Search results for: teaching and learning

Authors: Barzan Hadi Hama Karim

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The purpose of this research study is to determine how educators, students at the university level are using storytelling to support the educational process. This study provides a general framework about educational uses of storytelling as a pedagogical too to learn English language in the higher education and describes the different perceptions of people (teachers and students) at different levels. A survey is used to collect responses from a group of educators and students in educational settings to determine how they are using storytelling for educational purposes. The results show the current situation of educational uses of storytelling and explore some of the benefits and challenges educators face in implementing storytelling in their institutions. The purpose of our research is to investigate the impact of storytelling as a pedagogical tool to learn English language in higher education and its academic achievements on ESL students. It highlights findings that address the following questions: (1) How has storytelling been approached historically? (2) Is storytelling beneficial for students in early grades at university? (3) To what extent do teacher and student prefer storytelling as a pedagogical tool to teach and learn English language in higher education?

Keywords: storytelling, teacher's beliefs, student’s beliefs, student’s academic achievement, narrative, pedagogy, ESL

Procedia PDF Downloads 397

Authors: Mafarja Majdi, Salwani Abdullah, Najmeh S. Jaddi

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One of the global combinatorial optimization problems in machine learning is feature selection. It concerned with removing the irrelevant, noisy, and redundant data, along with keeping the original meaning of the original data. Attribute reduction in rough set theory is an important feature selection method. Since attribute reduction is an NP-hard problem, it is necessary to investigate fast and effective approximate algorithms. In this paper, we proposed two feature selection mechanisms based on memetic algorithms (MAs) which combine the genetic algorithm with a fuzzy record to record travel algorithm and a fuzzy controlled great deluge algorithm to identify a good balance between local search and genetic search. In order to verify the proposed approaches, numerical experiments are carried out on thirteen datasets. The results show that the MAs approaches are efficient in solving attribute reduction problems when compared with other meta-heuristic approaches.

Keywords: rough set theory, attribute reduction, fuzzy logic, memetic algorithms, record to record algorithm, great deluge algorithm

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Authors: Qingqing Gai, Junxing Shen, Yu Luo

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Due to the hardware architecture characteristics, some operators tend to acquire better performance if the input/output tensor dimensions are aligned to a certain minimum granularity, such as convolution and deconvolution commonly used in deep learning. Furthermore, if the requirements are not met, the general strategy is to pad with 0 to satisfy the requirements, potentially leading to the under-utilization of the hardware resources. Therefore, for the convolution and deconvolution whose input and output channels do not meet the minimum granularity alignment, we propose to transfer the W-dimensional data to the C-dimension for computation (W2C) to enable the C-dimension to meet the hardware requirements. This scheme also reduces the number of computations in the W-dimension. Although this scheme substantially increases computation, the operator’s speed can improve significantly. It achieves remarkable speedups on multiple hardware accelerators, including Nvidia Tensor cores, Qualcomm digital signal processors (DSPs), and Huawei neural processing units (NPUs). All you need to do is modify the network structure and rearrange the operator weights offline without retraining. At the same time, for some operators, such as the Reducemax, we observe that transferring the Cdimensional data to the W-dimension(C2W) and replacing the Reducemax with the Maxpool can accomplish acceleration under certain circumstances.

Keywords: convolution, deconvolution, W2C, C2W, alignment, hardware accelerator

Procedia PDF Downloads 111

Authors: Kulsoom S. Bughio, Naeem K. Janjua, Gordana Dermody, Leslie F. Sikos, Shamsul Islam

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The advancement in information and communication technologies (ICT) and wireless sensor networks have played a pivotal role in the design and development of real-time healthcare solutions, mainly targeting the elderly living in health-assistive smart homes. Such smart homes are equipped with sensor technologies to detect and record activities of daily living (ADL). This survey reviews and evaluates existing approaches and techniques based on real-time sensor-based modeling and reasoning in single-user and multi-user environments. It classifies the approaches into three main categories: learning-based, knowledge-based, and hybrid, and evaluates how they handle temporal relations, granularity, and uncertainty. The survey also highlights open challenges across various disciplines (including computer and information sciences and health sciences) to encourage interdisciplinary research for the detection and recognition of ADLs and discusses future directions.

