Search results for: teaching report writing for innovative learning

Authors: Aaron Kim, Nydia Hernandez

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Despite the known deficits in sleep duration among adolescents and the increasing prevalence of substance use behaviors among this group, relatively little is known about how insufficient sleep is related to various substance use behaviors and the underlying mechanisms. Informed by the literature suggesting the predictive role of insufficient sleep for substance use and depressive symptoms, we hypothesized that adolescents who lack sufficient sleep during school nights would report a higher level of depressive symptoms and substance use than their counterparts with sufficient sleep. We also hypothesized that depressive symptoms would explain the association of insufficient sleep with substance use, suggesting that mental health plays an important role as a mechanism between insufficient sleep and substance use. This study used the data drawn from the 2019 Youth Risk Behavior Surveillance System Data, which includes a nationally representative sample of U.S. high school students (N=13,677, 49.4% Female, 9th-12th graders). Self-report measures of insufficient sleep (sleeping<7 h on an average school night), depressive symptoms (yes/no), any past 30-day use of cigarette (yes/no), e-cigarette (yes/no), alcohol (yes/no), and marijuana (yes/no). Among the total sample, 47.9% of students reported that they did not have sufficient sleep on school nights, indicating sleeping less than 7 hours. Regarding depressive symptoms, 36.7% of students reported feeling sad or hopeless almost every day for two weeks or more in a row during the past 12 months. Also, the percentages of students who reported one or more times of cigarette use, e-cigarette use, alcohol use, and marijuana use in the past month were 5.32%, 30.11%, 26.83%, and 21.65%, respectively. For bivariate associations among these study variables, insufficient sleep was positively associated with other variables: depressive symptoms (r=.08, p<.001), cigarette use (r=.03, p<.001), e-cigarette use (r=.04, p<.001), alcohol use (r=.07, p<.001), and marijuana use (r=.08, p<.001). After controlling for students’ characteristics (i.e., age, gender, race/ethnicity, grades), sleeping less than 7 hours on school nights (vs. sleeping more than 7 hours) was significantly associated with the past 30-day use of alcohol and marijuana, whereas cigarette and e-cigarette uses were not. That is, the students who reported having an insufficient sleep on school nights had higher odds of alcohol (Odds Ratio [OR]=1.15, 95% Confidence Interval [CI]=1.014-1.301) and marijuana use (OR=1.36, 95% CI=1.132-1.543). In a subsequent analysis including depressive symptoms together with insufficient sleep, the association of insufficient sleep with alcohol use (OR=1.13, 95% CI=1.011-1.297) and marijuana use (OR=1.33, 95% CI=1.130-1.521) were attenuated and explained by depressive symptoms. Depressive symptoms significantly increased the odds of alcohol use by 32.2% (OR=1.32, 95% CI=1.131-1.557) and marijuana use by 202.1% (OR=2.02, 95% CI=1.672-2.502). These findings together suggest that insufficient sleep may contribute to increased risks of substance uses among adolescents. The current study also shows that psychological disorders of adolescents play important roles in understanding the association between insufficient sleep and substance use, suggesting insufficient sleep is related to substance use indirectly through depressive symptoms. This study indicates the importance of sleep deprivation among adolescents and screening for insufficient sleep in preventing/intervening in substance use.

Keywords: adolescents, depressive symptoms, sleep, substance use

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Authors: John D. Sanderson

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The popularity of American cinema worldwide has contributed to the development of sociolects related to specific film genres in other cultural contexts by means of screen translation, in many cases eluding norms of usage in the target language, a process whose result has come to be known as 'dubbese'. A consequence for the reception in countries where local audiovisual fiction consumption is far lower than American imported productions is that this linguistic construct is preferred, even though it differs from common everyday speech. The iconography of film genres such as science-fiction, western or sword-and-sandal films, for instance, generates linguistic expectations in international audiences who will accept more easily the sociolects assimilated by the continuous reception of American productions, even if the themes, locations, characters, etc., portrayed on screen may belong in origin to other cultures. And the non-normative language (e.g., calques, semantic loans) used in the preferred mode of linguistic transfer, whether it is translation for dubbing or subtitling, has diachronically evolved in many cases into a status of canonized sociolect, not only accepted but also required, by foreign audiences of American films. However, a remarkable step forward is taken when this typology of artificial linguistic constructs starts being used creatively by nationals of these target cultural contexts. In the case of Spain, the success of American sitcoms such as Friends in the 1990s led Spanish television scriptwriters to include in national productions lexical and syntactical indirect borrowings (Anglicisms not formally identifiable as such because they include elements from their own language) in order to target audiences of the former. However, this commercial strategy had already taken place decades earlier when Spain became a favored location for the shooting of foreign films in the early 1960s. The international popularity of the then newly developed sub-genre known as Spaghetti-Western encouraged Spanish investors to produce their own movies, and local scriptwriters made use of the dubbese developed nationally since the advent of sound in film instead of using normative language. As a result, direct Anglicisms, as well as lexical and syntactical borrowings made up the creative writing of these Spanish productions, which also became commercially successful. Interestingly enough, some of these films were even marketed in English-speaking countries as original westerns (some of the names of actors and directors were anglified to that purpose) dubbed into English. The analysis of these 'back translations' will also foreground some semantic distortions that arose in the process. In order to perform the research on these issues, a wide corpus of American films has been used, which chronologically range from Stagecoach (John Ford, 1939) to Django Unchained (Quentin Tarantino, 2012), together with a shorter corpus of Spanish films produced during the golden age of Spaghetti Westerns, from una tumba para el sheriff (Mario Caiano; in English lone and angry man, William Hawkins) to tu fosa será la exacta, amigo (Juan Bosch, 1972; in English my horse, my gun, your widow, John Wood). The methodology of analysis and the conclusions reached could be applied to other genres and other cultural contexts.

