Search results for: family ICT learning

Authors: Maryam Beiranvand, Sajad Yaghoubi

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Background: Some microbes can colonize plants’ inner tissues without causing obvious damage and can even produce useful bioactive substances. In the present study, the diversity of the endophytic bacteria associated with medicinal plants from Iran was investigated by culturing techniques, molecular gene identification, as well as measuring them for antibacterial activity. Results: In the spring season from 2013 to 2014, 35 herb pharmacology samples were collected, sterilized, meshed, and then cultured on selective media culture. A total of 199 endophytic bacteria were successfully isolated from 35 tissue cultures of medical plants, and sixty-seven out of 199 bacterial isolates were subjected to identification by the 16S rRNA gene sequence analysis method. Based on the sequence similarity gene and phylogenetic analyses, these isolates were grouped into five classes, fourteen orders, seventeen families, twenty-one genera, and forty strains. The most abundant group of endophytic bacteria was actinobacterial, consisting of thirty-two (47%) out of 67 bacterial isolates. Ten (22.3%) out of 67 bacterial isolates remained unidentified and classified at the genus level. The signature of the 16S rRNA gene formed a distinct line in a phylogenetic tree showing that they might be new species of bacteria. One (5.2%) out of 67 bacterial isolates was still not well categorized. Forty-two out of 67 strains were candidates for antimicrobial activity tests. Nineteen (45%) out of 42 strains showed antimicrobial activity multidrug-resistance (MDR); thirteen (68%) out of 19 strains were allocated to classes actinobacteria. Four (21%) out of 19 strains belonged to the Bacillaceae family, one (5.2%) out of 19 strains was the Paenibacillaceae family, and one (5.2%) out of 19 strains belonged to the Pseudomonadaceae family. The other twenty-three strains did not show inhibitory activities. Conclusions: Our research showed a high-level phylogenetic diversity and the intoxicating antibiotic activity of endophytic bacteria in the herb pharmacology of Iran.

Keywords: medical plant, endophytic bacteria, antimicrobial activity, whole genome sequencing analysis

Procedia PDF Downloads 118

Authors: Julian Wise

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Newcrest Mining is one of the world’s top five gold and rare earth mining organizations by production, reserves and market capitalization in the world. This paper elaborates on the data acquisition processes employed by Newcrest in collaboration with Fortune 500 listed organization, Insight Enterprises, to standardize machine learning solutions which process data from over a hundred thousand distributed Internet of Things (IoT) devices located at mine sites globally. Through the utilization of software architecture cloud technologies and edge computing, the technological developments enable for standardized processes of machine learning applications to influence the strategic optimization of mineral processing. Target objectives of the machine learning optimizations include time savings on mineral processing, production efficiencies, risk identification, and increased production throughput. The data acquired and utilized for predictive modelling is processed through edge computing by resources collectively stored within a data lake. Being involved in the digital transformation has necessitated the standardization software architecture to manage the machine learning models submitted by vendors, to ensure effective automation and continuous improvements to the mineral process models. Operating at scale, the system processes hundreds of gigabytes of data per day from distributed mine sites across the globe, for the purposes of increased improved worker safety, and production efficiency through big data applications.

Keywords: mineral technology, big data, machine learning operations, data lake

Procedia PDF Downloads 106

Authors: Zuhairah Abdul Hadi, Mohd Nazir bin Md. Zabit, Zuriadah Ismail

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Metacognitive has been empirically evidenced to be one important element influencing learning outcomes. Expert learners engage in metacognition by monitoring and controlling their thinking, and listing, considering and selecting the best strategies to achieve desired goals. Studies also found that good critical thinkers engage in more metacognition and people tend to activate more metacognition when solving complex problems. This study extends past studies by performing a qualitative analysis to understand metacognitive patterns among two high and two low performing groups by carefully examining video and audio records taken during Problem-based learning activities. High performing groups are groups with majority members scored well in Watson Glaser II Critical Thinking Appraisal (WGCTA II) and academic achievement tests. Low performing groups are groups with majority members fail to perform in the two tests. Audio records are transcribed and analyzed using schemas adopted from past studies. Metacognitive statements are analyzed using three stages model and patterns of metacognitive are described by contexts, components, and levels for each high and low performing groups.

