Search results for: self-regulated learning theory
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 10966

Search results for: self-regulated learning theory

6286 Unveiling Comorbidities in Irritable Bowel Syndrome: A UK BioBank Study utilizing Supervised Machine Learning

Authors: Uswah Ahmad Khan, Muhammad Moazam Fraz, Humayoon Shafique Satti, Qasim Aziz

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Approximately 10-14% of the global population experiences a functional disorder known as irritable bowel syndrome (IBS). The disorder is defined by persistent abdominal pain and an irregular bowel pattern. IBS significantly impairs work productivity and disrupts patients' daily lives and activities. Although IBS is widespread, there is still an incomplete understanding of its underlying pathophysiology. This study aims to help characterize the phenotype of IBS patients by differentiating the comorbidities found in IBS patients from those in non-IBS patients using machine learning algorithms. In this study, we extracted samples coding for IBS from the UK BioBank cohort and randomly selected patients without a code for IBS to create a total sample size of 18,000. We selected the codes for comorbidities of these cases from 2 years before and after their IBS diagnosis and compared them to the comorbidities in the non-IBS cohort. Machine learning models, including Decision Trees, Gradient Boosting, Support Vector Machine (SVM), AdaBoost, Logistic Regression, and XGBoost, were employed to assess their accuracy in predicting IBS. The most accurate model was then chosen to identify the features associated with IBS. In our case, we used XGBoost feature importance as a feature selection method. We applied different models to the top 10% of features, which numbered 50. Gradient Boosting, Logistic Regression and XGBoost algorithms yielded a diagnosis of IBS with an optimal accuracy of 71.08%, 71.427%, and 71.53%, respectively. Among the comorbidities most closely associated with IBS included gut diseases (Haemorrhoids, diverticular diseases), atopic conditions(asthma), and psychiatric comorbidities (depressive episodes or disorder, anxiety). This finding emphasizes the need for a comprehensive approach when evaluating the phenotype of IBS, suggesting the possibility of identifying new subsets of IBS rather than relying solely on the conventional classification based on stool type. Additionally, our study demonstrates the potential of machine learning algorithms in predicting the development of IBS based on comorbidities, which may enhance diagnosis and facilitate better management of modifiable risk factors for IBS. Further research is necessary to confirm our findings and establish cause and effect. Alternative feature selection methods and even larger and more diverse datasets may lead to more accurate classification models. Despite these limitations, our findings highlight the effectiveness of Logistic Regression and XGBoost in predicting IBS diagnosis.

Keywords: comorbidities, disease association, irritable bowel syndrome (IBS), predictive analytics

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6285 Using Peer Instruction in Physics of Waves for Pre-Service Science Teacher

Authors: Sumalee Tientongdee

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In this study, it was aimed to investigate Physics achievement of the pre-service science teacher studying in general science program at Suan Sunandha Rajabhat University, Bangkok, Thailand. The program has provided the new curriculum that focuses on 21st-century skills development. Active learning approaches are used to teach in all subjects. One of the active learning approaches Peer Instruction, or PI was used in this study to teach physics of waves as a compulsory course. It was conducted in the second semester from January to May of 2017. The concept test was given to evaluate pre-service science teachers’ understanding in concept of waves. Problem-solving assessment form was used to evaluate their problem-solving skill. The results indicated that after they had learned through Peer Instruction in physics of waves course, their concepts in physics of waves was significantly higher at 0.05 confident levels. Their problem-solving skill from the whole class was at the highest level. Based on the group interview on the opinions of using Peer Instruction in Physics class, they mostly felt that it was very useful and helping them understand more about physics, especially for female students.

Keywords: peer instruction, physics of waves, pre-service science teacher, Suan Sunandha Rajabhat university

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6284 Detecting Memory-Related Gene Modules in sc/snRNA-seq Data by Deep-Learning

Authors: Yong Chen

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To understand the detailed molecular mechanisms of memory formation in engram cells is one of the most fundamental questions in neuroscience. Recent single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) techniques have allowed us to explore the sparsely activated engram ensembles, enabling access to the molecular mechanisms that underlie experience-dependent memory formation and consolidation. However, the absence of specific and powerful computational methods to detect memory-related genes (modules) and their regulatory relationships in the sc/snRNA-seq datasets has strictly limited the analysis of underlying mechanisms and memory coding principles in mammalian brains. Here, we present a deep-learning method named SCENTBOX, to detect memory-related gene modules and causal regulatory relationships among themfromsc/snRNA-seq datasets. SCENTBOX first constructs codifferential expression gene network (CEGN) from case versus control sc/snRNA-seq datasets. It then detects the highly correlated modules of differential expression genes (DEGs) in CEGN. The deep network embedding and attention-based convolutional neural network strategies are employed to precisely detect regulatory relationships among DEG genes in a module. We applied them on scRNA-seq datasets of TRAP; Ai14 mouse neurons with fear memory and detected not only known memory-related genes, but also the modules and potential causal regulations. Our results provided novel regulations within an interesting module, including Arc, Bdnf, Creb, Dusp1, Rgs4, and Btg2. Overall, our methods provide a general computational tool for processing sc/snRNA-seq data from case versus control studie and a systematic investigation of fear-memory-related gene modules.

Keywords: sc/snRNA-seq, memory formation, deep learning, gene module, causal inference

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6283 Electroencephalography-Based Intention Recognition and Consensus Assessment during Emergency Response

Authors: Siyao Zhu, Yifang Xu

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After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. The hands-free requirement from the first responders excludes the use of tedious manual control and operation. In unknown, unstructured, and obstructed environments, natural-language-based supervision is not amenable for first responders to formulate, and is difficult for robots to understand. Brain-computer interface is a promising option to overcome the limitations. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: consensus assessment, electroencephalogram, emergency response, human-robot collaboration, intention recognition, search and rescue

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6282 An Interactive Institutional Framework for Evolution of Enterprise Technological Innovation Capabilities System: A Complex Adaptive Systems Approach

Authors: Sohail Ahmed, Ke Xing

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This research theoretically explored the evolution mechanism of enterprise technological innovation capability system (ETICS) from the perspective of complex adaptive systems (CAS). This research proposed an analytical framework for ETICS, its concepts, and theory by integrating CAS methodology into the management of the technological innovation capability of enterprises and discusses how to use the principles of complexity to analyze the composition, evolution, and realization of the technological innovation capabilities in complex dynamic environments. This paper introduces the concept and interaction of multi-agent, the theoretical background of CAS, and summarizes the sources of technological innovation, the elements of each subject, and the main clusters of adaptive interactions and innovation activities. The concept of multi-agents is applied through the linkages of enterprises, research institutions, and government agencies with the leading enterprises in industrial settings. The study was exploratory and based on CAS theory. Theoretical model is built by considering technological and innovation literature from foundational to state of the art projects of technological enterprises. On this basis, the theoretical model is developed to measure the evolution mechanism of the enterprise's technological innovation capability system. This paper concludes that the main characteristics for evolution in technological systems are based on the enterprise’s research and development personnel, investments in technological processes, and innovation resources are responsible for the evolution of enterprise technological innovation performance. The research specifically enriched the application process of technological innovation in institutional networks related to enterprises.

