Search results for: teaching and learning empathy

Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Susanna Asatryan

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The author will introduce the Language Portfolio for master course student-teachers of Yerevan Brusov State University of Languages and Social Sciences The overall aim of the Portfolio is to serve as a visual didactic tool for the pedagogical internship of master students in specialization “A Foreign Language Teacher of High Schools and Professional Educational Institutions”, based on the principles and fundamentals of the EPOSTL. The author will present the parts of the Portfolio, including the programme, goal and objectives of student-teacher’s internship, content and organization, expected outputs and the principles of the student’s self-assessment, based on Can-do philosophy suggested by the EPOSTL. The Language Portfolio for master course student-teachers outlines the distinctive stages of their scientific-pedagogical internship. In Lesson Observation and Teaching section student teachers present thematic planning of the syllabus course, including individual lesson plan-description and analysis of the lesson. In Realization of the Scientific-Pedagogical Research section student-teachers introduce the plan of their research work, its goal, objectives, steps of procedure and outcomes. In Educational Activity section student-teachers analyze the educational sides of the lesson, they introduce the plan of the extracurricular activity, provide psycho-pedagogical description of the group or the whole class, and outline extracurricular entertainments. In the Dossier the student-teachers store up the entire instructional “product” during their pedagogical internship: e.g. samples of surveys, tests, recordings, videos, posters, postcards, pupils’ poems, photos, pictures, etc. The author’s presentation will also cover the Self Assessment Checklist, which highlights the main didactic competences of student-teachers, extracted from the EPOSTL. The Self Assessment Checklist is introduced with some innovations, taking into consideration the local educational objectives that Armenian students come across with. The students’ feedback on the use of the Portfolio will also be presented.

Keywords: internship, lesson observation, can-do philosophy, self-assessment

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Authors: Alireza Vafaei Sadr, Vida Abedi, Jiang Li, Ramin Zand

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Missing data is a common challenge in medical research and can lead to biased or incomplete results. When the data bias leaks into models, it further exacerbates health disparities; biased algorithms can lead to misclassification and reduced resource allocation and monitoring as part of prevention strategies for certain minorities and vulnerable segments of patient populations, which in turn further reduce data footprint from the same population – thus, a vicious cycle. This study compares the performance of six imputation techniques grouped into Linear and Non-Linear models on two different realworld electronic health records (EHRs) datasets, representing 17864 patient records. The mean absolute percentage error (MAPE) and root mean squared error (RMSE) are used as performance metrics, and the results show that the Linear models outperformed the Non-Linear models in terms of both metrics. These results suggest that sometimes Linear models might be an optimal choice for imputation in laboratory variables in terms of imputation efficiency and uncertainty of predicted values.

Keywords: EHR, machine learning, imputation, laboratory variables, algorithmic bias

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Authors: June Keeling, Christina Athanasiades, Vaiva Hendrixson, Delyth Wyndham

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Recognition and education in violence, abuse, and neglect for medical and healthcare practitioners (REVAMP) is a trans-European project aiming to introduce a training programme that has been specifically developed by partners across seven European countries to meet the needs of medical and healthcare practitioners. Amalgamating the knowledge and experience of clinicians, researchers, and educators from interdisciplinary and multi-professional backgrounds, REVAMP has tackled the under-resourced and underdeveloped area of domestic violence and abuse. The team designed an online training programme to support medical and healthcare practitioners to recognise and respond appropriately to survivors of domestic violence and abuse at their point of contact with a health provider. The REVAMP partner countries include Europe: France, Lithuania, Germany, Greece, Iceland, Norway, and the UK. The training is delivered through a series of interactive online modules, adapting evidence-based pedagogical approaches to learning. Capturing and addressing the complexities of the project impacted the methodological decisions and approaches to evaluation. The challenge was to find an evaluation methodology that captured valid data across all partner languages to demonstrate the extent of the change in knowledge and understanding. Co-development by all team members was a lengthy iterative process, challenged by a lack of consistency in terminology. A mixed methods approach enabled both qualitative and quantitative data to be collected, at the start, during, and at the conclusion of the training for the purposes of evaluation. The module content and evaluation instrument were accessible in each partner country's language. Collecting both types of data provided a high-level snapshot of attainment via the quantitative dataset and an in-depth understanding of the impact of the training from the qualitative dataset. The analysis was mixed methods, with integration at multiple interfaces. The primary focus of the analysis was to support the overall project evaluation for the funding agency. A key project outcome was identifying that the trans-European approach posed several challenges. Firstly, the project partners did not share a first language or a legal or professional approach to domestic abuse and neglect. This was negotiated through complex, systematic, and iterative interaction between team members so that consensus could be achieved. Secondly, the context of the data collection in several different cultural, educational, and healthcare systems across Europe challenged the development of a robust evaluation. The participants in the pilot evaluation shared that the training was contemporary, well-designed, and of great relevance to inform practice. Initial results from the evaluation indicated that the participants were drawn from more than eight partner countries due to the online nature of the training. The primary results indicated a high level of engagement with the content and achievement through the online assessment. The main finding was that the participants perceived the impact of domestic abuse and neglect in very different ways in their individual professional contexts. Most significantly, the participants recognised the need for the training and the gap that existed previously. It is notable that a mixed-methods evaluation of a trans-European project is unusual at this scale.