Keywords: daily living activities, smart homes, single-user environment, multi-user environment

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Authors: Pataraporn Kheawwan

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Preceptorship represents an important aspect in new nurse orientation. However, there was no formal preceptor training program developed for nurse preceptor in Thailand. The purposes of this study were to develop and evaluate formal preceptor training program for nurse preceptors in King Chulalongkorn Memorial Hospital, Thailand. A research and development study design was utilized in this study. Participants were 37 nurse preceptors. The program contents were delivered by e-learning material, class lecture, group discussion followed by simulation training. Knowledge of the participants was assessed pre and post program. Skill and critical thinking were assessed using Preceptor Skill and Decision Making Evaluation form at the end of program. Statistical significant difference in knowledge regarding preceptor role and coaching strategies between pre and post program were found. All participants had satisfied skill and decision making score after completed the program. Most of participants perceived benefits of preceptor training course. In conclusion, The results of this study reveal that the newly developed preceptorship course is an effective formal training course for nurse preceptors.

Keywords: preceptor, preceptorship, new nurse, clinical education

Procedia PDF Downloads 263

Authors: Dania Baaboud, Renad Al-zahrani, Mahnoor Khan, Riya Afroz

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Flo is a smart period-tracking tool that uses artificial intelligence (AI) to offer individualized reproductive health predictions and insights. Flo makes very accurate predictions about menstrual cycles, ovulation, and fertility windows by evaluating user inputs, including cycle duration, symptoms, and patterns. Its machine learning algorithms are constantly evolving, providing personalized health recommendations, instructional materials, and early identification of possible health abnormalities such as reproductive problems and hormone imbalances. Flo, which was introduced in 2015 and upgraded with AI in 2017, is a revolutionary use of technology in healthcare that empowers people to make knowledgeable decisions regarding their well-being. Despite its advantages, our study included drawbacks, such as limited access to premium services and a small sample size. While highlighting unique characteristics, a comparative comparison with similar applications such as Clue and Glow confirmed Flo's outstanding AI integration for individualized healthcare. All things considered, Flo is a prime example of how AI can be used to tackle intricate biological processes, giving consumers the ability to efficiently control their reproductive health and opening the door for improvements in individualized medical technology.

Keywords: Flo, period-tracking app, period symptoms, women’s health, machinery

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Authors: N. Songumpai, W. Sumranwanich, S. Chatmaneerungcharoen

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This research aims to study the understanding of 8 aspects of nature of science (NOS). The research participants were 39 General Science student teachers who were selected by purposive sampling. In 2015 academic year, they enrolled in the course of Science Education Learning Management. Qualitative research was used as research methodology to understand how the student teachers propose on NOS. The research instruments consisted of open-ended questionnaires and semi-structure interviews that were used to assess students’ understanding of NOS. Research data was collected by 8 items- questionnaire and was categorized into students’ understanding of NOS, which consisted of complete understanding (CU), partial understanding (PU), misunderstanding (MU) and no understanding (NU). The findings reveal the majority of students’ misunderstanding of NOS regarding the aspects of theory and law(89.7%), scientific method(61.5%) and empirical evidence(15.4%) respectively. From the interview data, the student teachers present their misconceptions of NOS that indicate about theory and law cannot change; science knowledge is gained through experiment only (step by step); science is the things that are around humans. These results suggest that for effective science teacher education, the composition of design of NOS course needs to be considered. Therefore, teachers’ understanding of NOS is necessary to integrate into professional development program/course for empowering student teachers to begin their careers as strong science teachers in schools.

Keywords: nature of science, student teacher, no understanding, misunderstanding, partial understanding, complete understanding

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Authors: Simiao Ren, En Wei

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Drowning is a significant safety issue worldwide, and a robust computer vision-based alert system can easily prevent such tragedies in swimming pools. However, due to domain shift caused by the visual gap (potentially due to lighting, indoor scene change, pool floor color etc.) between the training swimming pool and the test swimming pool, the robustness of such algorithms has been questionable. The annotation cost for labeling each new swimming pool is too expensive for mass adoption of such a technique. To address this issue, we propose a domain-aware data augmentation pipeline based on Gaussian Poisson Generative Adversarial Network (GP-GAN). Combined with YOLOv8, we demonstrate that such a domain adaptation technique can significantly improve the model performance (from 0.24 mAP to 0.82 mAP) on new test scenes. As the augmentation method only require background imagery from the new domain (no annotation needed), we believe this is a promising, practical route for preventing swimming pool drowning.