Keywords: complex adaptive system, echo model, enterprise technological innovation capability system, research institutions, multi-agents

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6281 Sparse Representation Based Spatiotemporal Fusion Employing Additional Image Pairs to Improve Dictionary Training

Authors: Dacheng Li, Bo Huang, Qinjin Han, Ming Li

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Remotely sensed imagery with the high spatial and temporal characteristics, which it is hard to acquire under the current land observation satellites, has been considered as a key factor for monitoring environmental changes over both global and local scales. On a basis of the limited high spatial-resolution observations, challenged studies called spatiotemporal fusion have been developed for generating high spatiotemporal images through employing other auxiliary low spatial-resolution data while with high-frequency observations. However, a majority of spatiotemporal fusion approaches yield to satisfactory assumption, empirical but unstable parameters, low accuracy or inefficient performance. Although the spatiotemporal fusion methodology via sparse representation theory has advantage in capturing reflectance changes, stability and execution efficiency (even more efficient when overcomplete dictionaries have been pre-trained), the retrieval of high-accuracy dictionary and its response to fusion results are still pending issues. In this paper, we employ additional image pairs (here each image-pair includes a Landsat Operational Land Imager and a Moderate Resolution Imaging Spectroradiometer acquisitions covering the partial area of Baotou, China) only into the coupled dictionary training process based on K-SVD (K-means Singular Value Decomposition) algorithm, and attempt to improve the fusion results of two existing sparse representation based fusion models (respectively utilizing one and two available image-pair). The results show that more eligible image pairs are probably related to a more accurate overcomplete dictionary, which generally indicates a better image representation, and is then contribute to an effective fusion performance in case that the added image-pair has similar seasonal aspects and image spatial structure features to the original image-pair. It is, therefore, reasonable to construct multi-dictionary training pattern for generating a series of high spatial resolution images based on limited acquisitions.

Keywords: spatiotemporal fusion, sparse representation, K-SVD algorithm, dictionary learning

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6280 Uncovering Geometrical Ideas in Weaving: An Ethnomathematical Approaches to School Pedagogy

Authors: Jaya Bishnu Pradhan

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Weaving mat is one of the common activities performed in different community generally in the rural part of Nepal. Mat weavers’ practice mathematical ideas and concepts implicitly in order to perform their job. This study is intended to uncover the mathematical ideas embedded in mat weaving that can help teachers and students for the teaching and learning of school geometry. The ethnographic methodology was used to uncover and describe the beliefs, values, understanding, perceptions, and attitudes of the mat weavers towards mathematical ideas and concepts in the process of mat weaving. A total of 4 mat weavers, two mathematics teachers and 12 students from grade level 6-8, who are used to participate in weaving, were selected for the study. The whole process of the mat weaving was observed in a natural setting. The classroom observation and in-depth interview were taken with the participants with the help of interview guidelines and observation checklist. The data obtained from the field were categorized according to the themes regarding mathematical ideas embedded in the weaving activities, and its possibilities in teaching learning of school geometry. In this study, the mathematical activities in different sectors of their lives, their ways of understanding the natural phenomena, and their ethnomathematical knowledge were analyzed with the notions of pluralism. From the field data, it was found that the mat weaver exhibited sophisticated geometrical ideas in the process of construction of frame of mat. They used x-test method for confirming if the mat is rectangular. Mat also provides a good opportunity to understand the space geometry. A rectangular form of mat may be rolled up when it is not in use and can be converted to a cylindrical form, which usually can be used as larder so as to reserve food grains. From the observation of the situations, this cultural experience enables students to calculate volume, curved surface area and total surface area of the cylinder. The possibilities of incorporation of these cultural activities and its pedagogical use were observed in mathematics classroom. It is argued that it is possible to use mat weaving activities in the teaching and learning of school geometry.

Keywords: ethnography, ethnomathematics, geometry, mat weaving, school pedagogy

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6279 Predicting Provider Service Time in Outpatient Clinics Using Artificial Intelligence-Based Models

Authors: Haya Salah, Srinivas Sharan

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Healthcare facilities use appointment systems to schedule their appointments and to manage access to their medical services. With the growing demand for outpatient care, it is now imperative to manage physician's time effectively. However, high variation in consultation duration affects the clinical scheduler's ability to estimate the appointment duration and allocate provider time appropriately. Underestimating consultation times can lead to physician's burnout, misdiagnosis, and patient dissatisfaction. On the other hand, appointment durations that are longer than required lead to doctor idle time and fewer patient visits. Therefore, a good estimation of consultation duration has the potential to improve timely access to care, resource utilization, quality of care, and patient satisfaction. Although the literature on factors influencing consultation length abound, little work has done to predict it using based data-driven approaches. Therefore, this study aims to predict consultation duration using supervised machine learning algorithms (ML), which predicts an outcome variable (e.g., consultation) based on potential features that influence the outcome. In particular, ML algorithms learn from a historical dataset without explicitly being programmed and uncover the relationship between the features and outcome variable. A subset of the data used in this study has been obtained from the electronic medical records (EMR) of four different outpatient clinics located in central Pennsylvania, USA. Also, publicly available information on doctor's characteristics such as gender and experience has been extracted from online sources. This research develops three popular ML algorithms (deep learning, random forest, gradient boosting machine) to predict the treatment time required for a patient and conducts a comparative analysis of these algorithms with respect to predictive performance. The findings of this study indicate that ML algorithms have the potential to predict the provider service time with superior accuracy. While the current approach of experience-based appointment duration estimation adopted by the clinic resulted in a mean absolute percentage error of 25.8%, the Deep learning algorithm developed in this study yielded the best performance with a MAPE of 12.24%, followed by gradient boosting machine (13.26%) and random forests (14.71%). Besides, this research also identified the critical variables affecting consultation duration to be patient type (new vs. established), doctor's experience, zip code, appointment day, and doctor's specialty. Moreover, several practical insights are obtained based on the comparative analysis of the ML algorithms. The machine learning approach presented in this study can serve as a decision support tool and could be integrated into the appointment system for effectively managing patient scheduling.

