Search results for: learning experiences

Authors: H. Abas Nejad, A. R. Teymoori

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Facial expression recognition is one of the open problems in computer vision. Robust neutral face recognition in real time is a major challenge for various supervised learning based facial expression recognition methods. This is due to the fact that supervised methods cannot accommodate all appearance variability across the faces with respect to race, pose, lighting, facial biases, etc. in the limited amount of training data. Moreover, processing each and every frame to classify emotions is not required, as the user stays neutral for the majority of the time in usual applications like video chat or photo album/web browsing. Detecting neutral state at an early stage, thereby bypassing those frames from emotion classification would save the computational power. In this work, we propose a light-weight neutral vs. emotion classification engine, which acts as a preprocessor to the traditional supervised emotion classification approaches. It dynamically learns neutral appearance at Key Emotion (KE) points using a textural statistical model, constructed by a set of reference neutral frames for each user. The proposed method is made robust to various types of user head motions by accounting for affine distortions based on a textural statistical model. Robustness to dynamic shift of KE points is achieved by evaluating the similarities on a subset of neighborhood patches around each KE point using the prior information regarding the directionality of specific facial action units acting on the respective KE point. The proposed method, as a result, improves ER accuracy and simultaneously reduces the computational complexity of ER system, as validated on multiple databases.

Keywords: neutral vs. emotion classification, Constrained Local Model, procrustes analysis, Local Binary Pattern Histogram, statistical model

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Authors: M. Caporale

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French Curricula across the US have recently suffered low enrollment and have experienced difficulties with retention, thus resulting in fewer students minoring and majoring in French and enrolling in upper-level classes. Successful undergraduate programs offer French courses with a strong cultural and interdisciplinary or multidisciplinary component. The World Language Curriculum in liberal arts colleges in America needs to take into account the cultural aspects of the language and encourage students to think critically about the country or countries they are studying. Limiting the critical inquiry to language or literature narrowly defined provides and incomplete and stagnant picture of France and the Francophone world in today's global community. This essay discusses the creation and implementation of a hybrid interdisciplinary L1/L2 course titled "Topics in Francophone Cinema" (subtitle "Francophone Women on Screen and Behind the Camera"). Content-based interdisciplinary courses undoubtedly increase the profile of French and Francophone cultural Studies by introducing students of other disciplines to fundamental questions relating to the French and Francophone cultures (in this case, women's rights in the Francophone world). At the same time, this study determines that through targeted reading and writing assignments, sustained aural exposure to L2 through film,and student participation in a one-credit supplementary weekly practicum (creative film writing workshop), significant advances in L2 competence are achieved with students' oral and written production levels evolving from Advanced Low to Advanced-mid, as defined by the ACFL guidelines. Use of differentiated assessment methods for L1/L2 and student learning outcomes for both groups will also be addressed.

Keywords: interdisciplinary, Francophone cultural studies, language competency, content-based

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Authors: Irene Yi

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Machine learning, natural language processing, and neural network models of language are becoming more and more prevalent in the fields of technology and linguistics today. Training data for machines are at best, large corpora of human literature and at worst, a reflection of the ugliness in society. Machines have been trained on millions of human books, only to find that in the course of human history, derogatory and sexist adjectives are used significantly more frequently when describing females in history and literature than when describing males. This is extremely problematic, both as training data, and as the outcome of natural language processing. As machines start to handle more responsibilities, it is crucial to ensure that they do not take with them historical sexist and misogynistic notions. This paper gathers data and algorithms from neural network models of language having to deal with syntax, semantics, sociolinguistics, and text classification. Results are significant in showing the existing intentional and unintentional misogynistic notions used to train machines, as well as in developing better technologies that take into account the semantics and syntax of text to be more mindful and reflect gender equality. Further, this paper deals with the idea of non-binary gender pronouns and how machines can process these pronouns correctly, given its semantic and syntactic context. This paper also delves into the implications of gendered grammar and its effect, cross-linguistically, on natural language processing. Languages such as French or Spanish not only have rigid gendered grammar rules, but also historically patriarchal societies. The progression of society comes hand in hand with not only its language, but how machines process those natural languages. These ideas are all extremely vital to the development of natural language models in technology, and they must be taken into account immediately.

Keywords: gendered grammar, misogynistic language, natural language processing, neural networks

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Authors: Urooj Shafique, Salman Jamil

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In the context of an urban human life, city requires to meeting some standards which, at a glance are called the standards of a quality life. Measuring the quality of life according to particular social, economic and cultural conditions of a country and also the emphasis of a country twenty years visions on this issue has special importance. Cultural gathering spaces improve social and economic vitality on one side and on the other side provide favorable conditions for citizen leisure. But unfortunately these cultural gathering spaces in our society are losing their meaning and importance with time. Like coffee houses and libraries. Dedhee was the most prominent place among the cultural gathering spaces in Hazara division. People used to visit them in order to get something out of these spaces. At present they lie in our cities as places of no interest. Libraries are converted into storage houses where books lie untouched for years and years. The aim of my project is to create unique space that engage community members in the learning and creation process, where people can share their knowledge with others as well as enjoy their personal space. The spaces are flexible enough to accommodate people of different moods and interests, with the purpose of helping communities to become aware of their own cultures and to be socially engaged. The site for this specific project has been selected near Cantonment Park Abbottabad, Pakistan. The city of Abbottabad is famous for its writers, poets and storytellers. The site is selected next to the Cantonment Park, at a central location in the whole city so that it can attract users from almost every point of the city. The project provides a cultural gathering space for the people of the city where they can sit and discuss their ideas within a creative and expressive environment, which can represent the cultures of a community.

