocates for a shift towards embracing authentic materials within the ELT classroom, acknowledging their profound impact on language proficiency, intercultural competence, and learner engagement. It showed the transformative potential of authentic materials, educators can undergo a vibrant and immersive language learning experience, enriched with real-world application and cultural authenticity.

Keywords: authentic materials, ELT Classroom, ELT curriculum, students’ engagement

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Authors: Yakubu Bala Mohammed, Nadire Chavus, Mohammed Bulama

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Generative Pre-trained Transformer (ChatGPT) represents an artificial intelligence (AI) tool capable of swiftly generating comprehensive responses to prompts and follow-up inquiries. This emerging AI tool was introduced in November 2022 by OpenAI firm, an American AI research laboratory, utilizing substantial language models. This present study aims to delve into the potential future consequences of ChatGPT usage in education using AI-based algorithms. The paper will bring forth the likely potential risks of ChatGBT utilization, such as academic integrity concerns, unfair learning assessments, excessive reliance on AI, and dissemination of inaccurate information using four machine learning algorithms: eXtreme-Gradient Boosting (XGBoost), Support vector machine (SVM), Emotional artificial neural network (EANN), and Random forest (RF) would be used to analyze the study collected data due to their robustness. Finally, the findings of the study will assist education stakeholders in understanding the future implications of ChatGPT usage in education and propose solutions and directions for upcoming studies.

Keywords: machine learning, ChatGPT, education, learning, implications

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Authors: Margit Kastner

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To overcome the negative consequences associated with large class sizes and to support students in developing the necessary competences (e.g., critical thinking, problem-solving, or team-work skills) a marketing course has been redesigned by implementing project-based learning with peer assessment (PBL&PA). This means that students can voluntarily take advantage of this supplementary offer and explore -in addition to attending the lecture where clicker questions are asked- a real-world problem, find a solution, and assess the results of peers while working in small collaborative groups. In order to handle this with little further effort, the process is technically supported by the university’s e-learning system in such a way that students upload their solution in form of an assignment which is then automatically distributed to peer groups who have to assess the work of three other groups. Finally, students’ work is graded automatically considering both, students’ contribution to the project and the conformity of the peer assessment. The purpose of this study is to evaluate students’ perception of PBL&PA using an online-questionnaire to collect the data. More specifically, it aims to discover students’ motivations for (not) working on a project and the benefits and problems students encounter. In addition to the survey, students’ performance was analyzed by comparing the final grades of those who participated in PBL&PA with those who did not participate. Among the 260 students who filled out the questionnaire, 47% participated in PBL&PA. Besides extrinsic motivations (bonus credits), students’ participation was often motivated by learning and social benefits. Reasons for not working on a project were connected to students’ organization and management of their studies (e.g., time constraints, no/wrong information) and teamwork concerns (e.g., missing engagement of peers, prior negative experiences). In addition, high workload and insufficient extrinsic motivation (bonus credits) were mentioned. With regards to benefits and problems students encountered during the project, students provided more positive than negative comments. Positive aspects most often stated were learning and social benefits while negative ones were mainly attached to the technical implementation. Interestingly, bonus credits were hardly named as a positive aspect meaning that intrinsic motivations have become more important when working on the project. Team aspects generated mixed feelings. In addition, students who voluntarily participated in PBL&PA were, in general, more active and utilized further course offers such as clicker questions. Examining students’ performance at the final exam revealed that students without participating in any of the offered active learning tasks performed poorest in the exam while students who used all activities were best. In conclusion, the goals of the implementation were met in terms of students’ perceived benefits and the positive impact on students’ exam performance. Since the comparison of the automatic grading with faculty grading showed valid results, it is possible to rely only on automatic grading in the future. That way, the additional workload for faculty will be within limits. Thus, the implementation of project-based learning with peer assessment can be recommended for large classes.

