Search results for: learning science in english

Authors: Junqi Zou

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As one of the world’s most tech-ready countries, Singapore has initiated the Smart Nation plan to harness the full power and potential of digital technologies to transform the way people live and work, through the more efficient government and business processes, to make the economy more productive. The key evolutions of digital technology transformation in healthcare and the increasing deployment of Internet of Things (IoTs), Big Data, AI/cognitive, Robotic Process Automation (RPA), Electronic Health Record Systems (EHR), Electronic Medical Record Systems (EMR), Warehouse Management System (WMS in the most recent decade have significantly stepped up the move towards an information-driven healthcare ecosystem. The advances in information technology not only bring benefits to patients but also act as a key force in changing management accounting in healthcare sector. The aim of this study is to investigate the impacts of digital technology transformation on Singapore’s healthcare sector from a management accounting perspective. Adopting a Balanced Scorecard (BSC) analysis approach, this paper conducted an exploratory case study of a newly launched Singapore public hospital, which has been recognized as amongst the most digitally advanced healthcare facilities in Asia-Pacific region. Specifically, this study gains insights on how the new technology is changing healthcare organizations’ management accounting from four perspectives under the Balanced Scorecard approach, 1) Financial Perspective, 2) Customer (Patient) Perspective, 3) Internal Processes Perspective, and 4) Learning and Growth Perspective. Based on a thorough review of archival records from the government and public, and the interview reports with the hospital’s CIO, this study finds the improvements from all the four perspectives under the Balanced Scorecard framework as follows: 1) Learning and Growth Perspective: The Government (Ministry of Health) works with the hospital to open up multiple training pathways to health professionals that upgrade and develops new IT skills among the healthcare workforce to support the transformation of healthcare services. 2) Internal Process Perspective: The hospital achieved digital transformation through Project OneCare to integrate clinical, operational, and administrative information systems (e.g., EHR, EMR, WMS, EPIB, RTLS) that enable the seamless flow of data and the implementation of JIT system to help the hospital operate more effectively and efficiently. 3) Customer Perspective: The fully integrated EMR suite enhances the patient’s experiences by achieving the 5 Rights (Right Patient, Right Data, Right Device, Right Entry and Right Time). 4) Financial Perspective: Cost savings are achieved from improved inventory management and effective supply chain management. The use of process automation also results in a reduction of manpower costs and logistics cost. To summarize, these improvements identified under the Balanced Scorecard framework confirm the success of utilizing the integration of advanced ICT to enhance healthcare organization’s customer service, productivity efficiency, and cost savings. Moreover, the Big Data generated from this integrated EMR system can be particularly useful in aiding management control system to optimize decision making and strategic planning. To conclude, the new digital technology transformation has moved the usefulness of management accounting to both financial and non-financial dimensions with new heights in the area of healthcare management.

Keywords: balanced scorecard, digital technology transformation, healthcare ecosystem, integrated information system

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Authors: Hyunbin Choi, Jihyeon Noh, Changwon Lim

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In this paper, we propose SiamMask++, an architecture that performs layer-wise aggregation and depth-wise cross-correlation and introduce multi-RPN module and multi-MASK module to improve EAO (Expected Average Overlap), a representative performance evaluation metric for Visual Object Tracking (VOT) challenge. The proposed architecture, SiamMask++, has two versions, namely, bi_SiamMask++, which satisfies the real time (56fps) on systems equipped with GPUs (Titan XP), and rf_SiamMask++, which combines mask refinement modules for EAO improvements. Tests are performed on VOT2016, VOT2018 and VOT2019, the representative datasets of Visual Object Tracking tasks labeled as rotated bounding boxes. SiamMask++ perform better than SiamMask on all the three datasets tested. SiamMask++ is achieved performance of 62.6% accuracy, 26.2% robustness and 39.8% EAO, especially on the VOT2018 dataset. Compared to SiamMask, this is an improvement of 4.18%, 37.17%, 23.99%, respectively. In addition, we do an experimental in-depth analysis of how much the introduction of features and multi modules extracted from the backbone affects the performance of our model in the VOT task.