Keywords: cultural gathering space, Dedhee, Hazara literature, intellectuals’ hub

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Authors: Jung Ae Park, Jooyong Park

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Writing is an important learning activity that cultivates higher level thinking. Effective and immediate feedback is necessary to help improve students' writing skills. Peer assessment can be an effective method in writing tasks because it makes it possible for students not only to receive quick feedback on their writing but also to get a chance to examine different perspectives on the same topic. Peer assessment can be practiced frequently and has the advantage of immediate feedback. However, there is controversy about the accuracy of peer assessment. In this study, we tried to demonstrate experimentally how the accuracy of peer assessment could be improved. Participants (n=76) were randomly assigned to groups of 4 members. All the participant graded two sets of 4 essays on the same topic. They graded the first set twice, and the second set or the posttest once. After the first grading of the first set, each group in the experimental condition 1 (discussion group), were asked to discuss the results of the peer assessment and then to grade the essays again. Each group in the experimental condition 2 (reading group), were asked to read the assessment on each essay by an expert and then to grade the essays again. In the control group, the participants were asked to grade the 4 essays twice in different orders. Afterwards, all the participants graded the second set of 4 essays. The mean score from 4 participants was calculated for each essay. The accuracy of the peer assessment was measured by Pearson correlation with the scores of the expert. The results were analyzed by two-way repeated measure ANOVA. The main effect of grading was observed: Grading accuracy got better as the number of grading experience increased. Analysis of posttest accuracy revealed that the score variations within a group of 4 participants decreased in both discussion and reading conditions but not in the control condition. These results suggest that having students discuss their grading together can be an efficient means to improve peer assessment accuracy. By discussing, students can learn from others about what to consider in grading and whether their grading is too strict or lenient. Further research is needed to examine the exact cause of the grading accuracy.

Keywords: peer assessment, evaluation accuracy, discussion, score variations

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Authors: Shuyu Zhang

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The waterfront historical district, as a type of historical districts on the verge of waters such as the sea, lake, and river, have a relatively special urban form. In the past preservation and renewal of traditional historic districts, there have been many discussions on the land range, and the waterfront and marginal spaces are easily overlooked. However, the waterfront space of the historic districts, as a cultural landscape heritage combining historical buildings and landscape elements, has strong ecological and sustainable values. At the same time, Suzhou and Venice, as sister water cities in history, have more waterfront spaces that can be compared in urban form and other levels. Therefore, this paper focuses on the waterfront historic districts in Venice and Suzhou, establishes quantitative evaluation indicators for environmental perception, makes analogies, and promotes the renewal and activation of the entire historical district by improving the spatial quality and vitality of the waterfront area. First, this paper uses multi-source data for analysis, such as Baidu Maps and Google Maps API to crawl the street view of the waterfront historic districts, uses machine learning algorithms to analyze the proportion of cultural landscape elements such as green viewing rate in the street view pictures, and uses space syntax software to make quantitative selectivity analysis, so as to establish environmental perception evaluation indicators for the waterfront historic districts. Finally, by comparing and summarizing the waterfront historic districts in Venice and Suzhou, it reveals their similarities and differences, characteristics and conclusions, and hopes to provide a reference for the heritage preservation and renewal of other waterfront historic districts.

Keywords: waterfront historical district, cultural landscape, perception, multi-source Data

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Authors: Lucilla Crosta, Anthony Edwards

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Companies and the market place nowadays struggle to find employees with adequate skills in relation to anticipated growth of their businesses. At least half of workers will need to undertake some form of up-skilling process in the next five years in order to remain aligned with the requests of the market . In order to meet these challenges, there is a clear need to explore the potential uses of AI (artificial Intelligence) based tools in assessing transversal skills (critical thinking, communication and soft skills of different types in general) of workers and adult students while empowering them to develop those same skills in a reliable trustworthy way. Companies seek workers with key transversal skills that can make a difference between workers now and in the future. However, critical thinking seems to be the one of the most imprtant skill, bringing unexplored ideas and company growth in business contexts. What employers have been reporting since years now, is that this skill is lacking in the majority of workers and adult students, and this is particularly visible trough their writing. This paper investigates how critical thinking and communication skills are currently developed in Higher Education environments through use of AI tools at postgraduate levels. It analyses the use of a branch of AI namely Machine Learning and Big Data and of Neural Network Analysis. It also examines the potential effect the acquisition of these skills through AI tools and what kind of effects this has on employability This paper will draw information from researchers and studies both at national (Italy & UK) and international level in Higher Education. The issues associated with the development and use of one specific AI tool Edulai, will be examined in details. Finally comparisons will be also made between these tools and the more recent phenomenon of Chat GPT and forthcomings and drawbacks will be analysed.

Keywords: critical thinking, artificial intelligence, higher education, soft skills, chat GPT

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Authors: Saeid Haghjoo, Ebrahim Reyhani, Fahimeh Kolahdouz

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The present study aimed to evaluate the understanding of the students in Tehran universities (Iran) about the numerical representation of the average rate of change based on the Structure of Observed Learning Outcomes (SOLO). In the present descriptive-survey research, the statistical population included undergraduate students (basic sciences and engineering) in the universities of Tehran. The samples were 604 students selected by random multi-stage clustering. The measurement tool was a task whose face and content validity was confirmed by math and mathematics education professors. Using Cronbach's Alpha criterion, the reliability coefficient of the task was obtained 0.95, which verified its reliability. The collected data were analyzed by descriptive statistics and inferential statistics (chi-squared and independent t-tests) under SPSS-24 software. According to the SOLO model in the prestructural, unistructural, and multistructural levels, basic science students had a higher percentage of understanding than that of engineering students, although the outcome was inverse at the relational level. However, there was no significant difference in the average understanding of both groups. The results indicated that students failed to have a proper understanding of the numerical representation of the average rate of change, in addition to missconceptions when using physics formulas in solving the problem. In addition, multiple solutions were derived along with their dominant methods during the qualitative analysis. The current research proposed to focus on the context problems with approximate calculations and numerical representation, using software and connection common relations between math and physics in the teaching process of teachers and professors.

Keywords: average rate of change, context problems, derivative, numerical representation, SOLO taxonomy

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Authors: Citlali Aguilera Lira, David Lynch Steinicke, Andrea León García

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One of the challenges that higher education faces is to find how to approach the sustainability in an inclusive way to the student within all the different academic areas, how to move the sustainable development from the abstract field to the operational field. This research comes from the ecoliteracy and the pedagogical praxis as tools for rebuilding the teaching processes inside of universities. The purpose is to determine and describe which are the factors involved in the process of learning particularly in the Greenhouse-School Siembra UV. In the Greenhouse-School Siembra UV, of the University of Veracruz, are cultivated vegetables, medicinal plants and small cornfields under the usage of eco-technologies such as hydroponics, Wickingbed and Hugelkultur, which main purpose is the saving of space, labor and natural resources, as well as function as agricultural production alternatives in the urban and periurban zones. The sample was formed with students from different academic areas and who are actively involved in the greenhouse, as well as institutes from the University of Veracruz and governmental and non-governmental departments. This project comes from a pedagogic praxis approach, from filling the needs that the different professional profiles of the university students have. All this with the purpose of generate a pragmatic dialogue with the sustainability. It also comes from the necessity to understand the factors that intervene in the students’ praxis. In this manner is how the students are the fundamental unit in the sphere of sustainability. As a result, it is observed that those University of Veracruz students who are involved in the Greenhouse-school, Siembra UV, have enriched in different levels the sense of urban and periurban agriculture because of the diverse academic approaches they have and the interaction between them. It is concluded that the eco-technologies act as fundamental tools for ecoliteracy in society, where it is strengthen the nutritional and food security from a sustainable development approach.