Keywords: dubbing, film genre, screen translation, sociolect

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Authors: Ayanori Sugiyama, Takahisa Hanei, Yasuhide Higo

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Domestic demand for the construction of tunnels has been increasing in recent years in Japan. To meet this demand, various construction materials and construction methods have been developed to attain higher strength, reduction of negative impact on the environment and improvement for working conditions. In this report, we would like to introduce the newly developed shotcrete with superior hardening properties which were tested through the actual machine scale and its workability and strength development were evaluated. As a result, this new tunnel construction method was found to achieve higher workability and quicker strength development in only a couple of minutes.

Keywords: accelerator, shotcrete, tunnel, high-strength

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: E. Güler, M. Güler

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We report some elastic quantities of cubic fluorite type plutonium dioxide (PuO2) with a recent EAM type interatomic potential through geometry optimization calculations. Typical cubic elastic constants, bulk modulus, shear modulus, young modulus and other related elastic quantities were calculated during present research. After present calculations, we have compared our results with the existing theoretical data of literature. Our results are consistent with previous theoretical findings of the considered parameters of PuO2.

Keywords: PuO2, elastic properties, bulk modulus, mechanical properties

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Authors: L. S. Chathurika

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Early prediction of student performance is an important factor to be gained academic excellence. Whatever the study stream in secondary education, students lay the foundation for higher studies during the first year of their degree or diploma program in Sri Lanka. The information technology (IT) field has certain improvements in the education domain by selecting specialization areas to show the talents and skills of students. These specializations can be software engineering, network administration, database administration, multimedia design, etc. After completing the first-year, students attempt to select the best path by considering numerous factors. The purpose of this experiment is to predict the best study path using machine learning algorithms. Five classification algorithms: decision tree, support vector machine, artificial neural network, Naïve Bayes, and logistic regression are selected and tested. The support vector machine obtained the highest accuracy, 82.4%. Then affecting features are recognized to select the best study path.

Keywords: algorithm, classification, evaluation, features, testing, training

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Authors: S. Chee Choy, Pauline Swee Choo Goh, Yow Lin Liew

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The purpose of this study is to evaluate the English version and a Malay translation of the 21-item Learner Awareness Questionnaire for its application to assess student learning in higher education. The Learner Awareness Questionnaire, originally written in English, is a quantitative measure of how and why students learn. The questionnaire gives an indication of the process and motives to learn using four scales: survival, establishing stability, approval, and loving to learn. Data in the present study came from 680 university students enrolled in various programs in Malaysia. The Malay version of the questionnaire supported a similar four-factor structure and internal consistency to the English version. The four factors of the Malay version also showed moderate to strong correlations with those of the English versions. The results suggest that the Malay version of the questionnaire is similar to the English version. However, further refinement for the questions is needed to strengthen the correlations between the two questionnaires.

Keywords: student learning, learner awareness, questionnaire development, instrument validation

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Authors: Tso Sheng-Yang, Wang Tien-Ni

