Search results for: online learning tools

Authors: José A. Menezes, Giordano Cabral, Bruno T. Gomes

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Choosing good features is an essential part of machine learning. Recent techniques aim to automate this process. For instance, feature learning intends to learn the transformation of raw data into a useful representation to machine learning tasks. In automatic audio classification tasks, this is interesting since the audio, usually complex information, needs to be transformed into a computationally convenient input to process. Another technique tries to generate features by searching a feature space. Genetic algorithms, for instance, have being used to generate audio features by combining or modifying them. We find this approach particularly interesting and, despite the undeniable advances of feature learning approaches, we wanted to take a step forward in the use of genetic algorithms to find audio features, combining them with more conventional methods, like PCA, and inserting search control mechanisms, such as constraints over a confusion matrix. This work presents the results obtained on particular audio classification problems.

Keywords: feature generation, feature learning, genetic algorithm, music information retrieval

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Authors: Loghman Ansarian, Teoh Mei Lin

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In an attempt to increase oral proficiency of Iranian EFL learners, the researchers compared the effect of problem-based mobile-assisted language learning with the conventional language learning approach (Communicative Language Teaching) in Iran. The experimental group (n=37) went through PBL instruction and the control group (n=33) went through conventional instruction. The results of quantitative data analysis after 26 sessions of treatment revealed that PBL could positively affect participants' knowledge of grammar, vocabulary, spoken fluency, and pronunciation; however, in terms of task achievement, no significant effect was found. This study can have pedagogical implications for language teachers, and material developers.

Keywords: problem-based learning, spoken intelligibility, Iranian EFL context, cognitive learning

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Authors: E. Maoz

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Background: As a teaching method, project-based learning is strongly linked to developing students’ critical thinking skills. It combines creative independent thinking, team work, and disciplinary subject-field integration. In the 'Introduction to Nursing Research Methods' course (year 3, Generic Track), project based learning is used to teach the topic of 'Evidence-Based Nursing'. This topic examines a clinical care issue encountered by students in the field. At the end of their project, students present proposals for managing the said issue. Proposals are the product of independent integrative thinking integrating a wide range of factors influencing the issue’s management. Method: Papers by 27 groups of students (165 students) were content analyzed to identify which themes emerged from the students' recommendations for managing the clinical issue. Findings: Five main themes emerged—current management approach; adapting procedures in line with current recent research recommendations; training for change (veteran nursing staff, beginner students, patients, significant others); analysis of 'economic benefit vs. patient benefit'; multidisciplinary team engagement in implementing change in practice. Two surprising themes also emerged: advertising and marketing using new technologies, which reflects how the new generation thinks. Summary and Recommendations: Among the main challenges in nursing education is training nursing graduates to think independently, integratively, and critically. Combining PBL with classical teaching methods stimulates students cognitively while opening new vistas with implications on all levels of the profession: management, research, education, and practice. Advanced students can successfully grasp and interpret the current state of clinical practice. They are competent and open to leading change and able to consider the diverse factors and interconnections that characterize the nurse's work.

Keywords: evidence based nursing, critical thinking skills, project based learning, students education

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Authors: Lihua Zhu, Jianfeng Du, Yu Wang, Zhiqiang Wu

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Collision avoidance problems of a swarm of unmanned air vehicles (UAVs) flying in an obstacle-laden environment are investigated in this paper. Given that the UAV swarm needs to adapt to the obstacle distribution in dynamic operation, a priority configuration is designed to guide the UAVs to pass through the obstacles in turn. Based on the collision cone approach and the prediction of the collision time, a collision evaluation model is established to judge the urgency of the imminent collision of each UAV, and the evaluation result is used to assign the priority of each UAV to further instruct them going through the obstacles in descending order. At last, the simulation results provide the promising validation in terms of the efficiency and scalability of the proposed approach.

Keywords: UAV swarm, collision avoidance, complex environment, online priority design

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Authors: Radoslav Židek, Veronika Šidlová, Radovan Kasarda, Birgit Fuerst-Waltl

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Machine learning represents a set of topics dealing with the creation and evaluation of algorithms that facilitate pattern recognition, classification, and prediction, based on models derived from existing data. The data can present identification patterns which are used to classify into groups. The result of the analysis is the pattern which can be used for identification of data set without the need to obtain input data used for creation of this pattern. An important requirement in this process is careful data preparation validation of model used and its suitable interpretation. For breeders, it is important to know the origin of animals from the point of the genetic diversity. In case of missing pedigree information, other methods can be used for traceability of animal´s origin. Genetic diversity written in genetic data is holding relatively useful information to identify animals originated from individual countries. We can conclude that the application of data mining for molecular genetic data using supervised learning is an appropriate tool for hypothesis testing and identifying an individual.