Keywords: academic achievement, critical thinking, metacognitive, problem-based learning

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Authors: Ghoul Rachid Brahim

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Introduction: Degenerative disc disease is a process of premature and accelerated deterioration of the intervertebral disc; it is of multifactorial origin and is responsible for chronic low back pain. Objectives: Determine an epidemiological profile of patients with painful lumbar degenerative disc disease. Patients and methods: We performed a prospective study of 104 patients operated on for degenerative painful lumbar disc disease over a period of 25 months. The parameters analyzed were: age, sex, Body Mass Index (BMI), comorbidities, family history of low back pain, and difficulty with professional activity. Results: The average age was 43.3 years, with a clear predominance of men: 72 men for 32 women, the average BMI was 26.80Kg / m2, and 63.5% of the patients were overweight. The occurrence of disc degeneration in pathological conditions was noted in 14.4% of cases. The notion of familial low back pain was found in 49% of cases. The majority of patients perform more or less arduous work (51%) in the cases. Conclusion: In our series, degenerative painful lumbar disc disease predominates in the male subject, active obese who performs more or less painful work, in whom we find a family history of low back pain.

Keywords: degenerative disc disease, low back pain, body mass index, disque intervertebrale

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Authors: Chalermpol Tapsai

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The objectives of this research were to develop and find the efficiency of integrated online lessons by investigating the usage of online lessons, the relationship between learners’ background knowledge, and the achievement after learning with online lessons. The sample group in this study consisted of 97 students randomly selected from 121 students registering in 1/2012 at Trimitwittayaram Learning Center. The sample technique employed stratified sample technique of 4 groups according to their proficiency, i.e. high, moderate, low, and non-knowledge. The research instrument included online lessons in integration model on the topic of Java Programming, test after each lesson, the achievement test at the end of the course, and the questionnaires to find learners’ satisfaction. The results showed that the efficiency of online lessons was 90.20/89.18 with the achievement of after learning with the lessons higher than that before the lessons at the statistically significant level of 0.05. Moreover, the background knowledge of the learners on the programming showed the positive relationship with the achievement learning at the statistically significant level at 0.05. Learners with high background knowledge employed less exercises and samples than those with lower background knowledge. While learners with different background in the group of moderate and low did not show the significant difference in employing samples and exercises.

Keywords: integration model, online lessons, learners’ background knowledge, efficiency

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Authors: Sunil Gaikwad

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Gender discrimination is a very prevalent and much used word in the legal parlance. , The more socially, culturally, economically and educationally backward the community, the more gender discrimination is seen there. Gender discrimination is a worldwide Phenomena. In India it was more prevalent, due to illiteracy, bad social and religious customs. in Indian family system male child is considered as inheritor of the family clan, support for parents in their old age and girls as the property of others and unnecessary load on parents and on property as the dowry has to be give at her marriage as also some festivals like Raksha Bandhan and Bhau Teej during Deepawali (wherein having brother is compulsory)insist on having a male child in the family, hence most couples try to give birth only to male child at the cost of female child, hence the female feticide was going on a large scale due to which, sex ratio had considerably decreased creating problem for geeting groom for bride groom thereby putting question mark on family system. To redo the damage done to the society due to the female feticide Government of India has enacted various Laws and introduced various welfare schemes for the upliftment of girl child and also launched countrywide awareness campaign to create awareness among people about the importance of girl child and punitive laws for infanticide which is now bearing fruits but still cases of female feticide are coming fore. There is an urgent need to go to the roots of the problem and to find practicable and effective legal and social measures to overcome this issue, and the purpose of this research paper is the same. The research paper discusses in detail the reasons and superstitions that are responsible for the gender discriminations and comes out with effective measures including necessary and effective changes in the existing Laws, effective awareness campaign against religious superstitions for gender equality. For this research paper doctrinal research methodology is used to drive the research to its logical conclusion, for which various primary and secondary sources literature has been perused and studied. It is worth noting that while working on the paper suggestions and recommendations and conclusions have been drawn where it is suggested and concluded that there is an urgent need to re think about the festivals which encourages gender discriminations, to sensitize and create ample of awareness among people by effectively utilizing Radio, Television, Social Media folk arts, public shows and to make existing laws more effective and strict implementation for the purpose and zero tolerance for female feticide.