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Introduction and Purpose: Previous researchers have documented children with ASD (Autism Spectrum Disorders) prefer to escaping internal privates and external privates when they face tough conditions they can’t control or they don’t like.Especially, when children with ASD need to learn challenging tasks, such us Chinese language, their inappropriate behaviors will occur apparently. Recently, researchers apply positive behavior support strategies for children with ASD to enhance their self-efficacy and therefore to reduce their adverse behaviors. Thus, the purpose of this research was to design a series of lecture based on art therapy and to evaluate its effectiveness on the child’s self-efficacy. Method: This research was the single-case design study that recruited a high school boy with ASD. Whole research can be separated into three conditions. First, baseline condition, before the class started and ended, the researcher collected participant’s competencies of self-efficacy every session. In intervention condition, the research used dramatic conventions to teach the child in Chinese language twice a week.When the data was stable across three documents, the period entered to the maintenance condition. In maintenance condition, the researcher only collected the score of self-efficacynot to do other interventions five times a month to represent the effectiveness of maintenance.The time and frequency of data collection among three conditions are identical. Concerning art therapy, the common approach, e.g., music, drama, or painting is to use art medium as independent variable. Due to visual cues of art medium, the ASD can be easily to gain joint attention with teachers. Besides, the ASD have difficulties in understanding abstract objectives Thus, using the drama convention is helpful for the ASD to construct the environment and understand the context of Classical Chinese. By real operation, it can improve the ASD to understand the context and construct prior knowledge. Result: Bassd on the 10-points Likert scale and research, we product following results. (a) In baseline condition, the average score of self-efficacyis 1.12 points, rangedfrom 1 to 2 points, and the level change is 0 point. (b)In intervention condition, the average score of self-efficacy is 7.66 points rangedfrom 7 to 9 points, and the level change is 1 point. (c)In maintenance condition, the average score of self-efficacy is 6.66 points rangedfrom 6 to 7 points, and the level change is 1 point. Concerning immediacy of change, between baseline and intervention conditions, the difference is 5 points. No overlaps were found between these two conditions. Conclusion: According to the result, we find that it is effective that using dramatic conventions a s teaching strategies to teach children with ASD. The result presents the score of self-efficacyimmediately enhances when the dramatic conventions commences. Thus, we suggest the teacher can use this approach and adjust, based on the student’s trait, to teach the ASD on difficult task.

Keywords: dramatic conventions, autism spectrum disorder, slef-efficacy, teaching strategy

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Authors: S. Brahmi, S. Aitouche, M. D. Mouss

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Every modern company should measure the value of its intellectual capital and to report to complement the traditional annual balance sheets. The purpose of this work is to measure the intellectual capital in an Algerian company (or production system) using the Weightless Wealth Tool Kit (WWTK). The results of the measurement of intellectual capital are supplemented by traditional financial ratios. The measurement was applied to the National Company of Wells Services (ENSP) in Hassi Messaoud city, in the south of Algeria. We calculated the intellectual capital (intangible resources) of the ENSP to help the organization to better capitalize on its potential of workers and their know-how. The intangible value of the ENSP is evaluated at 16,936,173,345 DA in 2015.

Keywords: financial valuation, intangible capital, intellectual capital, intellectual capital measurement

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Authors: Justin D. Olmanson, Fitsum Abebe, Valerie Jones, Eric Kyle, Xianquan Liu, Katherine Robbins, Guieswende Rouamba

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The history of education technology--and designing, adapting, and adopting technologies for use in educational spaces--is nuanced, complex, and dynamic. Yet, despite a range of continually emerging technologies, the design and development process often yields results that appear quite similar in terms of affordances and interactions. Through this study we (1) verify the extent to which designs have been constrained, (2) consider what might account for it, and (3) offer a way forward in terms of how we might identify and strategically sidestep these influences--thereby increasing the diversity of our designs with a given technology or within a particular learning domain. We begin our inquiry from the perspective that a host of co-influencing elements, fields, and meta narratives converge on the education technology design process to exert a tangible, often homogenizing effect on the resultant designs. We identify several elements that influence design in often implicit or unquestioned ways (e.g. curriculum, learning theory, economics, learning context, pedagogy), we describe our methodology for identifying the elemental positionality embedded in a design, we direct our analysis to a particular subset of technologies in the field of literacy, and unpack our findings. Our early analysis suggests that the majority of education technologies designed for use/used in US public schools are heavily influenced by a handful of mainstream theories and meta narratives. These findings have implications for how we approach the education technology design process--which we use to suggest alternative methods for designing/ developing with emerging technologies. Our analytical process and re conceptualized design process hold the potential to diversify the ways emerging and established technologies get incorporated into our designs.