Keywords: farming eco-technologies, food security, multidisciplinary, pedagogical praxis

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Authors: M. S. Wickramarachchi, L. S. Nawarathna, C. M. B. Dematawewa

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Hatchery performance is critical for the profitability of poultry breeder operations. Some extrinsic parameters of eggs and breeders cause to increase or decrease the hatchability. This study aims to identify the affecting extrinsic parameters on the commercial hatchability of local chicken's eggs and determine the most efficient classification model with a hatchability rate greater than 90%. In this study, seven extrinsic parameters were considered: egg weight, moisture loss, breeders age, number of fertilised eggs, shell width, shell length, and shell thickness. Multiple linear regression was performed to determine the most influencing variable on hatchability. First, the correlation between each parameter and hatchability were checked. Then a multiple regression model was developed, and the accuracy of the fitted model was evaluated. Linear Discriminant Analysis (LDA), Classification and Regression Trees (CART), k-Nearest Neighbors (kNN), Support Vector Machines (SVM) with a linear kernel, and Random Forest (RF) algorithms were applied to classify the hatchability. This grouping process was conducted using binary classification techniques. Hatchability was negatively correlated with egg weight, breeders' age, shell width, shell length, and positive correlations were identified with moisture loss, number of fertilised eggs, and shell thickness. Multiple linear regression models were more accurate than single linear models regarding the highest coefficient of determination (R²) with 94% and minimum AIC and BIC values. According to the classification results, RF, CART, and kNN had performed the highest accuracy values 0.99, 0.975, and 0.972, respectively, for the commercial hatchery process. Therefore, the RF is the most appropriate machine learning algorithm for classifying the breeder outcomes, which are economically profitable or not, in a commercial hatchery.

Keywords: classification models, egg weight, fertilised eggs, multiple linear regression

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Authors: Annalakshmi G., Sakthivel Murugan S.

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This paper presents a local directional encoded derivative binary pattern (LDEDBP) feature extraction method that can be applied for the classification of submarine coral reef images. The classification of coral reef images using texture features is difficult due to the dissimilarities in class samples. In coral reef image classification, texture features are extracted using the proposed method called local directional encoded derivative binary pattern (LDEDBP). The proposed approach extracts the complete structural arrangement of the local region using local binary batten (LBP) and also extracts the edge information using local directional pattern (LDP) from the edge response available in a particular region, thereby achieving extra discriminative feature value. Typically the LDP extracts the edge details in all eight directions. The process of integrating edge responses along with the local binary pattern achieves a more robust texture descriptor than the other descriptors used in texture feature extraction methods. Finally, the proposed technique is applied to an extreme learning machine (ELM) method with a meta-heuristic algorithm known as weighted distance grey wolf optimizer (GWO) to optimize the input weight and biases of single-hidden-layer feed-forward neural networks (SLFN). In the empirical results, ELM-WDGWO demonstrated their better performance in terms of accuracy on all coral datasets, namely RSMAS, EILAT, EILAT2, and MLC, compared with other state-of-the-art algorithms. The proposed method achieves the highest overall classification accuracy of 94% compared to the other state of art methods.

Keywords: feature extraction, local directional pattern, ELM classifier, GWO optimization

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Authors: Nilda San Miguel, Elymar Pascual

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The main focus of this study is exploring the effective approaches in teaching Mathematics that is being applied in public schools, s.y. 2018-2019. This research was written as connected output to the district-wide School Learning Action Cell (DISLAC) on Math teaching approaches which was recently conducted in Victoria, Laguna. Fifty-four math teachers coming from 17 schools in Victoria became the respondents of this study. Qualitative method of doing research was applied. Teachers’ responses to the following concerns were gathered, analyzed and interpreted: (1) evaluation of the recently conducted DISLAC, (2) status of the use of different approaches, (3) perception on the effective use of approaches, (4) preference of approach to explore in classroom sessions, (5) factors affecting the choice of approach, (6) difficulties encountered, (7) and perceived benefit to learners. Results showed that the conduct of DISLAC was very highly satisfactory (mean 4.41). Teachers looked at collaborative approach as very highly effective (mean 4.74). Fifty-two percent of the teachers is using collaborative approach, 17% constructivist, 11% integrative, 11% inquiry-based, and 9% reflective. Reflective approach was chosen to be explored by most of the respondents (29%) in future sessions. The difficulties encountered by teachers in using the different approaches are: (1) learners’ difficulty in following instructions, (2) lack of focus, (3) lack of willingness and cooperation, (4) teachers’ lack of mastery in using different approaches, and (5) lack of time of doing visual aids because of time mismanagement. Teachers deemed the use of various teaching approaches can help the learners to have (1) mastery of competency, (2) increased communication, (3) improved confidence, (4) facility in comprehension, and (5) better academic output. The result obtained from this study can be used as an input for SLACs. Recommendations at the end of the study were given to school/district heads and future researchers.