Keywords: awareness, effective laws, female foeticide, festivals, superstitions

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Authors: Laura M. F. Bertens

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The houses we inhabit are important containers of memory. As homes, they take on meaning for those who live inside, and memories of family life become intimately tied up with rooms, windows, and gardens. Each new family creates a new layer of meaning, resulting in a palimpsest of family memory. These houses function quite literally as memory palaces, as a walk through a childhood home will show; each room conjures up images of past events. Over time, these personal memories become woven together with the cultural memory of countries and generations. The importance of the home is a central theme in art, and several contemporary artists have a special interest in the relationship between memory and the home. This paper analyses three case studies in order to get a deeper understanding of the ways in which the home functions and feels like a memory palace, both on an individual and on a collective, cultural level. Close reading of the artworks is performed on the theoretical intersection between Art History and Cultural Memory Studies. The first case study concerns works from the exhibition Mnemosyne by the artist duo Anne and Patrick Poirier. These works combine interests in architecture, archaeology, and psychology. Models of cities and fantastical architectural designs resemble physical structures (such as the brain), architectural metaphors used in representing the concept of memory (such as the memory palace), and archaeological remains, essential to our shared cultural memories. Secondly, works by Do Ho Suh will help us understand the relationship between the home and memory on a far more personal level; outlines of rooms from his former homes, made of colourful, transparent fabric and combined into new structures, provide an insight into the way these spaces retain individual memories. The spaces have been emptied out, and only the husks remain. Although the remnants of walls, light switches, doors, electricity outlets, etc. are standard, mass-produced elements found in many homes and devoid of inherent meaning, together they remind us of the emotional significance attached to the muscle memory of spaces we once inhabited. The third case study concerns an exhibition in a house put up for sale on the Dutch real estate website Funda. The house was built in 1933 by a Jewish family fleeing from Germany, and the father and son were later deported and killed. The artists Anne van As and CA Wertheim have used the history and memories of the house as a starting point for an exhibition called (T)huis, a combination of the Dutch words for home and house. This case study illustrates the way houses become containers of memories; each new family ‘resets’ the meaning of a house, but traces of earlier memories remain. The exhibition allows us to explore the transition of individual memories into shared cultural memory, in this case of WWII. Taken together, the analyses provide a deeper understanding of different facets of the relationship between the home and memory, both individual and collective, and the ways in which art can represent these.

Keywords: Anne and Patrick Poirier, cultural memory, Do Ho Suh, home, memory palace

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Authors: Begona del Pino, Beatriz Prieto, Alberto Prieto

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Two opposite approaches to teaching can be considered: in-class learning (teacher-oriented) versus virtual learning (student-oriented). The most known example of the latter is Massive Online Open Courses (MOOCs). Both methodologies have pros and cons. Nowadays there is an increasing trend towards combining both of them. Blending learning is considered a valuable tool for improving learning since it combines student-centred interactive e-learning and face to face instruction. The aim of this contribution is to exchange and share the experience and research results of a blended-learning project that took place in the University of Granada (Spain). The research objective was to prove how combining didactic resources of a MOOC with in-class teaching, interacting directly with students, can substantially improve academic results, as well as student acceptance. The proposed methodology is based on the use of flipped learning technics applied to the subject ‘Fundamentals of Computer Science’ of the first course of two degrees: Telecommunications Engineering, and Industrial Electronics. In this proposal, students acquire the theoretical knowledges at home through a MOOC platform, where they watch video-lectures, do self-evaluation tests, and use other academic multimedia online resources. Afterwards, they have to attend to in-class teaching where they do other activities in order to interact with teachers and the rest of students (discussing of the videos, solving of doubts and practical exercises, etc.), trying to overcome the disadvantages of self-regulated learning. The results are obtained through the grades of the students and their assessment of the blended experience, based on an opinion survey conducted at the end of the course. The major findings of the study are the following: The percentage of students passing the subject has grown from 53% (average from 2011 to 2014 using traditional learning methodology) to 76% (average from 2015 to 2018 using blended methodology). The average grade has improved from 5.20±1.99 to 6.38±1.66. The results of the opinion survey indicate that most students preferred blended methodology to traditional approaches, and positively valued both courses. In fact, 69% of students felt ‘quite’ or ‘very’ satisfied with the classroom activities; 65% of students preferred the flipped classroom methodology to traditional in-class lectures, and finally, 79% said they were ‘quite’ or ‘very’ satisfied with the course in general. The main conclusions of the experience are the improvement in academic results, as well as the highly satisfactory assessments obtained in the opinion surveys. The results confirm the huge potential of combining MOOCs in formal undergraduate studies with on-campus learning activities. Nevertheless, the results in terms of students’ participation and follow-up have a wide margin for improvement. The method is highly demanding for both students and teachers. As a recommendation, students must perform the assigned tasks with perseverance, every week, in order to take advantage of the face-to-face classes. This perseverance is precisely what needs to be promoted among students because it clearly brings about an improvement in learning.