Keywords: visual object tracking, video, deep learning, layer wise aggregation, Siamese network

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Authors: Balarabe Bilyaminu Ismail, Osman Cavus, Fügen Durlu Özkaya

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This study is aimed at determining the level of awareness of chefs and students of food science and technology on food safety in general and allergens in particular. To get appropriate data, a questionnaire comprising of 19 questions covering many food safety issues and allergens in foods were used to collect information for the study through face to face interviews. Interviews were conducted for 284 people in Nigeria and Turkey. Sixty-eight percent of respondents from Turkey; 31.3% were students and 68.7% were chefs. Thirty-one percent of respondents from Nigeria include 33.7% students and 66.3% chefs. The result of the study indicated that most of the findings of scientific studies on food safety issues have not been directly applied by the people working in the food sector. Additionally, the knowledge level of the gastronomy and culinary arts students on food safety and allergens are significantly higher than the restaurant chefs that prepare the food and serve it to the public. The study, therefore, concluded that proper training of food business operators is critical to ensuring the safety of foods and control of allergens.

Keywords: allergens, food safety, questionnaire survey, training

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Authors: Meghana Shankara, Priyadarshini Natarajan

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Infrared (IR) spectroscopy has revolutionized the way we look at materials around us. Unraveling the pattern in the molecular spectra of materials to analyze the composition and properties of it has been one of the most interesting challenges in modern science. Applications of the IR spectrometry are numerous in the field’s pharmaceuticals, health, food and nutrition, oils, agriculture, construction, polymers, beverage, fabrics and much more limited only by the curiosity of the people. Near Infrared (NIR) spectrometry is applied robustly in analyzing the solids and liquid substances because of its non-destructive analysis method. In this paper, we have reviewed the application of NIR spectrometry in milk quality analysis and have presented the modes of measurement applied in NIRS measurement setup, Design of Experiment (DoE), classification/quantification algorithms used in the case of milk composition prediction like Fat%, Protein%, Lactose%, Solids Not Fat (SNF%) along with different approaches for adulterant identification. We have also discussed the important NIR ranges for the chosen milk parameters. The performance metrics used in the comparison of the various Chemometric approaches include Root Mean Square Error (RMSE), R^2, slope, offset, sensitivity, specificity and accuracy

Keywords: chemometrics, design of experiment, milk quality analysis, NIRS measurement modes

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Authors: Lule Basha, Eralda Gjika

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The exchange rate is one of the most important economic variables, especially for a small, open economy such as Albania. Its effect is noticeable in one country's competitiveness, trade and current account, inflation, wages, domestic economic activity, and bank stability. This study investigates the fluctuation of Albania’s exchange rates using monthly average foreign currency, Euro (Eur) to Albanian Lek (ALL) exchange rate with a time span from January 2008 to June 2021, and the macroeconomic factors that have a significant effect on the exchange rate. Initially, the Random Forest Regression algorithm is constructed to understand the impact of economic variables on the behavior of monthly average foreign currencies exchange rates. Then the forecast of macro-economic indicators for 12 months was performed using time series models. The predicted values received are placed in the random forest model in order to obtain the average monthly forecast of the Euro to Albanian Lek (ALL) exchange rate for the period July 2021 to June 2022.

Keywords: exchange rate, random forest, time series, machine learning, prediction

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Authors: Botirjon Kosimov

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This work sheds light on the reforms towards the independence of the judiciary in Uzbekistan, as well as issues of further ensuring judicial independence in the country based on international values, particularly the legal practice of the United States. In every democratic state infringed human rights are reinstated and violated laws are protected by the help of justice based on the strict principle of judicial independence. The realization of this principle in Uzbekistan has been paid much attention since the proclamation of its independence. In the country, a series of reforms have been implemented in the field of the judiciary in order to actualize the principle of judicial independence. Uzbekistan has been reforming the judiciary considering both international and national values and practice of foreign countries. While forming a democratic state based on civil society, Uzbekistan shares practice with the most developed countries in the world. The United States of America can be a clear example which is worth learning how to establish and ensure an independent judiciary. It seems that although Uzbekistan has reformed the judiciary efficiently, it should further reform considering the legal practice of the United States.

