Search results for: learning loss

Authors: Jennifer Gallup, Beverly Ray, Esther Ntuli

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Many students such as students from linguistically or culturally diverse backgrounds and those with a disability remain chronically underrepresented in higher level science and mathematics disciplines as well as many hands-on-lab-based activities due to the need for remedial reading and mathematics instruction. Makerspace labs can be a conduit for supporting inclusive learning for these students through hands-on active learning strategies that support equitable access to STEM disciplines. Makerspace is a physical space where individuals gather to create, invent, innovate, and learn while using hands-on materials such as 2D and 3D printers, software programs, electronics, and other tools and supplies. Makerspaces are emerging across many P-12 settings; however, many teachers enter the field not prepared to harness the power inherent in a makerspace, especially for those with disabilities and differing needs. This paper offers suggestions on teaching pre-service teachers and practicing teachers how to incorporate a makerspace into their professional practice through guided instruction and hands-on practice. Recommendations for interested stakeholders are included as well.

Keywords: STEM learning, technology, autism, students with disabilities, makerspace

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Authors: Jacqueline Zammit

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Currently, a considerable number of individuals from different backgrounds are being drawn to Malta due to its favourable environment for business, investment, and employment. This influx has led to a growing interest among expats in learning Maltese as a second language (ML2) to enrich their experience of working and residing in Malta. However, the intricacies of Maltese grammar, particularly challenging for second language (L2) learners unfamiliar with Arabic, can pose difficulties in the learning process. Furthermore, it's worth noting that the teaching of ML2 is an emerging field with limited existing research on effective pedagogical strategies. The realm of second language acquisition (SLA) can be notably demanding for adults, requiring well-founded interventions to facilitate learning. Among these interventions, approaches grounded in empirical evidence have incorporated artistic and musical elements to augment SLA. Both art and music have proven roles in facilitating L2 communication, aiding vocabulary retention, and improving comprehension skills. This study aims to delve into the utilization of music and art as catalysts for enhancing the progress of adult learners in mastering ML2. The research employs a qualitative methodology, employing a sample selected through convenience sampling, which encompassed 37 adult learners of ML2. These participants engaged in individual interviews. The data derived from these interviews were subjected to thorough analysis. The outcomes of the study underscore the substantial positive influence exerted by art and music on the academic advancement of adult ML2 learners. Notably, it emerged from the participants' accounts that the current ML2 curricula lack the integration of art and music. Therefore, this study advocates for the incorporation of art and music components within both traditional classroom settings and online ML2 courses. The intention is to bolster the academic accomplishments of adult learners in the realm of Maltese as a second language, bridging the current gap between theory and practice.

Keywords: academic accomplishment, mature learners, visual art, learning Maltese as a second language, musical involvement, acquiring a second language

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Authors: Baba John, Abdullahi Mohammed

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The aim of this research is to compare the analysis of biodegradation on polythene and plastics buried in fadama soil amended with Organic and Inorganic fertilizer. Physico- chemical properties of the samples were determined. Bacteria and Fungi implicated in the biodegradation were identified and enumerated. Physico- chemical properties before the analysis indicated pH range of the samples from 4.28 – 5.80 , While the percentage Organic carbon and Organic matter was highest in cow dung samples with 3.89% and 6.69% respectively. The total Nitrogen percentage was recorded to be highest in Chicken dropping (0.68), while the availability of Phosphorus (P), Sodium (Na), Pottasium (K), and Magnessium (mg) was recorded to be highest in F – soil (Control), with values to be 37ppm, 1.63 Cmolkg-1, 0.35 Cmolkg-1 and 1.18 Cmolkg-1 respectively, except for calcium which was recorded to be highest in Cow dung (5.80 Cmolkg-1). However, physico – chemical properties of the samples after analysis indicated pH range of 4.6 – 5.80, Percentage Organic carbon and Organic matter was highest in Fadama soil mixed with fertilizer, having 0.7% and 1.2% respectively. Total Percentage Nitrogen content was found to be highest (0.56) in Fadama soil mixed with poultry dropping. Availability of Sodium (Na), Pottasium (K), and Calcium (Ca) was recorded to be highest in Fadama Soil mixed with Cow dung with values to be 0.64 Cmolkg-1, 2.07 Cmolkg-1 and 3.36 Cmolkg-1 respectively. The percentage weight loss of polythene and plastic bags after nine months in fadama soil mixed with poultry dropping was 11.9% for polythene and 6.0% for plastics. Weight loss in fadama soil mixed with cow dung was 18.1% for polythene and 4.7% for plastics. Weight loss of polythene and plastic in fadama soil mixed with fertilizer (NPK) was 7.4% for polythene and 3.3% for plastics. While, the percentage weight loss of polythene and plastics after nine months of burial in fadama soil (control) was 3.5% and 0.0% respectively. The bacteria species isolated from Fadama soil, organic and inorganic fertilizers before amendments include: S. aureus, Micrococcus sp, Streptococcus. pyogenes, Psuedomonas aeruginosa Bacillus subtilis and Bacillus cereus. The fungi species include: Aspergillus niger, Aspergillus fumigatus, Aspergillus flavus, Fusarium sp, Mucor sp Penicillium sp and Candida sp. The bacteria species isolated and characterized after nine months of seeding include: S. aureus, Micrococcus sp, S. pyogenes, P. aeruginosa and B. subtilis. The fungi species are: A. niger A. flavus, A. fumigatus, Mucor sp, Penicillium sp and Fusarium sp. The result of this study indicated that plastic materials can be degraded in the fadama soil irrespective of whether the soil is amended or not. The Period of composting also has a significant impact on the rate at which polythene and plastics are degraded.

