Search results for: learning experience and engagement

Authors: Robert Birkholc

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One of the basic issues related to the creation of characters in media, such as literature and film, is the representation of the characters' thoughts, emotions, and perceptions. This paper is devoted to the social perspective (or the focalization) expressed in film narration. The aim of the paper is to show how social point of view of the hero –conditioned by his origin and the environment from which he comes– can be created by using non-verbal, purely audiovisual means of expression. The issue will be considered on the example of the little-known polish movie The Dancing Hawk (1977) by Grzegorz Królikiewicz, based on the novel by Julian Kawalec. The thesis of the paper is that the polish director uses a narrative figure, which is somewhat analogous to literary form of free indirect discourse. In literature, free indirect discourse is formally ‘spoken’ by the external narrator, but the narration is clearly filtered through the language and thoughts of the character. According to some scholars (such as Roy Pascal), the narrator in this form of speech does not cite the character's words, but uses his way of thinking and imitates his perspective – sometimes with a deep irony. Free indirect discourse is frequently used in Julian Kawalec’s novel. Through the linguistic stylization, the author tries to convey the socially determined perspective of a peasant who migrates to the big city after the Second World War. Grzegorz Królikiewicz expresses the same social experience by pure cinematic form in the adaptation of the book. Both Kawalec and Królikiewicz show the consequences of so-called ‘social advancement’ in Poland after 1945, when the communist party took over political power. On the example of the fate of the main character, Michał Toporny, the director presents the experience of peasants who left their villages and had to adapt to new, urban space. However, the paper is not focused on the historical topic itself, but on the audiovisual form of the movie. Although Królikiewicz doesn’t use frequently POV shots, the narration of The Dancing Hawk is filtered through the sensations of the main character, who feels uprooted and alienated in the new social space. The director captures the hero's feelings through very complex audiovisual procedures – high or low points of view (representing the ‘social position’), grotesque soundtrack, expressionist scenery, and associative editing. In this way, he manages to create the world from the perspective of a socially maladjusted and internally split subject. The Dancing Hawk is a successful attempt to adapt the subjective narration of the book to the ‘language’ of the cinema. Mieke Bal’s notion of focalization helps to describe ‘free indirect discourse’ as a transmedial figure of representing of the characters’ perceptions. However, the polysemiotic medium of the film also significantly transforms this figure of representation. The paper shows both the similarities and differences between literary and cinematic ‘free indirect discourse.’

Keywords: film and literature, free indirect discourse, social experience, subjective narration

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Authors: Anila Syed, Manzoor Ahmad

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The relationship between United States and India has transformed from estrangement to wider engagement since 2004. With the convergence of interests and shared values both the US and India came close towards each other and evolved strategic partnership through civil nuclear cooperation. This paper analyze the cost and benefit of strategic partnership with India for US, the impact of India’s emergence as regional power on South Asian balance of power and its impact on Pak-US relationship. It also focuses on security structure of the region and challenges for the US to maintain strategic partnership with two rival states (India and Pakistan). The work also gives some recommendations for balancing power in the region in order to ensure durable peace not only between India and Pakistan but also in south Asia.

Keywords: US-India strategic partnership, civil-nuclear cooperation, balance of power, impacts on Pak-US relationship

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Authors: Reham Niazi, Marwa Helmy, Susanne Rizzo

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This classroom action research is designed to explore the possibility of adding effective online content to supplement and add learning value to the current reading module. The aim of this research was two-fold, first to investigate students’ acceptance of and interactivity with online components, chosen to orient students with the content, and to pave the way for more in-class activities and skill practice. Secondly, the instructor aimed to examine students’ willingness to have the course contact hours remain the same with some online components to be done at home (flipped approach) or if students were open to turn the class into a blended format with two scenarios; either to have the current contact hours and apply the blended and in this case the face to face component will be less or keep the number of face to face classes the same and add more online structured classes as part of the course hours.

Keywords: blended learning, flipped classroom, graduate students, education

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Authors: Napasri Suwanajote

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The purposes of this research were to analyse and evaluate successful factors in OTOP production process for the developing of learning centre on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production 2) product development 3) the community strength 4) marketing possibility and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors 2) evaluate the strategy based on Sufficiency Economic Philosophy and 3) the model of learning centre on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning centre on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, marketing management

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Authors: Supria Sarkar, Vasit Sagan, Sourav Bhadra, Meghnath Pokharel, Felix B.Fritschi