Keywords: clinical decision support system, machine learning algorithms, patient scheduling, prediction models, provider service time

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6278 Performants: A Digital Event Manager-Organizer

Authors: Ioannis Andrianakis, Manolis Falelakis, Maria Pavlidou, Konstantinos Papakonstantinou, Ermioni Avramidou, Dimitrios Kalogiannis, Nikolaos Milios, Katerina Bountakidou, Kiriakos Chatzidimitriou, Panagiotis Panagiotopoulos

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Artistic events, such as concerts and performances, are challenging to organize because they involve many people with different skill sets. Small and medium venues often struggle to afford the costs and overheads of booking and hosting remote artists, especially if they lack sponsors or subsidies. This limits the opportunities for both venues and artists, especially those outside of big cities. However, more and more research shows that audiences prefer smaller-scale events and concerts, which benefit local economies and communities. To address this challenge, our project “PerformAnts: Digital Event Manager-Organizer” aims to develop a smart digital tool that automates and optimizes the processes and costs of live shows and tours. By using machine learning, applying best practices and training users through workshops, our platform offers a comprehensive solution for a growing market, enhances the mobility of artists and the accessibility of venues and allows professionals to focus on the creative aspects of concert production.

Keywords: event organization, creative industries, event promotion, machine learning

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6277 Organizational Culture and Its Internalization of Change in the Manufacturing and Service Sector Industries in India

Authors: Rashmi Uchil, A. H. Sequeira

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Post-liberalization era in India has seen an unprecedented growth of mergers, both domestic as well as cross-border deals. Indian organizations have slowly begun appreciating this inorganic method of growth. However, all is not well as is evidenced in the lowering value creation of organizations after mergers. Several studies have identified that organizational culture is one of the key factors that affects the success of mergers. But very few studies have been attempted in this realm in India. The current study attempts to identify the factors in the organizational culture variable that may be unique to India. It also focuses on the difference in the impact of organizational culture on merger of organizations in the manufacturing and service sectors in India. The study uses a mixed research approach. An exploratory research approach is adopted to identify the variables that constitute organizational culture specifically in the Indian scenario. A few hypotheses were developed from the identified variables and tested to arrive at the Grounded Theory. The Grounded Theory approach used in the study, attempts to integrate the variables related to organizational culture. Descriptive approach is used to validate the developed grounded theory with a new empirical data set and thus test the relationship between the organizational culture variables and the success of mergers. Empirical data is captured from merged organizations situated in major cities of India. These organizations represent significant proportions of the total number of organizations which have adopted mergers. The mix of industries included software, banking, manufacturing, pharmaceutical and financial services. Mixed sampling approach was adopted for this study. The first phase of sampling was conducted using the probability method of stratified random sampling. The study further used the non-probability method of judgmental sampling. Adequate sample size was identified for the study which represents the top, middle and junior management levels of the organizations that had adopted mergers. Validity and reliability of the research instrument was ensured with appropriate tests. Statistical tools like regression analysis, correlation analysis and factor analysis were used for data analysis. The results of the study revealed a strong relationship between organizational culture and its impact on the success of mergers. The study also revealed that the results were unique to the extent that they highlighted a marked difference in the manner of internalization of change of organizational culture after merger by the organizations in the manufacturing sector. Further, the study reveals that the organizations in the service sector internalized the changes at a slower rate. The study also portrays the industries in the manufacturing sector as more proactive and can contribute to a change in the perception of the said organizations.

Keywords: manufacturing industries, mergers, organizational culture, service industries

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6276 Social Media Diffusion And Implications For Opinion Leadership In Northcentral Nigeria

Authors: Chuks Odiegwu-Enwerem

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The classical notion of opinion leadership presupposes that the media is at the center of an effective and successful opinion leadership. Under this idea, an opinion leader is an active media user who consumes, understands, digests and interprets the messages for the understanding and acceptance/adoption by lower-end media users – whose access and understanding of media content are supposedly low. Because of their unique access to and presumed understanding of media functions and their content, opinion leaders are typically esteemed by those who look forward to and accept their opinions. Lazarsfeld and Katz’s two-step flow of communication theory is the basis of opinion leadership – propelled by limited access to the media. With the emergence and spread of social media and its unlimited access by all and sundry, however, the study interrogates the relevance and application of opinion leaders and, by implication, the two-step flow communication theory in Nigeria’s Northcentral region. It seeks to determine whether opinion leaders still exist in the picture and if they still exert considerable influence, especially in matters of political conversations and decision-making among the citizens of this area. It further explores whether the diffusion of social media is a reality and how the ‘low-end’ media users react to the new-found freedom of access to media, and how they are using it to inform their decisions on important matters as well as examines if they are still glued to their opinion leaders. This study explores the empirical dimensions of the two-step flow hypothesis in relation to the activities of social media to determine if a change has occurred and in what direction, using mixed methos of Survey and in-depth interviews. Our understanding and belief in some theoretical assumptions may be enhanced or challenged by the study outcome.

Keywords: Opinion Leadership, Active Media User, Two-Step-Flow, Social media, Northcentral Nigeria

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6275 Improving Cell Type Identification of Single Cell Data by Iterative Graph-Based Noise Filtering

Authors: Annika Stechemesser, Rachel Pounds, Emma Lucas, Chris Dawson, Julia Lipecki, Pavle Vrljicak, Jan Brosens, Sean Kehoe, Jason Yap, Lawrence Young, Sascha Ott

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Advances in technology make it now possible to retrieve the genetic information of thousands of single cancerous cells. One of the key challenges in single cell analysis of cancerous tissue is to determine the number of different cell types and their characteristic genes within the sample to better understand the tumors and their reaction to different treatments. For this analysis to be possible, it is crucial to filter out background noise as it can severely blur the downstream analysis and give misleading results. In-depth analysis of the state-of-the-art filtering methods for single cell data showed that they do, in some cases, not separate noisy and normal cells sufficiently. We introduced an algorithm that filters and clusters single cell data simultaneously without relying on certain genes or thresholds chosen by eye. It detects communities in a Shared Nearest Neighbor similarity network, which captures the similarities and dissimilarities of the cells by optimizing the modularity and then identifies and removes vertices with a weak clustering belonging. This strategy is based on the fact that noisy data instances are very likely to be similar to true cell types but do not match any of these wells. Once the clustering is complete, we apply a set of evaluation metrics on the cluster level and accept or reject clusters based on the outcome. The performance of our algorithm was tested on three datasets and led to convincing results. We were able to replicate the results on a Peripheral Blood Mononuclear Cells dataset. Furthermore, we applied the algorithm to two samples of ovarian cancer from the same patient before and after chemotherapy. Comparing the standard approach to our algorithm, we found a hidden cell type in the ovarian postchemotherapy data with interesting marker genes that are potentially relevant for medical research.

