Search results for: language learning strategies

Authors: L. Bih Ni, D. Norizah Ag Kiflee, T. Choon Keong, R. Talip, S. Singh Bikar Singh, M. Noor Mad Japuni, R. Talin

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The purpose of this study is to determine the effectiveness of video clips to enhance students' achievement and motivation towards learning and facilitating of history. We use narrative literature studies to illustrate the current state of the two art and science in focused areas of inquiry. We used experimental method. The experimental method is a systematic scientific research method in which the researchers manipulate one or more variables to control and measure any changes in other variables. For this purpose, two experimental groups have been designed: one experimental and one groups consisting of 30 lower secondary students. The session is given to the first batch using a computer presentation program that uses video clips to be considered as experimental group, while the second group is assigned as the same class using traditional methods using dialogue and discussion techniques that are considered a control group. Both groups are subject to pre and post-trial in matters that are handled by the class. The findings show that the results of the pre-test analysis did not show statistically significant differences, which in turn proved the equality of the two groups. Meanwhile, post-test analysis results show that there was a statistically significant difference between the experimental group and the control group at an importance level of 0.05 for the benefit of the experimental group.

Keywords: Video clips, Learning and Facilitation, Achievement, Motivation

Procedia PDF Downloads 157

Authors: Mukadder Baran, Mustafa Sözbilir

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The purpose of this paper is to investigate the applicabillity of the Context- and Problem-Based Learning (CPBL) in general chemistry course to the subject of “Thermodynamics” but also the influence of CPBL on students’ achievement, retention of knowledge, their interest, attitudes, motivation and problem-solving skills. The study group included 13 freshman students who were selected with the sampling method appropriate to the purpose among those taking the course of General Chemistry within the Program of Medical Laboratory Techniques at Hakkari University. The application was carried out in the Spring Term of the academic year of 2012-2013. As the data collection tool, Lesson Observation form were used. In the light of the observations held, it was revealed that CPBL increased the students’ intragroup and intergroup communication skills as well as their self-confidence and developed their skills in time management, presentation, reporting, and technology use; and that they were able to relate chemistry to daily life. Depending on these findings, it could be suggested that the area of use of CPBL be widened; that seminars related to constructive methods be organized for teachers. In this way, it is believed that students will not be passive in the group any longer. In addition, it was concluded that in order to avoid the negative effects of the socio-cultural structure on the education system, research should be conducted in places where there is socio-cultural obstacles, and appropriate solutions should be suggested and put into practice.

Keywords: chemistry, education, science, context-based learning

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Authors: Meng-Li Lin, Shang-Hsuan Chiu

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Taiwan is a country of diverse ethnic groups, the historical background of each ethnic group is different, and the conflict between them influence on each other, result in Taiwan's multi-culture. The Changhua County in Taiwan is the largest county of Hoklo-Hakka. Hakka people get along with Hoklo people for a long time. There are integration and conflict during that time and makes Hakka people gradually assimilated Hoklo-Hakka people. Today in Changhua Plain area, many Hoklo-Hakka people do not speak Hakka language. Therefore, it has been difficult to find information of Hakka from the Hakka language in the group of Hoklo-Hakka. But in the living space or culture to find relevant historical traces of life could be confirmed in Hakka Culture. In this paper, through the investigation of descent, life field, religion, language and other investigations of the Dacun, Changhua County residents to carry out the analysis of the process of assimilating Hoklo in living cultural landscape. First is through the local literature, the elderly and other oral history stories, to investigate the changes in Dacun field historical. Second, the comparison of collected traditional Hakka culture and the living cultural landscape of Hoklo-Haka are done to explore the differences between the living cultural landscape and the traditional Hakka culture. After analysis Hoklo-Hakka living cultural landscape, the significant differences, we proposed preservation strategy to provide recommendations to save the cultural life of Hoklo-Hakka landscape in future. Changhua Dacun traditional Hakka landscape is disappearing, in this study, we explore and investigate the data of Changhua Dacun Hoklo-Hakka living cultural landscape to analyze and to provide strategic advice to save. Here we have three study purposes. 1. Discuss the Hoklo-Hakka living cultural landscape of Changhua Dacun. 2. Investigate and record the Hoklo-Hakka living cultural landscape. 3. Propose a reserve strategy of the Hoklo-Hakka living cultural landscape in future.

Keywords: Hoklo-Hakka, Dacun, save policy, life Culture

Procedia PDF Downloads 346

Authors: Rosana Marar, Edward Jaser

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This paper presents a software solution to enhance the content and presentation of graphic design and animation related textbooks. Using augmented and virtual reality concepts, a mobile application is developed to improve the static material found in books. This allows users to interact with animated examples and tutorials using their mobile phones and stereoscopic 3D viewers which will enhance information delivery. The application is tested on Google Cardboard with visual content in 3D space. Evaluation of the proposed application demonstrates that it improved the readability of static content and provided new experiences to the reader.

