Search results for: multiple instance learning

Authors: C. Maphosa, Ndileleni Mudzielwana, Lufuno Phillip Netshifhefhe

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In line with established mission and vision, a university articulates its focus and purpose of existence. The conduct of business in a university should be for the furtherance of the mission and vision. Teaching and learning should play a pivotal role in driving the purpose of a university. In this paper, the researchers examine how service learning could be significant in driving the purpose of a rural-based university whose focus is to promote rural development. The importance of institutions’ vision and mission statement is explored and the vision and mission of the said university examined closely. The concept rural development and the contribution of a university in its promotion is discussed. Service learning as a teaching and learning approach is examined and its significance in driving the purpose of a rural-based university explained.

Keywords: relevance, differentiation, purpose, teaching, learning

Procedia PDF Downloads 318

Authors: Diego Tancara, Raul Coto, Ariel Norambuena, Hoseein T. Dinani, Felipe Fanchini

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Quantum machine learning is a growing research field that aims to perform machine learning tasks assisted by a quantum computer. Kernel-based quantum machine learning models are paradigmatic examples where the kernel involves quantum states, and the Gram matrix is calculated from the overlapping between these states. With the kernel at hand, a regular machine learning model is used for the learning process. In this paper we investigate the quantum support vector machine and quantum kernel ridge models to predict the degree of non-Markovianity of a quantum system. We perform digital quantum simulation of amplitude damping and phase damping channels to create our quantum dataset. We elaborate on different kernel functions to map the data and kernel circuits to compute the overlapping between quantum states. We observe a good performance of the models.

Keywords: quantum, machine learning, kernel, non-markovianity

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Authors: T. Damak, S. Houidi, M. A. Ben Ayed, N. Masmoudi

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The Versatile Video Coding standard (VVC) is actually under development by the Joint Video Exploration Team (or JVET). An Adaptive Multiple Transforms (AMT) approach was announced. It is based on different transform modules that provided an efficient coding. However, the AMT solution raises several issues especially regarding the complexity of the selected set of transforms. This can be an important issue, particularly for a future industrial adoption. This paper proposed an efficient hardware implementation of the most used transform in AMT approach: the DCT II. The developed circuit is adapted to different block sizes and can reach a minimum frequency of 192 MHz allowing an optimized execution time.

Keywords: adaptive multiple transforms, AMT, DCT II, hardware, transform, versatile video coding, VVC

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Authors: Hechmi Saidi, Noureddine Hamdi

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The performance of decode and forward (DF) multihop free space optical (FSO) scheme deploying multiple input multiple output (MIMO) configuration under gamma-gamma (GG) statistical distribution, that adopts M-ary pulse position modulation (MPPM) coding, is investigated. We have extracted exact and estimated values of symbol-error rates (SERs) respectively. The probability density function (PDF)’s closed-form formula is expressed for our designed system. Thanks to the use of DF multihop MIMO FSO configuration and MPPM signaling, atmospheric turbulence is combatted; hence the transmitted signal quality is improved.

Keywords: free space optical, gamma gamma channel, radio frequency, decode and forward, multiple-input multiple-output, M-ary pulse position modulation, symbol error rate

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Authors: Dorit Alt, Nirit Raichel