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Soybean and their derivatives are very important agricultural commodities around the world because of their wide applicability in human food, animal feed, biofuel, and industries. However, the significance of soybean production depends on the quality of the soybean seeds rather than the yield alone. Seed composition is widely dependent on plant physiological properties, aerobic and anaerobic environmental conditions, nutrient content, and plant phenological characteristics, which can be captured by high temporal resolution remote sensing datasets. Planet scope (PS) satellite images have high potential in sequential information of crop growth due to their frequent revisit throughout the world. In this study, we estimate soybean seed composition while the plants are in the field by utilizing PlanetScope (PS) satellite images and different machine learning algorithms. Several experimental fields were established with varying genotypes and different seed compositions were measured from the samples as ground truth data. The PS images were processed to extract 462 hand-crafted vegetative and textural features. Four machine learning algorithms, i.e., partial least squares (PLSR), random forest (RFR), gradient boosting machine (GBM), support vector machine (SVM), and two recurrent neural network architectures, i.e., long short-term memory (LSTM) and gated recurrent unit (GRU) were used in this study to predict oil, protein, sucrose, ash, starch, and fiber of soybean seed samples. The GRU and LSTM architectures had two separate branches, one for vegetative features and the other for textures features, which were later concatenated together to predict seed composition. The results show that sucrose, ash, protein, and oil yielded comparable prediction results. Machine learning algorithms that best predicted the six seed composition traits differed. GRU worked well for oil (R-Squared: of 0.53) and protein (R-Squared: 0.36), whereas SVR and PLSR showed the best result for sucrose (R-Squared: 0.74) and ash (R-Squared: 0.60), respectively. Although, the RFR and GBM provided comparable performance, the models tended to extremely overfit. Among the features, vegetative features were found as the most important variables compared to texture features. It is suggested to utilize many vegetation indices for machine learning training and select the best ones by using feature selection methods. Overall, the study reveals the feasibility and efficiency of PS images and machine learning for plot-level seed composition estimation. However, special care should be given while designing the plot size in the experiments to avoid mixed pixel issues.

Keywords: agriculture, computer vision, data science, geospatial technology

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Authors: Lei Zhu, Nan Li

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Cold stamping has been widely applied in the automotive industry for the mass production of a great range of automotive panels. Predicting the springback to ensure the dimensional accuracy of the cold-stamped components is a critical step. The main approaches for the prediction and compensation of springback in cold stamping include running Finite Element (FE) simulations and conducting experiments, which require forming process expertise and can be time-consuming and expensive for the design of cold stamping tools. Machine learning technologies have been proven and successfully applied in learning complex system behaviours using presentative samples. These technologies exhibit the promising potential to be used as supporting design tools for metal forming technologies. This study, for the first time, presents a novel application of a Convolutional Neural Network (CNN) based surrogate model to predict the springback fields for variable U-shape cold bending geometries. A dataset is created based on the U-shape cold bending geometries and the corresponding FE simulations results. The dataset is then applied to train the CNN surrogate model. The result shows that the surrogate model can achieve near indistinguishable full-field predictions in real-time when compared with the FE simulation results. The application of CNN in efficient springback prediction can be adopted in industrial settings to aid both conceptual and final component designs for designers without having manufacturing knowledge.

Keywords: springback, cold stamping, convolutional neural networks, machine learning

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Authors: Aboagye Boye Gilbert

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Teaching and learning (Education), not only in Ghana but the whole world is regarded as the (Stepping stone) vehicle to accelerate the country’s economy, development and social growth. Basically the ingredients for human development and the country in general is Vocational and Technical education and this has been stressed in Ghana’s education system since Pre-independence. To this effect, this research seeks to determine using demonstration method of Teachings sewing to improve the skills of form 3 Fashion Designing students of Baworo Integrated Community Centre for Employable Skills. In this research, reviewed literature on opinions of other researchers and what other people have done and said on related articles or topics, analyzed the research design used, translate the data gathered in the study. The study was design to gather information from the school on how they use Teaching methods to teach sewing. The targeted respondent contacted to give assistance Consist of students from BICCES, fashion teachers and tailored garment makers. The sample size consisted of 5 teachers, 20 students and 5 tailors were selected to answer questionnaire items that were used to gather the data for the study. The study revealed that most teachers and students agreed to the fact that demonstration, teaching and learning materials had a positive attitude towards the students in learning sewing. The study recommends that there should be more mechanisms in place to serve as a guide.

Keywords: VOTEC, BECE, BICCES, SHS

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Authors: Abdulvahab Forati

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Religious intellectualism is the only stream of consciousness in Iran that its religious theories formed Democracy. The theory of Religious intellectualism was utilized in Constitutional Revolution and Islamic Revolution. To instate Democracy in Iran, in compare with West and sunnis, the theory of Religious Intellectualism is being used differently. Unlike Democracy in the west that has started with the concept of Individualism and Natural Rights or in Sunni world that has started with the concept of consultation, it has started in Iran with mima-la-nas-fih (what we don’t have any proof for)or mantaqa-alfiraq-altashri’ (area of vacuum from reason). Shia scholars first acquainted with the concept of Democracy through theories of Sheikh Mortiza Ansari, and later some of his followers, including Akhund-e-khorasani and Mirzaye naeini, regarding Sheikh Ansari’s thoughts, began to analyze its Constitutional system and Democratic elements. But Imam Khomeini, the great founder of Islamic Republic of Iran, with respect to RAKHS (religious permission for having a choice)could make connection between Islam and Democracy. Instead of focusing on Civil contracts, he relied on Sirah Ughala (Tradition) and accepted many of the current conducts, e.g. Democracy and Political Parties and acknowledged the authority (Hujiat) of them even in absence of Infallibles. These two are the most notable experiences of shia political thoughts about Democracy within the last 100 years. In this article, the author tries to explain the second experience in Imam Khomeini’s thoughts and Sirah.