Keywords: approaches, collaborative, constructivism, inquiry-based, integrative, reflective

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Authors: Sylvester Akpah, Selasi Vondee

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Unmanned Aerial Vehicles (UAV) as they are also known, drones have attracted increasing attention in recent years due to their ubiquitous nature and boundless applications in the areas of communication, surveying, aerial photography, weather forecasting, medical delivery, surveillance amongst others. Operated remotely in real-time or pre-programmed, drones can fly autonomously or on pre-defined routes. The application of these aerial vehicles has successfully penetrated the world due to technological evolution, thus a lot more businesses are utilizing their capabilities. Unfortunately, while drones are replete with the benefits stated supra, they are riddled with some problems, mainly attributed to the complexities in learning how to master drone flights, collision avoidance and enterprise security. Additional challenges, such as the analysis of flight data recorded by sensors attached to the drone may take time and require expert help to analyse and understand. This paper presents an autonomous drone control system using a chatbot. The system allows for easy control of drones using conversations with the aid of Natural Language Processing, thus to reduce the workload needed to set up, deploy, control, and monitor drone flight missions. The results obtained at the end of the study revealed that the drone connected to the chatbot was able to initiate flight missions with just text and voice commands, enable conversation and give real-time feedback from data and requests made to the chatbot. The results further revealed that the system was able to process natural language and produced human-like conversational abilities using Artificial Intelligence (Natural Language Understanding). It is recommended that radio signal adapters be used instead of wireless connections thus to increase the range of communication with the aerial vehicle.

Keywords: artificial ntelligence, chatbot, natural language processing, unmanned aerial vehicle

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Authors: Yulan Wu

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With the rapid development of social media, the issue of fake news has gained considerable prominence, drawing the attention of both the public and governments. The widespread dissemination of false information poses a tangible threat across multiple domains of society, including politics, economy, and health. However, much research has concentrated on supervised training models within specific domains, their effectiveness diminishes when applied to identify fake news across multiple domains. To solve this problem, some approaches based on domain labels have been proposed. By segmenting news to their specific area in advance, judges in the corresponding field may be more accurate on fake news. However, these approaches disregard the fact that news records can pertain to multiple domains, resulting in a significant loss of valuable information. In addition, the datasets used for training must all be domain-labeled, which creates unnecessary complexity. To solve these problems, an unsupervised domain knowledge discovery framework for fake news detection is proposed. Firstly, to effectively retain the multidomain knowledge of the text, a low-dimensional vector for each news text to capture domain embeddings is generated. Subsequently, a feature extraction module utilizing the unsupervisedly discovered domain embeddings is used to extract the comprehensive features of news. Finally, a classifier is employed to determine the authenticity of the news. To verify the proposed framework, a test is conducted on the existing widely used datasets, and the experimental results demonstrate that this method is able to improve the detection performance for fake news across multiple domains. Moreover, even in datasets that lack domain labels, this method can still effectively transfer domain knowledge, which can educe the time consumed by tagging without sacrificing the detection accuracy.

Keywords: fake news, deep learning, natural language processing, multiple domains

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Authors: I. Schiller, D. Morsomme, A. Remacle

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Children’s ability to process spoken language develops until the late teenage years. At school, where efficient spoken language processing is key to academic achievement, listening conditions are often unfavorable. High background noise and poor teacher’s voice represent typical sources of interference. It can be assumed that these factors particularly affect primary school children, because their language and literacy skills are still low. While it is generally accepted that background noise and impaired voice impede spoken language processing, there is an increasing need for analyzing impacts within specific linguistic areas. Against this background, the aim of the study was to investigate the effect of speech-shaped noise and imitated dysphonic voice on first-grade primary school children’s speech perception and sentence comprehension. Via headphones, 5 to 6-year-old children, recruited within the French-speaking community of Belgium, listened to and performed a minimal-pair discrimination task and a sentence-picture matching task. Stimuli were randomly presented according to four experimental conditions: (1) normal voice / no noise, (2) normal voice / noise, (3) impaired voice / no noise, and (4) impaired voice / noise. The primary outcome measure was task score. How did performance vary with respect to listening condition? Preliminary results will be presented with respect to speech perception and sentence comprehension and carefully interpreted in the light of past findings. This study helps to support our understanding of children’s language processing skills under adverse conditions. Results shall serve as a starting point for probing new measures to optimize children’s learning environment.

Keywords: impaired voice, sentence comprehension, speech perception, speech-shaped noise, spoken language processing

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Authors: Gaurav Bhanjana, Ganga Ram Chaudhary, Sandeep Kumar, Neeraj Dilbaghi

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Main sources of endocrine disrupting compounds in the ecosystem are hormones, pesticides, phthalates, flame retardants, dioxins, personal-care products, coplanar polychlorinated biphenyls (PCBs), bisphenol A, and parabens. These endocrine disrupting compounds are responsible for learning disabilities, brain development problems, deformations of the body, cancer, reproductive abnormalities in females and decreased sperm count in human males. Although discharge of these chemical compounds into the environment cannot be stopped, yet their amount can be retarded through proper evaluation and detection techniques. The available techniques for determination of these endocrine disrupting compounds mainly include high performance liquid chromatography (HPLC), mass spectroscopy (MS) and gas chromatography-mass spectrometry (GC–MS). These techniques are accurate and reliable but have certain limitations like need of skilled personnel, time consuming, interference and requirement of pretreatment steps. Moreover, these techniques are laboratory bound and sample is required in large amount for analysis. In view of above facts, new methods for detection of endocrine disrupting compounds should be devised that promise high specificity, ultra sensitivity, cost effective, efficient and easy-to-operate procedure. Nowadays, electrochemical sensors/biosensors modified with nanomaterials are gaining high attention among researchers. Bioelement present in this system makes the developed sensors selective towards analyte of interest. Nanomaterials provide large surface area, high electron communication feature, enhanced catalytic activity and possibilities of chemical modifications. In most of the cases, nanomaterials also serve as an electron mediator or electrocatalyst for some analytes.

Keywords: electrochemical, endocrine disruptors, microscopy, nanoparticles, sensors

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Authors: Hadjer Sadoune, Liza Lamini, Scherazade Krim, Amel Djouadi, Rachida Rihani

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Deep neural networks are highly regarded for their accuracy in predicting intricate fermentation processes. Their ability to learn from a large amount of datasets through artificial intelligence makes them particularly effective models. The primary obstacle in improving the performance of these models is to carefully choose the suitable hyperparameters, including the neural network architecture (number of hidden layers and hidden units), activation function, optimizer, learning rate, and other relevant factors. This study predicts biogas production from real wastewater treatment plant data using a sophisticated approach: hybrid Bayesian optimization with a tree-structured Parzen estimator (BO-TPE) for an optimised deep neural network (DNN) model. The plant utilizes an Upflow Anaerobic Sludge Blanket (UASB) digester that treats industrial wastewater from soft drinks and breweries. The digester has a working volume of 1574 m3 and a total volume of 1914 m3. Its internal diameter and height were 19 and 7.14 m, respectively. The data preprocessing was conducted with meticulous attention to preserving data quality while avoiding data reduction. Three normalization techniques were applied to the pre-processed data (MinMaxScaler, RobustScaler and StandardScaler) and compared with the Non-Normalized data. The RobustScaler approach has strong predictive ability for estimating the volume of biogas produced. The highest predicted biogas volume was 2236.105 Nm³/d, with coefficient of determination (R2), mean absolute error (MAE), and root mean square error (RMSE) values of 0.712, 164.610, and 223.429, respectively.