Keywords: blended learning, educational paradigm, flipped classroom, flipped learning technologies, lessons learned, massive online open course, MOOC, teacher roles through technology

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Authors: Sakineh Abbasi Bourondaragh

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The aim of this research is effectiveness of integrative behavioral couples therapy on the communication patterns of couples applying for divorce. We selected (N=20) reports from Tabriz Family Judicial Complex (FJC) of couples which have conflict in their marital relationships. All of reports were released during 2012. First, they were randomly divided into two experimental and control groups and all the couples were given pre-test. They participated in twelve therapy sessions. Then the experimental group was exposed to an experimental intervention, but the control group was not received experimental intervention. The subjects were treated. At the end of treatment, a post-test was performed about subjects (each of two groups).The results showed that integrative behavioral couple therapy could increase and improve communication patterns. The findings also showed that integrative behavioral couples therapy had increased mutual constructive pattern and decreased demand/withdraw pattern and mutual avoidance pattern of CPQ sub-scale. Steady change indicator showed that the difference is clinically meaningful.

Keywords: integrative behavioral couple therapy, communication patterns, cognitive sciences, Family Judicial Complex

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Authors: Azman Ramlie, Vivian Foo Jing Wen

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As the advancement of technology has tremendously changed the way people communicate with each other, it has opened up opportunities for interracial relationships. Interracial relationship is also known as intercultural or interethnic relationships. This research topic aims to study on students’ perceptions toward interracial relationship in terms of their level of acceptance and approval. In addition, the study also focuses on determining and ranking the factors that affects students’ perceptions towards interracial relationship. This study also targets to determine the differences in students’ perceptions from business and communication major. This study uses a sample of university students from Sunway University, particularly on students in business and communication major. The study was conducted through online survey questionnaires. Results revealed that students’ level of acceptance towards interracial relationship was high. In addition, results also further indicated that family members’ support was one of the most important factors in influencing students’ perception towards interracial relationship. No diverse differences of perceptions among students in business and communication major towards interracial relationship were shown in the findings. Most of the result showed that both majors turned out to have similar perceptions towards interracial relationship. It can be said that the students’ perception towards interracial relationship did not differ from which major the students was in but their family background that would shape their perceptions.

Keywords: interracial relationship, racial, relationship, perceptions

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Authors: M. Rodionov, Z. Dedovets

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The article analyses the composition and structure of the motivationally oriented methodological system of teaching mathematics (purpose, content, methods, forms, and means of teaching), viewed through the prism of the student as the subject of the learning process. Particular attention is paid to the problem of methods of teaching mathematics, which are represented in the form of an ordered triad of attributes corresponding to the selected characteristics. A systematic analysis of possible options and their methodological interpretation enriched existing ideas about known methods and technologies of training, and significantly expanded their nomenclature by including previously unstudied combinations of characteristics. In addition, examples outlined in this article illustrate the possibilities of enhancing the motivational capacity of a particular method or technology in the real learning practice of teaching mathematics through more free goal-setting and varying the conditions of the problem situations. The authors recommend the implementation of different strategies according to their characteristics in teaching and learning mathematics in secondary schools.

Keywords: education, methodological system, the teaching of mathematics, students motivation

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Authors: Roshanak Khodabakhsh Jolfaei, Javad Akbari Torkestani

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As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm.

Keywords: computational grid, job scheduling, learning automata, dynamic scheduling

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Authors: Mounir Ben Zid

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The controversy over the most effective teaching method to facilitate the increase of a student's knowledge has remained a frustration for poetry teachers at Sultan Qaboos University in Oman for the last ten years. Scholars and educationists have pursued answers to this question, and tremendous effort has been marshalled to discover the optimum teaching strategy, with little success. The present study stems from this perpetual frustration among teachers of poetry and the dispute about the repertoire of teaching methods. It attempts to shed light on an alternative direction which, it is believed, has received less scholarly attention than deserved. It emphasizes the need to create a democratic and human atmosphere of learning, arouses students' genuine interest, provides students with aesthetic pleasure, and enable them to appreciate and enjoy the beauty and musicality of words in poems. More important, this teaching-learning style should aim to secure rapport with students, invite teachers to inspire the passion and love of poetry in their students and help them not to lose the sense of wonder and enthusiasm that should be in the forefront of enjoying poetry. Hence, it is the need of the time that, after they have an interest, feeling and desire for poetry, university students can move to heavier tasks and discussions about poetry and how to further understand and analyze what is being portrayed. It is timely that the pendulum swung in support of the humanization of education and building rapport with students at Sultan Qaboos University.