Keywords: Fadama, fertilizer, plastic and polythene, biodegradation

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Authors: Babarina Maria, Andropova Margarita

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Introduction: Hypoparathyroidism (HypoPT) is a rare endocrine disorder with an estimated prevalence of 0.25 per 1000 individuals. The most common cause of HypoPT is the loss of active parathyroid tissue following thyroid or parathyroid surgery. Sometimes permanent postoperative HypoPT occures, manifested by hypocalcemia in combination with low levels of PTH during 6 months or more after surgery. Cognitive impairments in patients with hypocalcemia due to chronic HypoPT are observed, and this can lead to problems and challenges in everyday living: memory loss and impaired concentration, that may be the cause of poor compliance. Clinical case: Patient K., 66 years old, underwent thyroidectomy in 2013 (at the age of 55) because of papillary thyroid cancer T1NxMx, histopathology findings confirmed the diagnosis. 5 years after the surgery, she was followed up on an outpatient basis, TSH levelsonly were monitored, and the dose of levothyroxine was adjusted. In 2018 due to, increasing complaints include tingling and cramps in the arms and legs, memory loss, sleep disorder, fatigue, anxiety, hair loss, muscle pain, tachycardia, positive Chvostek, and Trousseau signs were diagnosed during examination, also in blood analyses: total Ca 1.86 mmol/l (2.15-2.55), Ca++ 0.96 mmol/l (1.12-1.3), P 1.55 mmol/l (0.74-1.52), Mg 0.79 mmol/l (0.66-1.07) - chronic postoperative HypoPT was diagnosed. Therapy was initiated: alfacalcidol 0.5 mcg per day, calcium carbonate 2000 mg per day, cholecalciferol 1000 IU per day, magnesium orotate 3000 mg per day. During the case follow-up, hypocalcemia, hyperphosphatemia persisted, hypercalciuria15.7 mmol/day (2.5-6.5) was diagnosed. Dietary recommendations were given because of the high content of phosphorus rich foods, and therapy was adjusted: the dose of alfacalcidol was increased to 2.5 mcg per day, and the dose of calcium carbonate was reduced to 1500 mg per day. As part of the screening for complications of hypoPT, data for cataracts, Fahr syndrome, nephrocalcinosis, and kidney stone disease were not obtained. However, HypoPT compensation was not achieved, and therefore hydrochlorothiazide 25 mg was initiated, the dose of alfacalcidol was increased to 3 mcg per day, calcium carbonate to 3000 mg per day, magnesium orotate and cholecalciferol were continued at the same doses. Therapeutic goals were achieved: calcium phosphate product <4.4 mmol2/l2, there were no episodes of hypercalcemia, twenty-four-hour urinary calcium excretion was significantly reduced. Conclusion: Timely prescription, careful explanation of drugs usage rules, and monitoring and maintaining blood and urine parameters within the target contribute to the prevention of HypoPT complications development and life-threatening events.

Keywords: hypoparathyroidism, hypocalcemia, hyperphosphatemia, hypercalciuria

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Authors: Sunghae Jun

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Technology management (TM) is important issue in a company improving the competitiveness. Among many activities of TM, technology analysis (TA) is important factor, because most decisions for management of technology are decided by the results of TA. TA is to analyze the developed results of target technology using statistics or Delphi. TA based on Delphi is depended on the experts’ domain knowledge, in comparison, TA by statistics and machine learning algorithms use objective data such as patent or paper instead of the experts’ knowledge. Many quantitative TA methods based on statistics and machine learning have been studied, and these have been used for technology forecasting, technological innovation, and management of technology. They applied diverse computing tools and many analytical methods case by case. It is not easy to select the suitable software and statistical method for given TA work. So, in this paper, we propose a methodology for quantitative TA using statistical computing software called R and data science to construct a general framework of TA. From the result of case study, we also show how our methodology is applied to real field. This research contributes to R&D planning and technology valuation in TM areas.

Keywords: technology management, R system, R data science, statistics, machine learning

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Authors: Matthias Haenisch, Marc Godau, Julia Barreiro, Dominik Maxelon

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In times of ubiquitous digitalization and the increasing entanglement of humans and technologies in musical practices in the 21st century, it is to be asked, how popular musicians learn in the (post)digital Age. Against the backdrop of the increasing interest in transferring informal learning practices into formal settings of music education the interdisciplinary research association »MusCoDA – Musical Communities in the (Post)Digital Age« (University of Erfurt/University of Applied Sciences Clara Hoffbauer Potsdam, funded by the German Ministry of Education and Research, pursues the goal to derive an empirical model of collective songwriting practices from the study of informal lelearningf songwriters and bands that can be translated into pedagogical concepts for music education in schools. Drawing on concepts from Community of Musical Practice and Actor Network Theory, lelearnings considered not only as social practice and as participation in online and offline communities, but also as an effect of heterogeneous networks composed of human and non-human actors. Learning is not seen as an individual, cognitive process, but as the formation and transformation of actor networks, i.e., as a practice of assembling and mediating humans and technologies. Based on video stimulated recall interviews and videography of online and offline activities, songwriting practices are followed from the initial idea to different forms of performance and distribution. The data evaluation combines coding and mapping methods of Grounded Theory Methodology and Situational Analysis. This results in network maps in which both the temporality of creative practices and the material and spatial relations of human and technological actors are reconstructed. In addition, positional analyses document the power relations between the participants that structure the learning process of the field. In the area of online informal lelearninginitial key research findings reveal a transformation of the learning subject through the specific technological affordances of TikTok and Instagram and the accompanying changes in the learning practices of the corresponding online communities. Learning is explicitly shaped by the material agency of online tools and features and the social practices entangled with these technologies. Thus, any human online community member can be invited to directly intervene in creative decisions that contribute to the further compositional and structural development of songs. At the same time, participants can provide each other with intimate insights into songwriting processes in progress and have the opportunity to perform together with strangers and idols. Online Lelearnings characterized by an increase in social proximity, distribution of creative agency and informational exchange between participants. While it seems obvious that traditional notions not only of lelearningut also of the learning subject cannot be maintained, the question arises, how exactly the observed informal learning practices and the subject that emerges from the use of social media as online learning technologies can be transferred into contexts of formal learning