Keywords: domestic violence, e-learning, health professionals, trans-European

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Authors: Chi-Cheng Cheng, Che-Hsin Lin, Yu-Jen Wang, Chua-Chin Wang

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The project-oriented capstone course has become a required element for most engineering educational units. It is not only because the capstone course is an important criterion for international accreditation of engineering degree programs under Washington Accord, but also the capstone course provides an opportunity for students to apply what they have learned in their school years to actual engineering problems. Nevertheless, most project-oriented capstone courses are conducted with one single project for all students or teams. In other words, students work to reach the same or similar goals by coming up with different layouts and approaches. It appears not suitable for a multidisciplinary engineering department. Therefore, a one-year multidisciplinary project-oriented capstone course was designed for the junior year of the undergraduate program. About one-half of faculty members in the department needs to be involved in generating as many projects as possible to meet different students' interests and specialties. Project achievement has to be displayed and demonstrated in the annual exposition and competition at the end of this course. Significant success in attracting attention and hardworking of students on projects was witnessed for the past two pilot years. Analysis of course evaluation demonstrates positive impact on all perspectives despite of slightly negative influence due to poor communication and collaboration between students and their project supervisors.

Keywords: Capstone course, CDIO, engineering education, project-oriented learning

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Authors: Ebasa Girma, Nathnael Minyelshowa, Lebsework Negash

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The use of unmanned aerial vehicles (UAVs) in precision agriculture has seen a huge increase recently. As such, systems that aim to apply various algorithms on the field need a structured framework of abstractions. This paper defines the various tasks of the UAVs in precision agriculture and models them into an architectural framework. The presented architecture is built on the context that there will be minimal physical intervention to do the tasks defined with multiple coordinated and cooperative UAVs. Various tasks such as image processing, path planning, communication, data acquisition, and field mapping are employed in the architecture to provide an efficient system. Besides, different limitation for applying Multi-UAVs in precision agriculture has been considered in designing the architecture. The architecture provides an autonomous end-to-end solution, starting from mission planning, data acquisition, and image processing framework that is highly efficient and can enable farmers to comprehensively deploy UAVs onto their lands. Simulation and field tests show that the architecture offers a number of advantages that include fault-tolerance, robustness, developer, and user-friendliness.

Keywords: deep learning, multi-UAVs, precision agriculture, UAVs architecture

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Authors: Anita Paddy, Millicent Obodai, Lebbaeus Asamani