Keywords: Shia school, Islamic revolution, democracy, political order

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Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Hammad Riaz, Abubakr Saeed

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Environmental Management System (EMS), i.e., ISO 14001 helps to build corporate reputation, legitimacy and can also be considered as firms’ strategic response to institutional pressure to reduce the impact of business activity on natural environment. The financial outcomes of certifying with ISO 14001 are still unclear and equivocal. Drawing on institutional and market learning theories, the impact of ISO 14001 on firms’ market performance is examined for Chinese firms. By employing rigorous event study approach, this paper compared ISO 14001 certified firms with non-certified counterpart firms based on different matching criteria that include size, return on assets and industry. The results indicate that the ISO 14001 has been negatively signed by the investors both in the short and long-run. This paper suggested implications for policy makers, managers, and other nonprofit organizations.

Keywords: ISO 14001, legitimacy, institutional forces, event study approach, emerging markets

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Authors: Chan Yan Nok

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The present study is a qualitative study based on the coping experiences of six Hong Kong Chinese mothers who had childhood trauma from their first-person perspective. Expanding the perspective beyond the dominant discourse of “inter-generation transmission of trauma”, this study explores the experiences and meanings of child trauma embedded in their narratives through the process of thematic analysis and narrative analysis. The interviewees painted a nuanced picture of their process of coping and trauma resolution. First, acknowledgement; second, feel safe and start to tell the story of trauma; third, feel the feelings and expression of emotions; fourth, clarifying and coping with the impacts of trauma; fifth, integration and transformation; and sixth, using their new understanding of experience to have a better life. It was seen that there was no “end” within the process of trauma resolution. Instead, this is an ongoing process with positive healing trajectory. Analysis of the stories of the mothers revealed recurrent themes around continuous self-reflective awareness in the process of trauma coping. Rather than being necessarily negative and detrimental, childhood trauma could highlight the meanings of being a mother and reveal opportunities for continuous personal growth and self-enhancement. Utilizing the sense of inadequacy as a core driver in the trauma recovery process while developing a heightened awareness of the unfinished business embedded in their “automatic pattern” of behaviors, emotions, and thoughts can help these mothers become more flexible to formulate new methods in facing future predicaments. Future social work and parent education practices should help mothers deal with unresolved trauma, make sense of their impacts of childhood trauma and discover the growth embedded in the past traumatic experience. They should be facilitated in “acknowledging the reality of the trauma”, including understanding their complicated emotions arising from the traumatic experiences and voicing their struggles. In addition, helping these mothers to be aware of short-term and long-term trauma impacts (i.e., secondary responses to the trauma) and explore their effective coping strategies in “overcoming secondary responses to the trauma” are crucial for their future positive adjustment and transformation. Through affirming their coping abilities and lessons learnt from past experiences, mothers can reduce feelings of shame and powerlessness and enhance their parental capacity.

Keywords: childhood trauma, coping, mothers, self-awareness, self-reflection, trauma resolution

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Authors: Yuguang Gao, Qiang Yang, Yanpeng Zhang, Mingtao Deng

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To enhance the safety, quality and efficiency of healthcare services provided by surgical doctors, we propose a comprehensive approach to the performance evaluation of individual doctors by incorporating insights from performance data as well as views of different stakeholders in the hospital. Exploratory factor analysis was first performed on collective multidimensional performance data of surgical doctors, where key factors were extracted that encompass assessment of professional experience and service performance. A two-level indicator system was then constructed, for which we developed a weighted interval-valued spherical fuzzy analytic hierarchy process to analyze the relative importance of the indicators while handling subjectivity and disparity in the decision-making of multiple parties involved. Our analytical results reveal that, for the key factors identified as instrumental for evaluating surgical doctors’ performance, the overall importance of clinical workload and complexity of service are valued more than capacity of service and professional experience, while the efficiency of resource consumption ranks comparatively the lowest in importance. We also provide a retrospective case study to illustrate the effectiveness and robustness of our quantitative evaluation model by assigning meaningful performance ratings to individual doctors based on the weights developed through our approach.