Keywords: dependent judges, independent judges, judicial independence, judicial reforms, judicial life tenure, obstacles to judicial independence

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Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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Authors: Nadia Masood Khan, Muhammad Salman Khan, Gul Muhammad Khan

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Cardiologists perform cardiac auscultation to detect abnormalities in heart sounds. Since accurate auscultation is a crucial first step in screening patients with heart diseases, there is a need to develop computer-aided detection/diagnosis (CAD) systems to assist cardiologists in interpreting heart sounds and provide second opinions. In this paper different algorithms are implemented for automated heart sound classification using unsegmented phonocardiogram (PCG) signals. Support vector machine (SVM), artificial neural network (ANN) and cartesian genetic programming evolved artificial neural network (CGPANN) without the application of any segmentation algorithm has been explored in this study. The signals are first pre-processed to remove any unwanted frequencies. Both time and frequency domain features are then extracted for training the different models. The different algorithms are tested in multiple scenarios and their strengths and weaknesses are discussed. Results indicate that SVM outperforms the rest with an accuracy of 73.64%.

Keywords: pattern recognition, machine learning, computer aided diagnosis, heart sound classification, and feature extraction

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Authors: Jaspreet Singh, Gurvinder Singh, Prabhsimran Singh, Rajinder Singh, Prithvipal Singh, Karanjeet Singh Kahlon, Ravinder Singh Sawhney

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Morphological evaluation of Indian languages is one of the burgeoning fields in the area of Natural Language Processing (NLP). The evaluation of a language is an eminent task in the era of information retrieval and text mining. The extraction and classification of knowledge from text can be exploited for sentiment analysis and morphological evaluation. This study coalesce morphological evaluation and sentiment analysis for the task of classification of farmer suicide cases reported in Punjab state of India. The pre-processing of Punjabi text involves morphological evaluation and normalization of Punjabi word tokens followed by the training of proposed model using deep learning classification on Punjabi language text extracted from online Punjabi news reports. The class-wise accuracies of sentiment prediction for four negatively oriented classes of farmer suicide cases are 93.85%, 88.53%, 83.3%, and 95.45% respectively. The overall accuracy of sentiment classification obtained using proposed framework on 275 Punjabi text documents is found to be 90.29%.

Keywords: deep neural network, farmer suicides, morphological processing, punjabi text, sentiment analysis

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Eftah Bte. Moh Hj Abdullah, Izazol Binti Idris, Abd Aziz Bin Abd Shukor

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This study aims to identify the understanding expectations of school administrators concerning school assessment. The researcher utilized a qualitative descriptive study on 19 administrators from three secondary schools in the North Kinta district. The respondents had been interviewed on their understanding expectations of school assessment using the focus group discussion method. Overall findings showed that the administrators’ understanding expectations of school assessment was weak; especially in terms of content focus, articulation across age and grade, transparency and fairness, as well as the pedagogical implications. Findings from interviews indicated that administrators explained their understanding expectations of school assessment from the aspect of school management, and not from the aspect of instructional leadership or specifically as assessment leaders. The study implications from the administrators’ understanding expectations may hint at the difficulty of the administrators to function as assessment leaders, in order to reduce their focus as manager, and move towards their primary role in the process of teaching and learning. The administrator, as assessment leaders, would be able to reach assessment goals via collaboration in identifying and listing teacher assessment competencies, how to construct assessment capacity, how to interpret assessment correctly, the use of assessment and how to use assessment information to communicate confidently and effectively to the public.

Keywords: assessment leaders, assessment goals, instructional leadership, understanding expectation of assessment

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: S. Gordon

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Dual language immersion is growing fast in language teaching today. This study provides an overview and evaluation of the different models of Dual language immersion programs in US K-12 schools. First, the paper provides a brief current literature review on the theory of Dual Language Immersion (DLI) in Second Language Acquisition (SLA) studies. Second, examples of several types of DLI language teaching models in US K-12 public schools are presented (including 50/50 models, 90/10 models, etc.). Third, we focus on the unique example of DLI education in the state of Utah, a successful, growing program in K-12 schools that includes: French, Chinese, Spanish, and Portuguese. The project investigates the theory and practice particularly of the case of public elementary and secondary school children that study half their school day in the L1 and the other half in the chosen L2, from kindergarten (age 5-6) through high school (age 17-18). Finally, the project takes the observations of Utah French DLI elementary through secondary programs as a case study. To conclude, we look at the principal challenges, pedagogical objectives and outcomes, and important implications for other US states and other countries (such as France currently) that are in the process of developing similar language learning programs.