Keywords: informal learning, postdigitality, songwriting, actor-network theory, community of musical practice, social media, TikTok, Instagram, apps

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Authors: Swathi Ganesan, Nalinda Somasiri, Rebecca Jeyavadhanam, Gayathri Karthick

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The COVID-19 crisis presents a substantial and critical hazard to worldwide health. Since the occurrence of the disease in late January 2020 in the UK, the number of infected people confirmed to acquire the illness has increased tremendously across the country, and the number of individuals affected is undoubtedly considerably high. The purpose of this research is to figure out a predictive machine learning archetypal that could forecast COVID-19 cases within the UK. This study concentrates on the statistical data collected from 31st January 2020 to 31st March 2021 in the United Kingdom. Information on total COVID cases registered, new cases encountered on a daily basis, total death registered, and patients’ death per day due to Coronavirus is collected from World Health Organisation (WHO). Data preprocessing is carried out to identify any missing values, outliers, or anomalies in the dataset. The data is split into 8:2 ratio for training and testing purposes to forecast future new COVID cases. Support Vector Machines (SVM), Random Forests, and linear regression algorithms are chosen to study the model performance in the prediction of new COVID-19 cases. From the evaluation metrics such as r-squared value and mean squared error, the statistical performance of the model in predicting the new COVID cases is evaluated. Random Forest outperformed the other two Machine Learning algorithms with a training accuracy of 99.47% and testing accuracy of 98.26% when n=30. The mean square error obtained for Random Forest is 4.05e11, which is lesser compared to the other predictive models used for this study. From the experimental analysis Random Forest algorithm can perform more effectively and efficiently in predicting the new COVID cases, which could help the health sector to take relevant control measures for the spread of the virus.

Keywords: COVID-19, machine learning, supervised learning, unsupervised learning, linear regression, support vector machine, random forest

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Authors: Yanwen Li, Shuguo Xie

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In electromagnetic imaging, because of the diffraction limited system, the pixel values could change slowly near the edge of the image targets and they also change with the location in the same target. Using traditional digital image segmentation methods to segment electromagnetic gradient images could result in lots of errors because of this change in pixel values. To address this issue, this paper proposes a novel image segmentation and extraction algorithm based on Mean-Shift and dictionary learning. Firstly, the preliminary segmentation results from adaptive bandwidth Mean-Shift algorithm are expanded, merged and extracted. Then the overlap rate of the extracted image block is detected before determining a segmentation region with a single complete target. Last, the gradient edge of the extracted targets is recovered and reconstructed by using a dictionary-learning algorithm, while the final segmentation results are obtained which are very close to the gradient target in the original image. Both the experimental results and the simulated results show that the segmentation results are very accurate. The Dice coefficients are improved by 70% to 80% compared with the Mean-Shift only method.

Keywords: gradient image, segmentation and extract, mean-shift algorithm, dictionary iearning

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Authors: Virgino Stephano Moniaga

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Thermal comfort inside a building can affect students in their learning process. The learning process of students can be improved if the condition of the classrooms is comfortable. This study will be conducted in SMA Negeri 1 Amurang which is a senior high school building located in South Minahasa Regency. Based on preliminary survey, generally, students were not satisfied with the existing level of comfort, which subsequently affected the teaching and learning process in the classroom. The purpose of this study is to analyze the comfort level of classrooms occupants and recommend building design solutions that can improve the thermal comfort of classrooms. In this study, three classrooms will be selected for thermal comfort measurements. The thermal comfort measurements will be taken in naturally ventilated classrooms. The measured data comprise of personal data (clothing and students activity), air humidity, air temperature, mean radiant temperature and air flow velocity. Simultaneously, the students will be asked to fill out a questionnaire that asked about the level of comfort that was felt at the time. The results of field measurements and questionnaires will be analyzed based on the PMV and PPD indices. The results of the analysis will decide whether the classrooms are comfortable or not. This study can be continued to obtain a more optimal design solution to improve the thermal comfort of the classrooms. The expected results from this study can improve the quality of teaching and learning process between teachers and students which can further assist the government efforts to improve the quality of national education.

Keywords: classrooms, PMV, PPD, thermal comfort

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Authors: Jian Qu, Akira Shimazu

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OOV (Out Of Vocabulary) terms are terms that cannot be found in many dictionaries. Although it is possible to translate such OOV terms, the translations do not provide any real information for a user. We present an OOV term definition extraction method by using information available from the Internet. We use features such as occurrence of the synonyms and location distances. We apply machine learning method to find the correct definitions for OOV terms. We tested our method on both biomedical type and name type OOV terms, our work outperforms existing work with an accuracy of 86.5%.

Keywords: information retrieval, definition retrieval, OOV (out of vocabulary), biomedical information retrieval

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Authors: Prompt Udomdech, Eleni Papadonikolaki, Andrew Davies

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Building information modelling (BIM) is the major technological trend amongst built environment organisations. Digitalising businesses and operations, BIM brings forth a digital transformation in any built environment industry. The adoption of BIM presents challenges for organisations, especially small- and medium-sizes enterprises (SMEs). The main problem for built-environment SMEs is the lack of project actors with adequate BIM competences. The research highlights learning in projects as the key and explores into the learning of BIM in projects of designers and engineers within Thai design and engineering SMEs. The study uncovers three impeding attributes, which are: a) lack of English proficiency; b) unfamiliarity with digital technologies; and c) absence of public standards. This research expands on the literature on BIM competences and adoption.