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Educational practice is continually subjected to renewal needs, due mainly to the growing proportion of information communication technology, globalization of education, and the pursuit of quality. These types of renewal needs require developing updated instructional and assessment practices that put a premium on adaptability to the emerging requirements of present society. However, university instruction is criticized for not coping with these new challenges while continuing to exemplify the traditional instruction. In order to overcome this critical inadequacy between current educational goals and instructional methods, the LLAF consortium (including 16 members from 8 countries) is collaborating to create a curricular reform for lifelong learning (LLL) in teachers' education, health care and other applied fields. This project aims to achieve its objectives by developing, and piloting models for training students in LLL and promoting meaningful learning activities that could integrate knowledge with the personal transferable skills. LLAF has created a practical guide for teachers containing updated pedagogical strategies and assessment tools based on the constructivist approach for learning. This presentation will be limited to teachers' education only and to the contribution of a pre-pilot research aimed at providing a scale designed to measure constructivist activities in higher education learning environments. A mix-method approach was implemented in two phases to construct the scale: The first phase included a qualitative content analysis involving both deductive and inductive category applications of students' observations. The results foregrounded eight categories: knowledge construction, authenticity, multiple perspectives, prior knowledge, in-depth learning, teacher- student interaction, social interaction and cooperative dialogue. The students' descriptions of their classes were formulated as 36 items. The second phase employed structural equation modeling (SEM). The scale was submitted to 597 undergraduate students. The goodness of fit of the data to the structural model yielded sufficient fit results. This research elaborates the body of literature by adding a category of in-depth learning which emerged from the content analysis. Moreover, the theoretical category of social activity has been extended to include two distinctive factors: cooperative dialogue and social interaction. Implications of these findings for the LLAF project are discussed.

Keywords: constructivist learning, higher education, mix-methodology, lifelong learning

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Authors: César Garza

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In supervised binary classification and regression problems, it is well-known that learnability is equivalent to a uniform convergence of the hypothesis class, and if a problem is learnable, it is learnable by empirical risk minimization. For the general learning setting of unsupervised learning tasks, there are non-trivial learning problems where uniform convergence does not hold. We present here the task of learning centers of mass with an extra feature that “activates” some of the coordinates over the unit ball in a Hilbert space. We show that the learning problem is learnable under a stable RLM rule. We introduce a family of distributions over the domain space with some mild restrictions for which the sample complexity of uniform convergence for these problems must grow logarithmically with the dimension of the Hilbert space. If we take this dimension to infinity, we obtain a learnable problem for which the uniform convergence property fails for a vast family of distributions.

Keywords: statistical learning theory, learnability, uniform convergence, stability, regularized loss minimization

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Authors: Molly Pui Man Wong

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In this study, a blended and interactive e-learning Courseware that our team developed will be introduced, and our team’s experiences on how the e-learning Courseware and the flipped classroom benefit student learning in bioethics in the medical program will be shared. This study is a continuation of the previously established study, which provides a summary of the well-developed e-learning Courseware in a blended learning approach and an update on its efficiency and efficacy. First, a collection of animated videos capturing selected topics of bioethics and related ethical issues and dilemma will be introduced. Next, a selection of problem-based learning videos (“simulated doctor-patient role play”) with pop-up questions and discussions will be further discussed. Our recent findings demonstrated that these activities launched by the Courseware strongly engaged students in bioethics education and enhanced students’ critical thinking and creativity, which were consistent with the previous data in the preliminary studies. Moreover, the educational benefits of the online art exhibition, art jamming, and competition will be discussed, through which students could express bioethics through arts and enrich their learning in medical research in an interactive, fun, and entertaining way, strengthening their interests in bioethics. Furthermore, online survey questionnaires and focus group interviews were conducted. Consistent with the preliminary studies, our results indicated that implementing the e-learning Courseware with a flipped classroom in bioethics education enhanced both active learning and student engagement. In conclusion, our Courseware not only reinforces education in art, bioethics, and medicine but also benefits students in understanding and critical thinking in socio-ethical issues and serves as a valuable learning tool in bioethics teaching and learning.