Keywords: dual language immersion, second language acquisition, language teaching, pedagogy, teaching, French

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Authors: Surendar Vaddepalli

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Management education plays a crucial role to enable industry to cope with emerging challenges. It has spread in the last fifteen-twenty years in India and gained popularity as it was aimed at imbibing versatility and multi-tasking abilities in student community. Several management institutions started looking at upgrading their competencies in terms of faculty, research and industry interaction. The competitive business environment has been one of the drivers that paved the way for growing demand for management graduates in the employment market. Industry expects their executives to be engaged in a constant learning process. The ever-increasing demand for managers has led to establish more management institutions; however, the growth was not in line with the expectations from the industry. While top Business Schools are continuously changing the contents and delivery methodologies, academic standards of most of the other Business Schools are not up to the mark and quality of service provided by these institutes has opened various issues for discussion. On this back ground it is important to address the concerns of Indian management education experiencing with time and we have to rethink about the management education and efforts should be made to create a dynamic environment. This paper ties to study the current trends and tries to find out need for value based management education in India to rejuvenate it.

Keywords: management education, management, value based management education, business school, India

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Authors: Widyani Fatwa Dewi, Subroto Athor

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In a telecommunication service provider, quantity and interval of customer demand often difficult to predict due to high dependency on customer expansion strategy and technological development. Demand arrives when a customer needs to add capacity to an existing site or build a network in a new site. Because demand is uncertain for each period, and sometimes there is a null demand for several equipments, it is categorized as intermittent. This research aims to improve demand forecast quality in Indonesia's telecommunication service providers by using Artificial Neural Network. In Artificial Neural Network, the pattern or relationship within data will be analyzed using the training process, followed by the learning process as validation stage. Historical demand data for 36 periods is used to support this research. It is found that demand forecast by using Artificial Neural Network outperforms the existing method if it is reviewed on two criteria: the forecast accuracy, using Mean Absolute Deviation (MAD), Mean of the sum of the Squares of the Forecasting Error (MSE), Mean Error (ME) and service level which is shown through inventory cost. This research is expected to increase the reference for a telecommunication demand forecast, which is currently still limited.

Keywords: artificial neural network, demand forecast, forecast accuracy, intermittent, service level, telecommunication

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Authors: Tuğçe Yavaş Akış

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In recent years, due to an increased use of radioactive materials, radioactive sources are constantly being transported via air, road and ocean ways for medical, industrial, research etc. purposes throughout the world. The quantity of radioactive materials transported all around the world varies from negligible quantities in shipments of consumer products to very large quantities in shipments of irradiated nuclear fuel. Radioactive materials have been less attractive for social science researchers in literature. In this study, it is aimed to discover desired flow of radioactive materials from logistics service quality (LSQ) perspective. In doing so, case study approach will be employed by using secondary data collected from one of the world’s leading transportation companies’ customer care system reports. Movement of radioactive cargoes containing IR-192 and logistics process will be analyzed with the help of logistics service quality dimensions. Based on the case study that will be conducted, interaction between dimensions, the importance of each dimension in desired flow, and their relevance with desired flow of radioactive materials will be explained. This study will bring out the desired flow of radioactive materials transportation and be a guide for all other companies, employees and researchers.

Keywords: logistics service quality, LSQ dimension , radioactive material, transportation

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Authors: Guerriche Amina

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The recent trends in foreign language teaching -influenced widely by the process of globalization, interculturalism, and global flows and migration- are leaning towards adopting an intercultural perspective to help in developing students who are global citizens able to effectively function across diverse boundaries (cultural, social, geographical). Researchers call for intercultural learning and teaching perspective that would foster and increase intercultural awareness and understanding (e.g., Guilherme, 2002; Byram et al., 2002). The present research aims at unfolding whether including the cultural dimension in foreign language instruction can help in developing students’ intercultural understanding and awareness. In doing so, a cultural pedagogical experiment was designed and conducted for the period of one year at the level of the university. Data were collected qualitatively and analyzed thematically. Results help in drawing important implications for educational institutions, foreign language teachers, and syllabus designers about the importance and effectiveness of perceiving foreign language instruction as a social activity that can nurture interculturally competent individuals who adequately respond to the demands of today’s intercultural and globalized societies.

