Search results for: learning curve

Authors: Kulachai Kultawanich, Prakob Koraneekij, Jaitip Na-Songkhla

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The way of learning has been changed into a new paradigm since the improvement of network and communication technology, so learners have to interact with massive amount of the information. Thus, information literacy has become a critical set of abilities required by every college and university in the world. Connectivism is considered to be an alternative way to design information literacy course in online learning environment, such as Virtual Classroom (VC). With the change of learning pedagogy, VC is employed to improve the social capability by integrating cloud-based technology. This paper aims to study the use of Cloud-based Virtual Classroom (CBVC) in Connectivism learning process to enhance information literacy and self-efficacy of twenty-one undergraduate students who registered in an e-publishing course at Chulalongkorn University. The data were gathered during 6 weeks of the study by using the following instruments: (1) Information literacy test (2) Information literacy rubrics (3) Information Literacy Self-Efficacy (ILSE) Scales and (4) Questionnaire. The result indicated that students have information literacy and self-efficacy posttest mean scores higher than pretest mean scores at .05 level of significant after using CBVC in Connectivism learning process. Additionally, the study identified that the Connectivism learning process proved useful for developing information rich environment and a sense of community, and the CBVC proved useful for developing social connection.

Keywords: cloud-based, virtual classroom, connectivism, information literacy

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Authors: Ben Nwokenkwo, Michael M. Eze, Felix Ike

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The need to study trends in land values around institutions of higher learning cannot be overemphasized. Numerous studies in Nigeria have investigated the economic, and social influence of the sitting of institutions of higher learning at the micro, meso and macro levels. However, very few studies have evaluated the temporal extent at which such institution influences local land values. Since institutions greatly influence both the physical and environmental aspects of their immediate vicinity, attention must be taken to understand the influence of such changes on land values. This study examines the trend in land values using the Mann-Kendall analysis in order to determine if, between its beginning and end, a monotonic increase, decrease or stability exist in the land values across six institutions of higher learning for the period between 2004 and 2014. Specifically, The analysis was applied to the time series of the price(or value) of the land .The results of this study revealed that land values has either been increasing or remained stabled across all the institution sampled. The study finally recommends measures that can be put in place as counter magnets for land values estimation across institutions of higher learning.

Keywords: influence, land, trend, value

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Authors: Mohammad Saleem, Neeta Kumar, Anita Sharma, Sazina Muzammil

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It is observed that some of the dental students in our setting take less interest in medical subjects. Various teaching methods are focus of research interest currently and being tried to generate interest among students. An approach of interactive integrated tutorial was used to assess its feasibility in teaching medical subjects to dental undergraduates. The aim was to generate interest and promote active self-learning among students. The objectives were to (1) introduce the integrated interactive learning method through two departments, (2) get feedback from the students and faculty on feasibility and effectiveness of this method. Second-year students in Bachelor of Dental Surgery course were divided into two groups. Each group was asked to study physiology and pathology of a common and important condition (anemia and hypertension) in a week’s time. During the tutorial, students asked questions on physiology and pathology of that condition from each other in the presence of teachers of both physiology and pathology departments. The teachers acted only as facilitators. After the session, the feedback from students and faculty on this alternative learning method was obtained. Results: Majority of the students felt that this method of learning is enjoyable, helped to develop reasoning skills and ability to correlate and integrate the knowledge from two related fields. Majority of the students felt that this kind of learning led to better understanding of the topic and motivated them towards deep learning. Teachers observed that the study promoted interdepartmental cross-discipline collaboration and better students’ linkages. Conclusion: Interactive integrated tutorial is effective in motivating dental students for better and deep learning of medical subjects.

Keywords: active learning, education, integrated, interactive, self-learning, tutorials

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

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Authors: Maria Luisa Boninelli

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This study wants to explore the effects of a mediated intervention program in a primary school. The participants where 120 students aged 8-9, half of them Italian and half immigrants of first or second generation. The activities consisted on the cognitive enhancement of the participants through Feuerstein’s Instrumental Enrichment, (IE) and on an activity centred on body awareness and mediated learning experience. Given that there are limited studied on learners in remedial schools, the current study intented to hypothesized that participants exposed to mediation would yiel a significant improvement in cognitive functioning. Hypothesis One proposed that, following the intervention, improved Q1vata scores of the participants would occur in each of the groups. Hypothesis two postulated that participants within the Mediated Learning Experience would perform significantly better than those group of control. For the intervention a group of 60 participants constituted a group of Mediation sample and were exposed to Mediated Learning Experience through Enrichment Programm. Similiary the other 60 were control group. Both the groups have students with special needs and were exposed to the same learning goals. A pre-experimental research design, in particular a one-group pretest-posttest approach was adopted. All the participants in this study underwent pretest and post test phases whereby they completed measures according to the standard instructions. During the pretest phase, all the participants were simultaneously exposed to Q1vata test for logical and linguistic evaluation skill. During the mediation intervention, significant improvement was demonstrated with the group of mediation. This supports Feuerstein's Theory that initial poor performance was a result of a lack of mediated learning experience rather than inherent difference or deficiencies. Furthermore the use of an appropriate mediated learning enabled the participants to function adequately.