Keywords: automated grading, large classes, peer assessment, project-based learning

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Authors: Stuti Modi, Aditi Kambli

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This paper addresses the need for intelligent water management and distribution system in smart cities to ensure optimal consumption and distribution of water for drinking and sanitation purposes. Water being a limited resource in cities require an effective system for collection, storage and distribution. In this paper, applications of two mostly widely used particular types of data-driven models, namely artificial neural networks (ANN) and fuzzy logic-based models, to modelling in the water resources management field are considered. The objective of this paper is to review the principles of various types and architectures of neural network and fuzzy adaptive systems and their applications to integrated water resources management. Final goal of the review is to expose and formulate progressive direction of their applicability and further research of the AI-related and data-driven techniques application and to demonstrate applicability of the neural networks, fuzzy systems and other machine learning techniques in the practical issues of the regional water management. Apart from this the paper will deal with water storage, using ANN to find optimum reservoir level and predicting peak daily demands.

Keywords: artificial neural networks, fuzzy systems, peak daily demand prediction, water management and distribution

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Authors: Jacob Green, Cecilia Cabrera, Maximilian Jakobs, Andrea Dimitracopoulos, Mark van der Wilk, Ryan Greenhalgh

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Predicting drug properties is key in drug discovery to enable de-risking of assets before expensive clinical trials and to find highly active compounds faster. Interest from the machine learning community has led to the release of a variety of benchmark datasets and proposed methods. However, it remains unclear for practitioners which method or approach is most suitable, as different papers benchmark on different datasets and methods, leading to varying conclusions that are not easily compared. Our large-scale empirical study links together numerous earlier works on different datasets and methods, thus offering a comprehensive overview of the existing property classes, datasets, and their interactions with different methods. We emphasise the importance of uncertainty quantification and the time and, therefore, cost of applying these methods in the drug development decision-making cycle. To the best of the author's knowledge, it has been observed that the optimal approach varies depending on the dataset and that engineered features with classical machine learning methods often outperform deep learning. Specifically, QSAR datasets are typically best analysed with classical methods such as Gaussian Processes, while ADMET datasets are sometimes better described by Trees or deep learning methods such as Graph Neural Networks or language models. Our work highlights that practitioners do not yet have a straightforward, black-box procedure to rely on and sets a precedent for creating practitioner-relevant benchmarks. Deep learning approaches must be proven on these benchmarks to become the practical method of choice in drug property prediction.

Keywords: activity (QSAR), ADMET, classical methods, drug property prediction, empirical study, machine learning

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Authors: Sandra Baßler, Peter Dünow, Mathias Marquardt

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A Fourier series based learning control (FSBLC) algorithm for tracking trajectories of mechanical systems with unknown nonlinearities is presented. Two processes are introduced to which the FSBLC with PD controller is applied. One is a simplified service robot capable of climbing stairs due to special wheels and the other is a propeller driven pendulum with nearly the same requirements on control. Additionally to the investigation of learning the feed forward for the desired trajectories some considerations on the implementation of such an algorithm on low cost microcontroller hardware are made. Simulations of the service robot as well as practical experiments on the pendulum show the capability of the used FSBLC algorithm to perform the task of improving control behavior for repetitive task of such mechanical systems.

Keywords: climbing stairs, FSBLC, ILC, service robot

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Authors: Khenfer-Koummich Fatima, Mesbahi Larbi, Hendel Fatiha

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This paper presents a recognition system for isolated words like robot commands. It’s carried out by Time Delay Neural Networks; TDNN. To teleoperate a robot for specific tasks as turn, close, etc… In industrial environment and taking into account the noise coming from the machine. The choice of TDNN is based on its generalization in terms of accuracy, in more it acts as a filter that allows the passage of certain desirable frequency characteristics of speech; the goal is to determine the parameters of this filter for making an adaptable system to the variability of speech signal and to noise especially, for this the back propagation technique was used in learning phase. The approach was applied on commands pronounced in two languages separately: The French and Arabic. The results for two test bases of 300 spoken words for each one are 87%, 97.6% in neutral environment and 77.67%, 92.67% when the white Gaussian noisy was added with a SNR of 35 dB.