Keywords: foreign language teaching, intercultural awareness, language and culture, intercultural understanding

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Authors: Daniel James Pitchforth, Timothy James Rogers, Ulf Tyge Tygesen, Elizabeth Jane Cross

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Wave loading is a primary cause of fatigue within offshore structures and its quantification presents a challenging and important subtask within the SHM framework. The accurate representation of physics in such environments is difficult, however, driving the development of data-driven techniques in recent years. Within many industrial applications, empirical laws remain the preferred method of wave loading prediction due to their low computational cost and ease of implementation. This paper aims to develop an approach that combines data-driven Gaussian process models with physical empirical solutions for wave loading, including Morison’s Equation. The aim here is to incorporate physics directly into the covariance function (kernel) of the Gaussian process, enforcing derived behaviors whilst still allowing enough flexibility to account for phenomena such as vortex shedding, which may not be represented within the empirical laws. The combined approach has a number of advantages, including improved performance over either component used independently and interpretable hyperparameters.

Keywords: offshore structures, Gaussian processes, Physics informed machine learning, Kernel design

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Authors: Muhammad Iqbal, Edi Istiyono

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Misconceptions are one of the problems in physics learning where students' understanding is not in line with scientific theory. The aim of this research is to find diagnostic tools to identify misconceptions and how to remediate physics misconceptions. In this research, the articles that will be reviewed come from the Scopus database related to physics misconceptions from 2013-2023. The articles obtained from the Scopus database were then selected according to the Prisma model, so 29 articles were obtained that focused on discussing physics misconceptions, especially regarding diagnostic tools and remediation methods. Currently, the most widely used diagnostic tool is the four-tier test, which is able to measure students' misconceptions in depth by knowing whether students are guessing or not and from then on, there is also a trend toward five-tier diagnostic tests with additional sources of information obtained. So that the origin of students' misconceptions is known. There are several ways to remediate student misconceptions, namely 11 ways and one of the methods used is digital practicum so that abstract things can be visualized into real ones. This research is limited to knowing what tools are used to diagnose and remediate misconceptions, so it is not yet known how big the effect of remediation methods is on misconceptions. The researcher recommends that in the future further research can be carried out to find out the most appropriate remediation method for remediating student misconceptions.

Keywords: misconception, remediation, systematic review, tools

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Authors: Haofei Li

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To support academic growth and foster love of learning, MathMates has been introduced for grade 6-8 students at Andrew Hamilton public school in 2022. The program is targeted at students from diverse backgrounds, particularly those underperforming in Pennsylvania System of School Assessment (PSSA) exams. Then, this study aims to evaluate the efficacy of MathMates by comparing student performance on the PSSA test, before and after the intervention. Through a randomized control trial, the study will collect associated costs using the ingredients method and measure the effectiveness for cost-effectiveness analysis. Text messages will be sent to parents/guardians as a reminder of the program and to encourage student participation. The findings of this study will provide valuable insights for funding organizations seeking to understand the impact and costs of math tutoring interventions on student academic achievement, which also emphasizes the importance of the collaborative efforts between higher education and local public schools.

Keywords: mathematics education, mathematics tutoring, college-community initiative, middle schools, Philadelphia public schools, after-school program, PSSA

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: Adam Bereczk

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Due to persistent socioeconomic problems regarding sustainability and labour market equilibrium in Europe, the subjects of social economy gained considerable academic attention recently. At the meantime, social enterprises pursuing the double bottom line criteria, struggling to find the proper management philosophies and strategies to make their social purpose business financially sustainable. Despite the strategic management literature was developed mainly on the bases of large corporations, in the past years, the interpretation of strategy concepts became a frequent topic in scientific discussions in the case of small and medium-sized enterprises also. The topic of strategic orientations is a good example of the trend. However, less is known about the case of social enterprises, despite the fact, the majority of them are small businesses engaged in real business activities. The main purpose of this work is to give a comprehensive summary of different perspectives regarding the interpretations of strategic orientations of social enterprises. The novelty of this work is it shows the previous outcomes and models of scholars from various fields of economic science who tried to intertwine the two spheres in different forms, methodize the findings and draw attention to the shortcomings.