Keywords: cognitive structural modifiability, learning to learn, mediated learning experience, Reuven Feuerstein, special needs

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Authors: Poom Thiparapkul, Tanat Jiravansirikul, Pakpoom Thongsari

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This study explores the design of electric vehicle (EV) dashboards with a focus on user interaction. Findings from a Thai sample reveal a preference for physical buttons over touch interfaces due to their immediate feedback. Touchscreens lack this assurance, leading to potential uncertainty. Users' smartphone experiences create a learning curve that doesn't translate well to in-car touch systems. Gender-wise, females exhibit slightly longer decision times. Designing EV dashboards should consider these factors, prioritizing user experience while avoiding overreliance on smartphone principles. A successful example is Subaru XV's design, which calculates screen angles and button positions for targeted users. In summary, EV dashboards should be intuitive, minimize touch dependency, and accommodate user habits. Balancing modernity with functionality can enhance driving experiences while ensuring safety. A user-centered approach, acknowledging gender differences, will yield efficient and safe driving environments.

Keywords: user experience design, user experience, electric vehicle, dashboard design, Thailand driver.

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Authors: Belkhadir Radouane

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In this study, author tried to explore the beliefs of some Moroccan teachers working in the delegations of Safi and Youcefia about the usefulness of first and second languages in learning the third language. More specifically, author attempted to see the extent to which these teachers believe that a first and second language can serve students in learning a third one. The first language in this context is Arabic, the second is French, and the third is English. The teachers’ beliefs were gathered through a questionnaire that was addressed via Google Forms. Then, the results were analyzed using the same application. It was found that teachers are positive about the usefulness of the first and second language in learning the third one, but most of them rarely use in a conscious way activities that serve this purpose.

Keywords: Bilinguilism, teachers beliefs, English as ESL, Morocco

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Authors: Gayathri Sadanala, Shibam Pokhrel, Owen Murphy

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In the ever-evolving landscape of education, Virtual Reality (VR) environments offer a promising avenue for enhancing student engagement and learning experiences. However, understanding and predicting student behavior within these immersive settings remain challenging tasks. This paper presents a comprehensive study on the predictive modeling of student behavior in VR using machine learning techniques. We introduce a rich data set capturing student interactions, movements, and progress within a VR orientation program. The dataset is divided into training and testing sets, allowing us to develop and evaluate predictive models for various aspects of student behavior, including engagement levels, task completion, and performance. Our machine learning approach leverages a combination of feature engineering and model selection to reveal hidden patterns in the data. We employ regression and classification models to predict student outcomes, and the results showcase promising accuracy in forecasting behavior within VR environments. Furthermore, we demonstrate the practical implications of our predictive models for personalized VR-based learning experiences and early intervention strategies. By uncovering the intricate relationship between student behavior and VR interactions, we provide valuable insights for educators, designers, and developers seeking to optimize virtual learning environments.

Keywords: interaction, machine learning, predictive modeling, virtual reality

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Authors: Megha Gupta, Nupur Prakash

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Identification of plant diseases has been performed using machine learning and deep learning models on the datasets containing images of healthy and diseased plant leaves. The current study carries out an evaluation of some of the deep learning models based on convolutional neural network (CNN) architectures for identification of plant diseases. For this purpose, the publicly available New Plant Diseases Dataset, an augmented version of PlantVillage dataset, available on Kaggle platform, containing 87,900 images has been used. The dataset contained images of 26 diseases of 14 different plants and images of 12 healthy plants. The CNN models selected for the study presented in this paper are AlexNet, ZFNet, VGGNet (four models), GoogLeNet, and ResNet (three models). The selected models are trained using PyTorch, an open-source machine learning library, on Google Colaboratory. A comparative study has been carried out to analyze the high degree of accuracy achieved using these models. The highest test accuracy and F1-score of 99.59% and 0.996, respectively, were achieved by using GoogLeNet with Mini-batch momentum based gradient descent learning algorithm.