Keywords: curriculum, design, innovation, meta narratives

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Authors: Betty Kibirige

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Students entering the University of Zululand (UNIZULU) Science Faculty mostly come with skills that allow them to prepare for exams and pass them in order to satisfy requirements for entry into a tertiary Institution. Some students hail from deep rural schools with limited facilities, while others come from well-resourced schools. Personal experience has shown that it may take a student the whole time at a tertiary institution following the same skills as those acquired in high school as a sure means of entering the next level in their development, namely a postgraduate program. While it is apparent that at this point in human history, it is totally impossible to teach all the possible content in any one subject, many academics approach teaching and learning from the traditional point of view. It therefore became apparent to explore ways of developing a graduate that will be able to approach life with skills that allows them to navigate knowledge by applying conceptual and critical thinking skills. Recently, the Science Faculty at the University of Zululand introduced two Engineering programs. In an endeavour to approach the development of the Engineering graduate in this institution to be able to tackle problem-solving in the present-day excessive information availability, it became necessary to study and review approaches used by various academics in order to settle for a possible best approach to the challenge at hand. This paper focuses on the development of a deep rural child in a graduate with conceptual and critical thinking skills as major attributes possessed upon graduation. For this purpose, various approaches were studied. A combination of these approaches was repackaged to form an approach that may appear novel to UNIZULU and the rural child, especially for the Engineering discipline. The approach was checked by offering quiz questions to students participating in an engineering module, observing test scores in the targeted module and make comparative studies. Test results are discussed in the article. It was concluded that students’ graduate attributes could be tailored subconsciously to indeed include conceptual and critical thinking skills, but through more than one approach depending mainly on the student's high school background.

Keywords: graduate attributes, conceptual skills, critical thinking skills, traditional approach

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Authors: Joseph M. Rich, Vinay A. Duddalwar, Assad A. Oberai

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Prostate adenocarcinoma is the most common cancer in males, with osseous metastases as the commonest site of metastatic prostate carcinoma (mPC). Treatment monitoring is based on the evaluation and characterization of lesions on multiple imaging studies, including Computed Tomography (CT). Monitoring of the osseous disease burden, including follow-up of lesions and identification and characterization of new lesions, is a laborious task for radiologists. Deep learning algorithms are increasingly used to perform tasks such as identification and segmentation for osseous metastatic disease and provide accurate information regarding metastatic burden. Here, nnUNet was used to produce a model which can segment CT scan images of prostate adenocarcinoma vertebral bone metastatic lesions. nnUNet is an open-source Python package that adds optimizations to deep learning-based UNet architecture but has not been extensively combined with transfer learning techniques due to the absence of a readily available functionality of this method. The IRB-approved study data set includes imaging studies from patients with mPC who were enrolled in clinical trials at the University of Southern California (USC) Health Science Campus and Los Angeles County (LAC)/USC medical center. Manual segmentation of metastatic lesions was completed by an expert radiologist Dr. Vinay Duddalwar (20+ years in radiology and oncologic imaging), to serve as ground truths for the automated segmentation. Despite nnUNet’s success on some medical segmentation tasks, it only produced an average Dice Similarity Coefficient (DSC) of 0.31 on the USC dataset. DSC results fell in a bimodal distribution, with most scores falling either over 0.66 (reasonably accurate) or at 0 (no lesion detected). Applying more aggressive data augmentation techniques dropped the DSC to 0.15, and reducing the number of epochs reduced the DSC to below 0.1. Datasets have been identified for transfer learning, which involve balancing between size and similarity of the dataset. Identified datasets include the Pancreas data from the Medical Segmentation Decathlon, Pelvic Reference Data, and CT volumes with multiple organ segmentations (CT-ORG). Some of the challenges of producing an accurate model from the USC dataset include small dataset size (115 images), 2D data (as nnUNet generally performs better on 3D data), and the limited amount of public data capturing annotated CT images of bone lesions. Optimizations and improvements will be made by applying transfer learning and generative methods, including incorporating generative adversarial networks and diffusion models in order to augment the dataset. Performance with different libraries, including MONAI and custom architectures with Pytorch, will be compared. In the future, molecular correlations will be tracked with radiologic features for the purpose of multimodal composite biomarker identification. Once validated, these models will be incorporated into evaluation workflows to optimize radiologist evaluation. Our work demonstrates the challenges of applying automated image segmentation to small medical datasets and lays a foundation for techniques to improve performance. As machine learning models become increasingly incorporated into the workflow of radiologists, these findings will help improve the speed and accuracy of vertebral metastatic lesions detection.

Keywords: deep learning, image segmentation, medicine, nnUNet, prostate carcinoma, radiomics

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Authors: Maier Dorin, Maier Andreea

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Today, any organization - regardless of the specific activity - must be prepared to face continuous radical changes, innovation thus becoming a condition of survival in a globalized market. Not all managers have an overall view on the real size of necessary innovation potential. Unfortunately there is still no common (and correct) understanding of the term of innovation among managers. Moreover, not all managers are aware of the need for innovation. This article highlights and analyzes a series of models of innovation processes and their evolution. The models analyzed encompass both the strategic level and the operational one within an organization, indicating performance innovation on each landing. As the literature review shows, there are no easy answers to the innovation process as there are no shortcuts to great results. Successful companies do not have a silver innovative bullet - they do not get results by making one or few things better than others, they make everything better.