Keywords: BIM competences and adoption, digital transformation, learning in projects, SMEs, and developing built environment industry

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Authors: K. M. Damodara Gowda

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Background: Maternal health and nutrition are considered as the predominant factors influencing brain functional development. If the mother is free of illness and genetic defects, maternal nutrition would be one of the most critical factors affecting the brain development. Calorie restrictions cause significant impairment in spatial learning ability and the levels of Brain Derived Neurotrophic Factor (BDNF) in rats. But, the mechanism by which the prenatal under-nutrition leads to impairment in brain learning and memory function is still unclear. In the present study, prenatal Astaxanthin supplementation on BDNF level, spatial learning and memory performance in the offspring’s of normal, calorie restricted and Astaxanthin supplemented rats was investigated. Methodology: The rats were administered with 6mg and 12 mg of astaxanthin /kg bw for 21 days following which acquisition and retention of spatial memory was tested in a partially-baited eight arm radial maze. The BDNF level in different regions of the brain (cerebral cortex, hippocampus and cerebellum) was estimated by ELISA method. Results: Calorie restricted animals treated with astaxanthin made significantly more correct choices (P < 0.05), and fewer reference memory errors (P < 0.05) on the tenth day of training compared to offsprings of calorie restricted animals. Calorie restricted animals treated with astaxanthin also made significantly higher correct choices (P < 0.001) than untreated calorie restricted animals in a retention test 10 days after the training period. The mean BDNF level in cerebral cortex, Hippocampus and cerebellum in Calorie restricted animals treated with astaxanthin didnot show significant variation from that of control animals. Conclusion: Findings of the study indicated that memory and learning was impaired in the offspring’s of calorie restricted rats which was effectively modulated by astaxanthin at the dosage of 12 mg/kg body weight. In the same way the BDNF level at cerebral cortex, Hippocampus and Cerebellum was also declined in the offspring’s of calorie restricted animals, which was also found to be effectively normalized by astaxanthin.

Keywords: calorie restiction, learning, Memory, Cerebral cortex, Hippocampus, Cerebellum, BDNF, Astaxanthin

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Authors: Nazmin Akter, Tariqul Islam, Abu Sayed

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Food loss and waste have become critical global issues, with approximately one-third of the world's food production being wasted. Among the various food products, horticultural fruits and vegetables are especially susceptible to loss due to their relatively short shelf lives. Litchi (Litchi chinensis) is one of Bangladesh's most important horticultural fruits. But the problem with this fruit is its short shelf life by losing weight faster after harvest. The experiment was carried out at Hajee Mohammad Danesh Science and Technology University, Dinajpur-5200 Bangladesh during 2020-2021. The objective of this experiment was to see the impact of nutrients viz., urea (1%), calcium chloride (1%), borax (1%), and their combinations on fruit quality and shelf life of litchi cv. Bombai. The experiment was laid out in a randomized block design with 7 treatments and 3 replications. Two sprays of each treatment were applied from the last week of May to June (at 20-day intervals). The results indicated that all the treatments significantly improved the quality parameters of litchi fruits as compared to the control. In terms of physicochemical characteristics fruit weight (20.30g), fruit volume (20m ml), and pulp percent (17.14) were found maximum with minimum stone percent (11.09) with the application of urea 1% + borax 1%+ calcium chloride 1%. Maximum TSS (19.62oBrix), TSS/acidity ratio (24.57), maximum ascorbic acid (45.19 mg/100 g pulp), and minimum acidity (0.80%) were reported with the application of T6 (Urea 1% + borax 1%+ calcium chloride 1%) treatments whereas fruits treated with urea 1% + borax 1% gave maximum total sugars (26.64%) and reducing sugars (19.19%) as compared to control. In the case of storage characters, application of Urea 1% + borax 1%+ calcium chloride 1% resulted in a minimum physiological loss in weight (6.11%), (8.41%), and (10.65%) for 2 days, 4 days, and 6 days respectively. In conclusion, to obtain better quality and increased storage period of litchi fruits, two sprays of urea, borax, and calcium chloride (1%) could be used during the fruit growth and development period at fortnightly intervals.

Keywords: litchi chinensis, preharvest, quality, shelf life, postharvest

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Authors: Cleto J. Sauer Jr

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Introduction: Brazil’s new national curriculum guidelines (NCG) for medical education were published in 2014, presenting active learning methodologies as a cornerstone. Simulation was initially applied for aviation pilots’ training and is currently applied in health sciences. The high-fidelity simulator replicates human body anatomy in detail, also reproducing physiological functions and its use is increasing in medical schools. Realistic Simulation (RS) has pedagogical aspects that are aligned with Brazil’s NCG teaching concepts. The main objective of this study is to carry on a narrative review on RS’s aspects that are aligned with Brazil’s new NCG teaching concepts. Methodology: A narrative review was conducted, with search in three databases (PubMed, Embase and BVS) of studies published between 2010 and 2020. Results: After systematized search, 49 studies were selected and divided into four thematic groups. RS is aligned with new Brazilian medical curriculum as it is an active learning methodology, providing greater patient safety, uniform teaching, and student's emotional skills enhancement. RS is based on reflective learning, a teaching concept developed for adult’s education. Conclusion: RS is a methodology aligned with NCG teaching concepts and has potential to assist in the implementation of new Brazilian medical school’s curriculum. It is an immersive and interactive methodology, which provides reflective learning in a safe environment for students and patients.