Keywords: comparative analysis, convolutional neural networks, deep learning, plant disease identification

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Authors: Pavan K. Rallabandi, Kailash C. Patidar

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In this paper, we present an optimization technique or a learning algorithm using the hybrid architecture by combining the most popular sequence recognition models such as Recurrent Neural Networks (RNNs) and Hidden Markov models (HMMs). In order to improve the sequence or pattern recognition/ classification performance by applying a hybrid/neural symbolic approach, a gradient descent learning algorithm is developed using the Real Time Recurrent Learning of Recurrent Neural Network for processing the knowledge represented in trained Hidden Markov Models. The developed hybrid algorithm is implemented on automata theory as a sample test beds and the performance of the designed algorithm is demonstrated and evaluated on learning the deterministic finite state automata.

Keywords: hybrid systems, hidden markov models, recurrent neural networks, deterministic finite state automata

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Authors: Eirini Busack

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Since the outbreak of the Covid-19 pandemic and the sudden transfer to online teaching, teachers have struggled to reconstruct their teaching and learning materials to adapt them to the new reality of online teaching and learning. Consequently, the pupils’ learning was disrupted during this orientation phase. Due to the above situation, teachers from all fields concluded that it is vital that their pupils should be able to continue their learning even without the teacher being physically present. Various websites and applications have been in use since then in hope that pupils will still enjoy a qualitative education; unfortunately, this was often not the case. To address this issue, it was therefore decided to focus the research on the development of digital learning paths. The fundamentals of these learning paths include the implementation of scenario-based learning (digital storytelling), the integration of media-didactic theory to make it pedagogically appropriate for learners, alongside instructional design knowledge and the drive to promote autonomous learners. This particular research is being conducted within the frame of the research project “Sustainable integration of subject didactic digital teaching-learning concepts” (InDiKo, 2020-2023), which is currently conducted at the University of Education Karlsruhe and investigates how pre-service teachers can acquire the necessary interdisciplinary and subject-specific media-didactic competencies to provide their future learners with digitally enhanced learning opportunities, and how these competencies can be developed continuously and sustainably. As English is one of the subjects involved in this project, the English Department prepared a seminar for the pre-service secondary teachers: “Media-didactic competence development: Developing learning paths & Digital Storytelling for English grammar teaching.” During this seminar, the pre-service teachers plan and design a Moodle-based differentiated lesson sequence on an English grammar topic that is to be tested by secondary school pupils. The focus of the present research is to assess the secondary school pupils’ expectations from an English grammar-focused digital learning path created by pre-service English teachers. The nine digital learning paths that are to be distributed to 25 pupils were produced over the winter and the current summer semester as the artifact of the seminar. Finally, the data to be quantitatively analysed and interpreted derive from the online questionnaires that the secondary school pupils fill in so as to reveal their expectations on what they perceive as a stimulating and thus effective grammar-focused digital learning path.

Keywords: digital storytelling, learning paths, media-didactics, autonomous learning

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Authors: Vaida Jurgile

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Intercultural learning is one of the approaches taken to understand the cultural diversity of the modern world and to accept changes in cultural identity and otherness and the expression of tolerance. During intercultural learning, students develop their abilities to interact and communicate with their group members. These abilities help to understand social and cultural differences, to form one’s identity, and to give meaning to intercultural learning. Intercultural education recognizes that a true understanding of differences and similarities of another culture is necessary in order to lay the foundations for working together with others, which contributes to the promotion of intercultural dialogue, appreciation of diversity, and cultural exchange. Therefore, it is important to examine the concept of intercultural learning, revealed through students’ learning experiences and understanding of how this learning takes place and what significance this phenomenon has in higher education. At a scientific level, intercultural learning should be explored in order to uncover the influence of cultural identity, i.e., intercultural learning should be seen in a local context. This experience would provide an opportunity to learn from various everyday intercultural learning situations. Intercultural learning can be not only a form of learning but also a tool for building understanding between people of different cultures. The research object of the study is the process of intercultural learning. The aim of the dissertation is to develop a grounded theory of the process of learning in an intercultural study environment, revealing students’ learning experiences. The research strategy chosen in this study is a constructivist grounded theory (GT). GT is an inductive method that seeks to form a theory by applying the systematic collection, synthesis, analysis, and conceptualization of data. The targeted data collection was based on the analysis of data provided by previous research participants, which revealed the need for further research participants. During the research, only students with at least half a year of study experience, i.e., who have completed at least one semester of intercultural studies, were purposefully selected for the research. To select students, snowballing sampling was used. 18 interviews were conducted with students representing 3 different fields of sciences (social sciences, humanities, and technology sciences). In the process of intercultural learning, language expresses and embodies cultural reality and a person’s cultural identity. It is through language that individual experiences are expressed, and the world in which Others exist is perceived. The increased emphasis is placed on the fact that language conveys certain “signs’ of communication and perception with cultural value, enabling the students to identify the Self and the Other. Language becomes an important tool in the process of intercultural communication because it is only through language that learners can communicate, exchange information, and understand each other. Thus, in the process of intercultural learning, language either promotes interpersonal relationships with foreign students or leads to mutual rejection.