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The management of sickle cell disease requires a multidisciplinary team for better outcomes. Thus, literature on the application of the biopsychosocial model for the management and explanation of chronic pain in sickle cell disease (SCD) and other chronic diseases abound. However, there is limited research on the use of the biopsychosocial model, together with a spiritual component (biopsychosocial-spiritual model). The study investigated the extent to which healthcare providers utilized the biopsychosocial-spiritual model in the management of chronic pain to improve the quality of life (QoL) of patients with SCD. This study employed the descriptive survey design involving a consecutive sampling of 261 patients with SCD who were between the ages of 18 to 79 years and were accessing hematological services at the Clinical Genetics Department of the Korle Bu Teaching Hospital. These patients willingly consented to participate in the study by appending their signatures. The theory of integrated quality of life, the gate control theory of pain and the biopsychosocial(spiritual) model were tested. An instrument for the biopsychosocial-spiritual model was developed, with a basis from the literature reviewed, while the World Health Organisation Quality of Life BREF (WHOQoLBref) and the spirituality rating scale were adapted and used for data collection. Data were analyzed using descriptive statistics (means, standard deviations, frequencies, and percentages) and partial least square structural equation modeling. The study revealed that healthcare providers had a great leaning toward the biological domain of the model compared to the other domains. Hence, participants’ QoL was not fully improved as suggested by the biopsychosocial(spiritual) model. Again, the QoL and spirituality of patients with SCD were quite high. A significant negative impact of spirituality on QoL was also found. Finally, the biosocial domain of the biopsychosocial-spiritual model was the most significant predictor of QoL. It was recommended that policymakers train healthcare providers to integrate the psychosocial-spiritual component in health services. Also, education on SCD and its resultant impact from the domains of the model should be intensified while health practitioners consider utilizing these components fully in the management of the condition.

Keywords: biopsychosocial (spritual), sickle cell disease, quality of life, healthcare, accra

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: G. Anjan Babu, G. Sumana, M. Rajasekhar

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Many inherited diseases and non-hereditary disorders are common in the development of renal cystic diseases. Polycystic kidney disease (PKD) is a disorder developed within the kidneys in which grouping of cysts filled with water like fluid. PKD is responsible for 5-10% of end-stage renal failure treated by dialysis or transplantation. New experimental models, application of molecular biology techniques have provided new insights into the pathogenesis of PKD. Researchers are showing keen interest for developing an automated system by applying computer aided techniques for the diagnosis of diseases. In this paper a multi-layered feed forward neural network with one hidden layer is constructed, trained and tested by applying back propagation learning rule for the diagnosis of PKD based on physical symptoms and test results of urinanalysis collected from the individual patients. The data collected from 50 patients are used to train and test the network. Among these samples, 75% of the data used for training and remaining 25% of the data are used for testing purpose. Furthermore, this trained network is used to implement for new samples. The output results in normality and abnormality of the patient.

Keywords: dialysis, hereditary, transplantation, polycystic, pathogenesis

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Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

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The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

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Authors: Cynthia A. Gallardo, Kelly S. Hall, Kristopher Garza, Linda Challoo, Mais Nijim

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Dual-enrollment programs have become more prevalent in college and high school settings. Also known as early college programs, dual-enrollment programs help students acquire a head start in earning college credit for post-secondary studies. The number and percentage of high school students who take college courses while in high school is growing. However, little is known about how dual-enrolled students fare. The classroom environment is important to learning. This study compares dually enrolled high school students who take courses that yield college credit either within their high school or at some other location. Mann-Whitney U was the statistical test used. Mean proportions were compared for each of the five standard letter grades earned across the state of Texas. Results indicated that students earn similar passing A, B, and C grades when they take dual-enrollment courses at their high school location but are more likely to fail if they take dual-enrollment courses at non-high school locations. Implications of results are that student success rate of dual-enrollment college courses may have a significant difference between the locations and student performance.

Keywords: educational leadership, dual-enrollment, student performance, college

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Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh

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Protection system is an essential feature of the electrical system which helps in detection and removal of faults. Protection system consists of many subsystems like relays, circuit breakers, instrument transformers, auxiliary DC system, auxiliary relays etc. Although the fundamental protective and relay operating concepts are similar throughout the world, there are very significant differences in their implementation. These differences arise through different traditions, operating philosophies, experiences and national standards. Protection system mis-operation due to problem in one or more of its subsystem or inadequate knowledge of numerical relay settings and configuration are very common throughout the world. Protection system mis-operation leads to unstable and unreliable grid operation. In this paper we will discuss about the fundamental concepts of protective relaying and the reasons for protection system mis-operation due to one or more of its subsystems. Many real-world case studies of protection system mis-operation from Indian power sector are discussed in detail in this paper.

