Search results for: learning behaviour
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8726

Search results for: learning behaviour

3686 Water-in-Diesel Fuel Nanoemulsions Prepared by Modified Low Energy: Emulsion Drop Size and Stability, Physical Properties, and Emission Characteristics

Authors: M. R. Noor El-Din, Marwa R. Mishrif, R. E. Morsi, E. A. El-Sharaky, M. E. Haseeb, Rania T. M. Ghanem

Abstract:

This paper studies the physical and rheological behaviours of water/in/diesel fuel nanoemulsions prepared by modified low energy method. Twenty of water/in/diesel fuel nanoemulsions were prepared using mixed nonionic surfactants of sorbitan monooleate and polyoxyethylene sorbitan trioleate (MTS) at Hydrophilic-Lipophilic Balance (HLB) value of 10 and a working temperature of 20°C. The influence of the prepared nanoemulsions on the physical properties such as kinematic viscosity, density, and calorific value was studied. Also, nanoemulsion systems were subjected to rheological evaluation. The effect of water loading percentage (5, 6, 7, 8, 9 and 10 wt.%) on rheology was assessed at temperatures range from 20 to 60°C with temperature interval of 10 for time lapse 0, 1, 2 and 3 months, respectively. Results show that all of the sets nanoemulsions exhibited a Newtonian flow character of low-shear viscosity in the range of 132 up to 191 1/s, and followed by a shear-thinning region with yield value (Non-Newtonian behaviour) at high shear rate for all water ratios (5 to 10 wt.%) and at all test temperatures (20 to 60°C) for time ageing up to 3 months. Also, the viscosity/temperature relationship of all nanoemulsions fitted well Arrhenius equation with high correlation coefficients that ascertain their Newtonian behavior.

Keywords: alternative fuel, nanoemulsion, surfactant, diesel fuel

Procedia PDF Downloads 303
3685 Hygrothermal Properties of Raw Earth Material

Authors: Ichrak Hamrouni, Tariq Ouahbi, Natalija Lhuissier, Saïd Taibi, Mehrez Jemai, Olivier Crumeyrolle, Hatem Zenzri

Abstract:

Raw earth is the oldest building technique used for over 11 centuries, thanks to its various benefits. The most known raw earth construction technics are compressed earth blocks, rammed earth, raw earth concrete, and daub. The raw earth can be stabilized with hydraulic binders, mixed by fibers, or hyper-compacted in order to improve its mechanical behaviour. Moreover, raw earth is characterized by a low thermal conductivity what make it a good thermal insulator, and it has a very important capacity to condense and evaporate relative humidity. In this context, many researches have been developed. They have shown that the mechanical characteristics of earth materials increase with the hyper-compaction and adding fibers or hydraulic binders. Besides, other researches have been determined the thermal and hygroscopic properties of raw earth. They have shown that this material able to contribute to moisture and heat control in constructions. Its hygrothermal properties are better than fired earth bricks and concrete. The aim of this study is to evaluate the thermal and hygrometric behavior of raw earth material using experimental tests allows to determine the main Hygrothermal properties such as the water Vapour permeability and thermal conductivity and compare the results with those of other building materials such as fired clay bricks and cement concrete is presented.

Keywords: raw earth material, hygro-thermal, thermal conductivity, water vapour permeability, building materials, building materials

Procedia PDF Downloads 166
3684 Nurses’ Views on ‘Effective Nurse Leader’ Characteristics in Iraq

Authors: S. Abed, S. O’Neill

Abstract:

This research explored ward nurses’ views about the characteristics of effective nurse leaders in the context of Iraq as a developing country, where the delivery of health care continues to face disruption and change. It is well established that the provision of modern health care requires effective nurse leaders, but in countries such as Iraq the lack of effective nurse leaders is noted as a major challenge. In a descriptive quantitative study, a survey questionnaire was administered to 210 ward nurses working in two public hospitals in a major city in the north of Iraq. The participating nurses were of the opinion that the effectiveness of their nurse leaders was evident in their ability to demonstrate: good clinical knowledge, effective communication and managerial skills. They also viewed their leaders as needing to hold high-level nursing qualifications, though this was not necessarily the case in practice. Additionally, they viewed nurse leaders’ personal qualities as important, which included politeness, ethical behaviour, and trustworthiness. When considered against the issues raised in interviews with a smaller group (20) of senior nurse leaders, representative of the various occupational levels, implications identify the need for professional development that focuses on how the underpinning competencies relate to leadership and how transformational leadership is evidenced in practice.

Keywords: health care, nurse education, nursing in Iraq, nurse leadership

Procedia PDF Downloads 263
3683 On the Influence of Sleep Habits for Predicting Preterm Births: A Machine Learning Approach

Authors: C. Fernandez-Plaza, I. Abad, E. Diaz, I. Diaz

Abstract:

Births occurring before the 37th week of gestation are considered preterm births. A threat of preterm is defined as the beginning of regular uterine contractions, dilation and cervical effacement between 23 and 36 gestation weeks. To author's best knowledge, the factors that determine the beginning of the birth are not completely defined yet. In particular, the incidence of sleep habits on preterm births is weekly studied. The aim of this study is to develop a model to predict the factors affecting premature delivery on pregnancy, based on the above potential risk factors, including those derived from sleep habits and light exposure at night (introduced as 12 variables obtained by a telephone survey using two questionnaires previously used by other authors). Thus, three groups of variables were included in the study (maternal, fetal and sleep habits). The study was approved by Research Ethics Committee of the Principado of Asturias (Spain). An observational, retrospective and descriptive study was performed with 481 births between January 1, 2015 and May 10, 2016 in the University Central Hospital of Asturias (Spain). A statistical analysis using SPSS was carried out to compare qualitative and quantitative variables between preterm and term delivery. Chi-square test qualitative variable and t-test for quantitative variables were applied. Statistically significant differences (p < 0.05) between preterm vs. term births were found for primiparity, multi-parity, kind of conception, place of residence or premature rupture of membranes and interruption during nights. In addition to the statistical analysis, machine learning methods to look for a prediction model were tested. In particular, tree based models were applied as the trade-off between performance and interpretability is especially suitable for this study. C5.0, recursive partitioning, random forest and tree bag models were analysed using caret R-package. Cross validation with 10-folds and parameter tuning to optimize the methods were applied. In addition, different noise reduction methods were applied to the initial data using NoiseFiltersR package. The best performance was obtained by C5.0 method with Accuracy 0.91, Sensitivity 0.93, Specificity 0.89 and Precision 0.91. Some well known preterm birth factors were identified: Cervix Dilation, maternal BMI, Premature rupture of membranes or nuchal translucency analysis in the first trimester. The model also identifies other new factors related to sleep habits such as light through window, bedtime on working days, usage of electronic devices before sleeping from Mondays to Fridays or change of sleeping habits reflected in the number of hours, in the depth of sleep or in the lighting of the room. IF dilation < = 2.95 AND usage of electronic devices before sleeping from Mondays to Friday = YES and change of sleeping habits = YES, then preterm is one of the predicting rules obtained by C5.0. In this work a model for predicting preterm births is developed. It is based on machine learning together with noise reduction techniques. The method maximizing the performance is the one selected. This model shows the influence of variables related to sleep habits in preterm prediction.

Keywords: machine learning, noise reduction, preterm birth, sleep habit

Procedia PDF Downloads 135
3682 English Language Competency among the Mathematics Teachers as the Precursor for Performance in Mathematics

Authors: Mirriam M. Moleko, Sekanse A. Ntsala

Abstract:

Language in mathematics instruction enables the teacher to communicate mathematical knowledge to the learners with precision. It also enables the learner to deal with mathematical activities effectively. This scholarly piece was motivated by the fact that mathematics performance in the South African primary classrooms has not been satisfactory, and English, which is a Language of Learning and Teaching (LoLT) for the majority of the learners, has been singled out as one of the major impediments. This is not only on the part of the learners, but also on the part of the teachers as well. The study thus focused on the lack of competency in English among the primary school teachers as one of the possible causes of poor performance in mathematics in primary classrooms. The qualitative processes, which were premised on the social interaction theory as a lens, sourced the narratives of 10 newly qualified primary school mathematics teachers from the disadvantaged schools on the matter. This was achieved through the use of semi-structured interviews and focus group discussions. The data, which were analyzed thematically, highlighted the actuality that the challenges cut across the pre-service stage to the in-service stage. The findings revealed that the undergraduate mathematics courses in the number of the institutions neglect the importance of language. The study further revealed that the in-service mathematics teachers lack adequate linguistic command, thereby finding it difficult to successfully teach some mathematical concepts, or even to outline instructions clearly. The study thus suggests the need for training institutions to focus on improving the teachers’ English language competency. The need for intensive in-service training targeting the problem areas was also highlighted. The study thus contributes to the body of knowledge by providing suggestions on how the mathematics teachers’ language incompetency can be mitigated.

Keywords: Competency, English language proficiency, language of learning and teaching, primary mathematics teachers

Procedia PDF Downloads 168
3681 Smart Safari: Safari Guidance Mobile Application

Authors: D. P. Lawrence, T. M. M. D. Ariyarathna, W. N. K. De Silva, M. D. S. C. De Silva, Lasantha Abeysiri, Pradeep Abeygunawardhna

Abstract:

Safari traveling is one of the most famous hobbies all over the world. In Sri Lanka, 'Yala' is the second-largest national park, which is a better place to go for a safari. Many number of local and foreign travelers are coming to go for a safari in 'Yala'. But 'Yala' does not have a mobile application that is made to facilitate the traveler with some important features that the traveler wants to achieve in the safari experience. To overcome these difficulties, the proposed mobile application by adding those identified features to make travelers, guiders, and administration's works easier. The proposed safari traveling guidance mobile application is called 'SMART SAFARI' for the 'Yala' National Park in Sri Lanka. There are four facilities in this mobile application that provide for travelers as well as the guiders. As the first facility, the guider and traveler can view the created map of the park, and the guider can add temporary locations of animals and special locations on the map. This is a Geographic Information System (GIS) to capture, analyze, and display geographical data. And as the second facility is to generate optimal paths according to the travelers' requirements through the park by using machine learning techniques. In the third part, the traveler can get information about animals using an animal identification system by capturing the animal. As in the other facility, the traveler will be facilitated to add reviews and a rate and view those comments under categorized sections and pre-defined score range. With those facilities, this user-friendly mobile application provides the user to get a better experience in safari traveling, and it will probably help to develop tourism culture in Sri Lanka.

Keywords: animal identification system, geographic information system, machine learning techniques, pre defined score range

Procedia PDF Downloads 125
3680 Applying the CA Systems in Education Process

Authors: A. Javorova, M. Matusova, K. Velisek

Abstract:

The article summarizes the experience of laboratory technical subjects teaching methodologies using a number of software products. The main aim is to modernize the teaching process in accordance with the requirements of today - based on information technology. Increasing of the study attractiveness and effectiveness is due to the introduction of CA technologies in the learning process. This paper discussed the areas where individual CA system used. Environment using CA systems are briefly presented in each chapter.