Keywords: cancer research, graph theory, machine learning, single cell analysis

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6274 SVM-RBN Model with Attentive Feature Culling Method for Early Detection of Fruit Plant Diseases

Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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6273 The Influence of English Immersion Program on Academic Performance: Case Study at a Sino-US Cooperative University in China

Authors: Leah Li Echiverri, Haoyu Shang, Yue Li

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Wenzhou-Kean University (WKU) is a Sino-US Cooperative University in China. It practices the English Immersion Program (EIP), where all the courses are taught in English. Class discussions and presentations are pervasively interwoven in designing students’ learning experiences. This WKU model has brought positive influences on students and is in some way ahead of traditional college English majors. However, literature to support the perceptions on the positive outcomes of this teaching and learning model remain scarce. The distinctive profile of Chinese-ESL students in an English Medium of Instruction (EMI) environment contributes further to the scarcity of literature compared to existing studies conducted among ESL learners in Western educational settings. Hence, the study investigated the students’ perceptions towards the English Immersion Program and determine how it influences Chinese-ESL students’ academic performance (AP). This research can provide empirical data that would be helpful to educators, teaching practitioners, university administrators, and other researchers in making informed decisions when developing curricular reforms, instructional and pedagogical methods, and university-wide support programs using this educational model. The purpose of the study was to establish the relationship between the English Immersion Program and Academic Performance among Chinese-ESL students enrolled at WKU for the academic year 2020-2021. Course length, immersion location, course type, and instructional design were the constructs of the English immersion program. English language learning, learning efficiency, and class participation were used to measure academic performance. Descriptive-correlational design was used in this cross-sectional research project. A quantitative approach for data analysis was applied to determine the relationship between the English immersion program and Chinese-ESL students’ academic performance. The research was conducted at WKU; a Chinese-American jointly established higher educational institution located in Wenzhou, Zhejiang province. Convenience, random, and snowball sampling of 283 students, a response rate of 10.5%, were applied to represent the WKU student population. The questionnaire was posted through the survey website named Wenjuanxing and shared to QQ or WeChat. Cronbach’s alpha was used to test the reliability of the research instrument. Findings revealed that when professors integrate technology (PowerPoint, videos, and audios) in teaching, students pay more attention. This contributes to the acquisition of more professional knowledge in their major courses. As to course immersion, students perceive WKU as a good place to study, providing them a high degree of confidence to talk with their professors in English. This also contributes to their English fluency and better pronunciation in their communication. In the construct of designing instruction, the use of pictures, video clips, and professors’ non-verbal communication, and demonstration of concern for students encouraged students to be more active in-class participation. Findings on course length and academic performance indicated that students’ perception regarding taking courses during fall and spring terms can moderately contribute to their academic performance. In conclusion, the findings revealed a significantly strong positive relationship between course type, immersion location, instructional design, and academic performance.

Keywords: class participation, English immersion program, English language learning, learning efficiency

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6272 Appropriation of Cryptocurrencies as a Payment Method by South African Retailers

Authors: Neliswa Dyosi

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Purpose - Using an integrated Technology-Organization-Environment (TOE) framework and the model of technology appropriation (MTA) as a theoretical lens, this interpretive qualitative study seeks to understand and explain the factors that influence the appropriation, non-appropriation, and disappropriation of bitcoin as a payment method by South African retailers. Design/methodology/approach –The study adopts the interpretivist philosophical paradigm. Multiple case studies will be adopted as a research strategy. For data collection, the study follows a qualitative approach. Qualitative data will be collected from the six retailers in various industries. Semi-structured interviews and documents will be used as the data collection techniques. Purposive and snowballing sampling techniques will be used to identify participants within the organizations. Data will be analyzed using thematic analysis. Originality/value - Using the deduction approach, the study seeks to provide a descriptive and explanatory contribution to theory. The study contributes to theory development by integrating the MTA and TOE frameworks as a means to understand technology adoption behaviors of organizations, in this case, retailers. This is also the first study that looks at an integrated approach of the Technology-Organization-Environment (TOE) framework and the MTA framework to understand the adoption and use of a payment method. South Africa is ranked amongst the top ten countries in the world on cryptocurrency adoption. There is, however, still a dearth of literature on the current state of adoption and usage of bitcoin as a payment method in South Africa. The study will contribute to the existing literature as bitcoin cryptocurrency is gaining popularity as an alternative payment method across the globe.

Keywords: cryptocurrency, bitcoin, payment methods, blockchain, appropriation, online retailers, TOE framework, disappropriation, non-appropriation

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6271 Theoretical Study of Gas Adsorption in Zirconium Clusters