Keywords: animation, augmented reality, google cardboard, interactive media, technology enhanced learning, virtual reality

Procedia PDF Downloads 187

Authors: Silvia Franco, Marcos Sarasola

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The Faculty of Business Administration at the Catholic University of Uruguay is performing an important educational innovation, unique in the country. In preparing future professionals in companies, teamwork competence is very important. However, there is no often a systematic and specific training in the acquisition of this competence in undergraduate students. For this reason, we have designed and implemented an educational innovation through an intervention method to improve teamwork competence for undergraduate students of business studies. Students’ teams are integrated according to the complementary roles of Belbin; changes in teamwork competence during training period are measured with CCSAC tool; classroom methodology in the prio-border teamwork by Team-Based Learning. Methodology also integrates coaching and support team performance during the first two semesters.

Keywords: business students, teamwork, learning, competences

Procedia PDF Downloads 369

Authors: E. O. George, P. Ojeaga, D. Odejimi, O. Mattehws

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Has macroeconomic management succeeded in making privatization promote growth in Africa? What are the probable strategies that should accompany the privatization reform process to promote growth in Africa? To what extent has the privatization process succeeded in attracting foreign direct investment to Africa? The study investigates the relationship between macroeconomic management and privatization. Many African countries have embarked on one form of privatization reform or the other since 1980 as one of the stringent conditions for accessing capital from the IMF and the World Bank. Secondly globalization and the gradually integration of the African economy into the global economy also means that Africa has to strategically develop its domestic market to cushion itself from fluctuations and probable contagion associated with global economic crisis that are always inevitable Stiglitz. The methods of estimation used are the OLS, linear mixed effects (LME), 2SLS and the GMM method of estimation. It was found that macroeconomic management has the capacity to affect the success of the privatization reform process. It was also found that privatization was not promoting growth in Africa; privatization could promote growth if long run growth strategies are implemented together with the privatization reform process. Privatization was also found not to have the capacity to attract foreign investment to many African countries.

Keywords: Africa, political economy, game theory, macroeconomic management and privatization

Procedia PDF Downloads 335

Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

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Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

Procedia PDF Downloads 447

Authors: Andres F. Ramirez, Carlos F. Valencia

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The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

Procedia PDF Downloads 327

Authors: Yu H. Chen, Li C. Chen, Hsiang Y. Wu, Wan Y. Chen, Yin S. Lai, Sarah S. Chen

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Little has been done to customize an appropriate program on gratitude for nurses, who work in high-stress environments. The purpose of this study is to design an appropriate program on gratitude for nurses and to investigate the effects of the program. Based on research done by Kaohsiung Medical University’s Positive Psychology Center, the only one of its kind in Taiwan, one of the top five strengths of nurses is gratitude. Instead of adapting from an older model created from past research, the Gratitude Workshop is developed from a quasi-experimental approach and designed with five additional dimensions that emphasize gratitude: thanking others, thanking one's surroundings, cherishing what one has, appreciating hardships, and appreciating the present. A sample of 84 nurses was randomly selected from the Kaohsiung Municipal Ta-Tung Hospital; 43 of who participated in the nine-hour Gratitude Workshop that spanned over three weeks, while the other 41 were part of the waitlist control group. The pretest and posttest included five questionnaires: Inventory of Undergraduates' Gratitude, The Gratitude Questionnaire-6, Mental Health Continuum‐Short Form, Perceived Stress Scale, and the Stress Coping Strategies Questionnaire. Results of the research showed that the Gratitude Workshop elevates gratitude, well-being, and perceived stress on the nurses; however, it was also found in the Stress Coping Strategies Questionnaire that the Gratitude Workshop only heightened the regulation of emotions.

Keywords: gratitude, nurses, positive psychology, well-being

Procedia PDF Downloads 390

Authors: Motonobu Hattori

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In neural networks, when new patters are learned by a network, they radically interfere with previously stored patterns. This drawback is called catastrophic forgetting. We have already proposed a biologically inspired dual-network memory model which can much reduce this forgetting for static patterns. In this model, information is first stored in the hippocampal network, and thereafter, it is transferred to the neocortical network using pseudo patterns. Because, temporal sequence learning is more important than static pattern learning in the real world, in this study, we improve our conventional dual-network memory model so that it can deal with temporal sequences without catastrophic forgetting. The computer simulation results show the effectiveness of the proposed dual-network memory model.

Keywords: catastrophic forgetting, dual-network, temporal sequences, hippocampal

Procedia PDF Downloads 276

Authors: Afrin Jaman Bonny, Mehrin Jahan, Zannatul Ferdhoush, Mumenunnessa Keya, Md. Shihab Mahmud, Sharun Akter Khushbu, Sheak Rashed Haider Noori, Sheikh Abujar

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In 2020, the SARS-CoV-2 pandemic had led all the educational institutions to move to online learning platforms to ensure safety as well as the continuation of learning without any disruption to students’ academic life. But after the reopening of those educational institutions suddenly in Bangladesh, it became a vital demand to observe students take on this decision and how much they are comfortable with the new habits. When all educational institutions were ordered to re-open after more than a year, data was collected from students of all educational levels. A Google Form was used to conduct this online survey, and a total of 565 students participated without being pressured. The survey reveals the students' preferences for online and offline education systems, as well as their mental health at the time including their behavior to get back to offline classes depending on getting vaccinated or not. After evaluating the findings, it is clear that respondents' choices vary depending on gender and educational level, with female and male participants experiencing various mental health difficulties and attitudes toward returning to offline classes. As a result of this study, the student’s overall perspective on the sudden reopening of their educational institutions has been analyzed.