Keywords: bioethics, courseware, e-learning, flipped classroom

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Authors: Ahlam Alnatour

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Background: To our knowledge, there is lack of studies that describe the experience of studying health promotion courses using an interactive approach, and compare students’ and teachers perceptions about this method of teaching. The purpose of this study is to provide a comparison between student and teacher experiences and perspectives in learning health promotion course using interactive learning. Design: A descriptive qualitative design was used to provide an in-depth description and understanding of students’ and teachers experiences and perceptions of learning health promotion courses using an interactive learning. Study Participants: About 14 fourteen students (seven male, seven female) and eight teachers at governmental university in northern Jordan participated in this study. Data Analysis: Conventional content analysis approach was used for participants’ scripts to gain an in-depth description for both students' and teacher’s experiences. Results: The main themes emerged from the data analysis describing the students’ and teachers perceptions of the interactive health promotion class: teachers’ and students positive experience in adopting interactive learning, advantages and benefits of interactive teaching, barriers to interactive teaching, and suggestions for improvement. Conclusion: Both teachers and students reflected positive attitudes toward interactive learning. Interactive learning helped to engage in learning process physically and cognitively. Interactive learning enhanced learning process, promote student attention, enhanced final performance, and satisfied teachers and students accordingly. Interactive learning approach should be adopted in teaching graduate and undergraduate courses using updated and contemporary strategies. Nursing scholars and educators should be motivated to integrate interactive learning in teaching different nursing courses.

Keywords: interactive learning, nursing, health promotion, qualitative study

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Authors: G. Krishna Mohana Rao, P. Ravi Kumar

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Milling is the process of removing unwanted material with suitable tool. Even though the milling process is having wider application, the vibration of machine tool and work piece during the process produces chatter on the products. Various methods of preventing the chatter have been incorporated into machine tool systems. Damper is cut into equal number of parts. Each part is called as finger. Multiple fingers were inserted in the hollow portion of the shank to reduce tool vibrations. In the present work, nonlinear static and dynamic analysis of the damper inserted end milling cutter used to reduce the chatter was done. A comparison is made for the milling cutter with multiple dampers. Surface roughness was determined by machining with multiple finger inserted milling cutters.

Keywords: damping inserts, end milling, vibrations, nonlinear dynamic analysis, number of fingers

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Authors: Y. Kavanagh, N. O'Hara, R. Palmer, P. Lowe, D. Rafferty

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Physical Physics is a physics education methodology for games programfmes that integrates physical activity with movement tracking and modelling. It significantly enhances the learning experience and it is effective in illustrating how physics is core in games design and programming, while allowing students to be active participants and take ownership of the learning process. It has been successfully piloted with undergraduate students studying Games Development.

Keywords: activity, enhanced learning, game development, physics

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Authors: YuLung Wu, YuTien Wu, ShuMey Yu

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Game-based learning can enhance the learning motivation of students and provide a means for them to learn through playing games. This study used augmented reality technology to develop an interactive card game as a game-based teaching aid for delivering elementary school science course content with the aim of enhancing student learning processes and outcomes. Through playing the proposed card game, students can familiarize themselves with appearance, features, and foraging behaviors of insects. The system records the actions of students, enabling teachers to determine their students’ learning progress. In this study, 37 students participated in an assessment experiment and provided feedback through questionnaires. Their responses indicated that they were significantly more motivated to learn after playing the game, and their feedback was mostly positive.

Keywords: game-based learning, learning motivation, teaching aid, augmented reality

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Authors: Sakchai Rachniyom

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Owing to the ASEAN community will formally take place in the few months; therefore, Thais should realize about the importance of English language. Since, it is regarded as a working language in the community. To promote Science students’ English proficiency, teacher should be able to teach in English language appropriately and effectively. The purposes of the quasi – experimental research are (1) to measure the learning achievement, (2) to evaluate students’ satisfaction on the teaching and learning and (3) to study the consequences of co – teaching method in order comprehend the learning achievement and improvement. The participants were 40 general science students teacher. Two types of research instruments were included; (1) an achievement test, and (2) a questionnaire. This research was conducted for 1 semester. The statistics used in this research were arithmetic mean and standard deviation. The findings of the study revealed that students’ achievement score was significantly increased at statistical level .05 and the students satisfied the teaching and learning at the highest level . The students’ involvement and teachers’ support were promoted. It was also reported students’ learning was improved by co – teaching method.