Authors: Rasha Al-Saedi, Anthony Meijer

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The progress of new porous materials has increased rapidly over the past decade for use in applications such as catalysis, gas storage and removal of environmentally unfriendly species due to their high surface area and high thermal stability. In this work, a theoretical study of the zirconium-based metal organic framework (MOFs) were examined in order to determine their potential for gas adsorption of various guest molecules: CO2, N2, CH4 and H2. The zirconium cluster consists of an inner Zr6O4(OH)4 core in which the triangular faces of the Zr6- octahedron are alternatively capped by O and OH groups which bound to nine formate groups and three benzoate groups linkers. General formula is [Zr(μ-O)4(μ-OH)4(HCOO)9((phyO2C)3X))] where X= CH2OH, CH2NH2, CH2CONH2, n(NH2); (n = 1-3). Three types of adsorption sites on the Zr metal center have been studied, named according to capped chemical groups as the ‘−O site’; the H of (μ-OH) site removed and added to (μ-O) site, ‘–OH site’; (μ-OH) site removed, the ‘void site’ where H2O molecule removed; (μ-OH) from one site and H from other (μ-OH) site, in addition to no defect versions. A series of investigations have been performed aiming to address this important issue. First, density functional theory DFT-B3LYP method with 6-311G(d,p) basis set was employed using Gaussian 09 package in order to evaluate the gas adsorption performance of missing-linker defects in zirconium cluster. Next, study the gas adsorption behaviour on different functionalised zirconium clusters. Those functional groups as mentioned above include: amines, alcohol, amide, in comparison with non-substitution clusters. Then, dispersion-corrected density functional theory (DFT-D) calculations were performed to further understand the enhanced gas binding on zirconium clusters. Finally, study the water effect on CO2 and N2 adsorption. The small functionalized Zr clusters were found to result in good CO2 adsorption over N2, CH4, and H2 due to the quadrupole moment of CO2 while N2, CH4 and H2 weakly polar or non-polar. The adsorption efficiency was determined using the dispersion method where the adsorption binding improved as most of the interactions, for example, van der Waals interactions are missing with the conventional DFT method. The calculated gas binding strengths on the no defect site are higher than those on the −O site, −OH site and the void site, this difference is especially notable for CO2. It has been stated that the enhanced affinity of CO2 of no defect versions is most likely due to the electrostatic interactions between the negatively charged O of CO2 and the positively charged H of (μ-OH) metal site. The uptake of the gas molecule does not enhance in presence of water as the latter binds to Zr clusters more strongly than gas species which attributed to the competition on adsorption sites.

Keywords: density functional theory, gas adsorption, metal- organic frameworks, molecular simulation, porous materials, theoretical chemistry

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6270 The Practices Perspective in Communication, Consumer and Cultural Studies: A Post-Heideggerian Narrative

Authors: Tony Wilson

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This paper sets out a practices perspective or practices theory, which has become pervasive from business to sociological studies. In doing so, it locates the perspective historically (in the work of the philosopher Heidegger) and provides a contemporary illustration of its application to communication, consumer and cultural studies as central to this conference theme. The structured account of practices (as articulated in eight ‘axioms’) presented towards the conclusion of this paper is an initial statement - planned to encourage further detailed qualitative and systematic research in areas of interest to the conference. Practice theories of equipped and situated construction of participatory meaning (as in media and marketing consuming) are frequently characterized as lacking common ground, or core principles. This paper explores whether by retracing a journey to earlier philosophical underwriting, a shared territory promoting new research can be located as current philosophical hermeneutics. Moreover, through returning to hermeneutic first principles, the paper shows that a series of spatio-temporal metaphors become available - appropriate to analyzing communication as a process across disciplines in which it is considered. Thus one can argue, for instance, that media users engage (enter) digital text from their diverse ‘horizons of expectation’, in a productive enlarging ‘fusion’ of horizons of understanding, thereby ‘projecting’ a new narrative, integrated in a ‘hermeneutic circle’ of meaning. A politics of communication studies may contest a horizon of understanding - so engaging in critical ‘distancing’. Marketing’s consumers can occupy particular places on a horizon of understanding. Media users pass over borders of changing, revised perspectives. Practices research can now not only be discerned in multiple disciplines but equally crosses disciplines. The ubiquitous practice of media use by managers and visitors in a shopping mall - the mediatization of malls - responds to investigating not just with media study expertise, but from an interpretive marketing perspective. How have mediated identities of person or place been changed? Emphasizing understanding of entities in a material environment as ‘equipment’, practices theory enables the quantitative correlation of use and demographic variable as ‘Zeug Score’. Human behavior is fundamentally habitual - shaped by its tacit assumptions - occasionally interrupted by reflection. Practices theory acknowledges such action to be minimally monitored yet nonetheless considers it as constructing narrative. Thus presented in research, ‘storied’ behavior can then be seen to be (in)formed and shaped from a shifting hierarchy of ‘horizons’ or of perspectives - from habituated to reflective - rather than a single seamless narrative. Taking a communication practices perspective here avoids conflating tacit, transformative and theoretical understanding in research. In short, a historically grounded and unifying statement of contemporary practices theory will enhance its potential as a tool in communication, consumer and cultural research, landscaping interpretative horizons of human behaviour through exploring widely the culturally (in)formed narratives equipping and incorporated (reflectively, unreflectively) in people’s everyday lives.

Keywords: communication, consumer, cultural practices, hermeneutics

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6269 Specific Language Impirment in Kannada: Evidence Form a Morphologically Complex Language

Authors: Shivani Tiwari, Prathibha Karanth, B. Rajashekhar

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Impairments of syntactic morphology are often considered central in children with Specific Language Impairment (SLI). In English and related languages, deficits of tense-related grammatical morphology could serve as a clinical marker of SLI. Yet, cross-linguistic studies on SLI in the recent past suggest that the nature and severity of morphosyntactic deficits in children with SLI varies with the language being investigated. Therefore, in the present study we investigated the morphosyntactic deficits in a group of children with SLI who speak Kannada, a morphologically complex Dravidian language spoken in Indian subcontinent. A group of 15 children with SLI participated in this study. Two more groups of typical developing children (15 each) matched for language and age to children with SLI, were included as control participants. All participants were assessed for morphosyntactic comprehension and expression using standardized language test and a spontaneous speech task. Results of the study showed that children with SLI differed significantly from age-matched but not language-matched control group, on tasks of both comprehension and expression of morphosyntax. This finding is, however, in contrast with the reports of English-speaking children with SLI who are reported to be poorer than younger MLU-matched children on tasks of morphosyntax. The observed difference in impairments of morphosyntax in Kannada-speaking children with SLI from English-speaking children with SLI is explained based on the morphological richness theory. The theory predicts that children with SLI perform relatively better in morphologically rich language due to occurrence of their frequent and consistent features that mark the morphological markers. The authors, therefore, conclude that language-specific features do influence manifestation of the disorder in children with SLI.

Keywords: specific language impairment, morphosyntax, Kannada, manifestation

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6268 Enhancing Spatial Interpolation: A Multi-Layer Inverse Distance Weighting Model for Complex Regression and Classification Tasks in Spatial Data Analysis

Authors: Yakin Hajlaoui, Richard Labib, Jean-François Plante, Michel Gamache

Abstract:

This study introduces the Multi-Layer Inverse Distance Weighting Model (ML-IDW), inspired by the mathematical formulation of both multi-layer neural networks (ML-NNs) and Inverse Distance Weighting model (IDW). ML-IDW leverages ML-NNs' processing capabilities, characterized by compositions of learnable non-linear functions applied to input features, and incorporates IDW's ability to learn anisotropic spatial dependencies, presenting a promising solution for nonlinear spatial interpolation and learning from complex spatial data. it employ gradient descent and backpropagation to train ML-IDW, comparing its performance against conventional spatial interpolation models such as Kriging and standard IDW on regression and classification tasks using simulated spatial datasets of varying complexity. the results highlight the efficacy of ML-IDW, particularly in handling complex spatial datasets, exhibiting lower mean square error in regression and higher F1 score in classification.