Keywords: covid-19 epidemic, educational proceeding, university students, school/college students, physical activity, online platforms, mental health, psychological distress

Procedia PDF Downloads 217

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

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‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

Procedia PDF Downloads 308

Authors: John Lorenzo Bautista, Yoon-Joong Kim

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In this paper, a set of Filipino Phonetically Balanced Word list consisting of 250 words (PBW250) were constructed for a phoneme-level ASR system for the Filipino language. The Entropy Maximization is used to obtain phonological balance in the list. Entropy of phonemes in a word is maximized, providing an optimal balance in each word’s phonological distribution using the Add-Delete Method (PBW algorithm) and is compared to the modified PBW algorithm implemented in a dynamic algorithm approach to obtain optimization. The gained entropy score of 4.2791 and 4.2902 for the PBW and modified algorithm respectively. The PBW250 was recorded by 40 respondents, each with 2 sets data. Recordings from 30 respondents were trained to produce an acoustic model that were tested using recordings from 10 respondents using the HMM Toolkit (HTK). The results of test gave the maximum accuracy rate of 97.77% for a speaker dependent test and 89.36% for a speaker independent test.

Keywords: entropy maximization, Filipino language, Hidden Markov Model, phonetically balanced words, speech recognition

Procedia PDF Downloads 459

Authors: Tuyuan Cheng

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As we age, many things become more difficult. Among the abilities are the linguistic and cognitive ones. Competing theories have shown that these two functions could diminish together or that one is selectively affected by the other. In other words, some proposes aging affects sentence production in the same way it affects sentence comprehension and other cognitive functions, while some argues it does not.To address this question, the current investigation is conducted into the critical aspect of sentences as well as cognitive abilities – the syntactic complexity and the number of perspective shifts being contained in the elicited production. Healthy non-pathological aging is often characterized by a cognitive and neural decline in a number of cognitive abilities. Although the language is assumed to be of the more stable domain, a variety of findings in the cognitive aging literature would suggest otherwise. Older adults often show deficits in language production and multiple aspects of comprehension. Nevertheless, while some age differences likely reflect cognitive decline, others might reflect changes in communicative goals, and some even display cognitive advantages. In the domain of language processing, research efforts have been made in tests that probed a variety of communicative abilities. In general, there exists a distinction: Comprehension seems to be selectively unaffected, while production does not. The current study raises a novel question and investigates whether aging affects the production of relative clauses (RCs) under the cognitive factor of perspective shifts. Based on Perspective Hypothesis (MacWhinney, 2000, 2005), our cognitive processes build upon a fundamental system of perspective-taking, and language provides a series of cues to facilitate the construction and shifting of perspectives. These cues include a wide variety of constructions, including RCs structures. In this regard, linguistic complexity can be determined by the number of perspective shifts, and the processing difficulties of RCs can be interpreted within the theory of perspective shifting. Two experiments were conducted to study language production under controlled conditions. In Experiment 1, older healthy participants were tested on standard measures of cognitive aging, including MMSE (Mini-Mental State Examination), ToMI-2 (a simplified Theory of Mind Inventory-2), and a perspective-shifting comprehension task programmed with E-Prime. The results were analyzed to examine if/how they are correlated with aging people’s subsequent production data. In Experiment 2, the production profile of differing RCs, SRC vs. ORC, were collected with healthy aging participants who perform a picture elicitation task. Variable containing 0, 1, or 2 perspective shifts were juxtaposed respectively to the pictures and counterbalanced presented for elicitation. In parallel, a controlled group of young adults were recruited to examine the linguistic and cognitive abilities in question. The results lead us to the discussion whetheraging affects RCs production in a manner determined by its semantic structure or the number of perspective shifts it contains or the status of participants’ mental understanding. The major findingsare: (1) Elders’ production on Chinese RCtypes did not display intrinsic difficulty asymmetry. (2) RC types (the linguistic structural features) and the cognitiveperspective shifts jointly play important roles in the elders’ RCproduction. (3) The production of RC may defy the aging in the case offlexibly preserved cognitive ability.

Keywords: cognition aging, perspective hypothesis, perspective shift, relative clauses, sentence complexity