Keywords: computer vision, deep learning, YOLOv8, detection, swimming pool, drowning, domain adaptation, generative adversarial network, GAN, GP-GAN

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Authors: Djelloul Nedjai

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The issue of cultural awareness triggers many controversies, especially in a context where individuals do not share the same cultural backgrounds and characteristics. The Algerian context is no exception. It has been widely documented by the literature that culture remains essential in many domains. In higher education, for instance, culture plays a pivotal role in shaping individuals’ perceptions and attitudes. Henceforth, the current paper attempts to look at the perceptions of the British culture held by students engaged in learning English as a Foreign Language (EFL) at the department of English at Banta 2 University, Algeria. It also inquires into EFL students’ perceptions of British culture. To address the aforementioned research queries, a descriptive study has been carried out wherein a questionnaire of fifteen (15) items has been deployed to collect students’ attitudes and perceptions toward British culture. Results showcase that, indeed, EFL students of the department of English at Banta 2 University hold both positive and negative perceptions towards British culture at different levels. The explanation could relate to the student's lack of acquaintance with and awareness of British culture. Consequently, this paper is an attempt to address the issue of cultural awareness from the perspective of EFL students.

Keywords: British culture, cultural awareness, EFL students’ perceptions, higher education

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Authors: Kaleem Kashif, Tayyaba Anam, Yizhi Wu

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This paper introduces a methodology for advancing Italian speech vowels landmark detection within the distinctive feature-based speech recognition domain. Leveraging the legacy tool 'xkl' by integrating combined convolutional neural networks (CNNs) and recurrent neural networks (RNNs), the study presents a comprehensive enhancement to the 'xkl' legacy software. This integration incorporates re-assigned spectrogram methodologies, enabling meticulous acoustic analysis. Simultaneously, our proposed model, integrating combined CNNs and RNNs, demonstrates unprecedented precision and robustness in landmark detection. The augmentation of re-assigned spectrogram fusion within the 'xkl' software signifies a meticulous advancement, particularly enhancing precision related to vowel formant estimation. This augmentation catalyzes unparalleled accuracy in landmark detection, resulting in a substantial performance leap compared to conventional methods. The proposed model emerges as a state-of-the-art solution in the distinctive feature-based speech recognition systems domain. In the realm of deep learning, a synergistic integration of combined CNNs and RNNs is introduced, endowed with specialized temporal embeddings, harnessing self-attention mechanisms, and positional embeddings. The proposed model allows it to excel in capturing intricate dependencies within Italian speech vowels, rendering it highly adaptable and sophisticated in the distinctive feature domain. Furthermore, our advanced temporal modeling approach employs Bayesian temporal encoding, refining the measurement of inter-landmark intervals. Comparative analysis against state-of-the-art models reveals a substantial improvement in accuracy, highlighting the robustness and efficacy of the proposed methodology. Upon rigorous testing on a database (LaMIT) speech recorded in a silent room by four Italian native speakers, the landmark detector demonstrates exceptional performance, achieving a 95% true detection rate and a 10% false detection rate. A majority of missed landmarks were observed in proximity to reduced vowels. These promising results underscore the robust identifiability of landmarks within the speech waveform, establishing the feasibility of employing a landmark detector as a front end in a speech recognition system. The synergistic integration of re-assigned spectrogram fusion, CNNs, RNNs, and Bayesian temporal encoding not only signifies a significant advancement in Italian speech vowels landmark detection but also positions the proposed model as a leader in the field. The model offers distinct advantages, including unparalleled accuracy, adaptability, and sophistication, marking a milestone in the intersection of deep learning and distinctive feature-based speech recognition. This work contributes to the broader scientific community by presenting a methodologically rigorous framework for enhancing landmark detection accuracy in Italian speech vowels. The integration of cutting-edge techniques establishes a foundation for future advancements in speech signal processing, emphasizing the potential of the proposed model in practical applications across various domains requiring robust speech recognition systems.

Keywords: landmark detection, acoustic analysis, convolutional neural network, recurrent neural network

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Armijos-Orellana Ana, González-Calle María, Maldonado-Matute Juan, Guerrero-Maxi Pedro

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Nowadays, the digital economy represents a fundamental element to guarantee economic and social development, whose importance increased significantly with the arrival of the COVID-19 pandemic. However, despite the benefits it offers, it can also be detrimental to those developing countries characterized by a wide digital divide. It is for this reason that the objective of this research was to identify and describe the main characteristics, benefits, and obstacles of the digital economy for Latin American countries. Through a bibliographic review, using the analytical-synthetic method in the period 1995-2021, it was determined that the digital economy could give way to structural changes, reduce inequality, and promote processes of social inclusion, as well as promote the construction and participatory development of organizational structures and institutional capacities in Latin American countries. However, the results showed that the digital economy is still incipient in the region and at least three factors are needed to establish it: joint work between academia, the business sector and the State, greater emphasis on learning and application of digital transformation and the creation of policies that encourage the creation of digital organizations.