Keywords: education, CA systems, simulation, technology

Procedia PDF Downloads 383
3679 The Influence of Students’ Race and Socioeconomic Status on Teachers’ Assessment of ADHD: Implications for Educational Inequalities

Authors: Justine McKay

Abstract:

Implicit Bias and its impact on the schooling experience of racial minorities with ADHD is significant. ADHD has become a globally diagnosed disorder. The lack of an objective diagnostic tool for ADHD has created controversy over the disease and its validity. ADHD is referred to as a social construct or a suburban problem related to active white boys who disrupt classrooms. The subjectivity of an ADHD diagnosis and the diagnostic process is based on norm-referenced checklists of behaviours completed by the student, caregiver, teachers, clinicians, and other community members. Teachers' perceptions of classroom behaviours are influenced by implicit bias related to race and socioeconomic status. The same behaviours displayed by white and marginalized or low-income students are perceived differently. The white student is perceived to be struggling academically and needing support, while the marginalized or lower-income student's behaviour is seen as disruptive or criminal. The presence of teacher implicit bias results in the inequity of diagnosis, and academic support, which has long-term implications for these students. The subjectivity of the diagnostic process socially reproduces the systemic injustice of opportunity for marginalized youth within the education system.

Keywords: ADHD, education, equity, implicit bias, subjectivity

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3678 Enhancing Creative Writing Skill through the Implementation of Creative Thinking Process

Authors: Bussabamintra Chalauisaeng

Abstract:

The creative writing skill of Thai fourth year university learners majoring in English at Khon Kaen University, Thailand has been enhanced in an English creative writing course through the implementation of creative thinking process. The creative writing assignments cover writing a variety of short poems and a short story, bibliography and short play scripts. However, this study focuses mainly on writing short poems and short stories through the implementation of creative thinking process via action research design with on-going needs analysis and feedbacks to meet their learning needs for 45 hours. At the end of the course, forty two learners’ creative writing skill appeared to be significantly improved. Through the research instruments such as the tasks assigned both inside and outside the class as self –study including class observation, semi-conversational interviews and teacher feedback both in persons and on line including peer feedbacks. The research findings show that the target learners could produce better short poems and short story assessed by the set of criteria such as the creative and innovative short poems and short stories with complete and interesting elements of a short story like plot, theme, setting, symbolism and so on. This includes a higher level of the awareness of the pragmatic use of English writing in terms of word choices, grammar rules and writing styles. All of these outcomes reflect positive trends of success in terms of the learners’ improved creative writing skill as well as better attitudes to and motivation for learning to write English for pleasure. More interestingly, many learners claimed that this innovative teaching method through the implementation of creative thinking process integrated with creative writing help stretch their imaginations and inspire them to become a writer in the future.

Keywords: creative thinking process, creative writing skill, enhancing, implementing

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3677 Challenges and Future Prospects of Teaching English in Secondary Schools of Jharkhand Board: An Extensive Survey of the Present Status

Authors: Neha Toppo

Abstract:

Plans and programs for successful secondary education are incomplete without the inclusion of teaching English as an important area. Even after sixteen years of the formation of Jharkhand as a separate state, the students are still struggling to achieve quality education of English. This paper intends to account the present condition of teaching English in Jharkhand board secondary level schools through discussion on various issues of English language teaching, language need and learning challenges of its students. The study is to analyze whether the learning environment, teaching methods and materials, teaching resources, goals of language curriculum are appropriately convincing for the students of the board or require to be reanalyzed and also to provide appropriate suggestions for improvement. Immediate attention must be drawn towards the problem for benefitting those students, who despite their knowledge and talent are lagging behind in numerous fields only due to the lack of proficiency in English. The data and discussion provided are on the basis of a survey, in which semi structured interview with teachers, students and administrators in several schools including both rural and urban area has been taken. Questionnaire, observation and testing were used as important tools. The survey has been conducted in Ranchi district, as it covers large geographical area which includes number of villages and at the same time several towns. The district primarily possesses tribes as well as different class of people including immigrants from all over and outside Jharkhand with their social, economical strata. The observation makes it clear that the English language teaching at the state board is not complementing its context and the whole language teaching system should be re-examined to establish learner oriented environment.

Keywords: material, method, secondary level, teaching resources

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3676 Travel Behavior Simulation of Bike-Sharing System Users in Kaoshiung City

Authors: Hong-Yi Lin, Feng-Tyan Lin

Abstract:

In a Bike-sharing system (BSS), users can easily rent bikes from any station in the city for mid-range or short-range trips. BSS can also be integrated with other types of transport system, especially Green Transportation system, such as rail transport, bus etc. Since BSS records time and place of each pickup and return, the operational data can reflect more authentic and dynamic state of user behaviors. Furthermore, land uses around docking stations are highly associated with origins and destinations for the BSS users. As urban researchers, what concerns us more is to take BSS into consideration during the urban planning process and enhance the quality of urban life. This research focuses on the simulation of travel behavior of BSS users in Kaohsiung. First, rules of users’ behavior were derived by analyzing operational data and land use patterns nearby docking stations. Then, integrating with Monte Carlo method, these rules were embedded into a travel behavior simulation model, which was implemented by NetLogo, an agent-based modeling tool. The simulation model allows us to foresee the rent-return behaviour of BSS in order to choose potential locations of the docking stations. Also, it can provide insights and recommendations about planning and policies for the future BSS.