Keywords: TDNN, neural networks, noise, speech recognition

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Authors: Muhalim Muhalim

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Drawing on Lakoff’s theory of metaphor conceptualization, this article explores the conceptualization of language two writing (L2W) of ten students-teachers in Indonesia via metaphors. The ten postgraduate English language teaching students and at the same time (former) English teachers received seven days of intervention in teaching and learning L2. Using introspective log and focus group discussion, the results illuminate us that all participants are unanimous on perceiving L2W as process-oriented rather than product-oriented activity. Specifically, the metaphor conceptualizations exhibit three categories of process-oriented L2W: deliberate process, learning process, and problem-solving process. However, it has to be clarified from the outset that this categorization is not rigid because some of the properties of metaphors might belong to other categories. Results of the study and implications for English language teaching will be further discussed.

Keywords: metaphor conceptualisation, second language, learning writing, teaching writing

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Authors: Bala Adamu Malami

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The necessity of low-cost electronic vehicle/car security designed in coordination with other security measures is always there in our society to reduce the risk of vehicle intrusion. Keeping this problem in mind, we are designing an automatic GPS system which is technology to build an integrated and fully customized vehicle to detect the movement of the vehicle and also serve as a security system at a reasonable cost. Users can locate the vehicle's position via GPS by using the Google Maps application to show vehicle coordinates on a smartphone. The tracking system uses a Global System for Mobile Communication (GSM) modem for communication between the mobile station and the microcontroller to send and receive commands. Further design can be improved to capture the vehicle movement range and alert the vehicle owner when the vehicle is out of range.

Keywords: electronic, GPS, GSM modem, communication, vehicle

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Authors: Ailene B. Anonuevo

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The aim of the study was to evaluate the quality of life presently available for the IP students in selected schools in the Division of Panabo City. This further explores their future dreams and current status in classes and examines some implications relative to their studies. The study adopted the mixed methodology and used a survey research design as the operational framework for data gathering. Data were collected by self-administered questionnaires and interviews with sixty students from three schools in Panabo City. In addition, this study describes the learners’ background and school climate as variables that might influence their performance in school. The study revealed that an IP student needs extra attention due to their unfavorable learning environment. The study also found out that like any other students, IP learners yearns for a brighter future with the support of our government.

Keywords: IP learners, learning landscape, school climate, quality of life

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Authors: Prajwal Prakash Vasisht, Sharath Rajamurthy, Nishanth Dara

Abstract:

In a supervised machine learning approach, metrics such as precision, accuracy, and coverage can be calculated using ground truth labels to help in model tuning, evaluation, and selection. In an unsupervised setting, however, where the data has no ground truth, there are few interpretable metrics that can guide us to do the same. Our approach creates a framework to adapt the Intersection over Union metric, referred to as Adapted IoU, usually used to evaluate supervised learning models, into the unsupervised domain, which solves the problem by factoring in subject matter expertise and intuition about the ideal output from the model. This metric essentially provides a scale that allows us to compare the performance across numerous unsupervised models or tune hyper-parameters and compare different versions of the same model.

Keywords: general metric, unsupervised learning, classification, intersection over union

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Authors: Cindy Davis

Abstract:

Higher education is changing globally and there is increasing pressure from professional social work accreditation bodies for academic programs to demonstrate how students have successfully met mandatory graduate competencies. As professional accreditation organizations increase their demand for evidence of graduate competencies, strategies to document and recording learning outcomes becomes increasingly challenging for academics and students. Studies in higher education have found support for the pedagogical value of ePortfolios, a flexible personal learning space that is owned by the student and include opportunity for assessment, feedback and reflection as well as a virtual space to store evidence of demonstration of professional competencies and graduate attributes. Examples of institutional uses of ePortfolios include e-administration of a diverse student population, assessment of student learning, and the demonstration of graduate attributes attained and future student career preparation. The current paper presents a case study on the introduction of ePortfolios for social work graduates in Australia as part of an institutional approach to technology-enhanced learning and e-learning. Social work graduates were required to submit an ePortfolio hosted on PebblePad. The PebblePad platform was selected because it places the student at the center of their learning whilst providing powerful tools for staff to structure, guide and assess that learning. The ePortofolio included documentation and evidence of how the student met each graduate competency as set out by the social work accreditation body in Australia (AASW). This digital resource played a key role in the process of external professional accreditation by clearly documenting and evidencing how students met required graduate competencies. In addition, student feedback revealed a positive outcome on how this resource provided them with a consolidation of their learning experiences and assisted them in obtaining employment post-graduation. There were also significant institutional factors that were key to successful implementation such as investment in the digital technology, capacity building amongst academics, and technical support for staff and students.