Procedia PDF Downloads 126

Authors: Alexandru-Ion Marinescu

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There exist a plethora of methods in the scientific literature which tackle the well-established task of credit score evaluation. In its most abstract form, a credit scoring algorithm takes as input several credit applicant properties, such as age, marital status, employment status, loan duration, etc. and must output a binary response variable (i.e. “GOOD” or “BAD”) stating whether the client is susceptible to payment return delays. Data imbalance is a common occurrence among financial institution databases, with the majority being classified as “GOOD” clients (clients that respect the loan return calendar) alongside a small percentage of “BAD” clients. But it is the “BAD” clients we are interested in since accurately predicting their behavior is crucial in preventing unwanted loss for loan providers. We add to this whole context the constraint that the algorithm must yield an actual, tractable mathematical formula, which is friendlier towards financial analysts. To this end, we have turned to genetic algorithms and genetic programming, aiming to evolve actual mathematical expressions using specially tailored mutation and crossover operators. As far as data representation is concerned, we employ a very flexible mechanism – LINQ expression trees, readily available in the C# programming language, enabling us to construct executable pieces of code at runtime. As the title implies, they model trees, with intermediate nodes being operators (addition, subtraction, multiplication, division) or mathematical functions (sin, cos, abs, round, etc.) and leaf nodes storing either constants or variables. There is a one-to-one correspondence between the client properties and the formula variables. The mutation and crossover operators work on a flattened version of the tree, obtained via a pre-order traversal. A consequence of our chosen technique is that we can identify and discard client properties which do not take part in the final score evaluation, effectively acting as a dimensionality reduction scheme. We compare ourselves with state of the art approaches, such as support vector machines, Bayesian networks, and extreme learning machines, to name a few. The data sets we benchmark against amount to a total of 8, of which we mention the well-known Australian credit and German credit data sets, and the performance indicators are the following: percentage correctly classified, area under curve, partial Gini index, H-measure, Brier score and Kolmogorov-Smirnov statistic, respectively. Finally, we obtain encouraging results, which, although placing us in the lower half of the hierarchy, drive us to further refine the algorithm.

Keywords: expression trees, financial credit scoring, genetic algorithm, genetic programming, symbolic evolution

Procedia PDF Downloads 122

Authors: Annette G. Walters Ph.D.

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With a global shortage of qualified educational professionals, school systems continue to struggle with adequate staffing. How might learning communities meet the needs of all students, in particular those with specialized needs. While the task may seem foreboding and certain factors may seem divergent, all are connected in the education of students. Special education has a significant impact on the teaching and learning experience of all students in an educational community. Even when there are concerted efforts at embracing learners with diverse aptitude and abilities, there are often many important local factors that are misaligned, overlooked, or misunderstood. Working with learners with diverse abilities, often requires intentional services and supports for students to achieve success. Developing and implementing specialized instruction requires a multifaceted approach to supports the entire learning community, which includes educational providers, learners, and families, all while being mindful of fiscal and natural resources. This research explores the implications and complexities of special education instruction and specializing instruction, as well as leading and teaching diverse learners. This work is separated into three sections: the state of special education, teaching and leading diverse learners, and developing educational competencies through collaborative engagement. This structured analysis extrapolates historical and current research on special education practices and the role of educators in ensuring diverse students meet success.

Keywords: - diverse learners, - special education, - modification and supports, - curriculum and instruction, - classroom management, - formal and informal assessments

Procedia PDF Downloads 58

Authors: Bambang Piscesa, Mario M. Attard, Dwi Presetya, Ali K. Samani

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A numerical strategy formulated using a plasticity approach is presented to model spalling of the concrete cover in reinforced concrete columns. The stage at which the concrete cover within reinforced concrete column spalls has a direct bearing on the load capacity. The concrete cover can prematurely spall before the full cross-section can be utilized if the concrete is very brittle under compression such as for very high strength concretes. If the confinement to the core is high enough, the column can achieve a higher peak load by utilizing the core. A numerical strategy is presented to model spalling of the concrete cover. Various numerical strategies are employed to model the behavior of reinforced concrete columns which include: (1) adjusting the material properties to incorporate restrained shrinkage; (2) modifying the plastic dilation rate in the presence of the tensile pressure; (3) adding a tension cut-off failure surface and (4) giving the concrete cover region and the column core different material properties. Numerical comparisons against experimental results are carried out that shown excellent agreement with the experimental results and justify the use of the proposed strategies to predict the axial load capacity of reinforce concrete columns.

Keywords: spalling, concrete, plastic dilation, reinforced concrete columns

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Authors: Amrane Meriem, Oukid Salyha

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The presence of defects or bugs in software can lead to costly setbacks, operational inefficiencies, and compromised user experiences. The integration of Machine Learning(ML) techniques has emerged to predict and preemptively address software defects. ML represents a proactive strategy aimed at identifying potential anomalies, errors, or vulnerabilities within code before they manifest as operational issues. By analyzing historical data, such as code changes, feature im- plementations, and defect occurrences. This en- ables development teams to anticipate and mitigate these issues, thus enhancing software quality, reducing maintenance costs, and ensuring smoother user interactions. In this work, we used a recommendation system to improve the performance of ML models in terms of predicting the code severity and effort estimation.

Keywords: software engineering, machine learning, bugs detection, effort estimation

Procedia PDF Downloads 91

Authors: Emmanuel Okechukwu Nwafor, Folake Olubunmi Akintayo, Denis Alcides Rezende

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Decision tree models are versatile and interpretable machine learning algorithms widely used for both classification and regression tasks, which can be related to cities, whether physical or digital. The aim of this research is to assess how well decision tree algorithms can predict trip purposes in Makurdi, Nigeria, while also exploring their connection to the strategic digital city initiative. The research methodology involves formalizing household demographic and trips information datasets obtained from extensive survey process. Modelling and Prediction were achieved using Python Programming Language and the evaluation metrics like R-squared and mean absolute error were used to assess the decision tree algorithm's performance. The results indicate that the model performed well, with accuracies of 84% and 68%, and low MAE values of 0.188 and 0.314, on training and validation data, respectively. This suggests the model can be relied upon for future prediction. The conclusion reiterates that This model will assist decision-makers, including urban planners, transportation engineers, government officials, and commuters, in making informed decisions on transportation planning and management within the framework of a strategic digital city. Its application will enhance the efficiency, sustainability, and overall quality of transportation services in Makurdi, Nigeria.