Keywords: education, humanization, learning style, Rapport

Procedia PDF Downloads 241

Authors: Adam Johnbull

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The paper discusses ICT in Education as a quest for quality learning in the 21st century. Education is the key that unlock the door to development, without adequate education of the citizenry, the development of a nation becomes a sham. Information Communication Technologies (ICTs) has revolutionized the way people work today and are now transforming education systems. As a result, if schools train children in yesterday’s skills and technologies they may not be effective and fit in tomorrow’s world. This is a sufficient reason for ICT’s to win global recognition and attention and thus ensure desire quality in our school system. Thus, the purpose of the paper is to discuss amongst others, what is ICT. The roles of ICT’s in education, limitation and key challenges of integrating ICT to education in the enhancement of student learning and experiences in other to encourage policy makers, school administrators and teachers pay the required attention to integrate this technology in the education system. The paper concludes that regardless of all the limitation characterizing it. ICT benefit education system to provide quality education in the 21st century.

Keywords: ICTs, quest, information, global, sham, century

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Authors: Taylan Kabbani, Ekrem Duman

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The design of adaptive systems that take advantage of financial markets while reducing the risk can bring more stagnant wealth into the global market. However, most efforts made to generate successful deals in trading financial assets rely on Supervised Learning (SL), which suffered from various limitations. Deep Reinforcement Learning (DRL) offers to solve these drawbacks of SL approaches by combining the financial assets price "prediction" step and the "allocation" step of the portfolio in one unified process to produce fully autonomous systems capable of interacting with its environment to make optimal decisions through trial and error. In this paper, a continuous action space approach is adopted to give the trading agent the ability to gradually adjust the portfolio's positions with each time step (dynamically re-allocate investments), resulting in better agent-environment interaction and faster convergence of the learning process. In addition, the approach supports the managing of a portfolio with several assets instead of a single one. This work represents a novel DRL model to generate profitable trades in the stock market, effectively overcoming the limitations of supervised learning approaches. We formulate the trading problem, or what is referred to as The Agent Environment as Partially observed Markov Decision Process (POMDP) model, considering the constraints imposed by the stock market, such as liquidity and transaction costs. More specifically, we design an environment that simulates the real-world trading process by augmenting the state representation with ten different technical indicators and sentiment analysis of news articles for each stock. We then solve the formulated POMDP problem using the Twin Delayed Deep Deterministic Policy Gradient (TD3) algorithm, which can learn policies in high-dimensional and continuous action spaces like those typically found in the stock market environment. From the point of view of stock market forecasting and the intelligent decision-making mechanism, this paper demonstrates the superiority of deep reinforcement learning in financial markets over other types of machine learning such as supervised learning and proves its credibility and advantages of strategic decision-making.

Keywords: the stock market, deep reinforcement learning, MDP, twin delayed deep deterministic policy gradient, sentiment analysis, technical indicators, autonomous agent

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Authors: David Ming Liu, Benjamin Hirsch, Bashir Aden

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Syndromic surveillance is to detect or predict disease outbreaks through the analysis of medical sources of data. Using social media data like tweets to do syndromic surveillance becomes more and more popular with the aid of open platform to collect data and the advantage of microblogging text and mobile geographic location features. In this paper, a Syndromic Surveillance Framework is presented with machine learning kernel using tweets data analytics. Influenza and the three cities Abu Dhabi, Al Ain and Dubai of United Arabic Emirates are used as the test disease and trial areas. Hospital cases data provided by the Health Authority of Abu Dhabi (HAAD) are used for the correlation purpose. In our model, Latent Dirichlet allocation (LDA) engine is adapted to do supervised learning classification and N-Fold cross validation confusion matrix are given as the simulation results with overall system recall 85.595% performance achieved.