Keywords: deep learning, multi-layer neural networks, gradient descent, spatial interpolation, inverse distance weighting

Procedia PDF Downloads 30
6267 Psychophysiological Adaptive Automation Based on Fuzzy Controller

Authors: Liliana Villavicencio, Yohn Garcia, Pallavi Singh, Luis Fernando Cruz, Wilfrido Moreno

Abstract:

Psychophysiological adaptive automation is a concept that combines human physiological data and computer algorithms to create personalized interfaces and experiences for users. This approach aims to enhance human learning by adapting to individual needs and preferences and optimizing the interaction between humans and machines. According to neurosciences, the working memory demand during the student learning process is modified when the student is learning a new subject or topic, managing and/or fulfilling a specific task goal. A sudden increase in working memory demand modifies the level of students’ attention, engagement, and cognitive load. The proposed psychophysiological adaptive automation system will adapt the task requirements to optimize cognitive load, the process output variable, by monitoring the student's brain activity. Cognitive load changes according to the student’s previous knowledge, the type of task, the difficulty level of the task, and the overall psychophysiological state of the student. Scaling the measured cognitive load as low, medium, or high; the system will assign a task difficulty level to the next task according to the ratio between the previous-task difficulty level and student stress. For instance, if a student becomes stressed or overwhelmed during a particular task, the system detects this through signal measurements such as brain waves, heart rate variability, or any other psychophysiological variables analyzed to adjust the task difficulty level. The control of engagement and stress are considered internal variables for the hypermedia system which selects between three different types of instructional material. This work assesses the feasibility of a fuzzy controller to track a student's physiological responses and adjust the learning content and pace accordingly. Using an industrial automation approach, the proposed fuzzy logic controller is based on linguistic rules that complement the instrumentation of the system to monitor and control the delivery of instructional material to the students. From the test results, it can be proved that the implemented fuzzy controller can satisfactorily regulate the delivery of academic content based on the working memory demand without compromising students’ health. This work has a potential application in the instructional design of virtual reality environments for training and education.

Keywords: fuzzy logic controller, hypermedia control system, personalized education, psychophysiological adaptive automation

Procedia PDF Downloads 62
6266 Defining Heritage Language Learners of Arabic: Linguistic and Cultural Factors

Authors: Rasha Elhawari

Abstract:

Heritage language learners (HLL) are part of the linguistic reality in Foreign Language Learning (FLL). These learners present several characteristics that are different from non-heritage language learners. They have a personal connection with the language and their motivation to learn the language is partly because of this personal connection. In Canada there is a large diversity in the foreign language learning classroom; the Arabic language classroom is no exception. The Arabic HLL is unique for more than one reason. First, is the fact that the Arabic language is spoken across twenty-two Arab countries across the Arab World. Across the Arab World there is a standard variation and a local dialect that co-exist side by side, i.e. diaglossia exists in a strong and unique way as a feature of Arabic. Second, Arabic is the language that all Muslims across the Muslim World use for their prayers. This raises a number of points when we consider Arabic as a Heritage Language; namely the role of diaglossia, culture and religion. The fact that there is a group of leaners that can be regarded as HLL who are not of Arabic speaking background but are Muslims and use the language for religious purposes is unique, thus course developers and language instructors need take this into consideration. The paper takes a closer look at this distinction and establishes sub-groups the Arabic HLLs in a language and/or culture specific way related mainly to the Arabic HLL. It looks at the learners at the beginners’ Arabic class at the undergraduate university level over a period of three years in order to define this learner. Learners belong to different groups and backgrounds but they all share common characteristics. The paper presents a detailed look at the learner types present at this class in order to help prepare and develop material for this specific learner group. The paper shows that separate HLL and non-HLL courses, especially at the introductory and intermediate level, is successful in resolving some of the pedagogical problems that occur in the Arabic as a Foreign Language classroom. In conclusion, the paper recommends the development of HLL courses at the early levels of language learning. It calls for a change in the pedagogical practices to overcome some of the challenges learner in the introductory Arabic class can face.

Keywords: Arabic, Heritage Language, langauge learner, teaching

Procedia PDF Downloads 390
6265 Antecedents of Knowledge Sharing: Investigating the Influence of Knowledge Sharing Factors towards Postgraduate Research Supervision

Authors: Arash Khosravi, Mohamad Nazir Ahmad

Abstract:

Today’s economy is a knowledge-based economy in which knowledge is a crucial facilitator to individuals, as well as being an instigator of success. Due to the impact of globalization, universities face new challenges and opportunities. Accordingly, they ought to be more innovative and have their own competitive advantages. One of the most important goals of universities is the promotion of students as professional knowledge workers. Therefore, knowledge sharing and transferring at tertiary level between students and supervisors is vital in universities, as it decreases the budget and provides an affordable way of doing research. Knowledge-sharing impact factors can be categorized into three groups, namely: organizational, individual and technical factors. There are some individual barriers to knowledge sharing, namely: lack of time and trust, lack of communication skills and social networks. IT systems such as e-learning, blogs and portals can increase knowledge sharing capability. However, it must be stated that IT systems are only tools and not solutions. Individuals are still responsible for sharing information and knowledge. This paper proposes new research model to examine the effect of individual factors and organisational factors, namely: learning strategy, trust culture, supervisory support, as well as technological factor on knowledge sharing in a research supervision process at the University of Technology Malaysia.