Keywords: anaerobic digestion, biogas production, deep neural network, hybrid bo-tpe, hyperparameters tuning

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Authors: Igor Peraza Curiel, Suzanne Strum

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Today, when many foreign architects are receiving commissions in the United Arab Emirates, it is essential to analyze how their designs are influenced by the region's culture, environment, and building traditions. This study examines the approach to siting, geometry, construction methods, and material choices in two private homes for a family in Dubai, a project being constructed on adjacent sites by the acclaimed Spanish team of RCR Architects. Their third project in Dubai, the houses mark a turning point in their design approach to the desert. The Pritzker Prize-winning architects of RCR gained renown for building works deeply responsive to the history, landscape, and customs of their hometown in a volcanic area of the Catalonia region of Spain. Key formative projects and their entry to practice in UAE will be analyzed according to the concepts of place identity, the poetics of construction, and material imagination. The poetics of construction, a theoretical position with a long practical tradition, was revived by the British critic Kenneth Frampton. The idea of architecture as a constructional craft is related to the concepts of material imagination and place identity--phenomenological concerns with the creative engagement with local matter and topography that are at the very essence of RCR's way of designing, detailing, and making. Our study situates RCR within the challenges of building in the region, where western forms and means have largely replaced the ingenious responsiveness of indigenous architecture to the climate and material scarcity. The dwellings, iterations of the same steel and concrete vaulting system, highlight the conceptual framework of RCR's design approach to offer a study in contemporary critical regionalism. The Kama House evokes Bedouin tents, while the Alwah House takes the form of desert dunes in response to the temporality of the winds. Metal mesh screens designed to capture the shifting sands will complete the forms. The original research draws on interviews with the architects and unique documentation provided by them and collected by the authors during on-site visits. By examining the two houses in-depth, this paper foregrounds a series of timely questions: 1) What is the impact of the local climatic, cultural, and material conditions on their project in the UAE? 2) How does this work further their experiences in the region? 3) How has RCR adapted their construction techniques as their work expands beyond familiar settings? The investigation seeks to understand how the design methodology developed for more than 20 years and enmeshed in the regional milieu of their hometown can transform as the architects encounter unique characteristics and values in the Middle East. By focusing on the contemporary interpretation of Arabic geometry and elements, the houses reveal the role of geometry, tectonics, and material specificity in the realization from conceptual sketches to built form. In emphasizing the importance of regional responsiveness, the dynamics of international construction practice, and detailing this study highlights essential issues for professionals and students looking to practice in an increasingly global market.

Keywords: material imagination, regional responsiveness, place identity, poetics of construction

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Authors: Israa A. Qari

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Learning to request in a foreign language is a key ability within pragmatics language teaching. This paper examines how requests are taught in English Unlimited Book 3 (Cambridge University Press), an EFL textbook series employed by King Abdulaziz University in Jeddah, Saudi Arabia to teach advanced foundation year students English. The focus of analysis is the evaluation of the request linguistic strategies present in the textbook, frequency of the use of these strategies, and the contextual information provided on the use of these linguistic forms. The researcher collected all the linguistic forms which consisted of the request speech act and divided them into levels employing the CCSARP request coding manual. Findings demonstrated that simple and commonly employed request strategies are introduced. Looking closely at the exercises throughout the chapters, it was noticeable that the book exclusively employed the most direct form of requesting (the imperative) when giving learners instructions: e.g. listen, write, ask, answer, read, look, complete, choose, talk, think, etc. The book also made use of some other request strategies such as ‘hedged performatives’ and ‘query preparatory’. However, it was also found that many strategies were not dealt with in the book, specifically strategies with combined functions (e.g. possibility, ability). On a sociopragmatic level, a strong focus was found to exist on standard situations in which relations between the requester and requestee are clear. In general, contextual information was communicated implicitly only. The textbook did not seem to differentiate between formal and informal request contexts (register) which might consequently impel students to overgeneralize. The paper closes with some recommendations for textbook and curriculum designers. Findings are also contrasted with previous results from similar body of research on EFL requests.

Keywords: EFL, requests, saudi, speech acts, textbook evaluation

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Authors: Hui Liu, Xiaozan Wang, Jiarong Zhong, Ziming Shao

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Introduction: Related research shows that students don’t concentrate on teacher’s speaking in the classroom. The d2 attention test is a time-limited test about selective attention. The d2 attention test can be used to evaluate individual selective attention. Purpose: To use the d2 attention test tool to measure the difference between the attention level of the experimental class and the control class before and after Brain-Break and to explore the effect of Brain-Break in the classroom on students' selective attention. Methods: According to the principle of no difference in pre-test data, two classes in the fourth- grade of Shenzhen Longhua Central Primary School were selected. After 20 minutes of class in the third class in the morning and the third class in the afternoon, about 3-minute Brain-Break intervention was performed in the experimental class for 10 weeks. The normal class in the control class did not intervene. Before and after the experiment, the d2 attention test tool was used to test the attention level of the two-class students. The paired sample t-test and independent sample t-test in SPSS 23.0 was used to test the change in the attention level of the two-class classes around 10 weeks. This article only presents results with significant differences. Results: The independent sample t-test results showed that after ten-week of Brain-Break, the missed errors (E1 t = -2.165 p = 0.042), concentration performance (CP t = 1.866 p = 0.05), and the degree of omissions (Epercent t = -2.375 p = 0.029) in experimental class showed significant differences compared with control class. The students’ error level decreased and the concentration increased. Conclusions: Adding Brain-Break interventions in the classroom can effectively improve the attention level of fourth-grade primary school students to a certain extent, especially can improve the concentration of attention and decrease the error rate in the tasks. The new sport's learning model is worth promoting