Keywords: auxiliary trip relays, bus zone, check zone, CT saturation, dead zone protection, DC ground faults, DMT, DR, end fault protection, instrument transformer, SOTF, STUB

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Authors: H. K. V. Narayan

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This study was conducted at Tata Memorial Hospital (TMH), Mumbai, India. The study was to evaluate the impact of adapting Smart Card (SC) for clinical and business transactions in order to reduce Lead times and to enforce business rules of the hospital. The objective for implementing the Smart Card was to improve the patient perception of quality in terms of structures process and outcomes and also to improve the productivity of the Institution. The Smart Card was implemented in phases from 2011 and integrated with the Hospital Information System (HIS/EMR). The implementation was a learning curve for all the stake holders as software obviated the need to use hardcopies of transactions. The acceptability to the stake holders was challenge in change management. The study assessed the impact 3 years into the implementation and the observed trends have suggested that it has decreased the lead times for services and increased the no of transactions and thereby the productivity. Patients who used to complain of multiple queues and cumbersome transactions now compliment the administration for effective use of Information and Communication Technology.

Keywords: smart card, high availability of health care information, reduction in potential medical errors due to elimination of transcription errors, reduction in no of queues, increased transactions, augmentation of revenue

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Authors: Endrick Barnacin, Jean-Luc Henry, Jimmy Nagau, Jack Molinie

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Being able to identify biological particles such as spores, viruses, or pollens is important for health care professionals, as it allows for appropriate therapeutic management of patients. Optical microscopy is a technology widely used for the analysis of these types of microorganisms, because, compared to other types of microscopy, it is not expensive. The analysis of an optical microscope slide is a tedious and time-consuming task when done manually. However, using machine learning and computer vision, this process can be automated. The first step of an automated microscope slide image analysis process is segmentation. During this step, the biological particles are localized and extracted. Very often, the use of an automatic thresholding method is sufficient to locate and extract the particles. However, in some cases, the particles are not extracted individually because they are stuck to other biological elements. In this paper, we propose a stuck particles separation method based on the use of the Sobel operator and thresholding. We illustrate it by applying it to the separation of 813 images of adjacent pollen grains. The method correctly separated 95.4% of these images.

Keywords: image segmentation, stuck particles separation, Sobel operator, thresholding

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Authors: Daud Abdia, Aqsa Shamim, Farhan Tabassum

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In order to achieve specific goals, basketball players have to use different skills to enhance their motivation, one such skill is deliberate practice. The aim of this study was to explore the relationship between deliberate practice of dribbling and self-regulatory behavior of male basketball players. For this purpose, a sample of 108 basketball players using stratified sampling was taken from public and private sector universities. Sample was divided into two groups that are experimental (n=54) and control group (n=54) using comparative experimental design. Experimental group was involved in the training of deliberate practice of dribbling for 5 weeks. Amounts of weekly practice activity and Self-Regulation of Learning Self-Report Scale (SRL-SRS) were used for self-regulatory behavior to collect data after the deliberate practice. The reliability of amounts of weekly practice activity was found to be 0.852, whereas SRL-SRS was found to be 0.890. The results of the study indicated a strong positive correlation between deliberate practice of dribbling and self-regulatory behavior (r=0.755, n=54, p=.000). Whereas, paired sample t-test; t(53)=1.37, p < 0.005 shows statistically significant improvement in the self-regulatory behavior after the training program of deliberate practice from 3.02 ± 0.64m to 3.21 ± 0.75m (p < 0.005). It was concluded that in order to enhance the self-regulatory behavior of basketball players we should work on the deliberate practice of the players.

Keywords: self-regulatory behavior, deliberate practice, dribbling, basketball

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Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj

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New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.

Keywords: CS pedagogy, student research, cluster computing, machine learning

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Authors: Wisdom Robert Duruji

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

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

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Authors: Leonardo C. Pacheco-Londoño, Nataly J. Galan-Freyle, Lisandro Pacheco-Lugo, Antonio Acosta, Elkin Navarro, Gustavo Aroca-Martínez, Karin Rondón-Payares, Samuel P. Hernández-Rivera

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In our Life Science Research Center of the University Simon Bolivar (LSRC), one of the focuses is the diagnosis and prognosis of different diseases; we have been implementing the use of gold nanoparticles (Au-NPs) for various biomedical applications. In this case, Au-NPs were used for Surface-Enhanced Raman Spectroscopy (SERS) in different diseases' diagnostics, such as Lupus Nephritis (LN), hypertension (H), preeclampsia (PC), and others. This methodology is proposed for the diagnosis of each disease. First, good signals of the different metabolites by SERS were obtained through a mixture of urine samples and Au-NPs. Second, PLS-DA models based on SERS spectra to discriminate each disease were able to differentiate between sick and healthy patients with different diseases. Finally, the sensibility and specificity for the different models were determined in the order of 0.9. On the other hand, a second methodology was developed using machine learning models from all data of the different diseases, and, as a result, a discriminant spectral map of the diseases was generated. These studies were possible thanks to joint research between two university research centers and two health sector entities, and the patient samples were treated with ethical rigor and their consent.