Keywords: co – teaching method, learning science in english, teacher, education

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Authors: Nadir Ali Mugheri

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This study has explored the perceptions of English language teachers (ELT) regarding use of technology in learning English as a second language (L2) at Universities in Pakistan. In this regard, 200 ELT teachers from 80 leading universities were selected through a judgmental sampling method. Results established that most of the teachers supported integration and incorporation of technology in the language classroom so as to teach L2 in an effective and efficient way. This study unearthed that the teachers termed the use of technology in learning English as a second language (ESL) as a positive step towards enhancing the learning capabilities and improving the personal traits of the students or learners. Findings suggest that the integration of technology in the language learning makes the learners within the classroom active and enthusiastic, and the teachers need to be equipped with the latest knowledge of mobile assisted language learning (MALL) and computer assisted language learning (CALL) so that they may ensure use of this innovative technology in their teaching practices. Results also indicated that the technology has proved itself a stimulus for improving language in the ELT milieu. The use of technology helps teachers develop themselves professionally. This study discovered that there are many determinants that make teaching and learning within the classroom efficacious, while the use of technology is one of them. Data was collected through qualitative design in order to get a complete depiction. Semi-structured interviews were conducted and analyzed through thematic analysis.

Keywords: english language teaching, computer assisted language learning, use of technology, thematic analysis

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Authors: Stanle Madonsela

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For learning to take place effectively, learners have to use language. Language becomes a critical tool by which to communicate, to express feelings, desires and thoughts, and most of all to learn. However, each individual’s capacity to use language is unique. In multilingual countries, classrooms usually comprise learners from different language backgrounds, and therefore the language used for teaching and learning requires rethinking. Interaction in the classroom, if done in a language that is understood by the learners, could maximise the outcomes of learning. This paper explores the extent to which the use of a single code becomes a source of anxiety to learners in multilingual classrooms in South African schools. It contends that a multilingual approach in the learning process should be explored in order to promote learner autonomy in the learning process.

Keywords: anxiety, classroom, foreign language teaching, multilingual

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Authors: Ashutosh Mishra, Nikhil Goyal

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A 3D facial emotion recognition model based on deep learning is proposed in this paper. Two convolution layers and a pooling layer are employed in the deep learning architecture. After the convolution process, the pooling is finished. The probabilities for various classes of human faces are calculated using the sigmoid activation function. To verify the efficiency of deep learning-based systems, a set of faces. The Kaggle dataset is used to verify the accuracy of a deep learning-based face recognition model. The model's accuracy is about 65 percent, which is lower than that of other facial expression recognition techniques. Despite significant gains in representation precision due to the nonlinearity of profound image representations.

Keywords: facial recognition, computational intelligence, convolutional neural network, depth map

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Authors: May George

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Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language, i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the students became mechanical and cannot produce the language easily. As a result, they are unable to predict the meaning of words in the context by relying heavily on the teacher, in that they cannot link their prior knowledge or even identify the meaning of the words without the support of the teacher. This study explores how the teacher guides students learning during the inference process and what are the processes of learning that can direct student’s inference.

Keywords: inference, reading, Arabic, language acquisition

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Authors: Lamiche Chaabane

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In this study, a new method for solving sequence alignment problem is proposed, which is named ITS (Improved Tabu Search). This algorithm is based on the classical Tabu Search (TS). ITS is implemented in order to obtain results of multiple sequence alignment. Several ideas concerning neighbourhood generation, move selection mechanisms and intensification/diversification strategies for our proposed ITS is investigated. ITS have generated high-quality results in terms of measure of scores in comparison with the classical TS and simple iterative search algorithm.

Keywords: multiple sequence alignment, tabu search, improved tabu search, neighbourhood generation, selection mechanisms

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Authors: Chia Wei Lim, Ning Yan