Keywords: cultural class, micromotor, attention, D2 test

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Authors: Hirokatsu Kawashima

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One important element of teaching/learning listening is intensive listening such as listening for precise sounds, words, grammatical, and semantic units. Several classroom-based investigations have been conducted to explore the usefulness of auditory recognition of phonological, grammatical and semantic errors in such a context. The current study reports the results of one such investigation, which targeted auditory recognition of phonological, grammatical, and semantic errors at the sentence level. 56 Japanese EFL learners participated in this investigation, in which their recognition performance of phonological, grammatical and semantic errors was measured on a 9-point scale by learners’ self-evaluation from the perspective of 1) two types of similar English sound (vowel and consonant minimal pair words), 2) two types of sentence word order (verb phrase-based and noun phrase-based word orders), and 3) two types of semantic consistency (verb-purpose and verb-place agreements), respectively, and their general listening proficiency was examined using standardized tests. A number of findings have been made about the interactive relationships between the three types of auditory error recognition and general listening proficiency. Analyses based on the OPLS (Orthogonal Projections to Latent Structure) regression model have disclosed, for example, that the three types of auditory error recognition are linked in a non-linear way: the highest explanatory power for general listening proficiency may be attained when quadratic interactions between auditory recognition of errors related to vowel minimal pair words and that of errors related to noun phrase-based word order are embraced (R2=.33, p=.01).

Keywords: auditory error recognition, intensive listening, interaction, investigation

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Authors: A. Kolendo

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Pacific Islands are one of the most vulnerable areas to climate change. Sea level rise and accelerating storm surge continuously threaten the communities' habitats on low-lying atolls. With scientific predictions of encroaching tides on their land, the Islanders have been informed about the need for future relocation planning. However, some communities oppose such retreat strategies through the reasoning that comprehends current climatic changes through the lenses of the biblical ark of Noah. This parable states God's promise never to flood the Earth again and never deprive people of their land and habitats. Several interpretations of this parable emerged in Oceania, prompting either climate action or denial. Resistance to relocation planning expressed through Christian thoughts led religion to be perceived as a barrier to dialogue between the Islanders and scientists. Since climate change concerns natural processes, the attitudes towards environmental stewardship prompt the communities' responses to it; some Christian teachings indicate humanity's responsibility over the environment, whereas others ascertain the people's dominion, which prompts resistance and sometimes denial. With church denominations and their various environmental standpoints, competing responses to climate change emerged in Oceania. Before miss-ionization, traditional knowledge had guided the environmental sphere, influencing current Christian teachings. Each atoll characterizes a distinctive manner of traditional knowledge; however, the unique relationship with nature unites all islands. The interconnectedness between the land, sea and people indicates the integrity between the communities and their environments. Such a factor influences the comprehension of Noah's story in the context of climate change that threatens their habitats. Pacific Islanders experience climate change through the slow disappearance of their homelands. However, the Western world perceives it as a global issue that will affect the population in the long-term perspective. Therefore, the Islanders seek to comprehend this global phenomenon in a local context that reads climate change as the Great Deluge. Accordingly, the safety measures that this parable promotes compensate for the danger of climate change. The rainbow covenant gives hope in God's promise never to flood the Earth again. At the same time, Noah's survival relates to the Islanders' current situation. Since these communities have the lowest carbon emissions rate, their contribution to anthropogenic climate change is scarce. Therefore, the lack of environmental sin would contextualize them as contemporary Noah with the ultimate survival of sea level rise. This study aims to defy religion constituting a barrier through secondary data analysis from a risk compensation perspective. Instead, religion is portrayed as a source of knowledge that enables comprehension of the communities' situation. By demonstrating that the Pacific Islanders utilize Noah's story as a vessel for coping with the danger of climate change, the study argues that religion provides safety measures that compensate for the future projections of land's disappearance. The purpose is to build a bridge between religious communities and scientific bodies and ultimately bring an understanding of two diverse perspectives. By addressing the practical challenges of interdisciplinary research with faith-based systems, this study uplifts the voices of communities and portrays their experiences expressed through Christian thoughts.

Keywords: Christianity, climate change, existential threat, Pacific Islands, story of Noah

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Authors: Muktadir Ahmed, Sayed Akhlakur Rahaman, Mridha Shihab Mahmud

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The parents of Bangladesh have scarcity of knowledge about children play. Most of them do not know which toys are perfect for their children. Appropriate toys for playing is one of the most significant parts of children development from early age, besides for proper amelioration of children’s mental growth and brain capacities, toys play an emergent role. So selection of proper toy for children is very important. A toy forms the sagacity of a child and instructs child’s attitude. In this era of globalization to keep pace with everything children toys are also going forward but in a deleterious way. Maximum toys are now battery-driven and for this psychological developments of children are not increasing in effective way; therefore, pedagogical toys are proper selection. This type of toy inspires the wisdom and helps a child to reveal himself/herself. Pedagogical toys are attractive to children and help to stimulate their imagination. Pedagogical toys help them to build senso-motoric skills and hand-eye coordination. In this study, some children divided into two groups, one group played with pedagogical toys and another group played with conventional toys. This study is going to exhibit the difference between pedagogical and conventional toys for kids. The main aim of this study is to reveal the potency of pedagogical toy for children. To implement this study two Daycare Centers (DCC) Projapoti 1 & 3 of Mymensingh city had chosen. Every DCC having 1.5-6 years old children but for this study 2-5 years old children had been selected. The children of Projapoti-1 played with pedagogical toys and the children of Projapoti-2 played with conventional toys. After 6 weeks of study, the children of Projapoti-1 proved that they have improved their skills more than those children of Projapoti-3 who were playing with conventional toys. The children of Projapoti-1 have developed their touch sensation, muscular movement, imitation power, hand-eye coordination whereas the children of Projapoti-3 have only developed their muscular movement fairly (while running after battery driven toys) which is not better than those children of Projapoti-1. They cannot imitate like the children of Projapoti-1. They just had fun from playing virtual games, battery driven toys, watching cartoons etc. Actually, it is not possible to develop a child’s brain without pedagogical toy.