Keywords: analytic hierarchy processes, factor analysis, fuzzy logic, performance evaluation

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Authors: Redouane Larbi Boufeniza, Jing-Jia Luo

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This study assesses the suitability of deep learning (DL) for downscaling sea surface temperature (SST) over the Mediterranean Sea in the context of seasonal forecasting. We design a set of experiments that compare different DL configurations and deploy the best-performing architecture to downscale one-month lead forecasts of June–September (JJAS) SST from the Nanjing University of Information Science and Technology Climate Forecast System version 1.0 (NUIST-CFS1.0) for the period of 1982–2020. We have also introduced predictors over a larger area to include information about the main large-scale circulations that drive SST over the Mediterranean Sea region, which improves the downscaling results. Finally, we validate the raw model and downscaled forecasts in terms of both deterministic and probabilistic verification metrics, as well as their ability to reproduce the observed precipitation extreme and spell indicator indices. The results showed that the convolutional neural network (CNN)-based downscaling consistently improves the raw model forecasts, with lower bias and more accurate representations of the observed mean and extreme SST spatial patterns. Besides, the CNN-based downscaling yields a much more accurate forecast of extreme SST and spell indicators and reduces the significant relevant biases exhibited by the raw model predictions. Moreover, our results show that the CNN-based downscaling yields better skill scores than the raw model forecasts over most portions of the Mediterranean Sea. The results demonstrate the potential usefulness of CNN in downscaling seasonal SST predictions over the Mediterranean Sea, particularly in providing improved forecast products.

Keywords: Mediterranean Sea, sea surface temperature, seasonal forecasting, downscaling, deep learning

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Authors: Anne Tan, Kok-Sing Tang, Audrey Cooke

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Play has always been a prominent pedagogy in early childhood. However, there is growing evidence of success in students’ learning using explicit instruction, especially in literacy in the early years. There is also limited research using explicit instruction in early childhood mathematics, and play is usually prominently mentioned. This proposed research aims to investigate the possibilities and benefits of integrating guided play with explicit instruction in early childhood mathematics education. While play has traditionally been a prominent pedagogy in early childhood, there is growing evidence of success in student learning through explicit instruction, particularly in literacy. However, limited research exists on the integration of explicit instruction in early childhood mathematics, where play remains prominently mentioned. This study utilises a multiple case study methodology to gather data and provide immediate opportunities for curriculum improvement. The research will commence with semi-structured interviews to gain insights into educators' background knowledge. Highly structured observations will be conducted to record the frequency and manner in which guided play is integrated with specific elements of explicit instruction during mathematics teaching in early childhood. To enhance the observations, video recordings will be made using cameras with video settings and Microsoft Teams meeting recordings. In addition to interviews and observations, educators will maintain journals and use the Microsoft Teams platform for self-reflection on the integration of guided play and explicit instruction in their classroom practices and experiences. The study participants will include educators with early childhood degrees and students in years one and two. The primary goal of this research is to inform the benefits of integrating two high-impact pedagogies, guided play, and explicit instruction, for enhancing student learning outcomes in mathematics education. By exploring the integration of these pedagogical approaches, this study aims to contribute to the development of effective instructional strategies in early childhood mathematics education.

Keywords: early childhood, early childhood mathematics, early childhood numbers, guided play, play-based learning, explicit instruction

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Authors: Rachelly Ashwall, Ephraim Tabory

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In an attempt to reduce the level of a major identity-based conflict in Israel between Ultra-orthodox and secular Jews, several initiatives in recent years have tried to bring members of the two societies together in facilitated joint discussion forums. Our study analyzes the impact of two types of such programs: joint mediation training classes and confrontation-based learning programs that are designed to facilitate discussions over controversial issues. These issues include claims about an unequal shouldering of national obligations such as military service, laws requiring public observance of the Sabbath, and discrimination against women, among others. The study examines the factors that enabled the two groups to reduce their social distance, and increase their understanding of each other, and develop a recognition and tolerance of the other group's particular social identity. The research conducted over a course of two years involved observations of the activities of the groups, interviews with the participants, and analysis of the social media used by the groups. The findings demonstrate the progression from a mutual initial lack of knowledge about habits, norms, and attitudes of the out-group to an increasing desire to know, understand and more readily accept the identity of a previously rejected outsider. Participants manifested more respect, concern for and even affection for those whose identity initially led them to reject them out of hand. We discuss the implications for seemingly intractable identity-based conflict in fragile societies.

Keywords: identity-based conflict, intergroup relations, joint mediation learning, out-group recognition, social identity