Keywords: agent-based model, bike-sharing system, BSS operational data, simulation

Procedia PDF Downloads 320
3675 Role of Speech Articulation in English Language Learning

Authors: Khadija Rafi, Neha Jamil, Laiba Khalid, Meerub Nawaz, Mahwish Farooq

Abstract:

Speech articulation is a complex process to produce intelligible sounds with the help of precise movements of various structures within the vocal tract. All these structures in the vocal tract are named as articulators, which comprise lips, teeth, tongue, and palate. These articulators work together to produce a range of distinct phonemes, which happen to be the basis of language. It starts with the airstream from the lungs passing through the trachea and into oral and nasal cavities. When the air passes through the mouth, the tongue and the muscles around it form such coordination it creates certain sounds. It can be seen when the tongue is placed in different positions- sometimes near the alveolar ridge, soft palate, roof of the mouth or the back of the teeth which end up creating unique qualities of each phoneme. We can articulate vowels with open vocal tracts, but the height and position of the tongue is different every time depending upon each vowel, while consonants can be pronounced when we create obstructions in the airflow. For instance, the alphabet ‘b’ is a plosive and can be produced only by briefly closing the lips. Articulation disorders can not only affect communication but can also be a hurdle in speech production. To improve articulation skills for such individuals, doctors often recommend speech therapy, which involves various kinds of exercises like jaw exercises and tongue twisters. However, this disorder is more common in children who are going through developmental articulation issues right after birth, but in adults, it can be caused by injury, neurological conditions, or other speech-related disorders. In short, speech articulation is an essential aspect of productive communication, which also includes coordination of the specific articulators to produce different intelligible sounds, which are a vital part of spoken language.

Keywords: linguistics, speech articulation, speech therapy, language learning

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3674 Potential Usefulness of Video Lectures as a Tool to Improve Synchronous and Asynchronous the Online Education

Authors: Omer Shujat Bhatti, Afshan Huma

Abstract:

Online educational system were considered a great opportunity for distance learning. In recent days of COVID19 pandemic, it enable the continuation of educational activities at all levels of education, from primary school to the top level universities. One of the key considered element in supporting the online educational system is video lectures. The current research explored the usefulness of the video lectures delivered to technical students of masters level with a focus on MSc Sustainable Environmental design students who have diverse backgrounds in the formal educational system. Hence they were unable to cope right away with the online system and faced communication and understanding issues in the lecture session due to internet and allied connectivity issues. Researcher used self prepared video lectures for respective subjects and provided them to the students using Youtube channel and subject based Whatsapp groups. Later, students were asked about the usefulness of the lectures towards a better understanding of the subject and an overall enhanced learning experience. More than 80% of the students appreciated the effort and requested it to be part of the overall system. Data collection was done using an online questionnaire which was prior briefed to the students with the purpose of research. It was concluded that video lectures should be considered an integral part of the lecture sessions and must be provided prior to the lecture session, ensuring a better quality of delivery. It was also recommended that the existing system must be upgraded to support the availability of these video lectures through the portal. Teachers training must be provided to help develop quality video content ensuring that is able to cover the content and courses taught.

Keywords: video lectures, online distance education, synchronous instruction, asynchronous communication

Procedia PDF Downloads 102
3673 Experiences of Trainee Teachers: A Survey on Expectations and Realities in Special Secondary Schools in Kenya

Authors: Mary Cheptanui Sambu

Abstract:

Teaching practice is an integral component of students who are training to be teachers, as it provides them with an opportunity to gain experience in an actual teaching and learning environment. This study explored the experiences of trainee teachers from a local university in Kenya, undergoing a three-month teaching practice in Special Secondary schools in the country. The main aim of the study was to understand the trainees’ experiences, their expectations, and the realities encountered during the teaching practice period. The study focused on special secondary schools for learners with hearing impairment. A descriptive survey design was employed and a sample size of forty-four respondents from special secondary schools for learners with hearing impairment was purposively selected. A questionnaire was administered to the respondents and the data obtained analysed using the Statistical Package for the Social Sciences (SPSS). Preliminary analysis shows that challenges facing special secondary schools include inadequate teaching and learning facilities and resources, low academic performance among learners with hearing impairment, an overloaded curriculum and inadequate number of teachers for the learners. The study findings suggest that the Kenyan government should invest more in the education of special needs children, particularly focusing on increasing the number of trained teachers. In addition, the education curriculum offered in special secondary schools should be tailored towards the needs and interest of learners. These research findings will be useful to policymakers and curriculum developers, and will provide information that can be used to enhance the education of learners with hearing impairment; this will lead to improved academic performance, consequently resulting in better transitions and the realization of Vision 2030.

Keywords: hearing impairment, special secondary schools, trainee, teaching practice

Procedia PDF Downloads 152
3672 Enhancing Early Detection of Coronary Heart Disease Through Cloud-Based AI and Novel Simulation Techniques

Authors: Md. Abu Sufian, Robiqul Islam, Imam Hossain Shajid, Mahesh Hanumanthu, Jarasree Varadarajan, Md. Sipon Miah, Mingbo Niu

Abstract:

Coronary Heart Disease (CHD) remains a principal cause of global morbidity and mortality, characterized by atherosclerosis—the build-up of fatty deposits inside the arteries. The study introduces an innovative methodology that leverages cloud-based platforms like AWS Live Streaming and Artificial Intelligence (AI) to early detect and prevent CHD symptoms in web applications. By employing novel simulation processes and AI algorithms, this research aims to significantly mitigate the health and societal impacts of CHD. Methodology: This study introduces a novel simulation process alongside a multi-phased model development strategy. Initially, health-related data, including heart rate variability, blood pressure, lipid profiles, and ECG readings, were collected through user interactions with web-based applications as well as API Integration. The novel simulation process involved creating synthetic datasets that mimic early-stage CHD symptoms, allowing for the refinement and training of AI algorithms under controlled conditions without compromising patient privacy. AWS Live Streaming was utilized to capture real-time health data, which was then processed and analysed using advanced AI techniques. The novel aspect of our methodology lies in the simulation of CHD symptom progression, which provides a dynamic training environment for our AI models enhancing their predictive accuracy and robustness. Model Development: it developed a machine learning model trained on both real and simulated datasets. Incorporating a variety of algorithms including neural networks and ensemble learning model to identify early signs of CHD. The model's continuous learning mechanism allows it to evolve adapting to new data inputs and improving its predictive performance over time. Results and Findings: The deployment of our model yielded promising results. In the validation phase, it achieved an accuracy of 92% in predicting early CHD symptoms surpassing existing models. The precision and recall metrics stood at 89% and 91% respectively, indicating a high level of reliability in identifying at-risk individuals. These results underscore the effectiveness of combining live data streaming with AI in the early detection of CHD. Societal Implications: The implementation of cloud-based AI for CHD symptom detection represents a significant step forward in preventive healthcare. By facilitating early intervention, this approach has the potential to reduce the incidence of CHD-related complications, decrease healthcare costs, and improve patient outcomes. Moreover, the accessibility and scalability of cloud-based solutions democratize advanced health monitoring, making it available to a broader population. This study illustrates the transformative potential of integrating technology and healthcare, setting a new standard for the early detection and management of chronic diseases.

Keywords: coronary heart disease, cloud-based ai, machine learning, novel simulation techniques, early detection, preventive healthcare

Procedia PDF Downloads 52
3671 Assessment of Hygroscopic Characteristics of Hevea brasiliensis Wood

Authors: John Tosin Aladejana

Abstract:

Wood behave differently under different environmental conditions. The knowledge of the hygroscopic nature of wood becomes a key factor in selecting wood for use and required treatment. This study assessed the hygroscopic behaviour of Hevea brasiliensis (Rubber) wood. Void volume, volumetric swelling in the tangential, radial and longitudinal directions and volumetric shrinkage were used to assess the response of the wood when loosing or taking up moisture. Hevea brasiliensis wood samples cut into 20 × 20 × 60 mm taken longitudinally and transversely were used for the study and dried in the oven at 103 ± 2⁰C. The mean values for moisture content in green Hevea brasiliensis wood were 49.74 %, 51.14 % and 54.36 % for top, middle and bottom portion respectively while 51.77 %, 50.02 % and 53.45 % were recorded for outer, middle and inner portions respectively for the tree. The values obtained for volumetric shrinkage and swelling indicated that shrinkage and swelling were higher at the top part of H. brasiliensis. It was also observed that the longitudinal shrinkage was negligible while tangential direction showed the highest shrinkage among the wood direction. The values of the void volume obtained were 43.0 %, 39.0 % and 38.0 % at the top, middle and bottom respectively. The result obtained showed clarification on the wood density of hevea brasiliensis based on the position and portion of the wood species and the variation in moisture content, void volume, volumetric shrinkage and swelling were also revealed. This will provide information in the process of drying hevea brasiliensis wood to ensure better wood quality devoid of defects.

Keywords: moisture content, shrinkage, swelling, void volume

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3670 Resistance and Sub-Resistances of RC Beams Subjected to Multiple Failure Modes

Authors: F. Sangiorgio, J. Silfwerbrand, G. Mancini

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Geometric and mechanical properties all influence the resistance of RC structures and may, in certain combination of property values, increase the risk of a brittle failure of the whole system. This paper presents a statistical and probabilistic investigation on the resistance of RC beams designed according to Eurocodes 2 and 8, and subjected to multiple failure modes, under both the natural variation of material properties and the uncertainty associated with cross-section and transverse reinforcement geometry. A full probabilistic model based on JCSS Probabilistic Model Code is derived. Different beams are studied through material nonlinear analysis via Monte Carlo simulations. The resistance model is consistent with Eurocode 2. Both a multivariate statistical evaluation and the data clustering analysis of outcomes are then performed. Results show that the ultimate load behaviour of RC beams subjected to flexural and shear failure modes seems to be mainly influenced by the combination of the mechanical properties of both longitudinal reinforcement and stirrups, and the tensile strength of concrete, of which the latter appears to affect the overall response of the system in a nonlinear way. The model uncertainty of the resistance model used in the analysis plays undoubtedly an important role in interpreting results.

Keywords: modelling, Monte Carlo simulations, probabilistic models, data clustering, reinforced concrete members, structural design

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3669 Effect of Infill’s in Influencing the Dynamic Responses of Multistoried Structures

Authors: Rahmathulla Noufal E.

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Investigating the dynamic responses of high rise structures under the effect of siesmic ground motion is extremely important for the proper analysis and design of multitoried structures. Since the presence of infilled walls strongly influences the behaviour of frame systems in multistoried buildings, there is an increased need for developing guidelines for the analysis and design of infilled frames under the effect of dynamic loads for safe and proper design of buildings. In this manuscript, we evaluate the natural frequencies and natural periods of single bay single storey frames considering the effect of infill walls by using the Eigen value analysis and validating with SAP 2000 (free vibration analysis). Various parameters obtained from the diagonal strut model followed for the free vibration analysis is then compared with the Finite Element model, where infill is modeled as shell elements (four noded). We also evaluated the effect of various parameters on the natural periods of vibration obtained by free vibration analysis in SAP 2000 comparing them with those obtained by the empirical expressions presented in I.S. 1893(Part I)-2002.

Keywords: infilled frame, eigen value analysis, free vibration analysis, diagonal strut model, finite element model, SAP 2000, natural period

Procedia PDF Downloads 316
3668 Regret-Regression for Multi-Armed Bandit Problem

Authors: Deyadeen Ali Alshibani

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In the literature, the multi-armed bandit problem as a statistical decision model of an agent trying to optimize his decisions while improving his information at the same time. There are several different algorithms models and their applications on this problem. In this paper, we evaluate the Regret-regression through comparing with Q-learning method. A simulation on determination of optimal treatment regime is presented in detail.