Keywords: knowledge management, knowledge sharing, research supervision, knowledge transferring

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6264 Formal History Teaching and Lifeworld Literacies: Developing Transversal Skills as an Embodied Learning Outcomes in Historical Research Projects

Authors: Paul Flynn, Luke O’Donnell

Abstract:

There is a pressing societal need for educators in formal and non-formal settings to develop pedagogical frameworks, programmes, and interventions that support the development of transversal skills for life beyond the classroom. These skills include communication, collaboration, interpersonal relationship building, problem-solving, and planning, and organizational skills; or lifeworld literacies encountered first hand. This is particularly true for young people aged between 15-18. This demographic represents both the future of society and those best positioned to take advantage of well-designed, structured educational supports within and across formal and non-formal settings. Secondary school history has been identified as an appropriate area of study which deftly develops many of those transversal skills so crucial to positive societal engagement. However, in the formal context, students often challenge history’s relevance to their own lived experience and dismiss it as a study option. In response to such challenges, teachers will often design stimulating lessons which are often well-received. That said, some students continue to question modern-day connections, presenting a persistent and pervasive classroom distraction. The continuing decline in numbers opting to study second-level history indicates an erosion of what should be a critical opportunity to develop all-important lifeworld literacies within formal education. In contrast, students readily acknowledge relevance in non-formal settings where many participants meaningfully engage with history by way of student-focused activities. Furthermore, many do so without predesigned pedagogical aids which support transversal skills development as embodied learning outcomes. As this paper will present, there is a dearth of work pertaining to the circular subject of history and its embodied learning outcomes, including lifeworld literacies, in formal and non-formal settings. While frequently challenging to reconcile formal (often defined by strict curricula and examination processes), and non-formal engagement with history, opportunities do exist. In the Irish context, this is exemplified by a popular university outreach programme: breaking the SEAL. This programme supports second-level history students as they fulfill curriculum requirements in completing a research study report. This report is a student-led research project pulling on communication skills, collaboration with peers and teachers, interpersonal relationships, problem-solving, and planning and organizational skills. Completion of this process has been widely recognized as excellent preparation not only for higher education (third level) but work-life demands as well. Within a formal education setting, the RSR harnesses non-formal learning virtues and exposes students to limited aspects of independent learning that relate to a professional work setting –a lifeworld literacy. Breaking the SEAL provides opportunities for students to enhance their lifeworld literacy by engaging in an independent research and learning process within the protective security of the classroom and its teacher. This paper will highlight the critical role this programme plays in preparing participating students (n=315) for life after compulsory education and presents examples of how lifeworld literacies may be developed through a scaffolded process of historical research and reporting anchored in non-formal contexts.

Keywords: history, education, literacy, transversal skills

Procedia PDF Downloads 149
6263 Playwriting in a German Language Class: How Creativity in a Language Lesson Supports Learning and the Acquisition of Political Agency

Authors: Ioannis Souris

Abstract:

In this paper, we would like to present how we taught German through playwriting and analyze the usefulness of this method for teaching languages and cultivating a sense of political agency in students and teachers alike. Last academic year, we worked at the German Saturday School in Greenwich, London. This school offers Saturday German lessons to children whose parents are German, living in London. The lessons are two hours long, and the children’s level of German varies according to how often or how much German is spoken at home or how often the families visit Germany (as well as other factors which will be discussed in more detail in the paper). The directors of the school provide teachers with learning material and course books, but they strongly encourage individual input on lesson structure and methods of teaching German. The class we taught consisted of six eight-to-nine-year-olds. Midway into the academic year, we ran out of teaching material, and we, therefore, decided to write a play. In the paper, we would like to explore the process we followed in creating or writing this play and how this encouraged the children to collaborate and exercise their skills in writing, storytelling, speaking, and opinion-sharing. We want to examine the impact this project had on the children who wrote and performed the play, the wider community of the Saturday school, and the development of our language teaching practice. We found, for instance, that some students, who were quiet or shy, became very open and outspoken in the process of writing and performing the play. They took the initiative and led the process, putting us, their teachers, in the role of simple observers or facilitators. When we showed the play in front of the school, the other children and teachers, as audience members, also became part of the process as they commented on the plot, language, and characters and gave feedback on further development. In the paper, we will discuss how this teaching project fits into recent developments in the research of creativity and the teaching of languages and how engagement with creative approaches to teaching has the potential to question and subvert traditional notions of ‘lesson’, ‘teacher’, and ‘student’. From the moment a questioning of norms takes place, we inadvertently raise questions about politics, agency, and resistance. We will conclude the paper with a definition of what we mean by ‘political agency’ within the context of our teaching project and education, in general, and why inspiring creativity and imagination within teaching can be considered a political act. Finally, our aim in this paper will be to propose the possibility of analyzing teaching languages through creativity and political agency theories.

Keywords: innovation in language teaching and learning, language acquisition and learning, language curriculum development, language education

Procedia PDF Downloads 68
6262 Deep Graph Embeddings for the Analysis of Short Heartbeat Interval Time Series

Authors: Tamas Madl

Abstract:

Sudden cardiac death (SCD) constitutes a large proportion of cardiovascular mortalities, provides little advance warning, and the risk is difficult to recognize based on ubiquitous, low cost medical equipment such as the standard, 12-lead, ten second ECG. Autonomic abnormalities have been shown to be strongly predictive of SCD risk; yet current methods are not trivially applicable to the brevity and low temporal and electrical resolution of standard ECGs. Here, we build horizontal visibility graph representations of very short inter-beat interval time series, and perform unsuper- vised representation learning in order to convert these variable size objects into fixed-length vectors preserving similarity rela- tions. We show that such representations facilitate classification into healthy vs. at-risk patients on two different datasets, the Mul- tiparameter Intelligent Monitoring in Intensive Care II and the PhysioNet Sudden Cardiac Death Holter Database. Our results suggest that graph representation learning of heartbeat interval time series facilitates robust classification even in sequences as short as ten seconds.

Keywords: sudden cardiac death, heart rate variability, ECG analysis, time series classification

Procedia PDF Downloads 221
6261 Application of Metric Dimension of Graph in Unraveling the Complexity of Hyperacusis

Authors: Hassan Ibrahim

Abstract:

The prevalence of hyperacusis, an auditory condition characterized by heightened sensitivity to sounds, continues to rise, posing challenges for effective diagnosis and intervention. It is believed that this work deepens will deepens the understanding of hyperacusis etiology by employing graph theory as a novel analytical framework. We constructed a comprehensive graph wherein nodes represent various factors associated with hyperacusis, including aging, head or neck trauma, infection/virus, depression, migraines, ear infection, anxiety, and other potential contributors. Relationships between factors are modeled as edges, allowing us to visualize and quantify the interactions within the etiological landscape of hyperacusis. it employ the concept of the metric dimension of a connected graph to identify key nodes (landmarks) that serve as critical influencers in the interconnected web of hyperacusis causes. This approach offers a unique perspective on the relative importance and centrality of different factors, shedding light on the complex interplay between physiological, psychological, and environmental determinants. Visualization techniques were also employed to enhance the interpretation and facilitate the identification of the central nodes. This research contributes to the growing body of knowledge surrounding hyperacusis by offering a network-centric perspective on its multifaceted causes. The outcomes hold the potential to inform clinical practices, guiding healthcare professionals in prioritizing interventions and personalized treatment plans based on the identified landmarks within the etiological network. Through the integration of graph theory into hyperacusis research, the complexity of this auditory condition was unraveled and pave the way for more effective approaches to its management.