Keywords: brain development, mental growth, pedagogical toys, play for children

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Authors: Insaf Sayar, Moôtez Marzougui, Abderraouf Ben Abderrahman

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Background: Physical Education and Sports (PES) plays an important role in the overall education of the student. It has physical, affective, psychological, and social repercussions. In fact, overweight children are sometimes underestimated by their lower physical performance and suffer from discriminatory attitudes by their peers and their physical education (PE) teachers. Objectives: The aim of this study was to investigate the impacts of both teacher’s pedagogy and overweight or obesity on the inclusion of obese students in physical education classes in the school setting in the Emirate of Ajman (United Arab Emirates) and to understand how physical education and sports (PES) teachers adapt their pedagogical interventions towards this category. Methods: A sample of 48 overweight or obese students and 20 teachers were approached from different schools in Ajman Emirate. Two standardized questionnaires for obese students and PSE teachers were used. Overweight and obesity were defined using age and sex-specific Body Mass Index (BMI). Results: Our results showed that the average BMI of the surveyed students is 28.58 ± 3.14 kg/m². According to the collected data, 85.42% of obese students report that they do not practice physical activity or rarely practice outside of school, and 73.42% go to school by bus or car. In addition, 66.7% of the surveyed students said that being overweight is a barrier to PES practice, and 100% of obese or overweight students do not prefer some physical activities such as running and jumping. Similarly, 75% of the surveyed teachers said that obese students are not integrated into the PES course, but only 55% of teachers reported that the obese student became an obstacle in PES sessions, while 80% of teachers reported that obese or overweight students were marginalized by their colleagues. In the same way, most of them (75%) said that obese students are exempted from PES courses. Conclusion: Overweight/obesity is prevalent among school children in the Emirate of Ajman, with a high correlation with sedentary behavior. The study confirmed an urgent need and effective teaching strategies/ pedagogies for including overweight or obese students in physical education engagement and learning.

Keywords: adolescent, mainstreaming, obesity, PES education, UAE

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Authors: May Maricel De Gracia

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Different generations respond differently to instruction because of their diverse characteristics, learning styles and study habits. Teaching strategies that were effective many years ago may not be effective now especially to the current generation which is Gen Z. Using quantitative research design, the main goal of this paper is to determine the impact of the implementation of educational technology integration in a private high school in the math performance of its Junior High School (JHS) students on SY 2014-2018 based on their periodical exam performance and on their final math grades. In support, survey on the use of technology was administered to determine the characteristics of both students and teachers of SY 2017-2018. Another survey regarding study habits was also administered to the students to determine their readiness with regards to note-taking skills, time management, test taking/preparation skills, reading, and writing and math skills. Teaching strategies were recommended based on the need of the current Gen Z JHS students. A total of 712 JHS students and 12 math teachers participated in answering the different surveys. Periodic exam means and final math grades between the school years without technology (SY 2004-2008) and with technology (SY 2014-2018) were analyzed through correlation and regression analyses. Result shows that the periodic exam mean has a 35.29% impact to the final grade of the students. In addition, z-test result where p > 0.05 shows that the periodical exam results do not differ significantly between the school years without integration of technology and with the integration of technology. However, with p < 0.01, a significant positive difference was observed in the final math grades of students between the school years without technology integration and with technology integration.

Keywords: classroom instruction, technology, generation z, math performance

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Authors: Ana Violante, Jodie Maccarrone, Maria Fimiani

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In the United States, over 30 million people are hospitalized annually for conditions that require acute, 24-hour, supervised care. The experience of hospitalization can be traumatic, exposing the patient to loss of control, autonomy, and productivity. Furthermore, 40% of patients admitted to hospitals for general medical illness have a comorbid psychiatric diagnosis. Research suggests individuals admitted with psychiatric comorbidities experience poorer health outcomes, higher utilization rates and increased overall cost of care. Empirical work suggests hospital settings that include a consultation liaison (CL) service report reduced length of stay, lower costs per patient, improved medical staff and patient satisfaction and reduced readmission after 180 days. Despite the overall positive impact CL services can have on patient care, it is estimated that only 1% - 2.8% of hospital admits receive these services, and most research has been conducted by the field of psychiatry. Health psychologists could play an important role in increasing access to this valuable service, though the extent to which health psychologists participate in CL settings is not well known. Objective: Outline the preliminary findings from an empirical study to understand how many APPIC internship training programs offer adult consultation liaison rotations within inpatient hospital settings nationally, as well as describe the specific nature of these training experiences. Research Method/Design: Data was exported into Excel from the 2022-2023 APPIC Directory categorized as “health psychology” sites. It initially returned a total of 537 health training programs out 1518 total programs (35% of all APPIC programs). A full review included a quantitative and qualitative comprehensive review of the APPIC program summary, the site website, and program brochures. The quantitative review extracted the number of training positions; amount of stipend; location or state of program, patient, population, and rotation. The qualitative review examined the nature of the training experience. Results: 29 (5%) of all APPIC health psychology internship training programs (2%) respectively of all APPIC training internship programs offering internship CL training were identified. Of the 29 internship training programs, 16 were exclusively within a pediatric setting (55%), 11 were exclusively within an adult setting (38%), and two were a mix of pediatric and adult settings (7%). CL training sites were located to 19 states, offering a total of 153 positions nationally, with Florida containing the largest number of programs (4). Only six programs offered 12-month training opportunities while the rest offered CL as a major (6 month) to minor (3-4 month) rotation. The program’s stipend for CL training positions ranged from $25,000 to $62,400, with an average of $32,056. Conclusions: These preliminary findings suggest CL training and services are currently limited. Training opportunities that do exist are mostly limited to minor, short rotations and governed by psychiatry. Health psychologists are well-positioned to better define the role of psychology in consultation liaison services and enhance and formalize existing training protocols. Future research should explore in more detail empirical outcomes of CL services that employ psychology and delineate the contributions of psychology from psychiatry and other disciplines within an inpatient hospital setting.