Keywords: innovation, innovation process, business success, models of innovation

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Authors: Anne Nicole Fuentes

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A 29 year old Gravida 1 Para 0 who presented at the hospital with a 5-week history of amenorrhea, abdominal pain and vaginal bleeding. Transvaginal ultrasound revealed 3 pathologic findings : Tuboovarian complex on the right adnexa, a complex mass indicative of an unruptured ectopic pregnancy and right ovarian new growth probably endometrioma. Pelvic laparotomy was done and histopathologic finding revealed tubal pregnancy, right and mature cystic teratoma of the right ovary. This case report demonstrates the importance of considering the coexistence of different gynecologic pathologies in the same patient and clinical importance of an accurate diagnostic evaluation.

Keywords: mature cystic teratoma, ectopic pregnancy, Tuboovarian abscess, bHCG

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Authors: D. K. Sreekantha, T. M. Girish, R. H. Fattepur

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In this article, we have given an overview of medical expert systems, which can be used for the developed of physicians in making decisions such as appropriate, prognostic, and therapeutic decisions which help to organize, store, and gives appropriate medical knowledge needed by physicians and practitioners during medical operations or further treatment. If they support the studies by using these systems, advanced tools in medicine will be developed in the future. New trends in the methodology of development of medical expert systems have also been discussed in this paper. So Authors would like to develop an innovative IT based solution to help doctors in rural areas to gain expertise in Medical Science for treating patients. This paper aims to survey the Soft Computing techniques in treating patient’s problems used throughout the world.

Keywords: expert system, fuzzy logic, knowledge base, soft computing, epilepsy

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Authors: Jacopo Baboni Schilingi

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We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication

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Authors: Oumaima Lahmar

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This paper aims to define a structured topography for finance researchers seeking to navigate the body of knowledge in their extrapolation of finance phenomena. To make sense of the body of knowledge in finance, a probabilistic topic modeling approach is applied on 6000 abstracts of academic articles published in three top journals in finance between 1976 and 2020. This approach combines both machine learning techniques and natural language processing to statistically identify the conjunctions between research articles and their shared topics described each by relevant keywords. The topic modeling analysis reveals 35 coherent topics that can well depict finance literature and provide a comprehensive structure for the ongoing research themes. Comparing the extracted topics to the Journal of Economic Literature (JEL) classification system, a significant similarity was highlighted between the characterizing keywords. On the other hand, we identify other topics that do not match the JEL classification despite being relevant in the finance literature.

Keywords: finance literature, textual analysis, topic modeling, perplexity

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Authors: Yuanchao Sang, Zhihao Gong, Longsheng Chen, Long Chen

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Clothing fashion represents a human’s aesthetic appreciation towards everyday outfits and appetite for fashion, and it reflects the development of status in society, humanity, and economics. However, modelling fashion by machine is extremely challenging because fashion is too abstract to be efficiently described by machines. Even human beings can hardly reach a consensus about fashion. In this paper, we are dedicated to answering a fundamental fashion-related problem: what image feature best describes clothing fashion? To address this issue, we have designed and evaluated various image features, ranging from traditional low-level hand-crafted features to mid-level style awareness features to various current popular deep neural network-based features, which have shown state-of-the-art performance in various vision tasks. In summary, we tested the following 9 feature representations: color, texture, shape, style, convolutional neural networks (CNNs), CNNs with distance metric learning (CNNs&DML), AutoEncoder, CNNs with multiple layer combination (CNNs&MLC) and CNNs with dynamic feature clustering (CNNs&DFC). Finally, we validated the performance of these features on two publicly available datasets. Quantitative and qualitative experimental results on both intra-domain and inter-domain fashion clothing image retrieval showed that deep learning based feature representations far outweigh traditional hand-crafted feature representation. Additionally, among all deep learning based methods, CNNs with explicit feature clustering performs best, which shows feature clustering is essential for discriminative fashion feature representation.

Keywords: convolutional neural network, feature representation, image processing, machine modelling

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Authors: Bharatendra Rai

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The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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Authors: Mahmoud Abdelrazig Mahmoud Barakat

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Achievement tests administered at national level play a significant role in the lives of test-takers as well as the whole society. This paper aims to investigate the effect of giving students a choice between two optional questions on their overall performance in a high stake achievement test for university admission. It is hypothesized that questions targeting writing-based productive skills and language system necessitate display of abilities which are different from fact-based questions designed around story content. The two items are assumed to reflect different constructs that require different criteria of assessment. Consequently, the student’s overall score is affected by the item they choose to answer, which might not be reflective of their real language abilities. An open-ended interview was carried out with ten teachers working with grade 3 students in model secondary schools to investigate the nature of the two test items and their impact on the student’s performance. The data has proved that giving choice in an achievement test generates different performances that are assessed differently. It is recommended that in order to address the question of fairness, it is important to clearly define and balance the construct of the items that affect the student’s choice and performance.