Keywords: developing countries, digital divide, digital economy, digital literacy, digital transformation

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Authors: Wisdom Robert Duruji

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Local farmers and fruit processors in developing countries of West Africa use different ripening agents to accelerate the ripening process of plantain and banana. This study reports on the influence of different ripening agents on the shelf-life and microbial load of organic and inorganic plantain (Musa paradisiaca) and banana (Musa sapientum) during ripening process and the health implication for food security in Nigeria. The experiment consisted of four treatments, namely: Calcium carbide, Irvingia gabonensis fruits, Newbouldia laevis leaves and a control, where no ripening agent was applied to the fingers of plantain and banana. The unripe and ripened plantain and banana were subjected to microbial analysis by isolating their micro flora (Bacteria, Yeast and Mould) using pour plate method. Microbes present in the samples were enumerated, characterized and classified to genera and species. The result indicated that the microbial load of inorganic plantain from (Urban day) open market in Ile-Ife increased from 8.00 for unripe to 12.11 cfu/g for ripened; and the microbial load of organic plantain from Obafemi Awolowo University Teaching and Research Farm (OAUTRF) increased from 6.00 for unripe to 11.60 cfu/g for ripened. Also, the microbial load of inorganic banana from (Urban day) open market in Ile-Ife increased from 8.00 for unripe to 11.50 cfu/g for ripened; while the microbial load of organic banana from OAUTRF increased from 6.50 for unripe to 9.40 cfu/g for ripened. The microbial effects of the ripening agents increased from 10.00 for control to 16.00 cfu/g for treated (ripened) organic and inorganic plantain; while that of organic and inorganic banana increased from 7.50 for control to 14.50 cfu/g for ripened. Visual observation for the presence of fungal colonies and deterioration rates were monitored till seven days after the plantain and banana fingers have fully ripened. Inorganic plantain and banana from (Urban day) open market in Ile-Ife are more contaminated than organic plantain and banana fingers from OAUTRF. The ripening accelerators reduced the shelf life, increased senescence, and microbial load of plantain and banana. This study concluded that organic Agriculture is better and microbial friendlier than inorganic farming.

Keywords: organic agriculture, food security, Musaceae, calcium carbide, Irvingia gabonensis, Newbouldia laevis

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Authors: Madara Apsalone

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Knowledge management and innovation is key to competitive advantage and sustainable business development in advanced economies. Small and medium-sized enterprises (SMEs) have lower capacity and more constrained resources for long-term and high-uncertainty research and development investments. At the same time, SMEs can implement organizational innovation to improve their performance and further foster other types of innovation. The purpose of this study is to analyze, how socio-cultural factors such as shared values, organizational behaviors, work organization and decision making processes can influence knowledge management and help to develop organizational innovation via an empirical study. Surveying 600 SMEs in Latvia, the author explores the contribution of different socio-cultural factors to organizational innovation and the role of knowledge management and organizational learning in this process. A conceptual model, explaining the impact of organizational team, development, result-orientation and structure is created. The study also proposes insights that contribute to theoretical and practical discussions on fostering innovation of small businesses in small economies.

Keywords: knowledge management, organizational innovation, small and medium-sized enterprises, socio-cultural factors

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Authors: Anne Eugenia Wright

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This study examines issues in accessibility to maritime cultural heritage. Using the Pillar Dollar Wreck in Biscayne National Park, Florida, this study presents an approach to public outreach based on the concept of Design for All. Design for All advocates creating products that are accessible and functional for all users, including those with visual, hearing, learning, mobility, or economic impairments. As a part of this study, a small exhibit was created that uses 3D products as a way to bring maritime cultural heritage to the public. It was presented to the public at East Carolina University’s Joyner Library. Additionally, this study presents a methodology for 3D printing scaled photogrammetry models of archaeological sites in full color. This methodology can be used to present a realistic depiction of underwater archaeological sites to those who are incapable of accessing them in the water. Additionally, this methodology can be used to present underwater archaeological sites that are inaccessible to the public due to conditions such as visibility, depth, or protected status. This study presents a practical use for 3D photogrammetry models, as well as an accessibility strategy to expand the outreach potential for maritime archaeology.