Keywords: consultation liaison, health psychology, hospital setting, training

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Authors: Andrew Kanzunguze, Lusayo Mwabumba, Jason K. Gilbertson, Dominic B. Gondwe, George Z. Nxumayo

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Knowledge about the spatio-temporal distribution of invasive plants in protected areas provides a base from which hypotheses explaining proliferation of plant invasions can be made alongside development of relevant invasive plant monitoring programs. The aim of this study was to investigate the spatio-temporal distribution of bracken fern on the grassland plateau of Nyika National Park over the past 30 years (1986-2016) as well as to determine the current extent of the invasion. Remote sensing, machine learning, and statistical modelling techniques (object-based image analysis, image classification and linear regression analysis) in geographical information systems were used to determine both the spatial and temporal distribution of bracken fern in the study area. Results have revealed that bracken fern has been increasing coverage on the Nyika plateau at an estimated annual rate of 87.3 hectares since 1986. This translates to an estimated net increase of 2,573.1 hectares, which was recorded from 1,788.1 hectares (1986) to 4,361.9 hectares (2016). As of 2017 bracken fern covered 20,940.7 hectares, approximately 14.3% of the entire grassland plateau. Additionally, it was observed that the fern was distributed most densely around Chelinda camp (on the central plateau) as well as in forest verges and roadsides across the plateau. Based on these results it is recommended that Ecological Niche Modelling approaches be employed to (i) isolate the most important factors influencing bracken fern proliferation as well as (ii) identify and prioritize areas requiring immediate control interventions so as to minimize bracken fern proliferation in Nyika National Park.

Keywords: bracken fern, image classification, Landsat-8, Nyika National Park, spatio-temporal distribution

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Authors: Rozi Laskaraki, Argyris Karapetsas, Aikaterini Karapetsa

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This paper is focused on the efficacy of a rehabilitation program based on musical activities, implied to a group of school-aged dyslexic children. Objective: The purpose of this study was to investigate the efficacy of auditory training including musical exercises in children with developmental dyslexia (DD). Participants and Methods: 45 third-, and fourth-grade students with DD and a matched control group (n=45) were involved in this study. In the beginning, students participated in a clinical assessment, including both electrophysiological (i.e., event related potentials (ERPs) esp.P300 waveform) and neuropsychological tests, being conducted in Laboratory of Neuropsychology, at University of Thessaly, in Volos, Greece. Initial assessment’s results confirmed statistically significant lower performance for children with DD, compared to that of the typical readers. After clinical assessment, a subgroup of children with dyslexia was submitted to a music auditory training program, conducted in 45-minute training sessions, once a week, for twenty weeks. The program included structured and digitized musical activities involving pitch, rhythm, melody and tempo perception and discrimination as well as auditory sequencing. After the intervention period, children underwent a new recording of ERPs. Results: The electrophysiological results revealed that children had similar P300 latency values to that of the controls, after the remediation program; thus children overcame their deficits. Conclusion: The outcomes of the current study suggest that ERPs is a valid clinical tool in neuropsychological assessment settings and dyslexia can be ameliorated through music auditory training.

Keywords: dyslexia, event related potentials, learning disabilities, music, rehabilitation

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Authors: Ching-Yu Liao, Ju-Joan Wong

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Recent years have shown a trend of younger stroke patients and an increase in ischemic strokes with the rise in stroke incidence. This has led to a growing demand for telemedicine, particularly during the COVID-19 pandemic, which has made the need for telemedicine even more urgent. This shift in healthcare is also closely related to advancements in Internet of Things (IoT) technology. Stroke-induced hemiparesis is a significant issue for patients. The medical community believes that if intervention occurs within three to six months of stroke onset, 80% of the residual effects can be restored to normal, a period known as the stroke golden period. During this time, patients undergo treatment and rehabilitation, and neural plasticity is at its best. Lower limb rehabilitation for stroke generally includes exercises such as support standing and walking posture, typically involving the healthy limb to guide the affected limb to achieve rehabilitation goals. Existing gait training aids in hospitals usually involve balance gait, sitting posture training, and precise muscle control, effectively addressing issues of poor gait, insufficient muscle activity, and inability to train independently during recovery. However, home training aids, such as braced and wheeled devices, often rely on the healthy limb to pull the affected limb, leading to lower usage of the affected limb, worsening circular walking, and compensatory movement issues. IoT technology connects devices via the internet to record, receive data, provide feedback, and adjust equipment for intelligent effects. Therefore, this study aims to explore how IoT can be integrated into existing gait training aids to monitor and sensor home rehabilitation movements, improve gait training compensatory issues through real-time feedback, and enable healthcare professionals to quickly understand patient conditions and enhance medical communication. To understand the needs of hemiparetic patients, a review of relevant literature from the past decade will be conducted. From the perspective of user experience, participant observation will be used to explore the use of home training aids by stroke patients and therapists, and interviews with physical therapists will be conducted to obtain professional opinions and practical experiences. Design specifications for home training aids for hemiparetic patients will be summarized. Applying IoT technology to lower limb training aids for stroke hemiparesis can help promote walking function recovery in hemiparetic patients, reduce muscle atrophy, and allow healthcare professionals to immediately grasp patient conditions and adjust gait training plans based on collected and analyzed information. Exploring these potential development directions provides a valuable reference for the further application of IoT technology in the field of medical rehabilitation.

Keywords: stroke, hemiplegia, rehabilitation, gait training, internet of things technology

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Authors: Caiwei Zhu, Remke Klapwijk

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Spatial thinking, a way of thinking based on the understanding and reasoning of spatial concepts and representations, is embedded in science, technology, engineering, arts, and mathematics (STEAM) learning. Aside from many studies that successfully used targeted training to improve students’ spatial thinking skills, few have closely examined how spatial thinking can be trained in classroom settings. Design and technology education, which receives increasing attention towards its integration into formal curriculums, inherently encompasses a wide range of spatial activities, such as constructing mental representations of design ideas, mentally transforming objects and materials to form designs, visually communicating design plans through annotated drawings, and creating 2D and 3D design artifacts. Among different design topics, biomimicry offers a unique avenue for students to recognize and analyze the shapes and structures in nature. By mapping the forms of plants and animals onto functions, students gain inspiration to solve human design challenges. This study is one of the first to highlight opportunities for training spatial thinking in a biomimicry design project for primary school students. Embracing methodological principles of educational design-based research, this case study is conducted along with iterations in the design of the intervention and collaboration with teachers. Data are harvested from small groups of 10- to 12-year-olds at an international school in the Netherlands. Classroom videos, semi-structured interviews with students, design drawings and artifacts, formative assessment, and the pre- and post-intervention spatial test triangulate evidence for students' spatial thinking. In addition to contributing to a theory of integrating spatial thinking in the primary curriculum, mechanisms underlying such improvement in spatial thinking are explored and discussed.

Keywords: biomimicry, design and technology education, primary education, spatial thinking

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