Keywords: achievement test, assessment, choice, fairness performance

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Authors: Lev Idels, Arcady Ponosov

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Stochastic fractional differential equations have recently attracted considerable attention, as they have been used to model real-world processes, which are subject to natural memory effects and measurement uncertainties. Compared to conventional hereditary differential equations, one of the advantages of fractional differential equations is related to more realistic geometric properties of their trajectories that do not intersect in the phase space. In this report, a Peano-like existence theorem for nonlinear stochastic fractional differential equations is proven under very general hypotheses. Several specific classes of equations are checked to satisfy these hypotheses, including delay equations driven by the fractional Brownian motion, stochastic fractional neutral equations and many others.

Keywords: delay equations, operator methods, stochastic noise, weak solutions

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Authors: My T. Truong

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Among various professional development (PD) options available for English as a second language (ESL) teachers, especially those at the tertiary level, research engagement has been recently recommended as an innovative model with a transformative force for both individual teachers’ PD and wider school improvement. Teachers who conduct research themselves tend to develop critical and analytical thinking about their instructional practices, and enhance their ability to make autonomous pedagogical judgments and decisions. With such capabilities, teacher researchers are thus more likely to contribute to curriculum innovation of their schools and improvement of the whole educational process. The extent to which ESL teachers are engaged in research, however, depends largely on their research motivation, which can not only decide teachers’ choice of a PD activity to pursue but also affect the degree and duration of effort they are willing to invest in pursuing it. To understand language teachers’ research practices, and to inform educational authorities about ways to promote research culture among their ESL teaching staff, it is therefore vital to investigate teachers’ research motivation. Despite its importance as such, this individual difference construct has not been paid due attention especially in the ESL contexts. To fill this gap, this study aims to explore Vietnamese tertiary ESL teachers’ motivations towards research. Guided by the self-determination theory and the process model of motivation, it investigates teachers’ initial motivations for conducting research, and the factors that sustained or degraded their motivation during the research engagement process. Adopting a qualitative case-study approach, the study collected longitudinal data via semi-structured interviews and guided diary entries from three ESL tertiary teachers who were conducting their own research project. The respondents attended two semi-structured interviews (one at the beginning of their project, and the other one three months afterwards); and wrote six guided diary entries between the two interviews. The results confirm the significant role motivation plays in driving teachers to initiate and maintain their participation in research, and challenge some common assumptions in teacher motivation literature. For instance, the quality of the past and actual research experience unsurprisingly emerged as an important factor that both motivated and demotivated teachers in their research engagement process. Unlike general suggestions in the motivation literature however, external demand was found in this study to be a critical motivation sustaining factor while intrinsic research interest actually did not suffice to help a teacher fulfil his research endeavor. With such findings, the study is expected to widen the motivational perspective in understanding language teacher research practice given the paucity of related studies. Practically, it is hoped to enable teacher educators, PD program designers and educational policy makers in Vietnam and similar contexts to approach the question of whether and how to promote research activities among ESL teachers feasibly. For practicing and in-service teachers, the findings may elucidate to them the motivational conditions in which they can be research engaged, and the motivational factors that might hinder or encourage them in so doing.

Keywords: teacher motivation, teacher professional development, teacher research engagement, English as a second language (ESL)

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Authors: Diwei Lin, Amanda Jia Hui Tan

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In 2012, testicular cancer was estimated to account for 940 disability adjusted life years in Australia; of these, 450 were years lost due to premature death and 500 were years of healthy life lost due to disease, disability or injury. Testicular choriocarcinoma is one of the rarest variants of testicular germ cell tumours, accounting for less than 1% of testicular germ cell tumours and only about 0.19% of all testicular tumours. Management involves radical orchiectomy followed by chemotherapy. Even then, the prognosis is extremely poor. This case report describes a 20-year-old male with pure testicular choriocarcinoma with pulmonary metastases.

Keywords: testicular cancer, choriocarcinoma, cryptorchidism, chemotherapy, metastatic testicular cancer

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Authors: Sara Blanc, José V. Benlloch-Dualde, Laura Grindei, Ana C. Torres, Angélica Monteiro

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This paper presents a study that leads a new experience by introducing digital learning applied to a case study focused on primary and secondary school garden-based education. The approach represents an example of interaction among different education and research agents at different countries and levels, such as universities, public and private research, and schools, to get involved in the implementation of education for sustainable development that will make students become more sensible to natural environment, more responsible for their consumption, more aware about waste reduction and recycling, more conscious of the sustainable use of natural resources and, at the same time, more ‘digitally competent’. The experience was designed attending to the European digital education context and OECD directives in transversal skills education. The paper presents the methodology carried out in the study as well as outcomes obtained from experience.