Keywords: decision tree algorithm, trip purpose, intelligent transport, strategic digital city, travel pattern, sustainable transport

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Authors: Mekdes Getu Chekol, Biniam Tedros Kahsay, Rahwa Berihu Haile

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The main objective of this study is to investigate the marketing strategy practice in the Case of St. George Brewery Factory in Addis Ababa. One of the core activities in a Business Company to stay in business is having a well-developed marketing strategy. It assessed how the marketing strategies were practiced in the company to achieve its goals aligned with segmentation, target market, positioning, and the marketing mix elements to satisfy customer requirements. Using primary and secondary data, the study is conducted by using both qualitative and quantitative approaches. The primary data was collected through open and closed-ended questionnaires. Considering the size of the population is small, the selection of the respondents was carried out by using a census. The finding shows that the company used all the 4 Ps of the marketing mix elements in its marketing strategies and provided quality products at affordable prices by promoting its products by using high and effective advertising mechanisms. The product availability and accessibility are admirable with the practices of both direct and indirect distribution channels. On the other hand, the company has identified its target customers, and the company’s market segmentation practice is geographical location. Communication effectiveness between the marketing department and other departments is very good. The adjusted R2 model explains 61.6% of the marketing strategy practice variance by product, price, promotion, and place. The remaining 38.4% of variation in the dependent variable was explained by other factors not included in this study. The result reveals that all four independent variables, product, price, promotion, and place, have a positive beta sign, proving that predictor variables have a positive effect on that of the predicting dependent variable marketing strategy practice. Even though the marketing strategies of the company are effectively practiced, there are some problems that the company faces while implementing them. These are infrastructure problems, economic problems, intensive competition in the market, shortage of raw materials, seasonality of consumption, socio-cultural problems, and the time and cost of awareness creation for the customers. Finally, the authors suggest that the company better develop a long-range view and try to implement a more structured approach to attain information about potential customers, competitor’s actions, and market intelligence within the industry. In addition, we recommend conducting the study by increasing the sample size and including different marketing factors.

Keywords: marketing strategy, market segmentation, target marketing, market positioning, marketing mix

Procedia PDF Downloads 68

Authors: Mohammad Arabi

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The development of advanced technologies in the field of signal processing and vibration analysis has enabled more accurate analysis and fault detection in electrical systems. This research investigates the application of temporal and frequency features in detecting faults in electric motor bearings, aiming to enhance fault detection accuracy and prevent unexpected failures. The use of methods such as deep learning algorithms and neural networks in this process can yield better results. The main objective of this research is to evaluate the efficiency and accuracy of methods based on temporal and frequency features in identifying faults in electric motor bearings to prevent sudden breakdowns and operational issues. Additionally, the feasibility of using techniques such as machine learning and optimization algorithms to improve the fault detection process is also considered. This research employed an experimental method and random sampling. Vibration signals were collected from electric motors under normal and faulty conditions. After standardizing the data, temporal and frequency features were extracted. These features were then analyzed using statistical methods such as analysis of variance (ANOVA) and t-tests, as well as machine learning algorithms like artificial neural networks and support vector machines (SVM). The results showed that using temporal and frequency features significantly improves the accuracy of fault detection in electric motor bearings. ANOVA indicated significant differences between normal and faulty signals. Additionally, t-tests confirmed statistically significant differences between the features extracted from normal and faulty signals. Machine learning algorithms such as neural networks and SVM also significantly increased detection accuracy, demonstrating high effectiveness in timely and accurate fault detection. This study demonstrates that using temporal and frequency features combined with machine learning algorithms can serve as an effective tool for detecting faults in electric motor bearings. This approach not only enhances fault detection accuracy but also simplifies and streamlines the detection process. However, challenges such as data standardization and the cost of implementing advanced monitoring systems must also be considered. Utilizing temporal and frequency features in fault detection of electric motor bearings, along with advanced machine learning methods, offers an effective solution for preventing failures and ensuring the operational health of electric motors. Given the promising results of this research, it is recommended that this technology be more widely adopted in industrial maintenance processes.