Keywords: intercultural learning, grounded theory, students, other

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Authors: David S. Rosenstein

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The author believes that modern spoken languages should be equally difficult (or easy) to learn, since all normal children learning their native languages do so at approximately the same rate and with the same competence, progressing from easy to more complex grammar and syntax in the same way. Why then, do some languages seem more difficult than others? Perhaps people are referring to the written language, where it may be true that mastering Chinese requires more time than French, which in turn requires more time than Spanish. But this may be marginal, since Chinese and French children quickly catch up to their Spanish peers in reading comprehension. Rather, the real differences in difficulty derive from two sources: hardened L1 language habits trying to cope with contrasting L2 habits; and unfamiliarity with unique L2 characteristics causing faulty expectations. It would seem that effective L2 teaching and learning must take these two sources of difficulty into consideration. The author feels that the latter (faulty expectations) causes the greatest difficulty, making effective teaching and learning somewhat different for each given foreign language. Examples from Chinese and other languages are presented.

Keywords: learning different languages, language learning difficulties, faulty language expectations

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Authors: Shahin Farajifar, Azadeh Safadoust, Ali Akbar Mahboubi

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A study was conducted to evaluate hydraulic properties of a sandy loam soil and corn (Zea mays L.) crop production under a short-term tillage and manure combinations field experiment carried out in west of Iran. Treatments included composted cattle manure application rates [0, 30, and 60 Mg (dry weight) ha-1] and tillage systems [no-tillage (NT), chisel plowing (CP), and moldboard plowing (MP)] arranged in a split-plot design. Soil water characteristic curve (SWCC) and saturated hydraulic conductivity (Ks) were significantly affected by manure and tillage treatments. At any matric suction, the soil water content was in the order of MP>CP>NT. At all matric suctions, the amount of water retained by the soil increased as manure application rate increased (i.e. 60>30>0 Mg ha-1). Similar to the tillage effects, at high suctions the differences of water retained due to manure addition were less than that at low suctions. The change of SWCC from tillage methods and manure applications may attribute to the change of pore size and aggregate size distributions. Soil Ks was in the order of CP>MP>NT for the first two layers and in the order of MP>CP and NT for the deeper soil layer. The Ks also increased with increasing rates of manure application (i.e. 60>30>0 Mg ha-1). This was due to the increase in the total pore size and continuity.

Keywords: corn, manuure, saturated hydraulic conductivity, soil water characteristic curve, tillage

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Authors: Leidy M. Aldana, Jorge E. Camargo

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Adversarial Machine Learning has gained importance in recent years as Cybersecurity has gained too, especially malware, it has affected different entities and people in recent years. This paper shows a literature review about defense methods created to prevent adversarial machine learning attacks, firstable it shows an introduction about the context and the description of some terms, in the results section some of the attacks are described, focusing on detecting adversarial examples before coming to the machine learning algorithm and showing other categories that exist in defense. A method with five steps is proposed in the method section in order to define a way to make the literature review; in addition, this paper summarizes the contributions in this research field in the last seven years to identify research directions in this area. About the findings, the category with least quantity of challenges in defense is the Detection of adversarial examples being this one a viable research route with the adaptive approach in attack and defense.

Keywords: Malware, adversarial, machine learning, defense, attack

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Authors: Gihan Thilakarathna, Fernando Ishara, Rathnayake Yasith, Bandara A. M. R. Y.

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E-learning is a crucial component of intelligent education. Even in the midst of a pandemic, E-learning is becoming increasingly important in the educational system. Several e-learning programs are accessible for students. Here, we decided to create an e-learning framework for children. We've found a few issues that teachers are having with their online classes. When there are numerous students in an online classroom, how does a teacher recognize a student's focus on academics and below-the-surface behaviors? Some kids are not paying attention in class, and others are napping. The teacher is unable to keep track of each and every student. Key challenge in e-learning is online exams. Because students can cheat easily during online exams. Hence there is need of exam proctoring is occurred. In here we propose an automated online exam cheating detection method using a web camera. The purpose of this project is to present an E-learning platform for math education and include games for kids as an alternative teaching method for math students. The game will be accessible via a web browser. The imagery in the game is drawn in a cartoonish style. This will help students learn math through games. Everything in this day and age is moving towards automation. However, automatic answer evaluation is only available for MCQ-based questions. As a result, the checker has a difficult time evaluating the theory solution. The current system requires more manpower and takes a long time to evaluate responses. It's also possible to mark two identical responses differently and receive two different grades. As a result, this application employs machine learning techniques to provide an automatic evaluation of subjective responses based on the keyword provided to the computer as student input, resulting in a fair distribution of marks. In addition, it will save time and manpower. We used deep learning, machine learning, image processing and natural language technologies to develop these research components.