Keywords: social enterprises, business sustainability, strategic orientations, literature review

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Authors: Fahad Al-Mufadi, F. Djavanroodi

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Ultrafine grained (UFG) and nanostructured (NS) materials have experienced a rapid development during the last decade and made profound impact on every field of materials science and engineering. The present work has been undertaken to develop ultra-fine grained pure copper by severe plastic deformation method and to examine the impact property by different characterizing tools. For this aim, equal channel angular pressing die with the channel angle, outer corner angle and channel diameter of 90°, 17° and 20 mm had been designed and manufactured. Commercial pure copper billets were ECAPed up to four passes by route BC at the ambient temperature. The results indicated that there is a great improvement at the hardness measurement, yield strength and ultimate tensile strength after ECAP process. It is found that the magnitudes of HV reach 136HV from 52HV after the final pass. Also, about 285% and 125% enhancement at the YS and UTS values have been obtained after the fourth pass as compared to the as-received conditions, respectively. On the other hand, the elongation to failure and impact energy have been reduced by imposing ECAP process and pass numbers. It is needed to say that about 56% reduction in the impact energy have been attained for the samples as contrasted to annealed specimens.

Keywords: SPD, ECAP, pure cu, impact property

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Authors: Md. Kamal Uddin

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Bangladesh is trying to achieve Sustainable Development Goals (SDGs) by 2030. Environmental Education (EE) is very vital to reaching the agenda of SDGs. However, a lack of environmental awareness and gaps in theoretical knowledge and its practices still exists in Bangladesh. Therefore, this research aims to understand the students’ perceptions of whether and how their behaviour is environment-friendly to achieve SDGs. It also addresses teachers’ perceptions of what are the shortcomings of environmental education in Bangladesh. It uses the qualitative and quantitative techniques of data collection and analysis based on in-depth interviews, surveys among different categories of participants and classroom observation. The paper finds that the level of EE and students’ awareness of the environment is inadequate. Some teachers believe that the EE is not better in Bangladesh due to the absence of practical learning of EE, lack of the motivations and actions, institutional weakness, inadequate policies, poor implementation, and cultural and traditional beliefs. Thus, this paper argues that Bangladeshi EE is not adequate to change the behaviour of the students towards the environment, which makes it difficult for the country to ensure SD. Thus, this research suggests that there is a need to revise the environmental education policy to change the behaviour and structure of the country for sustainable development.

Keywords: environmental education, sustainable development, environmental practice, environmental behaviour, Bangladesh

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Authors: Ali Akbar Zeinali

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Lack of appropriate equivalences for the terms or technical words is the result of ineffective translation guidelines adopted in the translation processes. The increasing number of foreign words and specific terms incorporated into the native language are due to the ongoing development of technology and science. Many problems appear in medical translation when the Persian translators try to employ non-Persian or imported words in medical texts, in which multiple equivalents may be created for one particular word based on the individual preferences of authors and translators in the target language due to lack of standardization. The study attempted to discuss the findings based on the compatibility of the international naming criteria, considering the translation procedures. About 67% of 339 equivalents under this study were grouped as incompatible words while about 33% of them were compatible terms. The similarities and differences were investigated and discussed according to the compatibility status of the equivalents with Sager’s criteria. Such equivalents have been classified into several groups through bi-dimensional descriptions that were different features of translation procedures related to the international naming criteria. In review of the frequency distribution of compatibilities, the equivalents were divided into two categories of compatibles and incompatibles, indicating the effectiveness of the applied translation procedures.

Keywords: linguistics, medical translation, naming, terminology

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Authors: Yi Meng, YunGao

Abstract:

Having been studied and worked in North America and Europe, we, two Chinese art educators, have been enormously influenced by eastern and western cultures. Thus, we aim to enhance students’ learning experiences by exploring and amalgamating both cultures for art creating. This text draws on our action research study of students’ visual literacy practices in a foundation sketching course in a major Chinese university, exploring art forms by cross-utilizing various cultural aspects. Instead of relying on the predominant western observational drawing skills in our classroom, we taught students about ancient Chinese art in the provincial museum, using Fu Hao owl-shaped vessel, a Shang Dynasty national treasure, as the final sketch project of this course. We took up multimodal literacy, which emphasized students’ critical use of creativity to exploit the semiotic potentials of communicative modes to address diverse cultural issues through their multimodal design. We used the Hong Kong-based artist Tik Ka’s artworks to demonstrate the cultural amalgamation of Chinese traditions and western pop cultures. Collectively, these approaches create a dialogical space for students to experience, analyze, and negotiate with complex modes and potentially transform their understanding of both cultures by redesigning Fu Hao.