Keywords: genetic data, Pinzgau cattle, supervised learning, machine learning

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Authors: Kauser Jahan, Jason Halvorsen, Kara Banks, Kara Natoli, Elizabeth McWeeney, Brittany LeMasney, Nicole Caramanna, Justin Hillman, Christopher Hauske, Meghan Sparks

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The Virtual Engineers on Wheels (ViEW) is a revised version of our established mobile K-12 outreach program Engineers on Wheels in order to address the pandemic. The Virtual Engineers on Wheels' (VIEW) goal has stayed the same as in prior years: to provide K-12 students and educators with the necessary resources to peak interest in the expanding fields of engineering. With these trying times, the Virtual Engineers on Wheels outreach has adapted its medium of instruction to be more seamless with the online approach to teaching and outreach. In the midst of COVID-19, providing a safe transfer of information has become a constraint for research. The focus has become how to uphold a level of quality instruction without diminishing the safety of those involved by promoting proper health practices and giving hope to students as well as their families. Furthermore, ViEW has created resources on effective strategies that minimize risk factors of COVID-19 and inform families that there is still a promising future ahead. To obtain these goals while still maintaining true to the hands-on learning that is so crucial to young minds, the approach is online video lectures followed by experiments within different engineering disciplines. ViEW has created a comprehensive website that students can leverage to explore the different fields of study. One of the experiments entails teaching about drone usage and how it might play a factor in the future of unmanned deliveries. Some of the other experiments focus on the differences in mask materials and their effectiveness, as well as their environmental outlook. Having students perform from home enables them a safe environment to learn at their own pace while still providing quality instruction that would normally be achieved in the classroom. Contact information is readily available on the website to provide interested parties with a means to ask their inquiries. As it currently stands, the interest in engineering/STEM-related fields is underrepresented from women and certain minority groups. So alongside the desire to grow interest, helping balance the scales is one of the main priorities of VIEW. In previous years, VIEW surveyed students before and after instruction to see if their perception of engineering has changed. In general, it is the understanding that being exposed to engineering/STEM at a young age increases the chances that it will be pursued later in life.

Keywords: STEM, engineering outreach, teaching pedagogy, pandemic

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Authors: Lizmol Mathew, Divya Thomas, Shiney Rajan

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Educational paradigm all over the globe is undergoing significant reform today. Because of this, so-called flipped classroom model is becoming increasingly popular in higher education. Flipped classroom has proved to be more effective than traditional lecture based model as flipped classroom model promotes active learning by encouraging students to work on in collaborative tasks and peer-led learning during the class-time. However, success of flipped classrooms relies on students’ ability and their attitudes towards collaboration and group work. This paper examines: 1) Students’ attitudes towards collaborative learning; 2) Main challenges to successful collaboration from students’ experience and 3) Students’ perception of criteria for successful team work. 4) Recommendations for enhancing collaborative learning. This study’s methodology involves quantitative analysis of surveys collected from students enrolled in undergraduate Architecture program at Qatar University. Analysis indicates that in general students enrolled in the program do not have positive perceptions or experiences associated with group work. Positive and negative factors that influence collaborative learning in higher education have been identified. Recommendations for improving collaborative work experience have been proposed.

Keywords: architecture, collaborative learning, female, group work, higher education, Middle East, Qatar, student experience

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Authors: Sakulsri Srisaracam