Keywords: Underwater Archaeology, 3D Printing, Photogrammetry, Design for All

Procedia PDF Downloads 148

Authors: Tawfik Thelaidjia, Salah Chenikher

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Bearing fault diagnosis has attracted significant attention over the past few decades. It consists of two major parts: vibration signal feature extraction and condition classification for the extracted features. In this paper, feature extraction from faulty bearing vibration signals is performed by a combination of the signal’s Kurtosis and features obtained through the preprocessing of the vibration signal samples using Db2 discrete wavelet transform at the fifth level of decomposition. In this way, a 7-dimensional vector of the vibration signal feature is obtained. After feature extraction from vibration signal, the support vector machine (SVM) was applied to automate the fault diagnosis procedure. To improve the classification accuracy for bearing fault prediction, particle swarm optimization (PSO) is employed to simultaneously optimize the SVM kernel function parameter and the penalty parameter. The results have shown feasibility and effectiveness of the proposed approach

Keywords: condition monitoring, discrete wavelet transform, fault diagnosis, kurtosis, machine learning, particle swarm optimization, roller bearing, rotating machines, support vector machine, vibration measurement

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Authors: Ali Babajanzade, Hossein Bozorgian

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Cognitive load plays an important role in learning in general and L2 listening comprehension in particular. This study is an attempt to investigate the effect of metacognitive strategy intervention through dialogic interaction (MSIDI) on L2 listeners’ cognitive load. A mixed-method design with 50 participants of male and female Iranian lower-intermediate learners between 20 to 25 years of age was used. An experimental group (n=25) received weekly interventions based on metacognitive strategy intervention through dialogic interaction for ten sessions. The second group, which was control (n=25), had the same listening samples with the regular procedure without a metacognitive intervention program in each session. The study used three different instruments: a) a modified version of the cognitive load questionnaire, b) digit span tests, and c) focused group interviews to investigate listeners’ level of cognitive load throughout the process. Results testified not only improvements in listening comprehension in MSIDI but a radical shift of cognitive load rate within this group. In other words, listeners experienced a lower level of cognitive load in MSIDI in comparison with their peers in the control group.

Keywords: cognitive load theory, human mental functioning, metacognitive theory, listening comprehension, sociocultural theory

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Authors: Zheng Zhihao

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Recently, Knowledge Graph Framework Network (KGCN) has developed powerful capabilities in knowledge representation and reasoning tasks. However, traditional KGCN often uses a fixed weight mechanism when aggregating information, failing to make full use of rich structural information, resulting in a certain expression ability of node representation, and easily causing over-smoothing problems. In order to solve these challenges, the paper proposes an new graph neural network model called KGCN-STAR (Knowledge Graph Convolutional Network with Structural Adaptive Receptive Fields). This model dynamically adjusts the perception of each node by introducing a structural adaptive receptive field. wild range, and a subgraph aggregator is designed to capture local structural information more effectively. Experimental results show that KGCN-STAR shows significant performance improvement on multiple knowledge graph data sets, especially showing considerable capabilities in the task of representation learning of complex structures.

Keywords: knowledge graph, graph neural networks, structural adaptive receptive fields, information aggregation

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

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We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

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Authors: Sobhy Fathy A. Hashesh

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The study was carried out in the High School Classes of Andalus Private Schools, boys section, using control and experimental groups that were randomly assigned. The study investigated the effect of Al-Andalus Improvement Model (AIM) on the development of students’ skills acquiring. The society of the study composed of Al-Andalus Private Schools, high school students, boys Section (N=700), while the sample of the study composed of four randomly assigned groups two groups of teachers (N=16) and two groups of students (N=42) with one experimental group and one control group for teachers and their students respectively. The study followed the quantitative and qualitative approaches in collecting and analyzing data to investigate the study hypotheses. Results of the study revealed that there were significant statistical differences in teachers’ performances and students' skills acquiring for the favor of the experimental groups and there was a strong correlation between the teachers performances and the students skills acquiring. The study recommended the implementation of the AIM model for the sake of teachers performances and students’ learning outcomes.

Keywords: AIM, improvement model, Classera, Al-Andalus Improvement Model.

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Authors: Farshad Zeinali, Sajedeh Norouzi, Nader Mokari, Eduard Jorswieck

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The capacity of fifth-generation (5G) vehicle-to-everything (V2X) networks poses significant challenges. To ad- dress this challenge, this paper utilizes New Radio (NR) and New Radio Unlicensed (NR-U) networks to develop a heterogeneous vehicular network (HetNet). We propose a new framework, named joint BS assignment and resource allocation (JBSRA) for mobile V2X users and also consider coexistence schemes based on flexible duty cycle (DC) mechanism for unlicensed bands. Our objective is to maximize the average throughput of vehicles while guaranteeing the WiFi users' throughput. In simulations based on deep reinforcement learning (DRL) algorithms such as deep deterministic policy gradient (DDPG) and deep Q network (DQN), our proposed framework outperforms existing solutions that rely on fixed DC or schemes without consideration of unlicensed bands.