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Authors: Aritra Majumdar

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While organizations strive to expand their new customer base, retaining existing relationships is a key aspect of improving overall profitability and also showcasing how successful an organization is in holding on to its customers. It is an experimentally proven fact that the lion’s share of profit always comes from existing customers. Hence seamless management of renewal journeys across different channels goes a long way in improving trust in the brand. From a quality assurance standpoint, time travel testing provides an approach to both business and technology teams to enhance the customer experience when they look to extend their partnership with the organization for a defined phase of time. This whitepaper will focus on key pillars of time travel testing: time travel planning, time travel data preparation, and enterprise automation. Along with that, it will call out some of the best practices and common accelerator implementation ideas which are generic across verticals like healthcare, insurance, etc. In this abstract document, a high-level snapshot of these pillars will be provided. Time Travel Planning: The first step of setting up a time travel testing roadmap is appropriate planning. Planning will include identifying the impacted systems that need to be time traveled backward or forward depending on the business requirement, aligning time travel with other releases, frequency of time travel testing, preparedness for handling renewal issues in production after time travel testing is done and most importantly planning for test automation testing during time travel testing. Time Travel Data Preparation: One of the most complex areas in time travel testing is test data coverage. Aligning test data to cover required customer segments and narrowing it down to multiple offer sequencing based on defined parameters are keys for successful time travel testing. Another aspect is the availability of sufficient data for similar combinations to support activities like defect retesting, regression testing, post-production testing (if required), etc. This section will talk about the necessary steps for suitable data coverage and sufficient data availability from a time travel testing perspective. Enterprise Automation: Time travel testing is never restricted to a single application. The workflow needs to be validated in the downstream applications to ensure consistency across the board. Along with that, the correctness of offers across different digital channels needs to be checked in order to ensure a smooth customer experience. This section will talk about the focus areas of enterprise automation and how automation testing can be leveraged to improve the overall quality without compromising on the project schedule. Along with the above-mentioned items, the white paper will elaborate on the best practices that need to be followed during time travel testing and some ideas pertaining to accelerator implementation. To sum it up, this paper will be written based on the real-time experience author had on time travel testing. While actual customer names and program-related details will not be disclosed, the paper will highlight the key learnings which will help other teams to implement time travel testing successfully.

Keywords: time travel planning, time travel data preparation, enterprise automation, best practices, accelerator implementation ideas

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Authors: J. S. Dhillon, K. K. Dhaliwal

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In almost all the digital filtering applications the digital infinite impulse response (IIR) filters are preferred over finite impulse response (FIR) filters because they provide much better performance, less computational cost and have smaller memory requirements for similar magnitude specifications. However, the digital IIR filters are generally multimodal with respect to the filter coefficients and therefore, reliable methods that can provide global optimal solutions are required. The artificial bee colony (ABC) algorithm is one such recently introduced meta-heuristic optimization algorithm. But in some cases it shows insufficiency while searching the solution space resulting in a weak exchange of information and hence is not able to return better solutions. To overcome this deficiency, the opposition based learning strategy is incorporated in ABC and hence a modified version called oppositional artificial bee colony (OABC) algorithm is proposed in this paper. Duplication of members is avoided during the run which also augments the exploration ability. The developed algorithm is then applied for the design of optimal and stable digital IIR filter structure where design of low-pass (LP) and high-pass (HP) filters is carried out. Fuzzy theory is applied to achieve maximize satisfaction of minimum magnitude error and stability constraints. To check the effectiveness of OABC, the results are compared with some well established filter design techniques and it is observed that in most cases OABC returns better or atleast comparable results.

Keywords: digital infinite impulse response filter, artificial bee colony optimization, opposition based learning, digital filter design, multi-parameter optimization

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Authors: L. Freeborn

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Recent years have seen an increasing number of neuroimaging studies related to language learning as imaging techniques such as fMRI and EEG have become more widely accessible to researchers. By using a variety of structural and functional neuroimaging techniques, these studies have already made considerable progress in terms of our understanding of neural networks and processing related to first and second language acquisition. However, the methodological designs employed in neuroimaging studies to test language learning have been questioned by applied linguists working within the field of second language acquisition (SLA). One of the major criticisms is that tasks designed to measure language learning gains rarely have a communicative function, and seldom assess learners’ ability to use the language in authentic situations. This brings the validity of many neuroimaging tasks into question. The fundamental reason why people learn a language is to communicate, and it is well-known that both first and second language proficiency are developed through meaningful social interaction. With this in mind, the SLA field is in agreement that second language acquisition and proficiency should be measured through learners’ ability to communicate in authentic real-life situations. Whilst authenticity is not always possible to achieve in a classroom environment, the importance of task authenticity should be reflected in the design of language assessments, teaching materials, and curricula. Tasks that bear little relation to how language is used in real-life situations can be considered to lack construct validity. This paper first describes the typical tasks used in neuroimaging studies to measure language gains and proficiency, then analyses to what extent these tasks can validly assess these constructs.

Keywords: neuroimaging studies, research design, second language acquisition, task validity

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Authors: Angela Yicely Castro Garces

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Aware of the relevance that intercultural education has gained in foreign language learning and teaching, and acknowledging the need to make it part of our classroom practices, this literature review explores studies that have been published in the Colombian context from the years 2012 to 2019. The inquiry was done in six national peer-reviewed journals, in order to examine the population benefited, types of studies and most recurrent topics of concern for educators. The findings present a promising panorama as teacher educators from public universities are leading the way in conducting research projects aimed at fostering intercultural awareness and building a critical intercultural discourse. Nonetheless, more studies that involve the different stakeholders and contexts need to be developed, in order to make intercultural education more visible in Colombian elementary and high school classrooms.