Keywords: electric motor, fault detection, frequency features, temporal features

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Authors: Malik Muhammad Arslan, Muneeb Ullah, Dai Shihan, Daniyal Haider, Xiaodong Yang

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Chest X-rays are instrumental in the detection and monitoring of a wide array of diseases, including viral infections such as COVID-19, tuberculosis, pneumonia, lung cancer, and various cardiac and pulmonary conditions. To enhance the accuracy of diagnosis, artificial intelligence (AI) algorithms, particularly deep learning models like Convolutional Neural Networks (CNNs), are employed. However, these deep learning models demand a substantial and varied dataset to attain optimal precision. Generative Adversarial Networks (GANs) can be employed to create new data, thereby supplementing the existing dataset and enhancing the accuracy of deep learning models. Nevertheless, GANs have their limitations, such as issues related to stability, convergence, and the ability to distinguish between authentic and fabricated data. In order to overcome these challenges and advance the detection and classification of CXR normal and abnormal images, this study introduces a distinctive technique known as DCWGAN (Diverse Conditional Wasserstein GAN) for generating synthetic chest X-ray (CXR) images. The study evaluates the effectiveness of this Idiosyncratic DCWGAN technique using the ResNet50 model and compares its results with those obtained using the traditional GAN approach. The findings reveal that the ResNet50 model trained on the DCWGAN-generated dataset outperformed the model trained on the classic GAN-generated dataset. Specifically, the ResNet50 model utilizing DCWGAN synthetic images achieved impressive performance metrics with an accuracy of 0.961, precision of 0.955, recall of 0.970, and F1-Measure of 0.963. These results indicate the promising potential for the early detection of diseases in CXR images using this Inimitable approach.

Keywords: CNN, classification, deep learning, GAN, Resnet50

Procedia PDF Downloads 93

Authors: Margit Kastner

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To overcome the negative consequences associated with large class sizes and to support students in developing the necessary competences (e.g., critical thinking, problem-solving, or team-work skills) a marketing course has been redesigned by implementing project-based learning with peer assessment (PBL&PA). This means that students can voluntarily take advantage of this supplementary offer and explore -in addition to attending the lecture where clicker questions are asked- a real-world problem, find a solution, and assess the results of peers while working in small collaborative groups. In order to handle this with little further effort, the process is technically supported by the university’s e-learning system in such a way that students upload their solution in form of an assignment which is then automatically distributed to peer groups who have to assess the work of three other groups. Finally, students’ work is graded automatically considering both, students’ contribution to the project and the conformity of the peer assessment. The purpose of this study is to evaluate students’ perception of PBL&PA using an online-questionnaire to collect the data. More specifically, it aims to discover students’ motivations for (not) working on a project and the benefits and problems students encounter. In addition to the survey, students’ performance was analyzed by comparing the final grades of those who participated in PBL&PA with those who did not participate. Among the 260 students who filled out the questionnaire, 47% participated in PBL&PA. Besides extrinsic motivations (bonus credits), students’ participation was often motivated by learning and social benefits. Reasons for not working on a project were connected to students’ organization and management of their studies (e.g., time constraints, no/wrong information) and teamwork concerns (e.g., missing engagement of peers, prior negative experiences). In addition, high workload and insufficient extrinsic motivation (bonus credits) were mentioned. With regards to benefits and problems students encountered during the project, students provided more positive than negative comments. Positive aspects most often stated were learning and social benefits while negative ones were mainly attached to the technical implementation. Interestingly, bonus credits were hardly named as a positive aspect meaning that intrinsic motivations have become more important when working on the project. Team aspects generated mixed feelings. In addition, students who voluntarily participated in PBL&PA were, in general, more active and utilized further course offers such as clicker questions. Examining students’ performance at the final exam revealed that students without participating in any of the offered active learning tasks performed poorest in the exam while students who used all activities were best. In conclusion, the goals of the implementation were met in terms of students’ perceived benefits and the positive impact on students’ exam performance. Since the comparison of the automatic grading with faculty grading showed valid results, it is possible to rely only on automatic grading in the future. That way, the additional workload for faculty will be within limits. Thus, the implementation of project-based learning with peer assessment can be recommended for large classes.

Keywords: automated grading, large classes, peer assessment, project-based learning

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Authors: Eva Laryea, Clement Yeboah Authors

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A pretest-posttest within subjects, experimental design was employed to examine the effects of a computerized basic statistics learning game on achievement and statistics-related anxiety of students enrolled in introductory graduate statistics course. Participants (N = 34) were graduate students in a variety of programs at state-funded research university in the Southeast United States. We analyzed pre-test posttest differences using paired samples t-tests for achievement and for statistics anxiety. The results of the t-test for knowledge in statistics were found to be statistically significant indicating significant mean gains for statistical knowledge as a function of the game-based intervention. Likewise, the results of the t-test for statistics-related anxiety were also statistically significant indicating a decrease in anxiety from pretest to posttest. The implications of the present study are significant for both teachers and students. For teachers, using computer games developed by the researchers can help to create a more dynamic and engaging classroom environment, as well as improve student learning outcomes. For students, playing these educational games can help to develop important skills such as problem solving, critical thinking, and collaboration. Students can develop interest in the subject matter and spend quality time to learn the course as they play the game without knowing that they are even learning the presupposed hard course. The future directions of the present study are promising, as technology continues to advance and become more widely available. Some potential future developments include the integration of virtual and augmented reality into educational games, the use of machine learning and artificial intelligence to create personalized learning experiences, and the development of new and innovative game-based assessment tools. It is also important to consider the ethical implications of computer game-based pedagogy, such as the potential for games to perpetuate harmful stereotypes and biases. As the field continues to evolve, it will be crucial to address these issues and work towards creating inclusive and equitable learning experiences for all students. This study has the potential to revolutionize the way basic statistics graduate students learn and offers exciting opportunities for future development and research. It is an important area of inquiry for educators, researchers, and policymakers, and will continue to be a dynamic and rapidly evolving field for years to come.