Keywords: SERS, Raman, PLS-DA, diseases

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Authors: Marylene N. Tizon

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English instructors pay attention on errors committed by students as errors show whether they know or master their oral skills and what difficulties they may have in the process of learning the English language. This descriptive quantitative study aimed at identifying and categorizing the oral presentation errors of the purposively chosen 118 English 2A students enrolled during the first semester of school year 2013 – 2014. The analysis of the data for this study was undertaken using the errors committed by the students in their presentation. Marking and classifying of errors were made by first classifying them into linguistic grammatical errors then all errors were categorized further into Surface Structure Errors Taxonomy with the use of Frequency and Percentage distribution. From the analysis of the data, the researcher found out: Errors in tenses of the verbs (71 or 16%) and in addition 167 or 37% were most frequently uttered by the students. And Question and negation mistakes (12 or 3%) and misordering errors (28 or 7%) were least frequently enunciated by the students. Thus, the respondents in this study most frequently enunciated errors in tenses and in addition while they uttered least frequently the errors in question, negation, and misordering.

Keywords: grammatical error, oral presentation error, surface structure errors taxonomy, descriptive quantitative design, Philippines, Asia

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Authors: Mohammad Ali Alavidoost, Hossein Bozorgian

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Criterion-referenced tests (CRTs) are designed to measure student performance against a fixed set of predetermined criteria or learning standards. The reliability of such tests cannot be based on internal reliability. Threshold loss agreement is one way to calculate the reliability of CRTs. However, the selection of master and non-master in such agreement is determined by the threshold point. The problem is if the threshold point witnesses a minute change, the selection of master and non-master may have a drastic change, leading to the change in reliability results. Therefore, in this study, the Fuzzy logic approach is employed as a remedial procedure for data analysis to obviate the threshold point problem. Forty-one Iranian students were selected; the participants were all between 20 and 30 years old. A quantitative approach was used to address the research questions. In doing so, a quasi-experimental design was utilized since the selection of the participants was not randomized. Based on the Fuzzy logic approach, the threshold point would be more stable during the analysis, resulting in rather constant reliability results and more precise assessment.

Keywords: criterion-referenced tests, threshold loss agreement, threshold point, fuzzy logic approach

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Authors: Pichamon Chansuchai

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This paper studied the expanding market opportunity palm oil ASEAN community: case study of Choomporn Palm Oil Cooperative as qualitative research. The purpose is to study and analyze expanding and linking the liberalization of trade in palm oil products under the terms of cooperation and ASEAN countries. Collection data were collected using participatory observation, in-depth interviews, focus groups, government officials, palm oil cooperative, entrepreneurs and farmers to exchange opinions. The study found that of major competitors is Indonesia and Malaysia which as ASEAM members countries has the potential to produce over Thailand. Thailand government must have a policy to increase the competitiveness of the palm oil Thailand. Using grants from the Free Trade Area fund should add value to agricultural products, palm oil and the development of standard products to meet the needs of the member countries. And creating a learning center of the palm oil sector can transfer knowledge, development of palm species, solution process from planting to harvest care privatization process. And the development of palm oil in order to expand market opportunities for Thailand's palm oil has the potential to be competitive in the neighboring countries and the region.