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The subject of reactor design, dealing with the transformation of chemical feedstocks into more valuable products, constitutes the central idea of chemical engineering. Despite its importance, the way it is taught to chemical engineering undergraduates has stayed virtually the same over the past several decades, even as the chemical industry increasingly leans towards the use of software for the design and daily monitoring of chemical plants. As such, there has been a widening learning gap as chemical engineering graduates transition from university to the industry since they are not exposed to effective platforms that relate the fundamental concepts taught during lectures to industrial applications. While the success of technology enhanced learning (TEL) has been demonstrated in various chemical engineering subjects, TELs in the teaching of reactor design appears to focus on the simulation of reactor processes, as opposed to arguably more important ideas such as the selection and optimization of reactor configuration for different types of reactions. This presents an opportunity for us to utilize the readily available easy-to-use MATLAB App platform to create an educational tool to aid the learning of fundamental concepts of reactor design and to link these concepts to the industrial context. Here, interactive software for the learning of reactor design has been developed to narrow the learning gap experienced by chemical engineering undergraduates. Dubbed the ReactorDesign App, it enables students to design reactors involving complex design equations for industrial applications without being overly focused on the tedious mathematical steps. With the aid of extensive visualization features, the concepts covered during lectures are explicitly utilized, allowing students to understand how these fundamental concepts are applied in the industrial context and equipping them for their careers. In addition, the software leverages the easily accessible MATLAB App platform to encourage self-directed learning. It is useful for reinforcing concepts taught, complementing homework assignments, and aiding exam revision. Accordingly, students are able to identify any lapses in understanding and clarify them accordingly. In terms of the topics covered, the app incorporates the design of different types of isothermal and non-isothermal reactors, in line with the lecture content and industrial relevance. The main features include the design of single reactors, such as batch reactors (BR), continuously stirred tank reactors (CSTR), plug flow reactors (PFR), and recycle reactors (RR), as well as multiple reactors consisting of any combination of ideal reactors. A version of the app, together with some guiding questions to aid explorative learning, was released to the undergraduates taking the reactor design module. A survey was conducted to assess its effectiveness, and an overwhelmingly positive response was received, with 89% of the respondents agreeing or strongly agreeing that the app has “helped [them] with understanding the unit” and 87% of the respondents agreeing or strongly agreeing that the app “offers learning flexibility”, compared to the conventional lecture-tutorial learning framework. In conclusion, the interactive ReactorDesign App has been developed to encourage self-directed explorative learning of the subject and demonstrate the industrial applications of the taught design concepts.

Keywords: explorative learning, reactor design, self-directed learning, technology enhanced learning

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Authors: K. M. Wong

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Engineering education is crucial to technological innovation and advancement worldwide by generating young talents who are able to integrate scientific principles and design practical solutions for real-world problems. Graduates of engineering curriculums are expected to demonstrate an extensive set of learning outcomes as required in international accreditation agreements for engineering academic qualifications, such as the Washington Accord and the Sydney Accord. On the other hand, students have different learning preferences of receiving, processing and internalizing knowledge and skills. If the learning environment is advantageous to the learning styles of the students, there is a higher chance that the students can achieve the intended learning outcomes. With proper identification of the learning styles of the students, corresponding teaching strategies can then be developed for more effective learning. This research was an investigation of learning styles of tertiary students studying higher diploma programmes in Hong Kong. Data from over 200 students in engineering programmes were collected and analysed to identify the learning characteristics of students. A small-scale longitudinal study was then started to gather academic results of the students throughout their two-year engineering studies. Preliminary results suggested that the sample students were reflective, sensing, visual, and sequential learners. Observations from the analysed data not only provided valuable information for teachers to design more effective teaching strategies, but also provided data for further analysis with the students’ academic results. The results generated from the longitudinal study shed light on areas of improvement for more effective engineering curriculum design for better teaching and learning.

Keywords: learning styles, learning characteristics, engineering education, vocational education, Hong Kong

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Carol C. Opara, Olukemi E. Adetuyi-Olu-Francis

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The need for ICT in Teacher Education due to the nature of 21st-century learners who are computer citizens is essential. The recent increase in the use of Mobile phones has equally revealed the importance of Mobile Applications for learning purposes. However, teacher-trainees and the trainers need to be well-grounded in basic ICT skills for an appropriate outcome. This study seeks to assess the use of Mobile Applications for language learning in Teacher Education teaching-learning process. A 22-item e-questionnaire was used to elicit information from teacher-trainers and teachers-trainees from Faculties of Education in Nigerian Universities. Major findings of this study include: That teacher-education sector is not adequately prepared for manipulative use of ICT and Mobile Applications for teaching and learning process; etc. It was recommended among others that, teacher-trainers should be trained and re-trained on the manipulative use of Mobile devices and the several applications for teaching-learning purpose, especially language education.