Keywords: Syndromic surveillance, Tweets, Machine Learning, data mining, Latent Dirichlet allocation (LDA), Influenza

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Authors: Giovanni Cicceri, Roberta Maisano, Nathalie Morey, Salvatore Distefano

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The main goal of this paper is to present a solution for a water purification system based on an Environmental Internet of Things (EIoT) platform to monitor and control water quality and machine learning (ML) models to support decision making and speed up the processes of purification of water. A real case study has been implemented by deploying an EIoT platform and a network of devices, called Gramb meters and belonging to the Gramb project, on wastewater purification systems located in Calabria, south of Italy. The data thus collected are used to control the wastewater quality, detect anomalies and predict the behaviour of the purification system. To this extent, three different statistical and machine learning models have been adopted and thus compared: Autoregressive Integrated Moving Average (ARIMA), Long Short Term Memory (LSTM) autoencoder, and Facebook Prophet (FP). The results demonstrated that the ML solution (LSTM) out-perform classical statistical approaches (ARIMA, FP), in terms of both accuracy, efficiency and effectiveness in monitoring and controlling the wastewater purification processes.

Keywords: environmental internet of things, EIoT, machine learning, anomaly detection, environment monitoring

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Authors: Liza Mariah Hj. Azahari

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This paper will look at a case study on English Camp which was an activity coordinated at the Sultan Sharif Ali Islamic University in 2011. English Camp is a fun and motivation filled activity which brings students and teachers together outside of the classroom setting into a more diverse environment. It also enables teacher and students to gain proximate time together for a mutual purpose which is to explore the language in a more dynamic and relaxed way. First of all, the study will look into the background of English Camp, and how it was introduced and implemented from different contexts. Thereafter, it will explain the objectives of the English Camp coordinated at our university, UNISSA, and what types of activities were conducted. It will then evaluate the effectiveness of the camp as to what extent it managed to meet its motto, which was to foster dynamic interactive learning of English Language. To conclude, the paper presents a potential for further research on the topic as well as a guideline for educators who wish to coordinate the activity. Proposal for collaboration in this activity is further highlighted and encouraged within the paper for future implementation and endeavor.

Keywords: English camp, UNISSA, interactive learning, outside

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Authors: Amit Kumar, Amanpreet Chander, Ashish Sahani

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This paper presents our recent work on real-time human activity detection based on the media pipe pipeline and machine learning algorithms. The proposed system can detect human activities, including running, jumping, squatting, bending to the left or right, and standing still. This is a robust solution for developing a yoga, dance, metaverse, and fitness application that checks for the correction of the pose without having any additional monitor like a personal trainer. MediaPipe solution offers an open-source cross-platform which utilizes a two-step detector-tracker ML pipeline for live detection of key landmarks on our body which can be used for motion data collection. The prediction of real-time poses uses a variety of machine learning techniques and different types of analysis. Without primarily relying on powerful desktop environments for inference, our method achieves real-time performance on the majority of contemporary mobile phones, desktops/laptops, Python, or even the web. Experimental results show that our method outperforms the existing method in terms of accuracy and real-time capability, achieving an accuracy of 99.92% on testing datasets.

Keywords: human activity detection, media pipe, machine learning, metaverse applications

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Authors: Haojie Wang, Xun Li, Rui Yin

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In order to solve the memorization overfitting in the model-agnostic meta-learning MAML algorithm, a method of generating mutually exclusive tasks based on data augmentation is proposed. This method generates a mutex task by corresponding one feature of the data to multiple labels so that the generated mutex task is inconsistent with the data distribution in the initial dataset. Because generating mutex tasks for all data will produce a large number of invalid data and, in the worst case, lead to an exponential growth of computation, this paper also proposes a key data extraction method that only extract part of the data to generate the mutex task. The experiments show that the method of generating mutually exclusive tasks can effectively solve the memorization overfitting in the meta-learning MAML algorithm.

Keywords: mutex task generation, data augmentation, meta-learning, text classification.

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Authors: Ali Nadi, Ali Edrissi

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Relief demand and transportation links availability is the essential information that is needed for every natural disaster operation. This information is not in hand once a disaster strikes. Relief demand and network condition has been evaluated based on prediction method in related works. Nevertheless, prediction seems to be over or under estimated due to uncertainties and may lead to a failure operation. Therefore, in this paper a stochastic programming model is proposed to evaluate real-time relief demand and network condition at the onset of a natural disaster. To address the time sensitivity of the emergency response, the proposed model uses reinforcement learning for optimization of the total relief assessment time. The proposed model is tested on a real size network problem. The simulation results indicate that the proposed model performs well in the case of collecting real-time information.