Keywords: Colombian scholarship, foreign language learning, foreign language teaching, intercultural awareness

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Authors: Sumeyra Karatas, Veysel Karatas, Reyhan Safak, Gamze Bulut-Ozturk, Ozgul Kartal

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Productive struggle entails a student's cognitive exertion to comprehend mathematical concepts and uncover solutions not immediately apparent. The significance of productive struggle in learning mathematics is accentuated by influential educational theorists, emphasizing its necessity for learning mathematics with understanding. Consequently, supporting productive struggle in learning mathematics is recognized as a high-leverage and effective mathematics teaching practice. In this study, the investigation into the role of productive struggle in learning mathematics led to the development of a comprehensive rubric for productive struggle pedagogy through an exhaustive literature review. The rubric consists of eight primary criteria and 37 sub-criteria, providing a detailed description of teacher actions and pedagogical choices that foster students' productive struggles. These criteria encompass various pedagogical aspects, including task design, tool implementation, allowing time for struggle, posing questions, scaffolding, handling mistakes, acknowledging efforts, and facilitating discussion/feedback. Utilizing this rubric, a team of researchers and teachers designed eight 90-minute lesson plans, employing a productive struggle pedagogy, for a two-week unit on solving systems of linear equations. Simultaneously, another set of eight lesson plans on the same topic, featuring identical content and problems but employing a traditional lecture-and-practice model, was designed by the same team. The objective was to assess the impact of supporting productive struggle on students' mathematics learning, defined by the strands of mathematical proficiency. This quasi-experimental study compares the control group, which received traditional lecture- and practice instruction, with the treatment group, which experienced a productive struggle in pedagogy. Sixty-six 10th and 11th-grade students from two algebra classes, taught by the same teacher at a high school, underwent either the productive struggle pedagogy or lecture-and-practice approach over two-week eight 90-minute class sessions. To measure students' learning, an assessment was created and validated by a team of researchers and teachers. It comprised seven open-response problems assessing the strands of mathematical proficiency: procedural and conceptual understanding, strategic competence, and adaptive reasoning on the topic. The test was administered at the beginning and end of the two weeks as pre-and post-test. Students' solutions underwent scoring using an established rubric, subjected to expert validation and an inter-rater reliability process involving multiple criteria for each problem based on their steps and procedures. An analysis of covariance (ANCOVA) was conducted to examine the differences between the control group, which received traditional pedagogy, and the treatment group, exposed to the productive struggle pedagogy, on the post-test scores while controlling for the pre-test. The results indicated a significant effect of treatment on post-test scores for procedural understanding (F(2, 63) = 10.47, p < .001), strategic competence (F(2, 63) = 9.92, p < .001), adaptive reasoning (F(2, 63) = 10.69, p < .001), and conceptual understanding (F(2, 63) = 10.06, p < .001), controlling for pre-test scores. This demonstrates the positive impact of supporting productive struggle in learning mathematics. In conclusion, the results revealed the significance of the role of productive struggle in learning mathematics. The study further explored the practical application of productive struggle through the development of a comprehensive rubric describing the pedagogy of supporting productive struggle.

Keywords: effective mathematics teaching practice, high school algebra, learning mathematics, productive struggle

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Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

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Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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Authors: Mamdouh Milad Adly Morkos

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Despite having the greatest rates of mortality and morbidity in the world, low- and middle-income (LMIC) nations trail high-income nations in terms of the number of clinical trials, the number of qualified researchers, and the amount of research information specific to their people. Health inequities and the use of precision medicine may be hampered by a lack of local genomic data, clinical pharmacology and pharmacometrics competence, and training opportunities. These issues can be solved by carrying out health care infrastructure development, which includes data gathering and well-designed clinical pharmacology training in LMICs. It will be advantageous if there is international cooperation focused at enhancing education and infrastructure and promoting locally motivated clinical trials and research. This paper outlines various instances where clinical pharmacology knowledge could be put to use, including pharmacogenomic opportunities that could lead to better clinical guideline recommendations. Examples of how clinical pharmacology training can be successfully implemented in LMICs are also provided, including clinical pharmacology and pharmacometrics training programmes in Africa and a Tanzanian researcher's personal experience while on a training sabbatical in the United States. These training initiatives will profit from advocacy for clinical pharmacologists' employment prospects and career development pathways, which are gradually becoming acknowledged and established in LMICs. The advancement of training and research infrastructure to increase clinical pharmacologists' knowledge in LMICs would be extremely beneficial because they have a significant role to play in global health

Keywords: electromagnetic solar system, nano-material, nano pharmacology, pharmacovigilance, quantum theoryclinical simulation, education, pharmacology, simulation, virtual learning low- and middle-income, clinical pharmacology, pharmacometrics, career development pathways