Keywords: school gardens, primary education, secondary education, science technology and innovation in education, digital learning, sustainable development goals, university, knowledge transference

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Authors: T. Rakhi, Thrivikram Shenoy

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Esophageal atresia is a disorder of maldevelopment of esophagus with or without a connection to the trachea. Radiological reviews are needed in consultation with the pediatric surgeon and neonatologist and we report a rare case of esophageal atresia associated with atrial septal defect-patent ductus arteriosus complex. A 2-day old female baby born at term, weighing 3.010kg, admitted to the Neonatal Intensive Care Unit with respiratory distress and excessive oral secretions. On examination, continuous murmur and cyanosis were seen. Esophageal atresia was suspected, after a failed attempt to pass a nasogastric tube. Chest radiograph showed coiling of the nasogastric tube and absent gas shadow in the abdomen. Echocardiography confirmed Patent Ductus Arteriosus with Atrial Septal Defect not in failure and was diagnosed with esophageal atresia with suspected fistula posted for surgical repair. After preliminary management with oxygenation, suctioning in prone position and antibiotics, investigations revealed Hb 17gms serum biochemistry, coagulation profile and C-Reactive Protein Test normal. The baby was premedicated with 5mcg of fentanyl and 100 mcg of midazolam and a rapid awake laryngoscopy was done to rule out difficult airway followed by induction with o2 air, sevo and atracurium 2 mg. Placement of a 3.5 tube was uneventful at first attempt and after confirming bilateral air entry positioned in the lateral position for Right thoracotomy. A pulse oximeter, Echocardiogram, Non-invasive Blood Pressure, temperature and a precordial stethoscope in left axilla were essential monitors. During thoracotomy, both the ends of the esophagus and the fistula could not be located after thorough search suggesting an on table finding of type A esophageal atresia. The baby was repositioned for gastrostomy, and cervical esophagostomy ventilated overnight and extubated uneventful. Absent gas shadow was overlooked and the purpose of this presentation is to create an awareness between the neonatologist, pediatric surgeons and anesthesiologist regarding variation of typing of Tracheoesophageal fistula pre and intraoperatively. A need for imaging modalities warranted for a definitive diagnosis in the presence of a gasless stomach.

Keywords: anesthetic, atrial septal defects, esophageal atresia, patent ductus arteriosus, perioperative, chest x-ray

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: C. N. Vanitha, M. Usha

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In a real world scenario, the viability of the sensor networks has been proved by standardizing the technologies. Wireless sensor networks are vulnerable to both electronic and physical security breaches because of their deployment in remote, distributed, and inaccessible locations. The compromised sensor nodes send malicious data to the base station, and thus, the total network effectiveness will possibly be compromised. To detect and seclude the Route modifiers, a neural network based Pattern Learning predictor (PLP) is presented. This algorithm senses data at any node on present and previous patterns obtained from the en-route nodes. The eminence of any node is upgraded by their predicted and reported patterns. This paper propounds a solution not only to detect the route modifiers, but also to seclude the malevolent nodes from the network. The simulation result proves the effective performance of the network by the presented methodology in terms of energy level, routing and various network conditions.

Keywords: neural networks, pattern learning, security, wireless sensor networks

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Authors: Awotidebe Taofeek, Oyinsuyi Oluwafunmbi