Keywords: information and communications technology, ICT, language learning, mobile application, sustainable development, teacher education

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Authors: Sanjay Adhikesaven

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Workplace accidents are a critical problem that causes many deaths, injuries, and financial losses. Climate change has a severe impact on industrial workers, partially caused by global warming. To reduce such casualties, it is important to proactively find unsafe environments where injuries could occur by detecting the use of personal protective equipment (PPE) and identifying unsafe activities. Thus, we propose an industrial workplace alerting and monitoring platform to detect PPE use and classify unsafe activity in group settings involving multiple humans and objects over a long period of time. Our proposed method is the first to analyze prolonged actions involving multiple people or objects. It benefits from combining pose estimation with PPE detection in one platform. Additionally, we propose the first open-source annotated data set with video data from industrial workplaces annotated with the action classifications and detected PPE. The proposed system can be implemented within the surveillance cameras already present in industrial settings, making it a practical and effective solution.

Keywords: computer vision, deep learning, workplace safety, automation

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Authors: Gilbert Makanda, Roelf Sypkens

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A mathematical model for knowledge acquisition in teaching and learning is proposed. In this study we adopt the mathematical model that is normally used for disease modelling into teaching and learning. We derive mathematical conditions which facilitate knowledge acquisition. This study compares the effects of dropping out of the course at early stages with later stages of learning. The study also investigates effect of individual interaction and learning from other sources to facilitate learning. The study fits actual data to a general mathematical model using Matlab ODE45 and lsqnonlin to obtain a unique mathematical model that can be used to predict knowledge acquisition. The data used in this study was obtained from the tutorial test results for mathematics 2 students from the Central University of Technology, Free State, South Africa in the department of Mathematical and Physical Sciences. The study confirms already known results that increasing dropout rates and forgetting taught concepts reduce the population of knowledgeable students. Increasing teaching contacts and access to other learning materials facilitate knowledge acquisition. The effect of increasing dropout rates is more enhanced in the later stages of learning than earlier stages. The study opens up a new direction in further investigations in teaching and learning using differential equations.

Keywords: differential equations, knowledge acquisition, least squares nonlinear, dynamical systems

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Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

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Authors: Carlos Oliveira, Ulrick Pimentel

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Digital games have conquered a growing space in the lives of children, adolescents and adults. In this perspective, the use of this resource has shown to be an important strategy that facilitates the learning process. This research is a literature review on the use of serious games in teaching, which shows the characteristics of these games, the benefits and possible harms that this resource can produce, in addition to the possible methods of evaluating the effectiveness of this resource in teaching. The results point out that Serious Games have significant potential as a tool for instruction. However, their effectiveness in terms of learning outcomes is still poorly studied, mainly due to the complexity involved in evaluating intangible measures.

Keywords: serious games, learning, application, literature review

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Authors: Tomas Premoli, Sareh Rowlands

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In this study, we investigate the impact of various convolutional neural network (CNN) architectures on the accuracy of diagnosing Alzheimer’s disease (AD) using patient MRI scans. Alzheimer’s disease is a debilitating neurodegenerative disorder that affects millions worldwide. Early, accurate, and non-invasive diagnostic methods are required for providing optimal care and symptom management. Deep learning techniques, particularly CNNs, have shown great promise in enhancing this diagnostic process. We aim to contribute to the ongoing research in this field by comparing the effectiveness of different CNN architectures and providing insights for future studies. Our methodology involved preprocessing MRI data, implementing multiple CNN architectures, and evaluating the performance of each model. We employed intensity normalization, linear registration, and skull stripping for our preprocessing. The selected architectures included VGG, ResNet, and DenseNet models, all implemented using the Keras library. We employed transfer learning and trained models from scratch to compare their effectiveness. Our findings demonstrated significant differences in performance among the tested architectures, with DenseNet201 achieving the highest accuracy of 86.4%. Transfer learning proved to be helpful in improving model performance. We also identified potential areas for future research, such as experimenting with other architectures, optimizing hyperparameters, and employing fine-tuning strategies. By providing a comprehensive analysis of the selected CNN architectures, we offer a solid foundation for future research in Alzheimer’s disease diagnosis using deep learning techniques. Our study highlights the potential of CNNs as a valuable diagnostic tool and emphasizes the importance of ongoing research to develop more accurate and effective models.