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Authors: Victoria Esteves

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Online memes have not only impacted different aspects of culture, but they have also left their mark on particular subcultures, where memes have reflected issues and debates surrounding specific spheres of interest. This is the first study that outlines how memes can address cultural intersections within the Lolita fashion community, which are much more specific and which fall outside of the broad focus of politics and/or social commentary. This is done by looking at the way online memes are used in this particular subculture as a form of meaning-making and group identity reinforcement, demonstrating not only the adaptability of online memes to specific cultural groups but also how subcultures tailor these digital objects to discuss both community-centered topics and more broad societal aspects. As part of an online ethnography, this study focuses on qualitative content analysis by taking a look at some of the meme communication that has permeated Lolita fashion communities. Examples of memes used in this context are picked apart in order to understand this specific layered phenomenon of communication, as well as to gain insights into how memes can operate as visual shorthand for the remix of meaning-making. There are existing parallels between internet culture and cultural behaviors surrounding Lolita fashion: not only is the latter strongly influenced by the former (due to its highly globalized dispersion and lack of physical shops, Lolita fashion is almost entirely reliant on the internet for its existence), both also emphasize curatorial roles through a careful collaborative process of documenting significant aspects of their culture (e.g., Know Your Meme and Lolibrary). Further similarities appear when looking at ideas of inclusion and exclusion that permeate both cultures, where memes and language are used in order to both solidify group identity and to police those who do not ascribe to these cultural tropes correctly, creating a feedback loop that reinforces subcultural ideals. Memes function as excellent forms of communication within the Lolita community because they reinforce its coded ideas and allows a kind of participation that echoes other cultural groups that are online-heavy such as fandoms. Furthermore, whilst the international Lolita community was mostly self-contained within its LiveJournal birthplace, it has become increasingly dispersed through an array of different social media groups that have fragmented this subculture significantly. The use of memes is key in maintaining a sense of connection throughout this now fragmentary experience of fashion. Memes are also used in the Lolita fashion community to bridge the gap between Lolita fashion related community issues and wider global topics; these reflect not only an ability to make use of a broader online language to address specific issues of the community (which in turn provide a very community-specific engagement with remix practices) but also memes’ ability to be tailored to accommodate overlapping cultural and political concerns and discussions between subcultures and broader societal groups. Ultimately, online memes provide the necessary elasticity to allow their adaption and adoption by subcultural groups, who in turn use memes to extend their meaning-making processes.

Keywords: internet culture, Lolita fashion, memes, online community, remix

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Authors: Jeff A. Tysinger, Dawn P. Tysinger

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There has been considerable growth in online learning. Researchers continue to explore the impact various methods of delivery. Podcasting is a popular method for sharing information. The purpose of this study was to examine the impact of student motivation and the perception of the acquisition of knowledge in an online environment of a skill-based class. 25 students in a school psychology graduate class completed a pretest and posttest examining podcast use and familiarity. In addition, at the completion of the course they were administered a modified version of the Instructional Materials Motivation Survey. The four subscales were examined (attention, relevance, confidence, and satisfaction). Results indicated that students are motivated, they perceive podcasts as positive instructional tools, and students are successful in acquiring the needed information. Additional benefits of using podcasts and recommendations in school psychology training are discussed.

Keywords: motivation, online learning, pedagogy, podcast

Procedia PDF Downloads 127

Authors: Davut Disci

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Objective: to measure the factors affecting expectations and intentions of using mobile phone in educational contexts by university students, using advanced equations and modeling techniques. Design and Methodology: According to the literature, Mobile Addiction, Parental Surveillance-Safety/Security, Social Relations, and Mobile Behavior are most used terms of defining mobile use of people. Therefore, these variables are tried to be measured to find and estimate their effects on expectations and intentions of using mobile phone in educational context. 421 university students participated in this study and there are 229 Female and 192 Male students. For the purpose of examining the mobile behavior and educational expectations and intentions, a questionnaire is prepared and applied to the participants who had to answer all the questions online. Furthermore, responses to close-ended questions are analyzed by using The Statistical Package for Social Sciences(SPSS) software, reliabilities are measured by Cronbach’s Alpha analysis and hypothesis are examined via using Multiple Regression and Linear Regression analysis and the model is tested with Structural Equation Modeling (SEM) technique which is important for testing the model scientifically. Besides these responses, open-ended questions are taken into consideration. Results: When analyzing data gathered from close-ended questions, it is found that Mobile Addiction, Parental Surveillance, Social Relations and Frequency of Using Mobile Phone Applications are affecting the mobile behavior of the participants in different levels, helping them to use mobile phone in educational context. Moreover, as for open-ended questions, participants stated that they use many mobile applications in their learning environment in terms of contacting with friends, watching educational videos, finding course material via internet. They also agree in that mobile phone brings greater flexibility to their lives. According to the SEM results the model is not evaluated and it can be said that it may be improved to show in SEM besides in multiple regression. Conclusion: This study shows that the specified model can be used by educationalist, school authorities to improve their learning environment.

Keywords: learning technology, instructional technology, mobile learning, technology

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Authors: Eunice Tan

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The purpose of this presentation is to look at an alternative to the approach and methodologies of working with special needs. The strength-based approach to education embodies a paradigm shift. It is a strategy to move away from a deficit-based methodology which inadvertently may lead to an extensive list of things that the child cannot do or is unable to do. Today, many parents of individuals with special needs are focused on the child’s deficits rather than on his or her strengths. Even when parents Recognise and identify their child’s strengths to be valuable and wish to develop their abilities, they face the challenge that there are insufficient programs committed to supporting the development and improvement of such abilities. What is a strength-based approach in education? A strength-based approach in education focuses on students' positive qualities and contributions to class instead of the skills and abilities they may not have. Many schools are focused on the child’s special educational needs rather than the whole child. Parents interviewed have said that they have to engage external tutors to help hone in on their child’s interests and strengths.