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Social media has become an important source of information for the public and the media profession. Some social issues raised on social media are picked up by journalists to report on other platforms. This relationship between social media and mainstream media can sometimes drive public debate or stimulate social movements. The question to examine is in what situations can social media conversations raise awareness and stimulate change on public issues. This study addresses the communication patterns of social media conversations driving covert issues into mainstream media and leading to social advocacy movements. In methodological terms, the study findings are based on a content analysis of Facebook, Twitter, news websites and television media reports on three different case studies – saving Bryde’s whale, protests against a government proposal to downsize the Office of Knowledge Management and Development in Thailand, and a dengue fever campaign. These case studies were chosen because they represent issues that most members of the public do not pay much attention to but social media conversations stimulated public debate and calls to action. This study found: 1) Collective social media conversations can stimulate public debate and encourage change at three levels – awareness, public debate, and action of policy and social change. The level depends on the communication patterns of online users and media coverage. 2) Patterns of communication have to be designed to combine social media conversations, online opinion leaders, mainstream media coverage and call to both online and offline action to motivate social change. Thus, this result suggests that social media is a powerful platform for collective communication and setting the agenda on public issues for mainstream media. However, for social change to succeed, social media should be used to mobilize online movements to move offline too.

Keywords: public issues, mainstream media, social media, social movement

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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: Vaikunthan Rajaratnam

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Maintaining continuous professional development among clinicians has been a challenge. Hand surgery is a unique speciality with the coming together of orthopaedics, plastics and trauma surgeons. The requirements for a team-based approach to care with the inclusion of other experts such as occupational, physiotherapist and orthotic and prosthetist provide the impetus for the creation of communities of practice. This study analysed the community of practice in hand surgery that was created through a social networking website for professionals. The main objectives were to discover the usefulness of this community of practice created in the platform of the group function of LinkedIn. The second objective was to determine the usability of this platform for the purposes of continuing professional development among members of this community of practice. The methodology used was one of mixed methods which included a quantitative analysis on the usefulness of the social network website as a community of practice, using the analytics provided by the LinkedIn platform. Further qualitative analysis was performed on the various postings that were generated by the community of practice within the social network website. This was augmented by a respondent driven survey conducted online to assess the usefulness of the platform for continuous professional development. A total of 31 respondents were involved in this study. This study has shown that it is possible to create an engaging and interactive community of practice among hand surgeons using the group function of this professional social networking website LinkedIn. Over three years the group has grown significantly with members from multiple regions and has produced engaging and interactive conversations online. From the results of the respondents’ survey, it can be concluded that there was satisfaction of the functionality and that it was an excellent platform for discussions and collaboration in the community of practice with a 69 % of satisfaction. Case-based discussions were the most useful functions of the community of practice. This platform usability was graded as excellent using the validated usability tool. This study has shown that the social networking site LinkedIn’s group function can be easily used as a community of practice effectively and provides convenience to professionals and has made an impact on their practice and better care for patients. It has also shown that this platform was easy to use and has a high level of usability for the average healthcare professional. This platform provided the improved connectivity among professionals involved in hand surgery care which allowed for the community to grow and with proper support and contribution of relevant material by members allowed for a safe environment for the exchange of knowledge and sharing of experience that is the foundation of a community practice.

Keywords: community of practice, online community, hand surgery, lifelong learning, LinkedIn, social media, continuing professional development

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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: 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: Carmela Mariano

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The literature, the scientific and disciplinary debate related to the impacts of climate change on the territory has highlighted, in recent years, the need for climate-proof and resilient tools of urban planning that adopt an integrated and inter-scalar approach for the construction of urban regeneration strategies by the objectives of the European Strategy on adaptation to climate change, the 2030 Agenda for Sustainable Development and the Climate Conference. This article addresses the operational implications of urban climate resilience in urban planning tools as a priority objective of policymakers (government bodies, institutions, etc.) to respond to the risks of climate change-related impacts on the environment. Within the general framework of the research activities carried out by the author, this article provides a critical synthesis of the analysis and evaluation of some case studies from the Italian national context, which enabled, through an inductive method, the assessment of the process of implementing the adaptation to climate change within the regional urban planning frameworks (regional urban laws), specific regional adaptation strategies or local adaptation plans and within the territorial and urban planning tools of a metropolitan or local scale. This study aims to identify theoretical–methodological, and operational references for the innovation and integration of planning tools concerning climate change that allow local planners to test these references in specific territorial contexts to practical adaptation strategies for local action.