Keywords: optimal, bandit problem, optimization, dynamic programming

Procedia PDF Downloads 445
3667 Prediction of Coronary Artery Stenosis Severity Based on Machine Learning Algorithms

Authors: Yu-Jia Jian, Emily Chia-Yu Su, Hui-Ling Hsu, Jian-Jhih Chen

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Coronary artery is the major supplier of myocardial blood flow. When fat and cholesterol are deposit in the coronary arterial wall, narrowing and stenosis of the artery occurs, which may lead to myocardial ischemia and eventually infarction. According to the World Health Organization (WHO), estimated 740 million people have died of coronary heart disease in 2015. According to Statistics from Ministry of Health and Welfare in Taiwan, heart disease (except for hypertensive diseases) ranked the second among the top 10 causes of death from 2013 to 2016, and it still shows a growing trend. According to American Heart Association (AHA), the risk factors for coronary heart disease including: age (> 65 years), sex (men to women with 2:1 ratio), obesity, diabetes, hypertension, hyperlipidemia, smoking, family history, lack of exercise and more. We have collected a dataset of 421 patients from a hospital located in northern Taiwan who received coronary computed tomography (CT) angiography. There were 300 males (71.26%) and 121 females (28.74%), with age ranging from 24 to 92 years, and a mean age of 56.3 years. Prior to coronary CT angiography, basic data of the patients, including age, gender, obesity index (BMI), diastolic blood pressure, systolic blood pressure, diabetes, hypertension, hyperlipidemia, smoking, family history of coronary heart disease and exercise habits, were collected and used as input variables. The output variable of the prediction module is the degree of coronary artery stenosis. The output variable of the prediction module is the narrow constriction of the coronary artery. In this study, the dataset was randomly divided into 80% as training set and 20% as test set. Four machine learning algorithms, including logistic regression, stepwise regression, neural network and decision tree, were incorporated to generate prediction results. We used area under curve (AUC) / accuracy (Acc.) to compare the four models, the best model is neural network, followed by stepwise logistic regression, decision tree, and logistic regression, with 0.68 / 79 %, 0.68 / 74%, 0.65 / 78%, and 0.65 / 74%, respectively. Sensitivity of neural network was 27.3%, specificity was 90.8%, stepwise Logistic regression sensitivity was 18.2%, specificity was 92.3%, decision tree sensitivity was 13.6%, specificity was 100%, logistic regression sensitivity was 27.3%, specificity 89.2%. From the result of this study, we hope to improve the accuracy by improving the module parameters or other methods in the future and we hope to solve the problem of low sensitivity by adjusting the imbalanced proportion of positive and negative data.

Keywords: decision support, computed tomography, coronary artery, machine learning

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3666 Solution of Singularly Perturbed Differential Difference Equations Using Liouville Green Transformation

Authors: Y. N. Reddy

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The class of differential-difference equations which have characteristics of both classes, i.e., delay/advance and singularly perturbed behaviour is known as singularly perturbed differential-difference equations. The expression ‘positive shift’ and ‘negative shift’ are also used for ‘advance’ and ‘delay’ respectively. In general, an ordinary differential equation in which the highest order derivative is multiplied by a small positive parameter and containing at least one delay/advance is known as singularly perturbed differential-difference equation. Singularly perturbed differential-difference equations arise in the modelling of various practical phenomena in bioscience, engineering, control theory, specifically in variational problems, in describing the human pupil-light reflex, in a variety of models for physiological processes or diseases and first exit time problems in the modelling of the determination of expected time for the generation of action potential in nerve cells by random synaptic inputs in dendrites. In this paper, we envisage the use of Liouville Green Transformation to find the solution of singularly perturbed differential difference equations. First, using Taylor series, the given singularly perturbed differential difference equation is approximated by an asymptotically equivalent singularly perturbation problem. Then the Liouville Green Transformation is applied to get the solution. Several model examples are solved, and the results are compared with other methods. It is observed that the present method gives better approximate solutions.

Keywords: difference equations, differential equations, singular perturbations, boundary layer

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3665 Using Shape Memory Alloys for Structural Engineering Applications

Authors: Donatello Cardone

Abstract:

Shape memory alloys (SMAs) have great potential for use in the field of civil engineering. The author of this manuscript has been involved, since 1996, in several experimental and theoretical studies on the application of SMAs in structural engineering, within national and international research projects. This paper provides an overview of the main results achieved, including the conceptual design, implementation, and testing of different SMA-based devices, namely: (i) energy-dissipating braces for RC buildings, (ii) seismic isolation devices for buildings and bridges, (iii) smart tie-rods for arches and vaults and (iv) seismic restrainers for bridges. The main advantages of using SMA-based devices in the seismic protection of structures derive from the double-flag shape of their hysteresis loops, which implies three favourable features, i.e., self-centering capability, good energy dissipation capability, and high stiffness for small displacements. The main advantages of SMA-based units for steel tie-rods are associated with the thermal behaviour of superelastic SMAs, which is antagonistic compared to that of steel. This implies a strong reduction of force changes due to air temperature variations. Finally, SMA-based seismic restrainers proved to be effective in preventing bridge deck unseating and pounding.