Keywords: curriculum, high-fidelity simulator, medical education, realistic simulation

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Authors: Sujata Gupta Kedar, Fasiha Fayaz

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This paper presents various studies being carried out by various researchers globally on the attitude of lecturers towards the advent of information technology and e-learning. An effort has been made in this paper to study the various trends being presented by researchers and draw some general conclusions. These show the effect of the lecturer’s gender, age and educational background on their attitude towards the e-learning. Also the favorable attitude of teachers' towards using new technology in teaching will certainly make teachers use them in appropriate situations in teaching and thus measuring of teachers attitude towards using new technology in teaching is very much needed. The sample of 50 males and 50 females were studied from different colleges of Bangalore “Attitudes towards using new technology scale” by Dr. Rajasekar was used. It was seen that male and female had no significant difference in hardware and software use, whereas both had favorable attitude. And there was a significant difference at 1% level among female lecturers belonging to arts faculty. There is no significant difference between the gender and age, because higher the age lower the score is. Irrespective of teaching experience males had no significant difference, whereas females are significant at 1% level, which says that higher the teaching experience of lecturers less knowledge they have towards the use of ICT, as the younger generation is more expose to technology.

Keywords: e-learning, ICT, attitudes, lecturers, communication technology

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Authors: Abul Hashem

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The experiment was conducted to find out the effect of different levels of Moringa oleifiera leaf extract and synthetic antioxidant (Beta Hydroxyl Anisole) on fresh and preserved beef meatballs. For this purpose, ground beef samples were divided into five treatment groups. They are treated as control, synthetic antioxidant, 0.1%, 0.2% and 0.3% Moringa oleifera leaf extract as T1, T2, T3, T4 and T5, respectively. Five kinds of meatballs were made and biscuit crushed and egg albumin was mixed with beef meatballs and cooking was practiced properly. Proximate analysis, sensory tests (color, flavor, tenderness, juiciness, overall acceptability), cooking loss, pH value, free fatty acids (FFA), thiobarbituric acid values (TBARS), peroxide value(POV) and microbiological examination were determined in order to evaluate the effect of Moringa oleifiera leaf extract as natural antioxidant & antimicrobial activities in comparing to BHA (Beta Hydroxyl Anisole) at first day before freezing and for maintaining meatballs qualities on the shelf life of beef meat balls stored for 60 days under frozen condition. Freezing temperature was -20˚C. Days of intervals of experiment were on 0, 15th, 30th, and 60th days. Dry matter content of all the treatment groups differ significantly (p<0.05). On the contrary, DM content increased significantly (p<0.05) with the advancement of different days of intervals. CP content of all the treatments were increased significantly (p<0.05) among the different treatment groups. EE content at different treatment levels differ significantly (p<0.05). Ash content at different treatment levels was also differ significantly (p<0.05). FFA values, TBARS, POV were decreased significantly (p<0.05) at different treatment levels. Color, odor, tenderness, juiciness, overall acceptability, raw PH, cooked pH were increased at different treatment levels significantly (p<0.05). The cooking loss (%) at different treatment levels were differ significantly (p<0.05). TVC (logCFU/g), TCC (logCFU/g) and TYMC (logCFU/g) was decreased significantly (p<0.05) at different treatment levels comparison to control. Considering CP, tenderness, juiciness, overall acceptability, cooking loss, FFA, POV, TBARS and microbial parameters it can be concluded that Moringa oleifera leaf extract at 0.1%, 0.2% and 0.3% can be used instead of 0.1% synthetic antioxidant BHA in beef meatballs.

Keywords: antioxidant, beef meatball, BHA, moringa leaf extract, quality

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Authors: Prejily Thomas John

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Flooding of urban areas often has an adverse impact on the dense population residing in cities. The vulnerable areas are the most affected due to flooding, which even results in loss of life. The increasing trend of urban floods is a universal phenomenon and leads to a vital loss in the physical, economic, social, and environmental dimensions. The shift from floods being natural disasters to man-made disasters due to unplanned urban growth is evident from national and international reports. Thiruvalla, bordered by the Manimala River in the Pathanamthitta district, is an important urban node and a drainage point of various estuaries. The city is often faced with flash floods and overflow from rivers since it is a low-lying land. The need for urban flood resilience for planned urban development is a necessity for livability in consideration of the topography. The paper focuses on developing an urban design framework in everyday urban spaces through the principles of resilient urbanism. The principles guide the creation of flood-resilient spaces and productive urban landscapes for the city to enable better and safer living conditions. A flood-resilient city not only prepares the city for disasters but also improves the ecological and economic conditions.

Keywords: everyday urban spaces, flood resilience, resilient urbanism, productive urban landscapes

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Authors: Harriet Koshie Lamptey, Richard Boateng