Keywords: math, education games, e-learning platform, artificial intelligence

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Authors: Matthias Grünke

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In this single-case study, we evaluated the effects of a self-graphing intervention to help students improve their reading fluency. Our participant was a 10-year-old girl with a suspected learning disability in reading. We applied an ABAB reversal design to test the efficacy of our approach. The dependent measure was the number of correctly read words from a children’s book within five minutes. Our participant recorded her daily performance using a simple line diagram. Results indicate that her reading rate improved simultaneously with the intervention and dropped as soon as the treatment was suspended. The findings give reasons for optimism that our simple strategy can be a very effective tool in supporting students with learning disabilities to boost their reading fluency.

Keywords: single-case study, learning disabilities, elementary education, reading problems, reading fluency

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Authors: Enrique Barra, Aldo Gordillo, Juan Quemada

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This paper presents the Virtual Science Hub platform. It is an open source platform that combines a social network, an e-learning authoring tool, a video conference service and a learning object repository for science teaching enrichment. These four main functionalities fit very well together. The platform was released in April 2012 and since then it has not stopped growing. Finally we present the results of the surveys conducted and the statistics gathered to validate this approach.

Keywords: e-learning, platform, authoring tool, science teaching, educational sciences

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Authors: Ehsan Sakhaei, Ali Taherabadi

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In this study, an aft sweep wing with specific characteristic feature was analysis with CFD method in Fluent software. In this analysis wings aerodynamic coefficient was calculated in different rake angle and wing lift curve slope to rake angle was achieved. Wing section was selected among NACA airfoils version 6. The sweep angle of wing is 15 degree, aspect ratio 8 and taper ratios 0.4. Designing and modeling this wing was done in CATIA software. This model was meshed in Gambit software and its three dimensional analysis was done in Fluent software. CFD methods used here were based on pressure base algorithm. SIMPLE technique was used for solving Navier-Stokes equation and Spalart-Allmaras model was utilized to simulate three dimensional wing in air. Roskam method is one of the common and most used methods for determining aerodynamics parameters in the field of airplane designing. In this study besides CFD analysis, an advanced aircraft analysis was used for calculating aerodynamic coefficient using Roskam method. The results of CFD were compared with measured data acquired from Roskam method and authenticity of relation was evaluated. The results and comparison showed that in linear region of lift curve there is a minor difference between aerodynamics parameter acquired from CFD to relation present by Roskam.

Keywords: aft sweep wing, CFD method, fluent, Roskam, Spalart-Allmaras model

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Authors: Sarah E. Nelson, Casey Weiner, Alexander Sigmon, Jun Hua, Haris I. Sair, Jose I. Suarez, Robert D. Stevens

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Graph-theoretical information from structural connectomes indicated significant connectivity changes and improved acute prognostication in a Random Forest (RF) model in aneurysmal subarachnoid hemorrhage (aSAH), which can lead to significant morbidity and mortality and has traditionally been fraught by poor methods to predict outcome. This study’s hypothesis was that structural connectivity changes occur in canonical brain networks of acute aSAH patients, and that these changes are associated with functional outcome at six months. In a prospective cohort of patients admitted to a single institution for management of acute aSAH, patients underwent diffusion tensor imaging (DTI) as part of a multimodal MRI scan. A weighted undirected structural connectome was created of each patient’s images using Constant Solid Angle (CSA) tractography, with 176 regions of interest (ROIs) defined by the Johns Hopkins Eve atlas. ROIs were sorted into four networks: Default Mode Network, Executive Control Network, Salience Network, and Whole Brain. The resulting nodes and edges were characterized using graph-theoretic features, including Node Strength (NS), Betweenness Centrality (BC), Network Degree (ND), and Connectedness (C). Clinical (including demographics and World Federation of Neurologic Surgeons scale) and graph features were used separately and in combination to train RF and Logistic Regression classifiers to predict two outcomes: dichotomized modified Rankin Score (mRS) at discharge and at six months after discharge (favorable outcome mRS 0-2, unfavorable outcome mRS 3-6). A total of 56 aSAH patients underwent DTI a median (IQR) of 7 (IQR=8.5) days after admission. The best performing model (RF) combining clinical and DTI graph features had a mean Area Under the Receiver Operator Characteristic Curve (AUROC) of 0.88 ± 0.00 and Area Under the Precision Recall Curve (AUPRC) of 0.95 ± 0.00 over 500 trials. The combined model performed better than the clinical model alone (AUROC 0.81 ± 0.01, AUPRC 0.91 ± 0.00). The highest-ranked graph features for prediction were NS, BC, and ND. These results indicate reorganization of the connectome early after aSAH. The performance of clinical prognostic models was increased significantly by the inclusion of DTI-derived graph connectivity metrics. This methodology could significantly improve prognostication of aSAH.