Keywords: palm oil, market, cooperative, ASEAN

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Authors: Mohit Gupta, Chialing Wei, Thomas Czerniawski

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In this paper, we have built a neural network that can detect walls on 2D sheets and subsequently create a 3D model in Revit using Dynamo. The training set includes 3500 labeled images, and the detection algorithm used is YOLO. Typically, engineers/designers make concentrated efforts to convert 2D cad drawings to 3D models. This costs a considerable amount of time and human effort. This paper makes a contribution in automating the task of 3D walls modeling. 1. Detecting Walls in 2D cad and generating 3D pop-ups in Revit. 2. Saving designer his/her modeling time in drafting elements like walls from 2D cad to 3D representation. An object detection algorithm YOLO is used for wall detection and localization. The neural network is trained over 3500 labeled images of size 256x256x3. Then, Dynamo is interfaced with the output of the neural network to pop-up 3D walls in Revit. The research uses modern technological tools like deep learning and artificial intelligence to automate the process of generating 3D walls without needing humans to manually model them. Thus, contributes to saving time, human effort, and money.

Keywords: neural networks, Yolo, 2D to 3D transformation, CAD object detection

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Authors: Shreyas Gambhirrao, Aditya Vichare, Aniket Tembhurne, Shahuraj Bhosale

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In today's rapidly evolving environment, stress has emerged as a significant health concern across different age groups. Stress that isn't controlled, whether it comes from job responsibilities, health issues, or the never-ending news cycle, can have a negative effect on our well-being. The problem is further aggravated by the ongoing connection to technology. In this high-tech age, identifying and controlling stress is vital. In order to solve this health issue, the study focuses on three key metrics for stress detection: body temperature, heart rate, and galvanic skin response (GSR). These parameters along with the Support Vector Machine classifier assist the system to categorize stress into three groups: 1) Stressed, 2) Not stressed, and 3) Moderate stress. Proposed training model, a NodeMCU combined with particular sensors collects data in real-time and rapidly categorizes individuals based on their stress levels. Real-time stress detection is made possible by this creative combination of hardware and software.

Keywords: real time stress detection, NodeMCU, sensors, heart-rate, body temperature, galvanic skin response (GSR), support vector machine

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Authors: A. Pedro, T. Goldschmidt

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Socio-emotional development is considered to be an essential prerequisite for school readiness. To our best knowledge, research on socio-emotional development specifically from the views of teachers in the South African context is limited. This study explored preschool teachers’ understanding of the role that socio-emotional development plays in preparing the child for school. Using the social learning theory, a qualitative approach with an exploratory design was used for the study. A total of 12 preschool teachers from both community-based and school-based preschools were purposively recruited. Upon receiving ethics clearance from the University of the Western Cape and the Western Cape Education Department, semi-structured interviews were conducted and analysed by utilizing Braun and Clarke’s (2006) six phases of thematic analysis. Participants’ rights, anonymity, and confidentiality were upheld throughout the research process. Findings reveal that preschool teachers emphasise the importance of holistic development for school readiness. Teachers deemed socio-emotional development as absolutely crucial for preparing children for school as it eases the transition to formal schooling and adaptation to the classroom environment.

Keywords: early childhood, preschool teachers, school readiness, socio-emotional development

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Authors: Siti Navila

Abstract:

Hedging as a kind of pragmatic competence is an essential part in achieving the goal in communication, especially in academic discourse where the process of sharing knowledge among academic community takes place. Academic discourse demands an appropriateness and modesty of an author or speaker in stating arguments, to name but few, by considering the politeness, being cautious and tentative, and differentiating personal opinions and facts in which these aspects can be achieved through hedging. This study was conducted to find the hedging devices used by students as well as to analyze how they use them in their oral presentation. Some oral presentations from English Department students of the State University of Jakarta on their Academic Presentation course final test were recorded and explored formally and functionally. It was found that the most frequent hedging devices used by students were shields from all hedging devices that students commonly used when they showed suggestion, stated claims, showed opinion to provide possible but still valid answer, and offered the appropriate solution. The researcher suggests that hedging can be familiarized in learning, since potential conflicts that is likely to occur while delivering ideas in academic contexts such as disagreement, criticism, and personal judgment can be reduced with the use of hedging. It will also benefit students in achieving the academic competence with an ability to demonstrate their ideas appropriately and more acceptable in academic discourse.