Keywords: urban resilience, urban regeneration, climate-proof-planning, urban planning

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Authors: Mohamed Seghouani, Ahmed Tafraoui, Soltane Lebaili

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The purpose of this study widened knowledge on the use of the cutting tools out of metal carbide and to define it the influence of the elements of the mode of cut on the behavior of these tools during the machining of treated steel XC38 and untreated. This work aims at evolution determined in experiments of the wear of a cutting tool out of metal carbide with plate reported of P30 nuance for an operation of slide-lathing in turning on soaked and not hardened steel XC38 test-tubes. This research is based on the model of Taylor to determine the life span of the cutting tool according to the various parameters of cut, like the cutting speed Vc, the advance of cut a, the depth of cutting P. In order to express the operational limits of the tool for slide-lathing in a preventive way. The model makes it possible to determine the time of change of the tool and to regard it as a constraint for the respect of the roughness of the workpiece during a work of series in conventional machining.

Keywords: machining, wear, lifespan, model of Taylor, cutting tool, carburize metal

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Authors: Ya-Mei Chen

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Online crowdsourced translation, an innovative translation practice brought by Web 2.0 technologies and the democratization of information, has become increasingly popular in the Internet era. Carried out by grass-root internet users, crowdsourced translation contains fundamentally different features from its off-line traditional counterpart, such as voluntary participation and parallel collaboration. To better understand such a participatory and collaborative nature, this paper will use the online Chinese translation project of Global Voices as a case study to investigate the following issues: (1) the changes in volunteer translators’ and reviewers’ motivations for participation, (2) translators’ and reviewers’ use of translation strategies and (3) the correlations of translators’ and reviewers’ motivations and strategies with the organizational mission, the translation style guide, the translator-reviewer interaction, the mediation of the translation platform and various types of capital within the translation field. With an aim to systematically explore the above three issues, this paper will collect both quantitative and qualitative data and then draw upon Engestrom’s activity theory and Bourdieu’s field theory as a theoretical framework to analyze the data in question. An online anonymous questionnaire will be conducted to obtain the quantitative data. The questionnaire will contain questions related to volunteer translators’ and reviewers’ backgrounds, participation motivations, translation strategies and mutual relations as well as the operation of the translation platform. Concerning the qualitative data, they will come from (1) a comparative study between some English news texts published on Global Voices and their Chinese translations, (2) an analysis of the online discussion forum associated with Global Voices’ Chinese translation project and (3) the information about the project’s translation mission and guidelines. It is hoped that this research, through a detailed sociological analysis of a cause-driven crowdsourced translation project, can enable translation researchers and practitioners to adequately meet the translation challenges appearing in the digital age.

Keywords: crowdsourced translation, global voices, motivation, translation strategies

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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: Edeaghe Ehikhamenor, Jennifer Nnamdi

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Introduction: Gender-based violence (GBV) was a well-known global crisis before the COVID-19 pandemic. The pandemic burden only intensified the crisis. With prevailing lockdowns, increased poverty due to high unemployment, especially affecting females, and other mobility restrictions that have left many women trapped with their abusers, plus isolation from social contact and support networks, GBV cases spiraled out of control. Prevalence of economic with cultural disparity, which is greatly manifested in Nigeria, is a major contributory factor to GBV. This is made worst by religious adherents where the females are virtually relegated to the background. Our societal approaches to investigations and sanctions to culprits have not sufficiently applied forensic/DNA tools in combating these major vices. Violence against women or some rare cases against men can prevent them from carrying out their duties regardless of the position they hold. Objective: The main objective of this research is to highlight the origin of GBV, the victims, types, contributing factors, and the applications of forensics/DNA tools and remedies so as to minimize GBV in our society. Methods: Descriptive information was obtained through the search on our daily newspapers, electronic media, google scholar websites, other authors' observations and personal experiences, plus anecdotal reports. Results: Findings from our exploratory searches revealed a high incidence of GBV with very limited or no applications of Forensics/DNA tools as an intervening mechanism to reduce GBV in Nigeria. Conclusion: Nigeria needs to develop clear-cut policies on forensics/DNA tools in terms of institutional framework to develop a curriculum for the training of all stakeholders to fast-track justice for victims of GBV so as to serve as a deterrent to other culprits.