Keywords: connectomics, diffusion tensor imaging, graph theory, machine learning, subarachnoid hemorrhage

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Authors: Suriyani Ariffin, Nor Aziah Alias, Khairil Iskandar Othman, Haslinda Yusoff

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An Integrated Cumulative Grade Point Average (iCGPA) is a mechanism and strategy to ensure the curriculum of an academic programme is constructively aligned to the expected learning outcomes and student performance based on the attainment of those learning outcomes that is reported objectively in a spider web. Much effort and time has been spent to develop a viable mechanism and trains academics to utilize the platform for reporting. The question is: How well do learners conceive the idea of their achievement via iCGPA and whether quality learner attributes have been nurtured through the iCGPA mechanism? This paper presents the architecture of an integrated CGPA mechanism purported to address a holistic evaluation from the evaluation of courses learning outcomes to aligned programme learning outcomes attainment. The paper then discusses the students’ understanding of the mechanism and evaluation of their achievement from the generated spider web. A set of questionnaires were distributed to a group of students with iCGPA reporting and frequency analysis was used to compare the perspectives of students on their performance. In addition, the questionnaire also explored how they conceive the idea of an integrated, holistic reporting and how it generates their motivation to improve. The iCGPA group was found to be receptive to what they have achieved throughout their study period. They agreed that the achievement level generated from their spider web allows them to develop intervention and enhance the programme learning outcomes before they graduate.

Keywords: learning outcomes attainment, iCGPA, programme learning outcomes, spider web, iCGPA reporting skills

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Authors: Guanghua Zhang, Fubao Wang, Weijun Duan

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Convolution neural network (CNN) has attracted more and more attention on recent years. Especially in the field of computer vision and image classification. However, unsupervised learning with CNN has received less attention than supervised learning. In this work, we use a new powerful tool which is deep convolutional generative adversarial networks (DCGANs) to generate images from Sloan Digital Sky Survey. Training by various star and galaxy images, it shows that both the generator and the discriminator are good for unsupervised learning. In this paper, we also took several experiments to choose the best value for hyper-parameters and which could help to stabilize the training process and promise a good quality of the output.

Keywords: convolution neural network, discriminator, generator, unsupervised learning

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Authors: Jun Ming Moey, Zhiyaun Chen, David Nicholson

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Bad actors are often hard to detect in data that imprints their behaviour patterns because they are comparatively rare events embedded in non-bad actor data. An unsupervised machine learning framework is applied here to detect bad actors in financial crime datasets that record millions of transactions undertaken by hundreds of actors (<0.01% bad). Specifically, the framework combines ‘shallow’ (PCA, Isolation Forest) and ‘deep’ (Autoencoder) methods to detect outlier patterns. Detection performance analysis for both the individual methods and their combination is reported.

Keywords: detection, machine learning, deep learning, unsupervised, outlier analysis, data science, fraud, financial crime

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Authors: Kumiko Inagaki

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In recent, years, Japanese universities have begun to face a dilemma: more than half of all high school graduates go on to attend an institution of higher learning, overwhelming Japanese universities accustomed to small student bodies. These universities have been forced to embrace qualitative changes to accommodate the increased number and diversity of students who enter their establishments, students who differ in their motivations for learning, their levels of eagerness to learn, and their perspectives on the future. One of these changes is an increase in awareness among Japanese educators of the importance of active learning, which deepens students’ understanding of course material through a range of activities, including writing, speaking, thinking, and presenting, in addition to conventional “passive learning” methods such as listening to a one-way lecture. 　The purpose of this study is to examine the effectiveness of the teaching method adapted to improve active learning. A teaching method designed to promote active learning was implemented in a social science course at one of the most popular universities in Japan. A questionnaire using a five-point response format was given to students in 2,305 courses throughout the university to evaluate the effectiveness of the method based on the following measures: ① the ratio of students who were motivated to attend the classes, ② the rate at which students learned new information, and ③ the teaching method adopted in the classes. The results of this study show that the percentage of students who attended the active learning course eagerly, and the rate of new knowledge acquired through the course, both exceeded the average for the university, the department, and the subject area of social science. In addition, there are strong correlations between teaching method and student motivation and between teaching method and knowledge acquisition rate. These results indicate that the active learning teaching method was effectively implemented and that it may improve student eagerness to attend class and motivation to learn.