Keywords: pretest-posttest within subjects, experimental design, achievement, statistics-related anxiety

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Authors: Layla Alzarah

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The purpose of this research was to study the effects of co-teaching upon study achievement by teaching unite of teaching strategy course to a sample of students at education college at King Faisal University. The sample of this study, which consisted of 100 students, was divided into two equal groups. 50 students were selected to be the Control group which had been taught by the traditional way with one teacher, whereas the remaining 50 students represented the experimental group who had been taught by co-teaching. The study had lasted for 4 weeks. Related achievement test had been prepared, consisted of 23 questions, from multi choice question type, which had been divided on the chosen unite syllabus. The validity and reliability had been tested. The study conducted at the second semester of 1433-1434 HT tests had been used to analysis the data. The research findings showed that the average exam scores of students receiving team teaching were higher than those of students receiving traditional teaching as there were significant differences in means at (<0.05) between the two groups in favor of the experimental group. Based on the study findings the researcher recommended applying co-teaching in teaching the course of teaching strategies and other courses also to conduct similar studies.

Keywords: co-teaching, cooperative teaching, teaching strategies, study achievement

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Authors: Xiaohui Pan

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As the most influential media for the dissemination of Chinese culture, films and television dramas have played cognitive orientation in guiding young audience to understand its cultural value. Taking a retrospective overview of the Chinese domestic film and television dramas in the last decade, it is tangible to notice that Westernization has become irresistible force in the presentation of Chinese youth culture, such as the rise of sensibility, publicity of subjectivity, and the resistance to mainstream discourse. However, the process of deconstruction and transition of these film and television works on Western youth culture brought about more comprehensive conflicts and integration rather than providing a panoramic interpretation to young Chinese. Issues of tradition and modernization, oriental and Western, and serious thinking and the spirit of entertainment overwhelmed those Chinese works. This study attempts to examine the mechanism of young Chinese’s resistance, compromise and re-construction in their marriages during the dynamic cultural intergration between traditional Chinese culture and Western culture. To investigate such a mechanism, this study analyzed four Chinese television dramas themed on family ethics to reveal the conflictions between two generations, mother-in-law and daughter-in-law, aiming to identify their strategies of their struggles. Incorporating the theory of Scott's weapons of the weak, this study examines the dynamic model of the struggles content analysis on their hidden language and the power. The finding shows that young Chinese identified their self-awakening during the resistance. The study also finds out that the external factors might have the functions of switching the power from the strong end to the weak end. The finding of this study can provide useful insights for researchers in this area and for those in the process of exploring cultural integration issues.

Keywords: intergration, integration, resistance, youth culture

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Authors: Chien Chin-Wen

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Collaborative teaching has different teaching models and station teaching is one type of collaborative teaching. Station teaching is not commonly practiced in elementary school English education and introduced in language teacher education programs in Taiwan. In station teaching, each teacher takes a small part of instructional content, working with a small number of students. Students rotate between stations where they receive the assignments and instruction from different teachers. The teachers provide the same content to each group, but the instructional method can vary based upon the needs of each group of students. This study explores thirty-four Taiwanese pre-service elementary school English teachers’ knowledge about station teaching and their competence demonstrated in designing activities for and delivering of station teaching in an English remedial education to six sixth graders in a local elementary school in northern Taiwan. The participants simultaneously enrolled in this Elementary School English Teaching Materials and Methods class, a part of an elementary school teacher education program in a northern Taiwan city. The instructor (Jennifer, pseudonym) in this Elementary School English Teaching Materials and Methods class collaborated with an English teacher (Olivia, pseudonym) in Maureen Elementary School (pseudonym), an urban elementary school in a northwestern Taiwan city. Of Olivia’s students, four male and two female sixth graders needed to have remedial English education. Olivia chose these six elementary school students because they were in the lowest 5 % of their class in terms of their English proficiency. The thirty-four pre-service English teachers signed up for and took turns in teaching these six sixth graders every Thursday afternoon from four to five o’clock for twelve weeks. While three participants signed up as a team and taught these six sixth graders, the last team consisted of only two pre-service teachers. Each team designed a 40-minute lesson plan on the given language focus (words, sentence patterns, dialogue, phonics) of the assigned unit. Data in this study included the KWLA chart, activity designs, and semi-structured interviews. Data collection lasted for four months, from September to December 2014. Data were analyzed as follows. First, all the notes were read and marked with appropriate codes (e.g., I don’t know, co-teaching etc.). Second, tentative categories were labeled (e.g., before, after, process, future implication, etc.). Finally, the data were sorted into topics that reflected the research questions on the basis of their relevance. This study has the following major findings. First of all, the majority of participants knew nothing about station teaching at the beginning of the study. After taking the course Elementary School English Teaching Materials and Methods and after designing and delivering the station teaching in an English remedial education program to six sixth graders, they learned that station teaching is co-teaching, and that it includes activity designs for different stations and students’ rotating from station to station. They demonstrated knowledge and skills in activity designs for vocabulary, sentence patterns, dialogue, and phonics. Moreover, they learned to interact with individual learners and guided them step by step in learning vocabulary, sentence patterns, dialogue, and phonics. However, they were still incompetent in classroom management, time management, English, and designing diverse and meaningful activities for elementary school students at different English proficiency levels. Hence, language teacher education programs are recommended to integrate station teaching to help pre-service teachers be equipped with eight knowledge and competences, including linguistic knowledge, content knowledge, general pedagogical knowledge, curriculum knowledge, knowledge of learners and their characteristics, pedagogical content knowledge, knowledge of education content, and knowledge of education’s ends and purposes.