Keywords: vehicle-to-everything (V2X), resource allocation, BS assignment, new radio (NR), new radio unlicensed (NR-U), coexistence NR-U and WiFi, deep deterministic policy gradient (DDPG), deep Q-network (DQN), joint BS assignment and resource allocation (JBSRA), duty cycle mechanism

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Authors: Alexander Goncharenko, Andrey Denisov, Sergey Alyamkin, Evgeny Terentev

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The neural network quantization is highly desired procedure to perform before running neural networks on mobile devices. Quantization without fine-tuning leads to accuracy drop of the model, whereas commonly used training with quantization is done on the full set of the labeled data and therefore is both time- and resource-consuming. Real life applications require simplification and acceleration of quantization procedure that will maintain accuracy of full-precision neural network, especially for modern mobile neural network architectures like Mobilenet-v1, MobileNet-v2 and MNAS. Here we present a method to significantly optimize training with quantization procedure by introducing the trained scale factors for discretization thresholds that are separate for each filter. Using the proposed technique, we quantize the modern mobile architectures of neural networks with the set of train data of only ∼ 10% of the total ImageNet 2012 sample. Such reduction of train dataset size and small number of trainable parameters allow to fine-tune the network for several hours while maintaining the high accuracy of quantized model (accuracy drop was less than 0.5%). Ready-for-use models and code are available in the GitHub repository.

Keywords: distillation, machine learning, neural networks, quantization

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Authors: Joanna Estkowska

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Sensory integration methods are very useful and improve daily functioning autistic and mentally disabled children. Autism is a neurobiological disorder that impairs one's ability to communicate with and relate to others as well as their sensory system. Children with autism, even highly functioning kids, can find it difficult to process language with surrounding noise or smells. They are hypersensitive to things we can ignore such as sight, sounds and touch. Adolescents with highly functioning autism or Asperger Syndrome can study Science and Math but the social aspect is difficult for them. Nature science is an area of study that attracts many of these kids. It is a systematic field in which the children can focus on a small aspect. If you follow these rules you can come up with an expected result. Sensory integration program and systematic classroom observation are quantitative methods of measuring classroom functioning and behaviors from direct observations. These methods specify both the events and behaviors that are to be observed and how they are to be recorded. Our students with and without autism attended the lessons in the classroom of nature science in the school and in the laboratory of University of Science and Technology in Bydgoszcz. The aim of this study is investigation the effects of sensory integration methods in teaching to students with autism. They were observed during experimental lessons in the classroom and in the laboratory. Their physical characteristics, sensory dysfunction, and behavior in class were taken into consideration by comparing their similarities and differences. In the chemistry classroom, every autistic student is paired with a mentor from their school. In the laboratory, the children are expected to wear goggles, gloves and a lab coat. The chemistry classes in the laboratory were held for four hours with a lunch break, and according to the assistants, the children were engaged the whole time. In classroom of nature science, the students are encouraged to use the interactive exhibition of chemical, physical and mathematical models constructed by the author of this paper. Our students with and without autism attended the lessons in those laboratories. The teacher's goals are: to assist the child in inhibiting and modulating sensory information and support the child in processing a response to sensory stimulation.

Keywords: autism spectrum disorder, science education, sensory integration techniques, student with special educational needs

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Authors: Maaly Jarrah

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There is no doubt that reflective practice has become a stable component in continuous professional development (CPD) courses around the world for the purpose of promoting teacher development, meaningful learning, and deliberate teacher personal and professional growth. However, while there is much research on the benefits of integrating reflective practice in teacher CPD courses, not enough research explores EFL teachers’ experiences with engagement in reflective practice in the CPD from their own perspectives. This research employed a case study approach to explore the experience of 7 EFL teachers with engaging in reflective practice in a CPD course that took place in Kuwait.The participating EFL teachers engaged in collaborative dialogue reflections and completed reflection journal entries as part of the course. Data was collected through semi-structured interviews and analyzed thematically. Findings indicate that the participating teachers’ positive experience with reflective practice is associated with their engagement in collaborative dialogue reflections, while challenges and negative feelings are associated with writing their reflection journal entries. Accordingly, the study offers recommendations for CPD courses to help improve EFL teachers’ experiences with engagement in reflective practice.