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Mobile learning (m-learning) is a novel approach to knowledge acquisition and dissemination and is gaining global attention. Steady progress in wireless technologies and the portability of communication devices continue to broaden the scope and use of mobiles. With the convergence of Web functionality onto mobile platforms and the affordability and availability of mobile technology, m-learning has the potential of being the next prevalent channel of education in both formal and informal settings. There is substantive literature on developed countries but the state in developing countries (DCs) however appears vague. This paper is a synthesis of extant literature on mobile learning in DCs. The research interest is based on the fact that in DCs, mobile communication and internet connectivity are popular. However, its use in education is under explored. There are some reviews on the state, conceptualizations, trends and teacher education, but to the authors’ knowledge, no study has focused on mobile learning adoption and integration issues. This study examines issues and gaps associated with its adoption and integration in DCs higher education institutions. A qualitative build-up of literature was conducted using articles pooled from electronic databases (Google Scholar and ERIC). To enable criteria for inclusion and incorporate diverse study perspectives, search terms used were m-learning, DCs, higher education institutions, challenges, benefits, impact, gaps and issues. The synthesis revealed that though mobile technology has diffused globally, its pedagogical pursuit in DCs remains quite low. The absence of a mobile Web and the difficulty of resource conversion into mobile format due to lack of funding and technical competence is a stumbling block. Again, the lack of established design and implementation rules to guide the development of m-learning platforms in DCs is a hindrance. The absence of access restrictions on devices poses security threats to institutional systems. Negative perceptions that devices are taking over faculty roles lead to resistance in some situations. Resistance to change can be a hindrance to the acceptance and success of new systems. Lack of interest for m-learning is also attributed to lower technological literacy levels of the underprivileged masses. Scholarly works on m-learning in DCs is yet to mature. Most technological innovations are handed down from developed countries, and this constantly creates a lag for DCs. Lack of theoretical grounding was also identified which reduces the objectivity of study reports. The socio-cultural terrain of DCs results in societies with different views and needs that have been identified as a hindrance to research. Institutional commitment decisions, adequate funding for the necessary infrastructural development as well as multiple stakeholder participation is important for project success. Evidence suggests that while adoption decisions are readily made, successful integration of the concept for its full benefits to be realized is often neglected. Recommendations to findings were made to provide possible remedies to identified issues.

Keywords: developing countries, higher education institutions, mobile learning, literature review

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Authors: Swee Kun Yap, Sachin Jangam, Suraj Vasudevan

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Experiential learning is dubbed as a highly effective way to enhance learning. Virtual reality (VR) is thus a helpful tool in providing a safe, memorable, and interactive learning environment. A class of 49 fluid mechanics students participated in starting up a pump, one of the most used equipment in the chemical industry, in VR. They experience the process in VR to familiarize themselves with the safety training and the standard operating procedure (SOP) in guided mode. Students subsequently observe their peers (in groups of 4 to 5) complete the same training. The training first brings each user through the personal protection equipment (PPE) selection, before guiding the user through a series of steps for pump startup. One of the most common feedback given by industries include the weakness of our graduates in pump design and operation. Traditional fluid mechanics is a highly theoretical module loaded with engineering equations, providing limited opportunity for visualization and operation. With VR pump, students can now learn to startup, shutdown, troubleshoot and observe the intricacies of a centrifugal pump in a safe and controlled environment, thereby bridging the gap between theory and practical application. Following the completion of the guided mode operation, students then individually complete the VR assessment for pump startup on the same day, which requires students to complete the same series of steps, without any cues given in VR to test their recollection rate. While most students miss out a few minor steps such as the checking of lubrication oil and the closing of minor drain valves before pump priming, all the students scored full marks in the PPE selection, and over 80% of the students were able to complete all the critical steps that are required to startup a pump safely. The students were subsequently tested for their recollection rate by means of an online quiz 3 weeks later, and it is again found that over 80% of the students were able to complete the critical steps in the correct order. In the survey conducted, students reported that the VR experience has been enjoyable and enriching, and 79.5% of the students voted to include VR as a positive supplementary exercise in addition to traditional teaching methods. One of the more notable feedback is the higher ease of noticing and learning from mistakes as an observer rather than as a VR participant. Thus, the cycling between being a VR participant and an observer has helped tremendously in their knowledge retention. This reinforces the positive impact VR has on learning.

Keywords: experiential learning, learning by doing, pump, unit operations, virtual reality

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Authors: V. K. Srivastava

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Graphene has recently attracted an increasing attention in nanocomposites applications because it has 200 times greater strength than steel, making it the strongest material ever tested. Graphene, as the fundamental two-dimensional (2D) carbon structure with exceptionally high crystal and electronic quality, has emerged as a rapidly rising star in the field of material science. Graphene, as defined, as a 2D crystal, is composed of monolayers of carbon atoms arranged in a honeycombed network with six-membered rings, which is the interest of both theoretical and experimental researchers worldwide. The name comes from graphite and alkene. Graphite itself consists of many graphite-sheets stacked together by weak van der Waals forces. This is attributed to the monolayer of carbon atoms densely packed into honeycomb structure. Due to superior inherent properties of graphene nanoplatelets (GnP) over other nanofillers, GnP particles were added in epoxy resin with the variation of weight percentage. It is indicated that the DMA results of storage modulus, loss modulus and tan δ, defined as the ratio of elastic modulus and imaginary (loss) modulus versus temperature were affected with addition of GnP in the epoxy resin. In epoxy resin, damping (tan δ) is usually caused by movement of the molecular chain. The tan δ of the graphene nanoplatelets/epoxy resin composite is much lower than that of epoxy resin alone. This finding suggests that addition of graphene nanoplatelets effectively impedes movement of the molecular chain. The decrease in storage modulus can be interpreted by an increasing susceptibility to agglomeration, leading to less energy dissipation in the system under viscoelastic deformation. The results indicates the tan δ increased with the increase of temperature, which confirms that tan δ is associated with magnetic field strength. Also, the results show that the nanohardness increases with increase of elastic modulus marginally. GnP filled epoxy resin gives higher value than the epoxy resin, because GnP improves the mechanical properties of epoxy resin. Debonding of GnP is clearly observed in the micrograph having agglomeration of fillers and inhomogeneous distribution. Therefore, DMA and nanohardness studies indiacte that the elastic modulus of epoxy resin is increased with the addition of GnP fillers.