Keywords: accreditation, social work, teaching, technology

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Authors: Theodorou Kyriaki, Ypsilantis George

Abstract:

Vocabulary learning has attracted a lot of attention in recent years, contrary to the neglected part of the past. Along with the interest in finding successful vocabulary teaching strategies, many scholars focused on locating learning strategies used by language learners. As a result, more and more studies in the area of language pedagogy have been investigating the use of strategies in vocabulary learning by different types of learners. A common instrument in this field is the questionnaire, a tool of work that was enriched by questions involving current technology, and it was further implemented to a sample of 300 Greek students whose age varied from 9 and 17 years. Strategies located were grouped into the three categories of memory, cognitive, and compensatory type and associations between these dependent variables were investigated. In addition, relations between dependent and independent variables (such as age, sex, type of school, cultural background, and grade in English) were pursued to investigate the impact on strategy selection. Finally, results were compared to findings of other studies in the same field to contribute to a hypothesis of ethnic differences in strategy selection. Results initially discuss preferred strategies of all participants and further indicate that: a) technology affects strategy selection while b) differences between ethnic groups are not statistically significant. A number of successful strategies are presented, resulting from correlations of strategy selection and final school grade in English.

Keywords: acquisition of English, internet technology, research among Greek students, vocabulary learning strategies

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Authors: Ian Omung'a

Abstract:

Breast cancer remains to be one of the deadliest cancers for women worldwide, with the risk of developing tumors being as high as 50 percent in Sub-Saharan African countries like Kenya. With as many as 42 percent of these cases set to be diagnosed late when cancer has metastasized and or the prognosis has become terminal, Full Field Digital [FFD] Mammography remains an effective screening technique that leads to early detection where in most cases, successful interventions can be made to control or eliminate the tumors altogether. FFD Mammograms have been proven to multiply more effective when used together with Computer-Aided Detection and Diagnosis [CADe] systems, relying on algorithmic implementations of Deep Learning techniques in Computer Vision to carry out deep pattern recognition that is comparable to the level of a human radiologist and decipher whether specific areas of interest in the mammogram scan image portray abnormalities if any and whether these abnormalities are indicative of a benign or malignant tumor. Within this paper, we review emergent Deep Learning techniques that will prove relevant to the development of State-of-The-Art FFD Mammogram CADe systems. These techniques will span self-supervised learning for context-encoded occlusion, self-supervised learning for pre-processing and labeling automation, as well as the creation of a standardized large-scale mammography dataset as a benchmark for CADe systems' evaluation. Finally, comparisons are drawn between existing practices that pre-date these techniques and how the development of CADe systems that incorporate them will be different.

Keywords: breast cancer diagnosis, computer aided detection and diagnosis, deep learning, whole mammogram classfication, ultrasound classification, computer vision

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Authors: Abdullah Abu-Tineh, Youmen Chaaban

Abstract:

This study examines the development of a professional development (PD) model for teacher growth and learning that is embedded into the school context. The School based Support Program (SBSP), designed for the Qatari context, targets the practices, knowledge and skills of both school leadership and teachers in an attempt to improve student learning outcomes. Key aspects of the model include the development of learning communities among teachers, strong leadership that supports school improvement activities, and the use of research-based PD to improve teacher practices and student achievement. This paper further presents findings from an evaluation of this PD program. Based on an adaptation of Guskey’s evaluation of PD models, 100 teachers at the participating schools were selected for classroom observations and 40 took part in in-depth interviews to examine changed classroom practices. The impact of the PD program on student learning was also examined. Teachers’ practices and their students’ achievement in English, Arabic, mathematics and science were measured at the beginning and at the end of the intervention.

Keywords: initiative, professional development, school based support Program (SBSP), school reform

Procedia PDF Downloads 470