Keywords: disaster management, real-time demand, reinforcement learning, relief demand

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Authors: Parthiban Srinivasan

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With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

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Authors: Mehravar Javid, Stacey Dershewitz, Shohreh Hashemighoochani, Artin Yousefi

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One of the most common reasons for destroying relationships is infidelity. This study was conducted to understand children's experience of infidelity in Iran. In this qualitative research, the interpretive phenomenological approach and theoretical (purposive) sampling method were used, and the data was saturated by conducting semi-structured interviews with eight offspring of families affected by infidelity. All interviews were audio recorded and analyzed on paper after implementation. Acceptability and homogeneity of data were confirmed by different methods. Eight main themes were identified from the participants' statements: description of the family atmosphere, lack of security and distrust, emotional reactions, behavioral reactions, worry about the future, financial problems, mother's physical-psychological state, and mother's coping strategies and offspring's proposed solutions. The children's experiences showed that in addition to causing irreparable harm to the wife, infidelity affected the whole family and caused the children to suffer crucial consequences such as emotional, behavioral, educational, and economic consequences and mistrust.

Keywords: consequences and hurt, infidelity, offspring, phenomenology, qualitative research

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Authors: Oleg Vlasovets, Fabian Schaipp, Christian L. Mueller

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we conduct a network analysis and predict the sex of 1000 participants based on ”connectome” - pairwise Pearson’s correlation across 436 brain parcels. We solve the non-smooth convex optimization problem, known under the name of Graphical Lasso, where the solution includes a low-rank component. With this solution and machine learning model for a sex prediction, we explain the brain parcels-sex connectivity patterns.

Keywords: network analysis, neuroscience, machine learning, optimization

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Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI) is a hybrid e-framework that consolidates instructional design and language development towards the development of a web-based instruction (WBI). WeCWI divides instructional design into macro and micro perspectives. In macro perspective, a 21st century educator is encouraged to disseminate knowledge and share ideas with in-class and global learners. By leveraging the virtue of technology, WeCWI aims to transform the educator into an aggregator, curator, publisher, social networker and finally, a web-based instructor. Since the most notable contribution of integrating technology is being a tool of teaching as well as a stimulus for learning, WeCWI focuses on the use of contemporary web tools based on the multiple roles played by the 21st century educator. The micro perspective draws attention to the pedagogical approaches focussing on three main aspects: reading, discussion, and writing. With the effective use of pedagogical approaches, technology adds new dimensions and expands the bounds of learning capacity. Lastly, WeCWI also imparts the fundamental theoretical concepts for web-based instructors’ awareness such as interactionism, e-learning interactional-based model, computer-mediated communication (CMC), cognitive theories, and learning style model.

Keywords: web-based cognitive writing instruction, WeCWI, instructional design, e-framework, web-based instructor

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Authors: M. Zezou

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This paper focuses on the design of a Massive Open Online Course (MOOC) about Content Language Integrated Learning (CLIL) and more specifically about how teachers can use CLIL as an educational approach incorporating technology in their teaching as well. All the four weeks of the MOOC will be presented and a step-by-step analysis of each lesson will be offered. Additionally, the paper includes detailed lesson plans about CLIL lessons with proposed CLIL activities and games in which technology plays a central part. The MOOC is structured based on certain criteria, in order to ensure success, as well as a positive experience that the learners need to have after completing this MOOC. It addresses to all language teachers who would like to implement CLIL into their teaching. In other words, it presents the methodology that needs to be followed so as to successfully carry out a CLIL lesson and achieve the learning objectives set at the beginning of the course. Firstly, in this paper, it is very important to give the definitions of MOOCs and LMOOCs, as well as to explore the difference between a structure-based MOOC (xMOOC) and a connectivist MOOC (cMOOC) and present the criteria of a successful MOOC. Moreover, the notion of CLIL will be explored, as it is necessary to fully understand this concept before moving on to the design of the MOOC. Onwards, the four weeks of the MOOC will be introduced as well as lesson plans will be presented: The type of the activities, the aims of each activity and the methodology that teachers have to follow. Emphasis will be placed on the role of technology in foreign language learning and on the ways in which we can involve technology in teaching a foreign language. Final remarks will be made and a summary of the main points will be offered at the end.