Keywords: gender-based violence, forensics, DNA, justice

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Authors: Maria L. Ulloa, Ruth M. Crawford, Stephanie Kelly, Joey Domdom

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In recent decades health and social service delivery have become more collaborative and interdisciplinary. Emerging trends suggest the need for an integrative and interprofessional approach to meet the challenges faced by professionals navigating the complexities of health and social service practice environments. Terms such as multidisciplinary practice, interprofessional collaboration, interprofessional education and transprofessional practice have become the common language used across a range of social services and health providers in western democratic systems. In Aotearoa New Zealand, one example of an interprofessional collaborative approach to curriculum design and delivery in health and social service is the development of an innovative Masters of Professional Practice programme. This qualification is the result of a strategic partnership between two tertiary institutions – Whitireia New Zealand (NZ) and the Wellington Institute of Technology (Weltec) in Wellington. The Master of Professional Practice programme was designed and delivered from the perspective of a collaborative, interprofessional and relational approach. Teachers and students in the programme come from a diverse range of cultural, professional and personal backgrounds and are engaged in courses using a blended learning approach that incorporates the values and pedagogies of interprofessional education. Students are actively engaged in professional practice while undertaking the programme. This presentation describes the themes of exploratory qualitative formative observations of engagement in class and online, student assessments, student research projects, as well as qualitative interviews with the programme teaching staff. These formative findings reveal the development of critical practice skills around the common themes of the programme: research and evidence based practice, education, leadership, working with diversity and advancing critical reflection of professional identities and interprofessional practice. This presentation will provide evidence of enhanced learning experiences in higher education and learning in multi-disciplinary contexts.

Keywords: diversity, exploratory research, interprofessional education, professional identity

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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: Regina Chua

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To reduce the costs of re-fielding a large survey, a Random Forest classifier was applied to measure the accuracy of classifying individuals into their assigned segments with the fewest possible questions. Given a long survey, one needed to determine the most predictive ten or fewer questions that would accurately assign new individuals to custom segments. Furthermore, the solution needed to be quick in its classification and usable in non-Python environments. In this paper, a supervised Random Forest classifier was modeled on a dataset with 7,000 individuals, 60 questions, and 254 features. The Random Forest consisted of an iterative collection of individual decision trees that result in a predicted segment with robust precision and recall scores compared to a single tree. A random 70-30 stratified sampling for training the algorithm was used, and accuracy trade-offs at different depths for each segment were identified. Ultimately, the Random Forest classifier performed at 87% accuracy at a depth of 10 with 20 instead of 254 features and 10 instead of 60 questions. With an acceptable accuracy in prioritizing feature selection, new tools were developed for non-Python environments: a worksheet with a formulaic version of the algorithm and an embedded function to predict the segment of an individual in real-time. Random Forest was determined to be an optimal classification model by its feature selection, performance, processing speed, and flexible application in other environments.

Keywords: machine learning, supervised learning, data science, random forest, classification, prediction, predictive modeling

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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: Yasemin Gulsen Yilmaz, Suleyman Hakan Yilmaz, Muhammet Erbay

Abstract:

The new communication technologies have gradually improved its efficiency in all fields of life and made its presence irreplaceable. These technologies which appear in every aspect of life differently showed itself during the failed coup attempt in Turkey too. The evening of July 15, 2016, have already taken its place in the Turkish political history. In the evening of July 15, Turkish nation confronted to a coup attempted by a group within the Turkish Armed Forces. That evening, the scene of the confrontation between the coup attempters and the resisting civilians were watched minute-by-minute by the people using the new communication technologies. Pro-coup soldiers and the resisting groups that came face to face in the streets of metropolitan cities, made their in-group communications by using new media tools very actively. New media turned into the most important weapon both for coup plotters and for those who resisted. In the morning of next day, whoever used these tools better had the upper hand. The civilians were successful in protecting democracy not only by resisting against tanks and bullets but also by following the internet, organising in social media, sharing information-photos on the net and telling large masses their experiences through these technologies. In this study, we focused on and analysed the use of new media both by coup soldiers and resisting civilians during the failed coup attempt in July 15. Within the scope of this study, coup attempt news that took place in printed media within one week were examined; the information about the use of new media tools during the night of failed coup were compiled; and it was determined how, to what extend and what for these tools were used and how effective they were.