Keywords: Alzheimer’s disease, convolutional neural networks, deep learning, medical imaging, MRI

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Authors: Joan Esper Kuhnly, Jess Holden, Lynn Shelley, Nicole Kuhnly

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Empathy serves as a foundational nursing principle inherent in the nurse’s ability to form those relationships from which to care for patients. Evidence supports, including empathy in nursing and healthcare education, but there is limited data on what methods are effective to do so. Building evidence supports experiential and interactive learning methods to be effective for students to gain insight and perspective from a personalized experience. The purpose of this project is to evaluate learning activities designed to promote the attainment of empathic behaviors across 5 levels of the nursing curriculum. Quantitative analysis will be conducted on data from pre and post-learning activities using the Toronto Empathy Questionnaire. The main hypothesis, that simulation learning activities will increase empathy, will be examined using a repeated measures Analysis of Variance (ANOVA) on Pre and Post Toronto Empathy Questionnaire scores for three simulation activities (Stroke, Poverty, Dementia). Pearson product-moment correlations will be conducted to examine the relationships between continuous demographic variables, such as age, credits earned, and years practicing, with the dependent variable of interest, Post Test Toronto Empathy Scores. Krippendorff’s method of content analysis will be conducted to identify the quantitative incidence of empathic responses. The researchers will use Colaizzi’s descriptive phenomenological method to describe the students’ simulation experience and understand its impact on caring and empathy behaviors employing bracketing to maintain objectivity. The results will be presented, answering multiple research questions. The discussion will be relevant to results and educational pedagogy in the nursing curriculum as they relate to the attainment of empathic behaviors.

Keywords: curriculum, empathy, nursing, simulation

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Authors: Omid Noroozi

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Digital dialogue games have opened up opportunities for learning skills by engaging students in complex problem solving that mimic real world situations, without importing unwanted constraints and risks of the real world. Digital dialogue games can be motivating and engaging to students for fun, creative thinking, and learning. This study explored how undergraduate students engage with argumentative discourse activities which have been designed to intensify debate. A pre-test, post-test design was used with students who were assigned to groups of four and asked to debate a controversial topic with the aim of exploring various 'pros and cons' on the 'Genetically Modified Organisms (GMOs)'. Findings reveal that the Digital dialogue game can facilitate argumentation-based learning. The digital Dialogue game was also evaluated positively in terms of students’ satisfaction and learning experiences.

Keywords: argumentation, dialogue, digital game, learning, motivation

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Authors: Naser Ojaroudi Parchin, Haleh Jahanbakhsh Basherlou, Raed A. Abd-Alhameed, Peter S. Excell

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In this paper, a multiple-input/multiple-output (MIMO) antenna design with polarization and radiation pattern diversity is presented for future smartphones. The configuration of the design consists of four double-fed circular-ring antenna elements located at different edges of the printed circuit board (PCB) with an FR-4 substrate and overall dimension of 75×150 mm². The antenna elements are fed by 50-Ohm microstrip-lines and provide polarization and radiation pattern diversity function due to the orthogonal placement of their feed lines. A good impedance bandwidth (S₁₁ ≤ -10 dB) of 3.4-3.8 GHz has been obtained for the smartphone antenna array. However, for S₁₁ ≤ -6 dB, this value is 3.25-3.95 GHz. More than 3 dB realized gain and 80% total efficiency are achieved for the single-element radiator. The presented design not only provides the required radiation coverage but also generates the polarization diversity characteristic.

Keywords: cellular communications, multiple-input/multiple-output systems, mobile-phone antenna, polarization diversity

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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