Keywords: CLIL, cMOOC, lesson plan, LMOOC, MOOC criteria, MOOC, technology, xMOOC

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Authors: Md. Shaiful Islam, Mahani Bt. Stapa

Abstract:

To help learners overcome their struggle in developing proficiency in spoken English, self-regulated learning strategies seem to be promising. Students in the private universities in Bangladesh are expected to communicate with the teachers, peers, and staff members in English, but most of them suffer from their inadequate oral communicative competence in English. To address this problem, the researchers adopted a qualitative research approach to answer the research questions. They employed the learner diary method to collect data from the first-semester undergraduate students of a reputed private university in Bangladesh who were involved in writing weekly diaries about their use of self-regulated learning strategies to improve speaking in an English speaking course. The learners were provided with prompts for writing the diaries. The thematic analysis method was applied to analyze the entries of the diaries for the identification of themes. Seven strategies related to the effectiveness of SRL for the improvement of spoken English were identified from the data, and they include goal-setting, strategic planning, identifying the sources of self-motivation, help-seeking, environmental restructuring, self-monitoring, and self-evaluation. However, the students reported in their diaries that they faced challenges that impeded their SRL strategy use. Five challenges were identified, and they entail the complex nature of SRL, lack of literacy on SRL, teachers’ preference for controlling the class, learners’ past habit of learning, and students’ addiction to gadgets. The implications the study addresses include revising the syllabus and curriculum, facilitating SRL training for students and teachers, and integrating SRL in the lessons.

Keywords: private university in Bangladesh, proficiency, self-regulated learning, spoken English

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Authors: Ghazi Alotaibi

Abstract:

The current study examined and described the views of secondary school students and their parents on their reasons for seeking private tutors in English. These views were obtained through two group interviews with the students and parents separately. Several causes were brought up during the two interviews. These causes included difficulty of the English language, weak teacher performance, the need to pass exams with high marks, lack of parents’ follow-up of student school performance, social pressure, variability in student comprehension levels at school, weak English foundation in previous school years, repeated student absence from school, large classes, as well as English teachers’ heavy teaching loads. The study started with a description of the EFL educational system in Saudi Arabia and concluded with recommendations for the improvement of the school learning environment.

Keywords: english, learning difficulty, private tutoring, Saudi, teaching practices, learning environment

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

Abstract:

In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Thomas James Bell III

Abstract:

Pedagogy is thought of as one's philosophy, theory, or teaching method. This study examines the science of learning, considering the forced reconsideration of effective pedagogy brought on by the aftermath of the 2020 coronavirus pandemic. With the aid of various technologies, online education holds challenges and promises to enhance the learning environment if implemented to facilitate student learning. Behaviorism centers around the belief that the instructor is the sage on the classroom stage using repetition techniques as the primary learning instrument. This approach to pedagogy ascribes complete control of the learning environment and works best for students to learn by allowing students to answer questions with immediate feedback. Such structured learning reinforcement tends to guide students' learning without considering learners' independence and individual reasoning. And such activities may inadvertently stifle the student's ability to develop critical thinking and self-expression skills. Fundamentally liberationism pedagogy dismisses the concept that education is merely about students learning things and more about the way students learn. Alternatively, the liberationist approach democratizes the classroom by redefining the role of the teacher and student. The teacher is no longer viewed as the sage on the stage but as a guide on the side. Instead, this approach views students as creators of knowledge and not empty vessels to be filled with knowledge. Moreover, students are well suited to decide how best to learn and which areas improvements are needed. This study will explore the classroom instructor as a servant leader in the twenty-first century, which allows students to integrate technology that encapsulates more individual learning styles. The researcher will examine the Professional Scrum Master (PSM I) exam pass rate results of 124 students in six sections of an Agile scrum course. The students will be separated into two groups; the first group will follow a structured instructor-led course outlined by a course syllabus. The second group will consist of several small teams (ten or fewer) of self-led and self-empowered students. The teams will conduct several event meetings that include sprint planning meetings, daily scrums, sprint reviews, and retrospective meetings throughout the semester will the instructor facilitating the teams' activities as needed. The methodology for this study will use the compare means t-test to compare the mean of an exam pass rate in one group to the mean of the second group. A one-tailed test (i.e., less than or greater than) will be used with the null hypothesis, for the difference between the groups in the population will be set to zero. The major findings will expand the pedagogical approach that suggests pedagogy primarily exist in support of teacher-led learning, which has formed the pillars of traditional classroom teaching. But in light of the fourth industrial revolution, there is a fusion of learning platforms across the digital, physical, and biological worlds with disruptive technological advancements in areas such as the Internet of Things (IoT), artificial intelligence (AI), 3D printing, robotics, and others.

Keywords: pedagogy, behaviorism, liberationism, flipping the classroom, servant leader instructor, agile scrum in education

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