Keywords: active learning, Japanese university, teaching method, university education

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Authors: Roghaieh Parvizsedghy, Seyyed Mojtaba Sadrameli

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Biodiesel as an alternative diesel fuel is steadily gaining more attention and significance. However, there are some drawbacks while using biodiesel regarding its properties that requires it to be blended with petrol based diesel and/or additives to improve the fuel characteristics. This study analyses thermal cracking as an alternative technology to improve biodiesel characteristics in which, FAME based biodiesel produced by transesterification of castor oil is fed into a continuous thermal cracking reactor at temperatures range of 450-500°C and flowrate range of 20-40 g/hr. Experiments designed by response surface methodology and subsequent statistical studies show that temperature and feed flowrate significantly affect the products yield. Response surfaces were used to study the impact of temperature and flowrate on the product properties. After each experiment, the produced crude bio-oil was distilled and diesel cut was separated. As shorter chain molecules are produced through thermal cracking, the distillation curve of the diesel cut fitted more with petrol based diesel curve in comparison to the biodiesel. Moreover, the produced diesel cut properties adequately pose within property ranges defined by the related standard of petrol based diesel. Cold flow properties, high heating value as the main drawbacks of the biodiesel are improved by this technology. Thermal cracking decreases kinematic viscosity, Flash point and cetane number.

Keywords: biodiesel, castor oil, fuel properties, thermal cracking

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Authors: Anwar U. Haque, Waqar Asrar, Ashraf Ali Omar, Erwin Sulaeman, Jaffer Sayed Mohamed Ali

Abstract:

Due to the interference effects, the intrinsic aerodynamic parameters obtained from the individual component testing are always fundamentally different than those obtained for complete model testing. Consideration and limitation for such testing need to be taken into account in any design work related to the component buildup method. In this paper, the scaled model of a straight rectangular canard of a hybrid buoyant aircraft is tested at 50 m/s in IIUM-LSWT (Low-Speed Wind Tunnel). Model and its attachment with the balance are kept rigid to have results free from the aeroelastic distortion. Based on the velocity profile of the test section’s floor; the height of the model is kept equal to the corresponding boundary layer displacement. Balance measurements provide valuable but limited information of the overall aerodynamic behavior of the model. Zero lift coefficient is obtained at -2.2o and the corresponding drag coefficient was found to be less than that at zero angles of attack. As a part of the validation of low fidelity tool, the plot of lift coefficient plot was verified by the experimental data and except the value of zero lift coefficient, the overall trend has under-predicted the lift coefficient. Based on this comparative study, a correction factor of 1.36 is proposed for lift curve slope obtained from the panel method.

Keywords: wind tunnel testing, boundary layer displacement, lift curve slope, canard, aerodynamics

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Authors: Sahar Shams

Abstract:

Coeliac disease (CD) is a widely reported disease particularly in countries with predominant Caucasian populations. It presents with many signs and symptoms including iron deficiency (ID) and iron deficiency anaemia/anaemia (IDA/A). The exact association between ID, IDA/A and CD and how accurate these signs are in diagnosing CD is not fully known. This systematic review was conducted to investigate the accuracy of both ID & IDA/A as a diagnostic indicator for CD and whether it warrants point of care testing. A systematic review was performed looking at studies published in MEDLINE, Embase, Cochrane Library, and Web of Science. QUADAS-2 tool was used to assess risk of bias in each study. ROC curve and forest plots were generated as part of the meta-analysis after data extraction. 16 studies were identified in total, 13 of which were IDA/A studies and 3 ID studies. The prevalence of CD regardless of diagnostic indicator was assumed as 1%. The QUADAS-2 tool indicated most of studies as having high risk of bias. The PPV for CD was higher in those with ID than for those with IDA/A. Meta-analysis showed the overall odds of having CD is 5 times higher in individuals with ID & IDA/A. The ROC curve showed that there is definitely an association between both diagnostic indicators and CD, the association is not a particularly strong one due to great heterogeneity between studies. Whilst an association between IDA/A & ID and coeliac disease was evident, the results were not deemed significant enough to prompt coeliac disease testing in those with IDA/A & ID.