Keywords: Collaborative dialogue reflections, continuous professional development, EFL teachers, reflection journals, teacher reflective practice

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Authors: Yi-Ping Lo, Shi-Yao Wei, Chih-Chun Ma

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Since Google launched Google Glass in 2012, numbers of commercial wearable devices were released, such as smart belt, smart band, smart shoes, smart clothes ... etc. However, most of these devices perform as sensors to show the readings of measurements and few of them provide the interactive feedback to the user. Furthermore, these devices are single task devices which are not able to communicate with each other. In this paper a new health promotion system, Ubiquitous Life People Informatics Engine (U-Life PIE), will be presented. This engine consists of People Informatics Engine (PIE) and the interactive user interface. PIE collects all the data from the compatible devices, analyzes this data comprehensively and communicates between devices via various application programming interfaces. All the data and informations are stored on the PIE unit, therefore, the user is able to view the instant and historical data on their mobile devices any time. It also provides the real-time hands-free feedback and instructions through the user interface visually, acoustically and tactilely. These feedback and instructions suggest the user to adjust their posture or habits in order to avoid the physical injuries and prevent illness.

Keywords: machine learning, wearable devices, user interface, user experience, internet of things

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Authors: Per Blomqvist

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This study is part of a larger research project on creativity and writing cultures in upper secondary schools in Sweden, with the purpose of exploring how formative assessment practices can be developed to better support students' writing of subject-specific texts. The purpose of the study is to shed light on how writing has changed over time in the subjects of Social Studies and Swedish, especially regarding changes in the formative assessment practice in relation to students opportunities to take part in creative writing processes that can develop their subject specific-writing. Theoretically, the study is based on concepts and models concerning creativity, writing instructions and formative assessment, especially regarding scaffolding in relation to the development of students' subject-specific writing. The empirical data consists of video recordings of teacher groups' conversations from five upper secondary schools in Sweden, compromising a total of twenty teachers. The conversations were conducted as so-called collective remembering interviews, a method to stimulate the participants' memory through social interaction, and focused on addressing issues on how writing assessment has changed over time. Topic analysis was used to analyze the conversations in order to identify common descriptions and expressions among the teachers in each group. The result highlights two different assessment practices that are described as giving students different opportunities to take part in creative writing processes to develop their writing of subject-specific texts. One of the assessment practices is characterized by teachers focusing on explaining to the students what the grading criteria mean and showing sample texts that correspond to a certain grade. The teachers describe that this assessment practice has led to a formalized, instrumental and product-oriented writing culture that has negative consequences for the student's development of their subject-specific writing, which often lacks independent reasoning, own conclusions and understanding of concepts. The other assessment practice is characterized by students examining text qualities and discussing a variety of sample texts to understand what different texts require. These teachers describe the assessment practice as an exploratory work that leads to more creative writing processes where the students gradually deepen their understanding of subject-specific texts and develop their writing.

Keywords: teaching for creativity, writing processes, formative assessment, subject-specific writing

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Authors: Raghad Dwaik

Abstract:

It is well known in language acquisition literature that a mere understanding of a reading text is not enough to help students build proficiency in comprehension. Students should rather follow understanding by attempting to express what has been understood by pushing their competence to the limit. Learners' attempt to push their competence was given the term "comprehensible output" by Swain (1985). Teachers in large classes, however, find it sometimes difficult to give all students a chance to communicate their views or to share their ideas during the short class time. In most cases, students who are outgoing dominate class discussion and get more opportunities for practice which leads to ignoring the shy students totally while helping the good ones become better. This paper presents the idea of using Google Classroom features of posting and commenting to allow students who hesitate to participate in class discussions about a reading text to write their views on the wall of a Google Classroom and share them later after they have received feedback and comments from classmates. Such attempts lead to developing their proficiency through additional practice in comprehensible output and to enhancing their confidence in themselves and their views. It was found that virtual classroom interaction would help students maintain vocabulary, use more complex structures and focus on meaning besides form.