Keywords: agglomeration, elastic modulus, epoxy resin, graphene nanoplatelet, loss modulus, nanohardness, storage modulus

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Authors: Martin Hagan

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Teacher identity has been recognised as a crucial field of research which supports understanding of the ways in which teachers navigate the complexities of professional life in order to grow in competence, knowledge and practice. As a field of study, teacher identity is concerned with understanding: how identity is defined; how it develops; how teachers make sense of their emerging identity; and how the act of teaching is mediated through the individual teacher’s values, beliefs and sense of professional self. By comparing two particular, socially constructed learning contexts or ‘learning milieu’, one in Northern Ireland and the other in the United States of America, this study aims specifically, to gain better understanding of how teacher identity develops during the initial phase of teacher education. The comparative approach was adopted on the premise that experiences are constructed through interactive, socio-historical and cultural negotiations with others within particular environments, situations and contexts. As such, whilst the common goal is to ‘become’ a teacher, the nuances emerging from the different learning milieu highlight variance in discourse, priorities, practice and influence. A qualitative, interpretative research design was employed to understand the world-constructions of the participants through asking open-ended questions, seeking views and perspectives, examining contexts and eventually deducing meaning. Data were collected using semi structured interviews from a purposive sample of student teachers (n14) in either the first or second year of study in their respective institutions. In addition, a sample of teacher educators (n5) responsible for the design, organisation and management of the programmes were also interviewed. Inductive thematic analysis was then conducted, which highlighted issues related to: the participants’ personal dispositions, prior learning experiences and motivation; the influence of the teacher education programme on the participants’ emerging professional identity; and the extent to which the experiences of working with teachers and pupils in schools in the context of the practicum, challenged and changed perspectives on teaching as a professional activity. The study also highlights the varying degrees of influence exercised by the different roles (tutor, host teacher/mentor, student) within the teacher-learning process across the two contexts. The findings of the study contribute to the understanding of teacher identity development in the early stages of professional learning. By so doing, the research makes a valid contribution to the discourse on initial teacher preparation and can help to better inform teacher educators and policy makers in relation to appropriate strategies, approaches and programmes to support professional learning and positive teacher identity formation.

Keywords: initial teacher education, professional learning, professional growth, teacher identity

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Authors: Lagnajeet Mohanty, Mohnish Mishra, Pratham Tapdiya, Himanshu Sekhar Nayak, Swetapadma Singh

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In the era of global interconnectedness, effective risk assessment and management are critical for organizational resilience. This review explores the integration of machine learning (ML) into risk processes, examining its transformative potential and the challenges it presents. The literature reveals ML's success in sectors like consumer credit, demonstrating enhanced predictive accuracy, adaptability, and potential cost savings. However, ethical considerations, interpretability issues, and the demand for skilled practitioners pose limitations. Looking forward, the study identifies future research scopes, including refining ethical frameworks, advancing interpretability techniques, and fostering interdisciplinary collaborations. The synthesis of limitations and future directions highlights the dynamic landscape of ML in risk management, urging stakeholders to navigate challenges innovatively. This abstract encapsulates the evolving discourse on ML's role in shaping proactive and effective risk management strategies in our interconnected and unpredictable global landscape.

Keywords: machine learning, risk assessment, ethical considerations, financial inclusion

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Authors: Adrian Sebastian, Chris Gillespie

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We describe a case of diffuse rectal involvement with cap polyposis, manifesting with a protein-losing colopathy and occurring in the setting of advanced mechanical pelvic floor dysfunction. A 59-year-old male with a 5-year history of persistent excessive flatulence, defecatory difficulties, and diarrhea. He had extensive cap polyposis of the entire rectum endoscopically. His symptoms progressed to severe fecal incontinence with mucus leakage, pelvic pain, weight loss, and hypoalbuminemia. Clinical examination exhibited severe perineal descent, a large rectocele, poor anal squeeze, and a poor defecatory technique. After a trial of nonoperative therapies addressing his defecatory dysfunction, and Helicobacter pylori eradication, surgical resection was offered due to severe symptoms with ongoing incontinence and protein loss with no other reasonable options. A robotic abdominoperineal resection with a permanent colostomy was performed, followed by an uncomplicated recovery. Our observation of coexisting mechanical pelvic floor changes in this patient lends weight to the concept of a prolapse-related phenomenon in the pathophysiology of this rare condition.

Keywords: cap polyposis, pelvic dysfunction, fecal incontinence, case report

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Authors: Larry Wang

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The aim of this paper is to demonstrate how an online homework system is integrated in teaching and learning mathematics and how it improves the student success rates in some gateway mathematics courses. WeBWork provided by the Mathematical Association of America is adopted as the online homework system. During the period of 2010-2015, the system was implemented in classes of precalculus, calculus, probability and statistics, discrete mathematics, linear algebra, and differential equations. As a result, the passing rates of the sections with WeBWork are well above other sections without WeBWork (about 7-10% higher). The paper also shows how the WeBWork system was used.

Keywords: gateway mathematics, online grading, pass rate, WeBWorK

Procedia PDF Downloads 278

Authors: Beatriz Lafuente Alcázar, Yash Wani, Amit J. Nimunkar

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Cardiovascular Diseases (CVDs) are the leading cause of death globally, and around 80% of sudden cardiac deaths are due to arrhythmias or irregular heartbeats. The majority of these pathologies are revealed by either short-term or long-term alterations in the electrocardiogram (ECG) morphology. The ECG is the main diagnostic tool in cardiology. It is a non-invasive, pain free procedure that measures the heart’s electrical activity and that allows the detecting of abnormal rhythms and underlying conditions. A cardiologist can diagnose a wide range of pathologies based on ECG’s form alterations, but the human interpretation is subjective and it is contingent to error. Moreover, ECG records can be quite prolonged in time, which can further complicate visual diagnosis, and deeply retard disease detection. In this context, deep learning methods have risen as a promising strategy to extract relevant features and eliminate individual subjectivity in ECG analysis. They facilitate the computation of large sets of data and can provide early and precise diagnoses. Therefore, the cardiology field is one of the areas that can most benefit from the implementation of deep learning algorithms. In the present study, a deep learning algorithm is trained following a novel approach, using a combination of different databases as the training set. The goal of the algorithm is to achieve the detection of R-peaks in ECG signals. Its performance is further evaluated in ECG signals with different origins and features to test the model’s ability to generalize its outcomes. Performance of the model for detection of R-peaks for clean and noisy ECGs is presented. The model is able to detect R-peaks in the presence of various types of noise, and when presented with data, it has not been trained. It is expected that this approach will increase the effectiveness and capacity of cardiologists to detect divergences in the normal cardiac activity of their patients.