Keywords: Chinese traditions, western pop cultures, Fu Hao, arts education, design sketch

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Authors: Matthew Perkins-McVey

Abstract:

The pharmacological arm of mental health treatment is in a state of crisis. The promises of the Prozac century have fallen short; the number of different therapeutically significant medications that successfully complete development shrinks with every passing year, and the demand for better treatments only grows. Answering these hardships is a renewed optimism concerning the efficacy of controlled psychedelic therapy, a renaissance that has seen the return of a familiar concept: intoxication as a model psychosis. First appearing in the mid-19th century and featuring in an array of 20th century efforts in psychedelic research, model psychosis has, once more, come to the foreground of psychedelic research. And yet, little has been made of where this peculiar, perhaps even intoxicatingly mad, the idea originates. This paper seeks to uncover the conceptual foundations underlying the early emergence of model psychosis. This narrative will explore the conceptual foundations behind their independent development of the concept of model psychosis, considering their similarities and differences. In the course of this examination, it becomes apparent that the definition of endogenous psychosis, which formed in the mid-19th century, is the direct product of emerging understandings of exogenous psychosis, or model psychosis. Ultimately, the goal is not merely to understand how and why model psychosis became thinkable but to examine how seemingly secondary concept changes can engender new ways of being a psychiatric subject.

Keywords: history of psychiatry, model psychosis, history of medicine, history of science

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Authors: Seyed Mohammadbagher Jafari, Izmeera Shiham, Masoud Arianfar

Abstract:

The increased usage of Social media for different uses in turn makes it important to develop an understanding of users and their attitudes toward these sites, and moreover, the uses of such sites in a broader perspective such as broadcasting. This quantitative study addressed the problem of factors influencing the adoption of social media as a medium of public service broadcasting in the Republic of Maldives. These powerful and increasingly usable tools, accompanied by large public social media datasets, are bringing in a golden age of social science by empowering researchers to measure social behavior on a scale never before possible. This was conducted by exploring social responses on the use of social media. Research model was developed based on the previous models such as TAM, DOI and Trust combined model. It evaluates the influence of perceived ease of use, perceived usefulness, trust, complexity, compatibility and relative advantage influence on the adoption of social Media. The model was tested on a sample of 365 Maldivian people using survey method via questionnaire. The result showed that perceived usefulness, trust, relative advantage and complexity would highly influence the adoption of social media.

Keywords: adoption, broadcasting, maldives, social media

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Authors: Nicole Pyle, Daniel Pyle, Christa Haring, Marty Hougen

Abstract:

Effective special education teachers utilize evidence-based practices for adolescent reading instruction and target the skills needed to improve the reading of older struggling readers. High-Leverage Practices (HLPs) are critical to helping students with disabilities learn important content. Therefore, special education teachers are encouraged to implement HLPs to maximize the learning of students with disabilities, including students with reading difficulties. Teachers’ implementation of HLPs in reading comprehension instruction should aim to develop adolescents’ understanding of grade-level narrative texts and informational texts, including content area texts. Instruction High-Leverage Practices (11-22) that ensure effective implementation of evidence-based practice in reading comprehension instruction for adolescents are presented. Effective reading comprehension activities within the 12 Instruction HLPs are illustrated.

Keywords: high-leverage practices, adolescent, instructional activities, students with disabilities

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Authors: Amaal Almigal

Abstract:

Technology has been argued to offer distinct advantages and benefits for teaching children with autism spectrum disorder (ASD) to communicate. One aspect of this technology is augmentative and alternative communication (AAC) systems such as picture exchange or speech generation devices. Whilst there has been significant progress in teaching these children to request their wants and needs with AAC, there remains a need for developing technologies that can really make a difference in teaching them to ask questions. iPad-based AAC can be effective for communication. However, the effectiveness of this type of AAC in teaching children to ask questions needs to be examined. Thus, in order to examine the effectiveness of iPad-based AAC in teaching children with ASD to ask questions, This research will test whether iPad leads to more learning than a traditional approach picture and text cards does. Two groups of children who use AAC will be taught to ask ‘What is it?’ questions. With the first group, low-tech AAC picture and text cards will be used, while an iPad-based AAC application called Proloquo2Go will be used with the second group. Interviews with teachers and parents will be conducted before and after the experiment. The children’s perspectives will also be considered. The initial outcomes of this research indicate that iPad can be an effective tool to help children with autism to ask questions.

Keywords: autism, communication, information, iPad, pictures, requesting

Procedia PDF Downloads 244