Keywords: anemia, iron deficiency anemia, coeliac disease, point of care testing

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Authors: Wangxu Xia

Abstract:

BACKGROUND BI-RADS 4 lesions raise the possibility of malignancy that warrant further clinical and radiologic work-up. This study aimed to evaluate the predictive performance of diffusion-weighted imaging(DWI) and microcalcifications on mammography for predicting malignancy of BI-RADS 4 lesions. In addition, the predictive performance of DWI combined with microcalcifications was alsocompared with the Kaiser score. METHODS During January 2021 and June 2023, 144 patients with 178 BI-RADS 4 lesions underwent conventional MRI, DWI, and mammography were included. The lesions were dichotomized intobenign or malignant according to the pathological results from core needle biopsy or surgical mastectomy. DWI was performed with a b value of 0 and 800s/mm2 and analyzed using theapparent diffusion coefficient, and a Kaiser score > 4 was considered to suggest malignancy. Thediagnostic performances for various diagnostic tests were evaluated with the receiver-operatingcharacteristic (ROC) curve. RESULTS The area under the curve (AUC) for DWI was significantly higher than that of the of mammography (0.86 vs 0.71, P<0.001), but was comparable with that of the Kaiser score (0.86 vs 0.84, P=0.58). However, the AUC for DWI combined with mammography was significantly highthan that of the Kaiser score (0.93 vs 0.84, P=0.007). The sensitivity for discriminating malignant from benign BI-RADS 4 lesions was highest at 89% for Kaiser score, but the highest specificity of 83% can be achieved with DWI combined with mammography. CONCLUSION DWI combined with microcalcifications on mammography could discriminate malignant BI-RADS4 lesions from benign ones with a high AUC and specificity. However, Kaiser score had a better sensitivity for discrimination.

Keywords: MRI, DWI, mammography, breast disease

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Authors: Erhan Eroğlu

Abstract:

This paper presents a new method called Mentor and Mentee Based Learning. This new method is becoming more and more common especially at workplaces. This study is significant as it clearly underlines how it works well. Education has always aimed at equipping people with the necessary knowledge and information. For many decades it went on teachers’ talk and chalk methods. In the second half of the nineteenth century educators felt the need for some changes in delivery systems. Some new terms like self- discovery, learner engagement, student centered learning, hands on learning have become more and more popular for such a long time. However, some educators believe that there is much room for better learning methods in many fields as they think the learners still cannot fulfill their potential capacities. Thus, new systems and methods are still being developed and applied at education centers and work places. One of the latest methods is assigning some mentors for the newly recruited employees and training them within a mentor and mentee program which allows both parties to see their strengths and weaknesses and the areas which can be improved. This paper aims at finding out the perceptions of the mentors and mentees on the programs they are offered at their workplaces and suggests some betterment alternatives. The study has been conducted via a qualitative method whereby some interviews have been done with both mentors and mentees separately and together. Results show that it is a great way to train inexperienced one and also to refresh the older ones. Some points to be improved have also been underlined. The paper shows that education is not a one way path to follow.

Keywords: learning, mentor, mentee, training

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Authors: E. Vlachopapadopoulou, E. Dikaiakou, E. Anagnostou, I. Panagiotopoulos, E. Kaloumenou, M. Kafetzi, A. Fotinou, S. Michalacos

Abstract:

Aim: To investigate the relation and impact of Body Mass Index (BMI), Waist Circumference (WC) and Body Fat Weight (BFW) on insulin resistance (MATSUDA INDEX < 2.5) in children and adolescents. Methods: Data from 95 overweight and obese children (47 boys and 48 girls) with mean age 10.7 ± 2.2 years were analyzed. ROC analysis was used to investigate the predictive ability of BMI, WC and BFW for insulin resistance and find the optimal cut-offs. The overall performance of the ROC analysis was quantified by computing area under the curve (AUC). Results: ROC curve analysis indicated that the optimal-cut off of WC for the prediction of insulin resistance was 97 cm with sensitivity equal to 75% and specificity equal to 73.1%. AUC was 0.78 (95% CI: 0.63-0.92, p=0.001). The sensitivity and specificity of obesity for the discrimination of participants with insulin resistance from those without insulin resistance were equal to 58.3% and 75%, respectively (AUC=0.67). BFW had a borderline predictive ability for insulin resistance (AUC=0.58, 95% CI: 0.43-0.74, p=0.101). The predictive ability of WC was equivalent with the correspondence predictive ability of BMI (p=0.891). Obese subjects had 4.2 times greater odds for having insulin resistance (95% CI: 1.71-10.30, p < 0.001), while subjects with WC more than 97 had 8.1 times greater odds for having insulin resistance (95% CI: 2.14-30.86, p=0.002). Conclusion: BMI and WC are important clinical factors that have significant clinical relation with insulin resistance in children and adolescents. The cut off of 97 cm for WC can identify children with greater likelihood for insulin resistance.

Keywords: body fat weight, body mass index, insulin resistance, obese children, waist circumference

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