Keywords: differential learning needs, special needs, instructional style, talents

Procedia PDF Downloads 188

Authors: N. Liu, K.Miao

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This research investigates novel methods to enhance people’s experience in religious culture through technology and digitization. This stage focuses on promoting Taiwanese culture regarding traditional religion. There are three primary research areas in this research field, namely the cultural and creative industry, digitalization, and digital games and cultural cognition. The research is designed based on mixed methodologies, which consist of two experiments. In Experiment I, experts who have religious and cultural background are being interviewed for qualitative data. The suggestions and opinions obtained from this experiment provide a deeper understanding of Taiwanese religious culture. In Experience II, quantitative approach is being adopted. This includes a survey among the younger generation in Taiwan to give a broader look at peoples’ thought about experiencing religious cultures with digitalization. This research allows us to determine the people’s interest in the digitalization of culture. It will help us to combine technology, culture, creativity, industrial, and cultural promotion. Including the design of applications, serious games, and immersive technology. This study shows that technology and digitalization can be used to help people to understand a traditional culture better. The outcome of this research can help designers and developers related to the cultural creativity industries by providing results on people’s interest regarding culture across three vital aspects: 1. Their attitude regarding the education of culture. 2. Their attitude regarding the promotion of culture. 3. Their attitude regarding the information on culture. In addition, this research will help designers who wish to implement cultural elements into their works. It also has great benefits for associations, governments, or individuals who try an innovative way of cultural perversion.

Keywords: culture heritage, digital games, digitalization, traditional religious culture

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Authors: Basheer Ahmad Al-Alwan

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This study aimed to assess the extent of administrative creativity and identify its barriers from the perspective of employees working in youth centers in Jordan. The sample comprised 156 individuals employed in youth centers within the Hashemite Kingdom of Jordan. Data collection involved the utilization of two measures: the administrative creativity scale and the obstacles to administrative work scale. Correlation and stepwise multiple regression analyses were conducted. The findings revealed a high level of administrative creativity, as indicated by a mean score of 3.82 and a standard deviation of 0.51. Furthermore, statistically significant gender-based differences in administrative creativity were observed, favoring males, with a mean score of 3.32 for males compared to 2.91 for females. The results also demonstrated statistically significant differences in the level of administrative creativity based on experience, with the highest mean score observed for individuals with 5 to less than 10 years of experience. Regarding the obstacles to administrative creativity, the findings revealed an average level, with a mean score of 2.86 and a standard deviation of 0.791. Based on these results, the study recommends the promotion of a culture of creativity among employees and the provision of a broader scope of authority to foster an environment conducive to administrative creativity. Additionally, it suggests offering training courses encompassing the annual plan for these centers and minimizing obstacles that hinder the creative process among employees in Jordanian youth centers.

Keywords: administrative creativity, obstacles, workers in youth centers, Jordan

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Authors: Ulas Vural, M. Ergun Okay, E. Mesut Yildiz

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Telecommunication service providers demand accurate and precise prediction of customer churn probabilities to increase the effectiveness of their customer relation services. The large amount of customer data owned by the service providers is suitable for analysis by machine learning methods. In this study, expenditure data of customers are analyzed by using an artificial neural network (ANN). The ANN model is applied to the data of customers with different billing duration. The proposed model successfully predicts the churn probabilities at 83% accuracy for only three months expenditure data and the prediction accuracy increases up to 89% when the nine month data is used. The experiments also show that the accuracy of ANN model increases on an extended feature set with information of the changes on the bill amounts.

Keywords: customer relationship management, churn prediction, telecom industry, deep learning, artificial neural networks

Procedia PDF Downloads 139

Authors: Bekkem Chakradhar Reddy, Y. Soni Priya, Mathivanan G., L. K. Joshila Grace, N. Srinivasan, Asha P.

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Currently, there are a lot of problems related to marking attendance in schools, offices, or other places. Organizations tasked with collecting daily attendance data have numerous concerns. There are different ways to mark attendance. The most commonly used method is collecting data manually by calling each student. It is a longer process and problematic. Now, there are a lot of new technologies that help to mark attendance automatically. It reduces work and records the data. We have proposed to implement attendance marking using the latest technologies. We have implemented a system based on face identification and analyzing faces. The project is developed by gathering faces and analyzing data, using deep learning algorithms to recognize faces effectively. The data is recorded and forwarded to the host through mail. The project was implemented in Python and Python libraries used are CV2, Face Recognition, and Smtplib.

Keywords: python, deep learning, face recognition, CV2, smtplib, Dlib.

Procedia PDF Downloads 47