Keywords: academic discourse, hedging, hedging devices, lexical hedges, Meyer classification

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Authors: Edward Schwalb, Matthias Dehmer, Michael Schlenkrich, Farzaneh Taslimi, Ketron Mitchell-Wynne, Horen Kuecuekyan

Abstract:

We present a generalized feature extraction approach for supporting Machine Learning (ML) algorithms which perform tasks similar to Finite-Element Analysis (FEA). We report results for estimating the Head Injury Categorization (HIC) of vehicle engine compartments across various impact scenarios. Our experiments demonstrate that models learned using features derived with a simple discretization approach provide a reasonable approximation of a full simulation. We observe that Decision Trees could be as effective as Neural Networks for the HIC task. The simplicity and performance of the learned Decision Trees could offer a trade-off of a multiple order of magnitude increase in speed and cost improvement over full simulation for a reasonable approximation. When used as a complement to full simulation, the approach enables rapid approximate feedback to engineering teams before submission for full analysis. The approach produces mesh independent features and is further agnostic of the assembly structure.

Keywords: mechanical design validation, FEA, supervised decision tree, convolutional neural network.

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Authors: Joanna Estkowska

Abstract:

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

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

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Authors: Karthick Prasad Gunasekaran, B. Chase Babrich, Saurabh Shirodkar, Hee Hwang

Abstract:

Construction preparation is crucial for the success of a construction project. By involving project participants early in the construction phase, project managers can plan ahead and resolve issues early, resulting in project success and satisfaction. This study uses quantitative data from construction management projects to determine the relationship between the pre-construction phase, construction schedule, and customer satisfaction. This study examined a total of 65 construction projects and 93 clients per job to (a) identify the relationship between the pre-construction phase and program reduction and (b) the pre-construction phase and customer retention. Based on a quantitative analysis, this study found a negative correlation between pre-construction status and project schedule in 65 construction projects. This finding means that the more preparatory work done on a particular project, the shorter the total construction time. The Net Promoter Score of 93 clients from 65 projects was then used to determine the relationship between construction preparation and client satisfaction. The pre-construction status and the projects were further analyzed, and a positive correlation between them was found. This shows that customers are happier with projects with a higher ready-to-build ratio than projects with less ready-to-build.

Keywords: NLP, BERT, LLM, deep learning, classification

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Authors: Yuko Tomoto

Abstract:

The purpose of this research is to examine the assumption that female bilingual speakers more often change the way they talk or think depending on the language they use compared with male bilingual speakers. The author collected data through questionnaires on 241 bilingual speakers. Also, in-depth interview surveys were conducted with 13 Japanese/English bilingual speakers whose native language is Japanese and 16 English/Japanese bilingual speakers whose native language is English. The results indicate that both male and female bilingual speakers are more or less influenced consciously and unconsciously by the language they use, as well as by the background cultural values of each language. At the same time, it was found that female speakers are much more highly affected by the language they use, its background culture and also by the interlocutors they were talking to. This was probably due to the larger cultural expectations on women. Through conversations, speakers are not only conveying a message but also attempting to express who they are, and what they want to be like. In other words, they are constantly building up and updating their own identities by choosing the most appropriate language and descriptions to express themselves in the dialogues. It has been claimed that the images of ideal L2 self could strongly motivate learners. The author hopes to make the best use of the fact that bilingual speakers change their presence depending on the language they use, in order to motivate Japanese learners of English, especially female learners from the viewpoint of finding their new selves in English.

Keywords: cultural influence, gender expectation, language learning, L2 self

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Authors: Neha Bhushan

Abstract:

For the purpose of this study a village of district Azamgarh has been selected which is a part of the most populous and backward state of the country, Uttar Pradesh. In the age of information, everyone has the right to acquire information and it becomes important to assess the acceptance and non-acceptance of social media among rural population. Rural women of the state are showing positive trends in the form of increased social media and mobile usage. This study is an effort to know the purpose of rural women for using social media. The study design is exploratory and qualitative in nature. Data collection primarily consisted of 25 semi-structured individual interviews having 10 open-ended specific questions in one of the villages of Azamgarh district of Eastern Uttar Pradesh. Sampling approach is flexible and situational. Data reveals that rural women have become active on social media since last six months to one year. Most of them are using Facebook, Whatsapp, and YouTube for the purpose of interaction, learning new skills, checking out recipes and latest fashion. This pilot study gives a bird eye view of the problem and opens door for exploring this least explored area.

Keywords: exploratory research, mobile usage, rural women, social media

Procedia PDF Downloads 145