Keywords: communication, July 15, new media, media

Procedia PDF Downloads 245

Authors: Valentin Père, Mathieu Milhé, Fabien Baillon, Jean-Louis Dirion

Abstract:

Microgrids offer potential solutions to meet the need for local grid stability and increase isolated networks autonomy with the integration of intermittent renewable energy production and storage facilities. In such a context, sizing production and storage for a given network is a complex task, highly depending on input data such as power load profile and renewable resource availability. This work aims at developing an operating cost computation methodology for different microgrid designs based on the use of deep reinforcement learning (RL) algorithms to tackle the optimal operation problem in stochastic environments. RL is a data-based sequential decision control method based on Markov decision processes that enable the consideration of random variables for control at a chosen time scale. Agents trained via RL constitute a promising class of Energy Management Systems (EMS) for the operation of microgrids with energy storage. Microgrid sizing (or design) is generally performed by minimizing investment costs and operational costs arising from the EMS behavior. The latter might include economic aspects (power purchase, facilities aging), social aspects (load curtailment), and ecological aspects (carbon emissions). Sizing variables are related to major constraints on the optimal operation of the network by the EMS. In this work, an islanded mode microgrid is considered. Renewable generation is done with photovoltaic panels; an electrochemical battery ensures short-term electricity storage. The controllable unit is a hydrogen tank that is used as a long-term storage unit. The proposed approach focus on the transfer of agent learning for the near-optimal operating cost approximation with deep RL for each microgrid size. Like most data-based algorithms, the training step in RL leads to important computer time. The objective of this work is thus to study the potential of Batch-Constrained Q-learning (BCQ) for the optimal sizing of microgrids and especially to reduce the computation time of operating cost estimation in several microgrid configurations. BCQ is an off-line RL algorithm that is known to be data efficient and can learn better policies than on-line RL algorithms on the same buffer. The general idea is to use the learned policy of agents trained in similar environments to constitute a buffer. The latter is used to train BCQ, and thus the agent learning can be performed without update during interaction sampling. A comparison between online RL and the presented method is performed based on the score by environment and on the computation time.

Keywords: batch-constrained reinforcement learning, control, design, optimal

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Authors: Doaa Alhaboby

Abstract:

Behavior change is a complex process that often requires ongoing support and guidance. Telecoaching programs have emerged as effective tools in facilitating behavior change by providing personalized support remotely. This abstract explores the lessons learned from a randomized controlled trial (RCT) evaluation of a telecoaching program focused on behavior change for Diabetics and discusses strategies for implementing these lessons to overcome the challenge of making physical activity a habit. The telecoaching program involved participants engaging in regular coaching sessions delivered via phone calls. These sessions aimed to address various aspects of behavior change, including goal setting, self-monitoring, problem-solving, and social support. Over the course of the program, participants received personalized guidance tailored to their unique needs and preferences. One of the key lessons learned from the RCT was the importance of engagement, readiness to change and the use of technology. Participants who set specific, measurable, attainable, relevant, and time-bound (SMART) goals were more likely to make sustained progress toward behavior change. Additionally, regular self-monitoring of behavior and progress was found to be instrumental in promoting accountability and motivation. Moving forward, implementing the lessons learned from the RCT can help individuals overcome the hardest part of behavior change: making physical activity a habit. One strategy is to prioritize consistency and establish a regular routine for physical activity. This may involve scheduling workouts at the same time each day or week and treating them as non-negotiable appointments. Additionally, integrating physical activity into daily life routines and taking into consideration the main challenges that can stop the process of integrating physical activity routines into the daily schedule can help make it more habitual. Furthermore, leveraging technology and digital tools can enhance adherence to physical activity goals. Mobile apps, wearable activity trackers, and online fitness communities can provide ongoing support, motivation, and accountability. These tools can also facilitate self-monitoring of behavior and progress, allowing individuals to track their activity levels and adjust their goals as needed. In conclusion, telecoaching programs offer valuable insights into behavior change and provide strategies for overcoming challenges, such as making physical activity a habit. By applying the lessons learned from these programs and incorporating them into daily life, individuals can cultivate sustainable habits that support their long-term health and well-being.

Keywords: lifestyle, behavior change, physical activity, chronic conditions

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Authors: Chaitanya Vyas

Abstract:

This paper identifies limitations of existing two e-Governance services viz. railway ticket booking and passport service in India. The comparison has been made as to how in the past these two citizen services were operating manually and how these services are taken online via e-Governance. Different e-Governance projects, investment aspects, and role of corporate are discussed. For Indian Railway online ticketing a comparison has been made between state run booking website and popular private firm run booking website. For passport service, observation through personal visit to passport center is described. Suggestions are made to improve these services further to improve citizen service experiences.

Keywords: e-Governance, citizen services, passport, Indian Railways

Procedia PDF Downloads 246