Keywords: auditory condition, connected graph, hyperacusis, metric dimension

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6260 Exploiting Identity Grievances: Al-Shabaab Propaganda Targeting Individuals Abroad

Authors: Mustafa Mabruk

Abstract:

Groups such as Al-Shabaab have managed to radicalize many individuals abroad, including the first American citizen to ever be radicalized. Yet the pathways of radicalization for these foreign individuals are understudied. Moreover, current measures to prevent foreign radicalization are ineffective, with privacy, screening and profiling implications that render current counter-radicalization efforts counterproductive. Such measures exhibit strictness, political bias, and harshness. As confirmed by recent studies, such counter-radicalization issues exacerbate existing grievances and channel fresh recruits to Al-Shabaab. Addressing these challenges is paramount, requiring alternative strategies to effectively reduce radicalization without triggering further harm. The development of counter-narratives emerges as a potential measure with minimal risk of exacerbating grievances, yet the development of such counter-narratives necessitates a thorough understanding of the radicalization pathways of foreign individuals that are understudied. This study investigates the success of Al-Shabaab in recruiting individuals abroad by analyzing their propaganda in conjunction with analyzing identity-focused theories of radicalization, including Framing Theory and Social Identity Theory. Qualitative content analysis is used to analyze various propaganda material, including tweets, speeches, and webpages. The analysis reveals that issues of identity are of major significance in the radicalization patterns identified and that grievances of Muslims worldwide are used to exploit identity-related grievances. Based on these findings, the paper argues that such evidence enhances our understanding of potential deradicalization pathways and present counter-narratives based on Islamic scripture.

Keywords: counter-narratives, foreign radicalization, identity grievances, propaganda analysis

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6259 Intercultural Initiatives and Canadian Bilingualism

Authors: Muna Shafiq

Abstract:

Growth in international immigration is a reflection of increased migration patterns in Canada and in other parts of the world. Canada continues to promote itself as a bilingual country, yet the bilingual French and English population numbers do not reflect this platform. Each province’s integration policies focus only on second language learning of either English or French. Moreover, since English Canadians outnumber French Canadians, maintaining, much less increasing, English-French bilingualism appears unrealistic. One solution to increasing Canadian bilingualism requires creating intercultural communication initiatives between youth in Quebec and the rest of Canada. Specifically, the focus is on active, experiential learning, where intercultural competencies develop outside traditional classroom settings. The target groups are Generation Y Millennials and Generation Z Linksters, the next generations in the career and parenthood lines. Today, Canada’s education system, like many others, must continually renegotiate lines between programs it offers its immigrant and native communities. While some purists or right-wing nationalists would disagree, the survival of bilingualism in Canada has little to do with reducing immigration. Children and youth immigrants play a valuable role in increasing Canada’s French and English speaking communities. For instance, a focus on more immersion, over core French education programs for immigrant children and youth would not only increase bilingual rates; it would develop meaningful intercultural attachments between Canadians. Moreover, a vigilant increase of funding in French immersion programs is critical, as are new initiatives that focus on experiential language learning for students in French and English language programs. A favorable argument supports the premise that other than French-speaking students in Québec and elsewhere in Canada, second and third generation immigrant students are excellent ambassadors to promote bilingualism in Canada. Most already speak another language at home and understand the value of speaking more than one language in their adopted communities. Their dialogue and participation in experiential language exchange workshops are necessary. If the proposed exchanges take place inter-provincially, the momentum to increase collective regional voices increases. This regional collectivity can unite Canadians differently than nation-targeted initiatives. The results from an experiential youth exchange organized in 2017 between students at the crossroads of Generation Y and Generation Z in Vancouver and Quebec City respectively offer a promising starting point in assessing the strength of bringing together different regional voices to promote bilingualism. Code-switching between standard, international French Vancouver students, learn in the classroom versus more regional forms of Quebec French spoken locally created regional connectivity between students. The exchange was equally rewarding for both groups. Increasing their appreciation for each other’s regional differences allowed them to contribute actively to their social and emotional development. Within a sociolinguistic frame, this proposed model of experiential learning does not focus on hands-on work experience. However, the benefits of such exchanges are as valuable as work experience initiatives developed in experiential education. Students who actively code switch between French and English in real, not simulated contexts appreciate bilingualism more meaningfully and experience its value in concrete terms.

Keywords: experiential learning, intercultural communication, social and emotional learning, sociolinguistic code-switching

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6258 Effects of Artificial Intelligence and Machine Learning on Social Media for Health Organizations

Authors: Ricky Leung

Abstract:

Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

Procedia PDF Downloads 74
6257 Psychological Nano-Therapy: A New Method in Family Therapy

Authors: Siamak Samani, Nadereh Sohrabi

Abstract:

Psychological nano-therapy is a new method based on systems theory. According to the theory, systems with severe dysfunctions are resistant to changes. Psychological nano-therapy helps the therapists to break this ice. Two key concepts in psychological nano-therapy are nano-functions and nano-behaviors. The most important step in psychological nano-therapy in family therapy is selecting the most effective nano-function and nano-behavior. The aim of this study was to check the effectiveness of psychological nano-therapy for family therapy. One group pre-test-post-test design (quasi-experimental Design) was applied for research. The sample consisted of ten families with severe marital conflict. The important character of these families was resistance for participating in family therapy. In this study, sending respectful (nano-function) text massages (nano-behavior) with cell phone were applied as a treatment. Cohesion/respect sub scale from self-report family processes scale and family readiness for therapy scale were used to assess all family members in pre-test and post-test. In this study, one of family members was asked to send a respectful text massage to other family members every day for a week. The content of the text massages were selected and checked by therapist. To compare the scores of families in pre-test and post-test paired sample t-test was used. The results of the test showed significant differences in both cohesion/respect score and family readiness for therapy between per-test and post-test. The results revealed that these families have found a better atmosphere for participation in a complete family therapy program. Indeed, this study showed that psychological nano-therapy is an effective method to make family readiness for therapy.

Keywords: family therapy, family conflicts, nano-therapy, family readiness

Procedia PDF Downloads 647