Keywords: co-teaching, competence, knowledge, pre-service teachers, station teaching

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Authors: Fatou Cisse

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Depression is one of the most serious health problems experienced by immigrants and refugees, who are likely to undergo heightened political, economic, social, and environmental stressors as they transition to a new culture. The purpose of this literature review is to identify and compare risks associated with depression among young adult immigrants and refugees aged 18 to 25. Ten articles focused on risks associated with depression symptoms among this population were reviewed, revealing several common themes: Stress, identity, culture, language barriers, discrimination, social support, self-esteem, length of time in the receiving country, origins, or background. Existing research has failed to account adequately for sample size, language barriers, how the concept of "depression" differs across cultures, and stressors immigrants and refugees experience prior to the transition to the new culture. The study revealed that immigrants and refugees are at risk for depression and that the risk is greater in the refugee population due to their history of trauma. The Roy Adaptation Model was employed to understand the coping mechanisms that refugees and immigrants could use to reduce rates of depression. The psychiatric nurse practitioner must be prepared to intervene and educate this population on these coping mechanisms to help them overcome the feelings that lead to depression and facilitate a smooth integration into the new culture.

Keywords: immigration, refugees, depression, young adults

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Authors: Raeed Alanazi

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Introduction: Nursing students have a crucial role to play in the inhibition of infectious diseases and, therefore, must be trained in infection control and prevention modules prior to entering clinical settings. Simulations have been found to have a positive impact on infection control skills and the use of standard precautions. Aim: The purpose of this study was to use the four sources of self-efficacy in explaining the level of clinical self-efficacy and adherence to infection control practices in Saudi nursing students during simulation practice. Method: A cross-sectional design with convenience sampling was used. This study was conducted in all Saudi nursing schools, with a total number of 197 students participated in this study. Three scales were used simulation self- efficacy Scale (SSES), the four sources of self-efficacy scale (SSES), and Compliance with Standard Precautions Scale (CSPS). Multiple linear regression was used to test the use of the four sources of self-efficacy (SSES) in explaining level of clinical self-efficacy and adherence to infection control in nursing students. Results: The vicarious experience subscale (p =.044) was statistically significant. The regression model indicated that for every one unit increase in vicarious experience (observation and reflection in simulation), the participants’ adherence to infection control increased by .13 units (β =.22, t = 2.03, p =.044). In addition, the regression model indicated that for every one unit increase in education level, the participants’ adherence to infection control increased by 1.82 units (beta=.34= 3.64, p <.001). Also, the mastery experience subscale (p <.001) and vicarious experience subscale (p = .020) were shared significant associations with clinical self-efficacy. Conclusion: The findings of this research support the idea that simulation-based learning can be a valuable teaching-learning method to help nursing students develop clinical competence, which is essential in providing quality and safe nursing care.

Keywords: simulation-based learning, clinical self-efficacy, infection control, nursing students

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Authors: Sergio Zabala-Vargas, Miguel Jiménez-Barrera, Luz VArgas-Sánchez

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In recent years, information related to project management in organizations has been increasing exponentially. Performance data, management statistics, indicator results have forced the collection, analysis, traceability, and dissemination of project managers to be essential. In this sense, there are current trends to facilitate efficient decision-making in emerging technology projects, such as: Machine Learning, Data Analytics, Data Mining, and Big Data. The latter is the most interesting in this project. This research is part of the thematic line Construction methods and project management. Many authors present the relevance that the use of emerging technologies, such as Big Data, has taken in recent years in project management in the construction sector. The main focus is the optimization of time, scope, budget, and in general mitigating risks. This research was developed in the northeastern region of Colombia-South America. The first phase was aimed at diagnosing the use of emerging technologies (Big-Data) in the construction sector. In Colombia, the construction sector represents more than 50% of the productive system, and more than 2 million people participate in this economic segment. The quantitative approach was used. A survey was applied to a sample of 91 companies in the construction sector. Preliminary results indicate that the use of Big Data and other emerging technologies is very low and also that there is interest in modernizing project management. There is evidence of a correlation between the interest in using new data management technologies and the incorporation of Building Information Modeling BIM. The next phase of the research will allow the generation of guidelines and strategies for the incorporation of technological tools in the construction sector in Colombia.

Keywords: big data, building information modeling, tecnology, project manamegent

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