Keywords: learning groups, reading TESOL, Google Classroom, comprehensible output

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Authors: S. Yussuf Abdulmaliq

Abstract:

Experiment was conducted for two years (2013 and 2014) at Ibrahim Badamasi Babangida University, Lapai, Teaching and Research Farm to study the effects of soil organic amendment types and rates on soil chemical fertility improvement, growth and yield of Amarathus cruentus in the southern guinea savannah, lapai, Niger state, Nigeria. Soil and manure samples were collected and analysed for physical and chemical components. The experiments were laid out in 3 x 4 factorial in a randomized complete block design (RCBD). Consisting of three (3) levels of soil amendment types (Poultry manure, goat manure and cowdung) and four (4) levels of amendment rates (0, 6, 12 and 18 t ha-1). Data collected include plant height/plant (cm), number of leaves/plant, leaf area/ plant (cm2) at 2, 4, 6 and 8WAT, fresh vegetable yield/plant, fresh vegetable yield/plot and fresh vegetable yield in tons ha-1. The result obtained showed that, Amaranthus cruentus height, number of leaves and leaf area were not significantly affected by the type of organic amendment and rates at 2WAT in 2013 and 2014 cropping seasons. However, at 4, 6 and 8 WAT, significant differences were observed among the types of amendment and their rates. Application of poultry manure as soil amendment supported taller, large number of leaves and wider leaf area, and higher marketable vegetable yield in 2013 and 2014 cropping seasons (Pα 0.05) which was closely followed by goat manure in the two (2) cropping seasons. In addition, the application of 18 t ha-1 was superior to 12, 6 and the control by producing tallest amaranthus plants, higher number of leaves, wider leaf area and higher marketable vegetable yield in 2013 and 2014 cropping seasons (Pα 0.05). In conclusion, the use of 18 t ha-1poultry manure is therefore recommended as soil amendment for Amaranthus cruentus in southern guinea savannah of Nigeria.

Keywords: Amaranthus cruentus, cowdung, goat manure, poultry manure, soil amendment

Procedia PDF Downloads 372

Authors: Tharwat El-Sakran

Abstract:

The linguistic choices accident news reporters make when reporting killing cases within family circles aid in augmenting the wrath readers feel towards the perpetrators. Undoubtedly, when killers or murderers are labelled with particular words, prospective readers will associate them with the cultural connotations and emotions, whether positive or negative, attached to those words. One of these strategies is the use of kinship terms to anaphorically or cataphorically refer to the defendants. While some articles opt for using the killer’s name, others make use of other kinship labels such as “the mother,” “the father,” “the step-father, and “the step-mother.” The preference for proper nouns over kinship terms and vice versa can be indicative of some of the underlying implications that the article writer may be trying to make about either the status of the killer or the overall incident circumstances. This research examines how the use of referential kinship labels could point to hidden and shared connotations between writers and their prospective readers. This study examined seventy newspaper articles from English-medium publications based in the United Arab Emirates (UAE), the USA, and several other countries. Some of these articles make use of proper nouns referring to the individual directly by name, whereas others refer to individuals based on their kinship relation with the victim or by their occupational status. Furthermore, information was collected from two hundred fifty-one students at several UAE-based universities by asking them what certain kinship words meant to them. The survey questions allowed for real insight into some of the most prevalent interpretations attached to kinship labels and the possible implications for preferring kinship terms over occupational labels and persons’ proper names. Results indicate that newspaper writers employ kinship labels to inspire an emotion in their future readers’ reactions that may not be achieved through the use of the person’s proper name(s). Additionally, respondents to the survey believe that the use of kinship nouns like “mother,” “father,” “step-mother,” and “step-father” tends to inspire a stronger emotional response, as they are almost always associated with particular behavioral cultural codes and conventions. The study concludes with recommendations for teaching the grammar of English words to EFL and mass communication students and with suggestions for translation theorists and further research.

Keywords: kinship terms, accident reports, cultural connotations, translation of kinship terms

Procedia PDF Downloads 140

Authors: Yvonne Kainuku, Wendy Trimmer

Abstract:

A critical element in closing the gaps in health disparities is the presence of a culturally appropriate health workforce. This study presents one of the findings from a qualitative study that explored the lived experiences of Cook Islands peoples during their three-year nursing training within a Bachelor of Nursing Pacific (BNP) programme in Aotearoa NZ. The study utilized both qualitative and context-specific methods; these included the Tivaevae Research Model and Qualitative Inquiry. The aim of the research was to collect stories from registered nurses about their experiences of culturally responsive pedagogy and their connection to content relating to Pacific world views and Pacific ways of knowing while they were students. Further to this, the researcher sought to recognize factors that supported the participant's successful completion of becoming a registered nurse. This study will introduce the theme of Tiaki moemoeā (dream keeper), identifying essential elements that engage learners along their journey. The various features that define the theme Tiaki moemoeā (dream keeper) have the potential to contribute to transformational change in nursing education training in Aotearoa, New Zealand.

Keywords: education, nursing, pacific, pedagogy

Procedia PDF Downloads 57