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Psychosocial factors play a significant role in physical activity participation in diseased conditions and the general population. However, little is known about the role of exercise self-efficacy (ESE), exercise perceived barriers (EPB), and social support (SOS) in patients with asthma. This study investigated the influence of psychosocial factors on physical activity participation in patients with asthma in ile-ife. This cross-sectional study involved 130 patients with asthma. They were recruited from the Chest Clinic of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife using purposive sampling technique. Ethical approval was obtained from the Ethics and Research Committee of the Obafemi Awolowo University Teaching Hospitals Complex, Ile-ife, Nigeria. Socio-demographic characteristics of respondents were recorded. Information on ESE, EPB, and SOS were obtained using Exercise Self-Efficacy, Exercise Benefit, and Barrier and Medical Outcome Social Support Scales respectively. Physical activity level was assessed in the last 7 days using international physical activity questionnaire. Descriptive and inferential statistics were used to analyze the data. Alpha level was set at p<0.5. The mean age of the respondents was 25.15 ± 9.38, and a majority, 110 (84.60%), engaged in low physical activity, 69(53%) had low exercise self-efficacy. However, less than two-third 80 (62.20%) reported high social support, with the majority of 95 (73.10%) reported high exercise perceived barriers. The means of ESE for male and femalerespondents were 29.01 ± 20.62 and 24.35 ± 17.36, respectively. The means of SOS formale and female respondents were 49.52 ± 22.22 and 61.87 ± 22.66, respectively. Themeans of EPB for male and female respondents were 53.37 ± 10.23 and 57.43 ± 9.65, respectively. The respondents were comparable in exercise self-efficacy and physicalactivity level (p>0.05). However, there were significant differences in social support (t=-2.791; p=0.006) and exercise perceived barriers (t=-2.108, p=0.037).Theresultsshowthattherewasasignificantrelationshipbetweenexerciseperceivedbarriersandlowphysicalactivitylevel(r=-0.216;p=0.023).TherewasasignificantassociationbetweenExerciseself-efficacyandmarried individuals(OR=0.967;95%CI=0.936-0.998;p= 0.037). Similarly, However,thereweresignificantassociationsbetweensocialsupport Andagegroup35-54years(OR=1.036;95%CI=1.007-1.067;p=0.014),females(OR= 1.024;95%CI=1.006;p=0.009)andmarriedindividuals(OR=1.049;95%CI=1.020-1.079. p=0.001).Therewasasignificantassociationbetweenexerciseperceivedbarriersand females(OR=1.043;95%CI=1.002-1.085;p=0.040).However, thereweresignificant associationsbetweenexerciseperceivedbarriersandoccupationgroup;civilservants (OR=1.092;95%CI=1.009-1.182;p=0.028),retiree(OR=1.092;95%CI=1.040-1.469;p= 0.016)andstudents(OR=1.110;95%CI=1.040;p=0.002). Inconclusion,agreaterpercentageofpatientswithasthmahadlowphysicalactivityleveland it was associatedwithhighexerciseperceivedbarriers,whileexerciseself-efficacyandsocialsupportwerenot.

Keywords: asthma, psychosocial factors, physical activity, physical fitness

Procedia PDF Downloads 115

Authors: Vijaya K. Narne, Gerard Loquet, Tobias Piechowiak, Dorte Hammershoi, Jesper H. Schmidt

Abstract:

BEAR, which stands for better hearing rehabilitation is a large-scale project in Denmark designed and executed by three national universities, three hospitals, and the hearing aid industry with the aim to improve hearing aid fitting. A total of 1963 hearing impaired people were included and were segmented into subgroups based on hearing-loss, demographics, audiological and questionnaires data (i.e., the speech, spatial and qualities of hearing scale [SSQ-12] and the International Outcome Inventory for Hearing-Aids [IOI-HA]). With the aim to provide a better hearing-aid fit to individual patients, we applied modern machine learning techniques with traditional audiograms rule-based systems. Results show that age, speech discrimination scores, and audiogram configurations were evolved as important parameters in characterizing sub-population from the data-set. The attempt to characterize sub-population reveal a clearer picture about the individual hearing difficulties encountered and the benefits derived from more individualized hearing aids.

Keywords: hearing loss, audiological data, machine learning, hearing aids

Procedia PDF Downloads 139

Authors: O. V. Vyazovska

Abstract:

Behavioral efficiency is one of the main principles to be successful in nature. Accuracy of visual discrimination is determined by the attention, learning experience, and memory. In the experimental condition, pigeons’ responses to visual stimuli presented on the screen of the monitor are behaviorally manifested by pecking or not pecking the stimulus, by the number of pecking, reaction time, etc. The higher the probability of rewarding is, the more likely pigeons will respond to the stimulus. We trained 8 pigeons (Columba livia) on a stagewise go/no-go visual discrimination task.16 visual stimuli were created from all possible combinations of four binary dimensions: brightness (dark/bright), size (large/small), line orientation (vertical/horizontal), and shape (circle/square). In the first stage, we presented S+ and 4 S-stimuli: the first that differed in all 4-dimensional values from S+, the second with brightness dimension sharing with S+, the third sharing brightness and orientation with S+, the fourth sharing brightness, orientation and size. Then all 16 stimuli were added. Pigeons rejected correctly 6-8 of 11 new added S-stimuli at the beginning of the second stage. The results revealed that pigeons’ behavior at the beginning of the second stage was controlled by probabilities of rewarding for 4 dimensions learned in the first stage. More or fewer mistakes with dimension discrimination at the beginning of the second stage depended on the number S- stimuli sharing the dimension with S+ in the first stage. A significant inverse correlation between the number of S- stimuli sharing dimension values with S+ in the first stage and the dimensional learning rate at the beginning of the second stage was found. Pigeons were more confident in discrimination of shape and size dimensions. They made mistakes at the beginning of the second stage, which were not associated with these dimensions. Thus, the received results help elucidate the principles of dimensional stimulus control during learning compound multidimensional visual stimuli.

Keywords: visual go/no go discrimination, selective attention, dimensional stimulus control, pigeon

Procedia PDF Downloads 127