Keywords: seismic protection of structures, shape memory alloys, structural engineering, steel tie-rods, seismic restrainers for bridges

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3664 The Fefe Indices: The Direction of Donal Trump’s Tweets Effect on the Stock Market

Authors: Sergio Andres Rojas, Julian Benavides Franco, Juan Tomas Sayago

Abstract:

An increasing amount of research demonstrates how market mood affects financial markets, but their primary goal is to demonstrate how Trump's tweets impacted US interest rate volatility. Following that lead, this work evaluates the effect that Trump's tweets had during his presidency on local and international stock markets, considering not just volatility but the direction of the movement. Three indexes for Trump's tweets were created relating his activity with movements in the S&P500 using natural language analysis and machine learning algorithms. The indexes consider Trump's tweet activity and the positive or negative market sentiment they might inspire. The first explores the relationship between tweets generating negative movements in the S&P500; the second explores positive movements, while the third explores the difference between up and down movements. A pseudo-investment strategy using the indexes produced statistically significant above-average abnormal returns. The findings also showed that the pseudo strategy generated a higher return in the local market if applied to intraday data. However, only a negative market sentiment caused this effect on daily data. These results suggest that the market reacted primarily to a negative idea reflected in the negative index. In the international market, it is not possible to identify a pervasive effect. A rolling window regression model was also performed. The result shows that the impact on the local and international markets is heterogeneous, time-changing, and differentiated for the market sentiment. However, the negative sentiment was more prone to have a significant correlation most of the time.

Keywords: market sentiment, Twitter market sentiment, machine learning, natural dialect analysis

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3663 Event Data Representation Based on Time Stamp for Pedestrian Detection

Authors: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

Abstract:

In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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3662 Telemedicine in Physician Assistant Education: A Partnership with Community Agency

Authors: Martina I. Reinhold, Theresa Bacon-Baguley

Abstract:

A core challenge of physician assistant education is preparing professionals for lifelong learning. While this conventionally has encompassed scientific advances, students must also embrace new care delivery models and technologies. Telemedicine, the provision of care via two-way audio and video, is an example of a technological advance reforming health care. During a three-semester sequence of Hospital Community Experiences, physician assistant students were assigned experiences with Answer Health on Demand, a telemedicine collaborative. Preceding the experiences, the agency lectured on the application of telemedicine. Students were then introduced to the technology and partnered with a provider. Prior to observing the patient-provider interaction, patient consent was obtained. Afterwards, students completed a reflection paper on lessons learned and the potential impact of telemedicine on their careers. Thematic analysis was completed on the students’ reflection papers (n=13). Preceding the lecture and experience, over 75% of students (10/13) were unaware of telemedicine. Several stated they were 'skeptical' about the effectiveness of 'impersonal' health care appointments. After the experience, all students remarked that telemedicine will play a large role in the future of healthcare and will provide benefits by improving access in rural areas, decreasing wait time, and saving cost. More importantly, 30% of students (4/13) commented that telemedicine is a technology they can see themselves using in their future practice. Initial results indicate that collaborative interaction between students and telemedicine providers enhanced student learning and exposed students to technological advances in the delivery of care. Further, results indicate that students perceived telemedicine more favorably as a viable delivery method after the experience.

Keywords: collaboration, physician assistant education, teaching innovative health care delivery method, telemedicine

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3661 A Case Study Using Sounds Write and The Writing Revolution to Support Students with Literacy Difficulties

Authors: Emilie Zimet

Abstract:

During our department meetings for teachers of children with learning disabilities and difficulties, we often discuss the best practices for supporting students who come to school with literacy difficulties. After completing Sounds Write and Writing Revolution courses, it seems there is a possibility to link approaches and still maintain fidelity to a program and provide individualised instruction to support students with such difficulties and disabilities. In this case study, the researcher has been focussing on how best to use the knowledge acquired to provide quality intervention that targets the varied areas of challenge that students require support in. Students present to school with a variety of co-occurring reading and writing deficits and with complementary approaches, such as The Writing Revolution and Sounds Write, it is possible to support students to improve their fundamental skills in these key areas. Over the next twelve weeks, the researcher will collect data on current students with whom this approach will be trialled and then compare growth with students from last year who received support using Sounds-Write only. Maintaining fidelity may be a potential challenge as each approach has been tested in a specific format for best results. The aim of this study is to determine if approaches can be combined, so the implementation will need to incorporate elements of both reading (from Sounds Write) and writing (from The Writing Revolution). A further challenge is the time length of each session (25 minutes), so the researcher will need to be creative in the use of time to ensure both writing and reading are targeted while ensuring the programs are implemented. The implementation will be documented using student work samples and planning documents. This work will include a display of findings using student learning samples to demonstrate the importance of co-targeting the reading and writing challenges students come to school with.

Keywords: literacy difficulties, intervention, individual differences, methods of provision

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3660 Effect of Maize Straw-Derived Biochar on Imidacloprid Adsorption onto Soils Prior to No-Tillage and Rotary Tillage Practices

Authors: Jean Yves Uwamungu, Fiston Bizimana, Chunsheng Hu

Abstract:

Although pesticides are used in crop productivity, their use is highly harming the soil environment, and measures must be taken in the future to eradicate soil and groundwater pollution. The primary aim was to determine the effect of biochar addition on the imidacloprid adsorption on soil prior to no-tillage (NT) and rotational tillage (RT) conditions. In the laboratory, batch tests were conducted to determine the imidacloprid adsorption on soil using equilibrium and kinetic modelling with the addition of biochar. The clay level of the soil was found to be more significant when no-tillage was applied (22.42) than when rotational tillage was applied (14.27). The imidacloprid adsorption equilibrium was significantly shortened to 25 min after biochar addition. The isotherms and kinetic findings confirmed that the adsorption occurred according to Freundlich and pseudo-second-order kinetic models, respectively. The adsorption capacity of imidacloprid (40<35<25 °C) increased with decreasing temperature, indicating an exothermic adsorption behaviour, whereas negative Gibbs free energy (G) values of -6980.5 and 5983.93 Jmol-1, respectively, for soil prior to NT and RT at 25 °C, asserted spontaneous adsorption. The negative values of entropy (ΔS); -22.83 and -38.15 Jmol-1K-1, prior to NT and RT applications, respectively, described a lowered randomness process. The enthalpy was greater when RT was applied (-17533 J mol-1) than when NT was applied (-450 J mol-1). Lastly, it was shown that NTtreatment enhanced imidacloprid adsorption capacity more than RT treatment and that biochar addition enhanced pesticide adsorption in both treatments.