Keywords: arrhythmia, deep learning, electrocardiogram, machine learning, R-peaks

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Authors: O. Sunantha, S. Zhenfeng, S. Phattraporn, A. Zeeshan

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The decline of soil organic carbon (SOC) in global agriculture is a critical issue requiring rapid and accurate estimation for informed policymaking. Previous studies have demonstrated the variability of SOC predictors derived from remote sensing data and environmental variables. However, the specific parameters most suitable for accurately estimating SOC in agricultural areas remain unclear. This study utilizes remote sensing data to precisely estimate SOC and identify influential factors in diverse agricultural areas, such as paddy, corn, sugarcane, cassava, and perennial crops. Extreme gradient boosting (XGBoost), random forest (RF), and support vector regression (SVR) models are employed to analyze these factors impact on SOC estimation. The results show key factors influencing SOC estimation include slope, vegetation indices (EVI), spectral reflectance indices (red index, red edge2), temperature, land use, and surface soil moisture, as indicated by their averaged importance scores across XGBoost, RF, and SVR models. Therefore, using different machine learning algorithms for SOC estimation reveals varying influential factors from remote sensing data and environmental variables. This approach emphasizes feature selection, as different machine learning algorithms identify various key factors from remote sensing data and environmental variables for accurate SOC estimation.

Keywords: factors influencing SOC estimation, remote sensing data, environmental variables, machine learning

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Authors: Salim Yusif

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Fiber optic technology has revolutionized telecommunications and data transmission, providing unmatched speed, bandwidth, and reliability. This paper presents the latest advancements in fiber optic technology, focusing on innovations in fiber materials, transmission techniques, and network architectures that enhance the performance of high-speed data transmission systems. Key advancements include the development of ultra-low-loss optical fibers, multi-core fibers, advanced modulation formats, and the integration of fiber optics into next-generation network architectures such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV). Additionally, recent developments in fiber optic sensors are discussed, extending the utility of optical fibers beyond data transmission. Through comprehensive analysis and experimental validation, this research offers valuable insights into the future directions of fiber optic technology, highlighting its potential to drive innovation across various industries.

Keywords: fiber optics, high-speed data transmission, ultra-low-loss optical fibers, multi-core fibers, modulation formats, coherent detection, software-defined networking, network function virtualization, fiber optic sensors

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Authors: Muhammad Badamasi Abdullahi

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Teacher education, both pre- and in-service programs, is offered in many countries of the world by different teacher education institutions as declared in the Policies on Education of the countries. However, differences exist from one country to another as a result of some factors peculiar to them. Notwithstanding, there also exist similarities among them in regard to teacher education. This paper is expected to dig into teacher education programs in Nigeria and India so that areas of similarities and differences would be highlighted as well as provide a venue for possible recommendation of both countries to learn from one another. All this is directed towards providing a no -border approach in enhancing effective teaching and learning.

Keywords: teacher education, teaching and learning, pre-service, in-service

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Authors: Brooke A. Moore

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Developing teachers’ cultural awareness ensures schools are culturally responsive and socially just for diverse and exceptional students. An ideology of ‘normal’ exists in schools, creating boundaries where some students belong and others are marginalized based on difference. It is important that teacher preparation work to create democratic classrooms where teachers foster tolerance of difference and promote critical thinking and social justice. This paper outlines a framework for developing educator cultural awareness through the use of critically reflective professional learning communities (PLCs) drawing from the research on teacher critical reflection, collaborative PLCs, and Engeström’s theory of expansive learning. A case study using the framework was conducted with ten practicing teachers. Participants read and reflected on critical literature to make visible unexamined beliefs, engaged in conversations that pushed them to reflect more deeply and project forward new ideas, and set goals for acting as agents of change in their schools.

Keywords: cultural and linguistic diversity, diversity, special education, teacher beliefs

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Authors: Mustafa S. Agha, Asma M. Eshahriy

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The propagation of electromagnetic waves in millimeter band is severely affected by rain, and dust particles in terms of attenuation and de-polarization. The computations of dust and/or sand storms require knowledge of electrical properties of the scattering particles and climate conditions at the studied region in the west north region of Libya. (Al -Khoms) To compute the effect of dust and sand particles on the propagation of electromagnetic waves, it is required to collect the sand particles carried out by the wind, measure the particles size distribution (PSD), calculate the concentration, and carry chemical analysis of the contents, then the dielectric constant can be calculated. The main object of this paper is to study the effect of sand and dust storms on wireless communication, such as microwave links, in the north region of Libya (Al -Khoms) of Libya (Nagaza stations, Al-khoms center stations, Al-khoms gateway stations) by determining of the attenuation loss per unit length and cross-polarization discrimination (XPD) change due to the effect of sand and dust storms on wireless communication systems (GSM signal). The result showed that there is some consideration that has to be taken into account in the communication power budget .

Keywords: attenuation, scattering, transmission loss, electromagnetic waves

Procedia PDF Downloads 413