Keywords: adsorption, biochar, imidacloprid, soil, tillage

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3659 Promoting Libraries' Services and Events by Librarians Led Instagram Account: A Case Study on Qatar National Library's Research and Learning Instagram Account

Authors: Maryam Alkhalosi, Ahmad Naddaf, Rana Alani

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Qatar National Library has its main accounts on social media, which presents the general image of the library and its daily news. A paper will be presented based on a case study researching the outcome of having a separate Instagram account led by librarians, not the Communication Department of the library. The main purpose of the librarians-led account is to promote librarians’ services and events, such as research consultation, reference questions, community engagement programs, collection marketing, etc. all in the way that librarians think it reflects their role in the community. Librarians had several obstacles to help users understanding librarians' roles. As was noticed that Instagram is the most popular social media platform in Qatar, it was selected to promote how librarians can help users through a focused account to create a direct channel between librarians and users. Which helps librarians understand users’ needs and interests. This research will use a quantitative approach depending on the case study, librarians have used their case in the department of Research and learning to find out the best practices might help in promoting the librarians' services and reaching out to a bigger number of users. Through the descriptive method, this research will describe the changes observed in the numbers of community users who interact with the Instagram account and engaged in librarians’ events. Statistics of this study are based on three main sources: 1. The internal monthly statistics sheet of events and programs held by the Research and Learning Department. 2. The weekly tracking of the Instagram account statistics. 3. Instagram’s tools such as polls, quizzes, questions, etc. This study will show the direct effect of a librarian-led Instagram account on the number of community members who participate and engage in librarian-led programs and services. In addition to highlighting the librarians' role directly with the community members. The study will also show the best practices on Instagram, which helps reaching a wider community of users. This study is important because, in the region, there is a lack of studies focusing on librarianship, especially on contemporary problems and its solution. Besides, there is a lack of understanding of the role of a librarian in the Arab region. The research will also highlight how librarians can help the public and researchers as well. All of these benefits can come through one popular easy channel in social media. From another side, this paper is a chance to share the details of this experience starting from scratch, including the phase of setting the policy and guidelines of managing the social media account, until librarians reached to a point where the benefits of this experience are in reality. This experience had even added many skills to the librarians.

Keywords: librarian’s role, social media, instagram and libraries, promoting libraries’ services

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3658 The Educational Philosophies and Teaching Style Preferences of College Faculty at Selected Universities in the South of Metro Manila

Authors: Grace D. Severo, Lopita U. Jung

Abstract:

This study aimed to determine the educational philosophies and teaching styles of the college faculty of the University of Perpetual Help System DALTA in the campuses of Las-Piñas, Molino, and Calamba, south of Metro Manila. It sought to determine the relationships of educational philosophy and teaching styles of the college faculty vis-à-vis the university system’s educational philosophies and teaching style preferences. A hundred and five faculty members from the Colleges of Education, Arts and Sciences responded to the survey during the academic year 2014-2015. The Philosophy of Adult Education Inventory measured the faculty’s preferred educational philosophies. The Principles of Adult Learning Scale measured the faculty’s teaching style preference. Findings show that there is a similarity between the university system and the faculty members in using the progressive educational philosophy, however both contrasted in the preferred teaching style. Majority of the faculty held progressive educational philosophy but their preference for teacher-centered teaching style did not match. This implies that the majority are certain of having progressive educational philosophy but are not utilizing the learner-centered teaching styles; a high degree of support and commitment to practice a progressive and humanist philosophical orientation in education; and a high degree of support on teacher-centered teaching style promotion from the institution can strengthen a high degree of commitment for the faculty to enunciate their values and practice through these educational philosophies and teaching styles.

Keywords: educational philosophies, teaching styles, philosophy of adult education inventory, principles of adult learning scale

Procedia PDF Downloads 357
3657 Assessing the Impacts of Frugivorous Birds on Dispersal and Recruitment of Invasive Phytolacca Americana in an Urban Landscape

Authors: Ning Li, Yaner Yan, Yajun Qiao, Shu-qing An

Abstract:

Although seed dispersal is considered to be a key process determining the spatial structure and spread of invasive plant populations, few studies have explicitly addressed the link between dispersal vector behaviour, and seedling recruitment to gain insight into the process of exotic species invasion within a urban landscape. The present study tests the effects of native bird species on the dispersal and recruitment of invasive Phytolacca Americana in an urban garden. We found the invasive population of American pokeweed attracted both generalist species and specialist species to forage and disperse its seeds, with generalists Pycnonotus sinensis and Urocissa erythrorhyncha being by far the most important dispersers. Seedling numbers of P. Americana was strongly affected by perching behavior of bird dispersers. Moreover, two main disperser species, P. sinensis and U. erythrorhyncha govern a high quality dispersal service for P. Americana. Our results highlight the ability of invasive P. americana to recruit seed dispersal agents in urban habitats. However, if the newly recruited species could use the seedling safe site for perching shelter, the invasive plants will get a high regenerate rate in the invasive new habitats thus enhancing their invasive ability.

Keywords: frugivorous birds, phytolacca americana, seed dispersal, urban landscape

Procedia PDF Downloads 532